in Sleep and Insomnia

ENDOCRINOLOGY RESEARCH AND CLINICAL DEVELOPMENTS

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ENDOCRINOLOGY RESEARCH AND CLINICAL DEVELOPMENTS

MELATONIN, SLEEP AND INSOMNIA

YOLANDA E. SORIENTO EDITOR

Nova Biomedical Books New York

Copyright © 2010 by Nova Science Publishers, Inc. All rights reserved. No part of this book may be reproduced, stored in a retrieval system or transmitted in any form or by any means: electronic, electrostatic, magnetic, tape, mechanical photocopying, recording or otherwise without the written permission of the Publisher. For permission to use material from this book please contact us: Telephone 631-231-7269; Fax 631-231-8175 Web Site: http://www.novapublishers.com NOTICE TO THE READER The Publisher has taken reasonable care in the preparation of this book, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained in this book. The Publisher shall not be liable for any special, consequential, or exemplary damages resulting, in whole or in part, from the readers‘ use of, or reliance upon, this material. Any parts of this book based on government reports are so indicated and copyright is claimed for those parts to the extent applicable to compilations of such works. Independent verification should be sought for any data, advice or recommendations contained in this book. In addition, no responsibility is assumed by the publisher for any injury and/or damage to persons or property arising from any methods, products, instructions, ideas or otherwise contained in this publication. This publication is designed to provide accurate and authoritative information with regard to the subject matter covered herein. It is sold with the clear understanding that the Publisher is not engaged in rendering legal or any other professional services. If legal or any other expert assistance is required, the services of a competent person should be sought. FROM A DECLARATION OF PARTICIPANTS JOINTLY ADOPTED BY A COMMITTEE OF THE AMERICAN BAR ASSOCIATION AND A COMMITTEE OF PUBLISHERS. Library of Congress Cataloging-in-Publication Data Melatonin, sleep and insomnia / editor, Yolanda E. Soriento. p. ; cm. Includes bibliographical references and index. ISBN 978-1-61122-834-2 (eBook)

Published by Nova Science Publishers, Inc.  New York

Contents Preface

vii

Chapter I

Conditioned Arousal in Insomnia Patients: Physiological, Cognitive, Cortical—An and/or Question? Aisha Cortoos, Elke De Valck and Raymond Cluydts

Chapter II

Neuropathology of Insomnia in the Adult: Still an Enigma! Jean-Jacques Hauw and Chantal Hausser-Hauw

Chapter III

Non-Pharmacological Alternatives for the Treatment of Insomnia – Instrumental EEG Conditioning, a New Alternative? Kerstin Hoedlmoser, Thien Thanh Dang-Vu, Martin Desseilles and Manuel Schabus

Chapter IV

A Novel Disease Condition Presenting with Insomnia and Hypersomnia Asynchronization Jun Kohyama

Chapter V

Aggression in Older Adult Populations Sarah E. Parsons, Luis F. Ramirez, Philipp Dines, Scott Magnuson and Martha Sajatovic

Chapter VI

The Impact of Cultural Changes on the Relationship between Senior Sleep Disturbance and Body Mass Index among Older Adults in Two Asian Societies Bingh Tang and Lyn Tiu

Chapter VII

Chapter VIII

A Novel Model Using Generalized Regression Neural Network (GRNN) for Estimating Sleep Apnea Index in the Elderly Suffering from Sleep Disturbance Bingh Tang and Weizhong Yan Hormones and Insomnia Axel Steiger and Mayumi Kimura

1 35

69

103 135

161

191 205

vi Chapter IX

Contents Insomnia Among Suicidal Adolescents and Young Adults: A Modifiable Risk Factor of Suicidal Behaviour and A Warning Sign of Suicide? Latha Nrugham and Vandana Varma Prakash

Chapter X

Melatonin and Nocturia Kimio Sugaya, Saori Nishijima, Katsumi Kadekawa and Minoru Miyazato

Chapter XI

Melatonin and Other Sleep-Promoting Melatoninergic Drugs Under the Aspects of Binding Properties and Metabolism Rüdiger Hardeland

Chapter XII

Melatonin for Medical Treatment of Childhood Insomnias Jan Froelich and Gerd Lehmkuhl

Chapter XIII

Melatonin: Its Significance with Special Reference to Sedation and Anesthesia Argyro Fassoulaki, Anteia Paraskeva and Sophia Markantonis

Chapter XIV

Sleep Disturbance in Obsessive-Compulsive Disorder Enrico Pessina, Sylvia Rigardetto, Umberto Albert, Filippo Bogetto and Giuseppe Maina

Chapter XV

Effects of Sunbathing on Insomnia, Behavioural Disturbance and Serum Melatonin Level Keiko Ikemoto

Chapter XVI

Neuroimaging Insights into Insomnia Martin Desseille, Thien Thanh Dang-Vu, Manuel Schabus, Kerstin Hoedlmoser, Camille Piguet, Maxime Bonjean, Sophie Schwartz and Pierre Maquet

227 249

273 291

303 315

329 337

Chapter XVII Neuroimaging Insights into the Dreaming Brain Martin Desseilles, Thien Thanh Dang-Vu, Manuel Schabus, Virginie Sterpenich, Laura Mascetti, Ariane Foret, Luca Matarazzo, Pierre Maquet and Sophie Schwartz

357

Index

375

Preface Melatonin is a naturally occurring hormone that is released into the body when the eyes register that it's getting dark. When the eyes send the message to the brain that darkness is falling, a gland in the brain (the pineal gland) releases melatonin, which then signals the body to "wind down" and prepare for sleep. Melatonin regulates our waking and sleeping cycles in addition to performing other jobs. Consequently, insomnia is a symptom of a sleeping disorder characterized by persistent difficulty falling asleep or staying asleep despite the opportunity. Insomnia is a symptom, not a stand-alone diagnosis or a disease. By definition, insomnia is "difficulty initiating or maintaining sleep, or both" and it may be due to inadequate quality or quantity of sleep. It is typically followed by functional impairment while awake. This new and important book gathers the latest research from around the world in the study of melatonin and insomnia with a focus on such topics as: the neuropathology of insomnia in adults, hormones and insomnia, insomnia among suicidal adolescents, melatonin and nocturia, melatonin and its significance with anesthesia and sedation, and others. Chapter I - Insomnia has become fully recognized as one of the most prevalent sleep disorders in society with a profound impact on multiple aspects of daytime functioning and quality of life. Major advances in the non-pharmacological approach to insomnia include the work of Morin and colleagues on the behavioral and cognitive treatment of insomnia and the introduction of the behavioral model published by Spielman and Glovinsky (1991). Other researchers quickly followed resulting in an increasing amount of studies validating this perspective with its separate components. In the last 15 years, the nature of the conditioned arousal as one of the components in this model has been a major topic of interest. In this context, the neurocognitive model, published by Perlis and colleagues in 1997, argues for the extension of the arousal concept with a third component: cortical arousal. The latter is reflected by high frequency EEG activity during sleep, which is thought to mirror the lack of cognitive deactivation, resulting in a disruption of the normal sleep onset and maintenance processes. Some studies have shown the presence of high frequency EEG activity during the sleep onset period, NREM and REM sleep. Furthermore, beta and gamma EEG activity seem to be related to the subjective misperception of sleep, so often seen in insomnia patients. However, other studies revealed no significant differences in the sleep EEG between insomnia patients and controls. In addition to the theoretical overview, this chapter includes a

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study exploring the different arousal components in a group of selected insomnia patients with objective findings. Seventeen insomnia patients diagnosed according to DSM-IV criteria and 12 healthy controls were included in our study. Next to a general assessment of hyperarousal through the use of cortisol assay and questionnaires, a wake EEG and polysomnography were performed to evaluate the presence of cortical hyperarousal both during wakefulness and sleep. In comparison to a control group, insomnia patients experienced more cognitive and emotional arousal, but no increase in physiological arousal, both subjectively as well as objectively. Indications of cortical arousal were only present during the sleep onset period, reflected by a stable alpha EEG level and slower increase of delta power, related to longer sleep onset latencies. Furthermore, the cortical arousal variables were correlated significantly with objective sleep disruption, not with sleep perception. Together with previous studies, these results point to a large variability in insomnia patients as to the expression of hyperarousal and its different components. Chapter II – Insomnia Insomniais a very frequent symptom, usually due to non organic brain diseases. In some organic brain disorders, however, sleep impairment occurs through a series of mechanisms: structures responsible for need for sleep are lesionned ; the biological clock doesn‘t give the start for sleep; sleep networks responsible for inhibition of waking structures are not efficient; mechanisms carrying on sleep or responsible for waking stages are damaged. In each case, examples of those brain disorders leading to insomnia (tumors, strokes, traumas, neurodegenerative disorders) are reviewed, focusing on the neuropathological description of structures involved in sleep network. When possible, clinicopathological correlates are suggested. Chapter III - There is already profound knowledge about the evidence that cognitive behavioral therapy (CBT) is effective for the treatment of insomnia (Benca, 2005; Morin et al., 1999; Morin, 2004; Morin et al., 2006). However, the characterization of nonpharmacological treatment effects like CBT on specific sleep parameters (e.g., sleep spindles, sleep architecture, electroencephalographic (EEG) power densities during sleep after CBT) are scarce (Cervena et al., 2004). In our approach we investigated if instrumental conditioning of 12-15Hz EEG oscillations would enhance sleep quality as well as declarative memory performance in healthy subjects. Additionally preliminary data indicating instrumental conditioning of 12-15Hz EEG oscillations as a promising treatment of insomnia will be presented. EEG recordings over the sensorimotor cortex show a very distinctive oscillatory pattern in a frequency range between 12-15Hz termed sensorimotor rhythm (SMR). SMR appears to be dominant during quiet but alert wakefulness, desynchronizes by the execution of movements and synchronizes by the inhibition of motor behavior. This frequency range is also known to be high during light non-rapid eye movement (NREM) sleep, and represents the sleep spindle peak frequency. In the early 70ies Sterman, Howe, and MacDonald (1970) could demonstrate in cats that instrumental conditioning of SMR during wakefulness can influence subsequent sleep. Hauri (1981) was then the first to apply effectively a combination of biofeedback and neurofeedback to humans suffering from psychophysiologic insomnia. Results revealed that the patients benefited from the instrumental conditioning protocols. As research surprisingly stopped at that point, we

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intended to clarify the effects of instrumental SMR conditioning (ISC) on sleep quality as well as on declarative memory performance with today‘s technologies and by using a well controlled design which included a control group receiving the same amount of attention and training. Our results confirmed that within 10 sessions of ISC it is possible to increase 1215Hz activity significantly. Interestingly, the increased SMR activity (i) was also expressed during subsequent sleep by eliciting positive changes in various sleep parameters like sleep spindle number or sleep onset latency and (ii) was associated with the enhancement of declarative learning. In addition to these fascinating results, preliminary data from our laboratory point to the possibility that people suffering from primary insomnia could likewise benefit from this conditioning protocol as indicated by improved measures of subjective and objective sleep quality. Chapter IV - More than half of the preschoolers/students in Japan have recently complained of daytime sleepiness, while approximately one quarter of junior and senior high school students reportedly suffer from insomnia. These children might suffer from behavioral-induced insufficient sleep syndrome due to inadequate sleep hygiene, and conventional therapeutic approaches often fail. The present study addressed whether asynchronization, a novel clinical notion, could be responsible for the pathophysiology of these sleep disturbances and could provide a better understanding for successful interventions. This clinical concept was designed with special reference to the basic concept of singularity. The essence of asynchronization comprises disturbances in various aspects (e.g., cycle, amplitude, phase, and interrelationship) of biological rhythms that normally exhibit circadian oscillation. These disturbances presumably involve decreased activity of melatonergic and serotonergic systems. The major triggers for asynchronization are hypothesized to be a combination of light exposure during the night, which decreases melatonin secretion, as well as lack of light exposure in the morning, which decreases activity in the serotonergic system. Prevention of asynchronization must include acquisition of morning light and avoidance of nocturnal light. Possible potential therapeutic approaches for asynchronization involve conventional and alternative therapies. We should know more about the property of the biological clock. Chapter V - In 2005, a report from the United Nations Populations Division noted that the number of individuals aged 60 years and older is expected to nearly triple, increasing from 672 million in 2005 to almost 1.9 billion by 2050. Currently the elderly population in developed countries has surpassed the number of individuals under the age of 14 years, and by the year 2050 it is anticipated that there will be two elderly persons for every child. Population aging is thus anticipated to precipitate a situation in the United States where health care needs for older-adult populations may exceed care access and availability. This may be particularly pressing in the case of mental health conditions accompanied by behavior that put individuals at physical risk. It has been reported that 27% of all workplace violence occurs in nursing homes. Aggressive behavior by older individuals with mental disorders incurs substantial humanitarian and financial burden on patients, families and society at large. This review will address aggression in elderly populations with general medical conditions that include delirium, toxic states and drug-drug interactions as well as in populations with dementing illness, mood and anxiety disorders and psychotic disorders. A pragmatic approach

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optimizing safety and quality of life for individuals, families and caregivers is stressed. Lastly, recommendations for future research in late-life aggressive behavior are provided. Chapter VI – Population aging has materialized as an innovative demographic inclination with imperative insinuation for government programs, public health and education, and family restructuring. Among such changes, insomnia, snoring and sleep apnea, in conjunction with sleep hygiene have been usually ignored. Changes in sleep are part of the ageing process. Nocturnal total sleep time can become more fragmented with age, with an increase in awaking early in the morning and nighttime awakenings. Body mass Index (BMI) and body weight have important health and educational implications across the lifespan. Most recent attention has been focused on the issue of obesity, an epidemic that occurs in most parts of the world. Yet the older Filipinos have prevalence of underweight, approximately thirty per cent of the population, while that of overweight close to ten percent. By comparison, in Taiwan, the prevalence of underweight is less than ten percent, while approximately thirty percent of Taiwanese elderly are overweight. The main purpose of this chapter is to signify the economic and cultural impacts on healthy weight and BMI maintenance in potentially decreasing the prevalence of sleep disturbance and improving quality of the elderly life in two Asian societies. With advancing age, age-related changes have been described for sleep–wakefulness and additional behavioral cycles. Trends in the relationship between elderly sleep disturbance and BMI in the observed two societies merit our serious attention. Further study is necessary to investigate whether the differences between two societies are caused the limitation of hospital-based study or by differences in ethnicity. Chapter VII – Objective: The main objective of this chatper is to present a novel model for classifying senior patients into different apnea/hypopnea index (AHI) categories based on their clinical variables. Methods and materials: The proposed model is a generalized regression neural network (GRNN). Three important variables were first selected from the original 30 clinical variables. The GRNN was trained using 75 patients that were randomly selected from the 117 patients. The remaining 42 patients were used for testing GRNN model. The design parameter of the network, i.e., the spread of the radial basis function, was empirically optimized. To alleviate the model complexity, the original AHI values were dichotomized into two different groups, i.e., AHI>13 and AHI<=13. The use of GRNN for this application appear fairly novel, notwithstanding that there is a host of literature on predicting obstructive sleep apnea (OSA) syndrome from demographic or other easy means to assess clinical variables. Results: The proposed model has sensitivity and specificity of 95.7% and 50.0%, respectively, for the training cases, while 88.0% and 52.9%, respectively, for the testing cases. Conclusions: The proposed neural network model has outperformed existing classification approaches in terms of classification accuracy and generalization, thus it can be potentially used in clinical applications, which would lead to a reduction of the necessity of in-laboratory nocturnal sleep studies. Chapter VIII - Human sleep is characterised by an electrophysiological component, which is recorded by the sleep EEG, and by distinct patterns of the secretion of various

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hormones. A bidirectional interaction exists between these two components of sleep. During disturbed sleep, changes of sleep EEG and of hormone secretion occur. For example during an episode of depression and during normal ageing, slow wave sleep and growth hormone (GH) secretion decrease whereas wakefulness increases and the activity of the hypothalamopituitary-adrenocortical (HPA) system is changed. During depression and during primary insomnia, elevated HPA activity is mirrored by increased cortisol levels. There is much evidence from preclinical and clinical studies that various neuropeptides and steroids participate in sleep regulation, and that changes in their activity contribute to disturbed sleep. The reciprocal interaction of the peptides growth hormone-releasing hormone (GHRH) and corticotropin-releasing hormone (CRH) plays a keyrole in sleep regulation. In young normal male subjects, GHRH promotes slow wave sleep and GH secretion, whereas CRH exerts opposite effects. Changes in the GHRH/CRH ratio in favour of CRH are thought to result in disturbed sleep, particularly in insomnia-related depression (CRH overactivity) and in normal ageing (reduced GHRH activity). Treatment with a CRH-1 receptor antagonist was shown to improve sleep in patients with depression. The menopause is a major turnpoint of sleep quality in women. In postmenopausal women the levels of circulating estrogens and progesterone are low. Replacement therapy with these steroids improved sleep in postmenopausal women. Chapter IX – This chapter examines existing research literature on sleep difficulties, primarily insomnia and the various dimensions of suicidality among adolescents and young adults as compared to adults. Studies have been grouped into epidemiological studies, clinical studies and reviews. Findings on gender have been given special importance. The literature overview has been complemented by case vignettes from a major corporate hospital in New Delhi (India). The chapter concludes by stating that a relationship appears to exist between insomnia and suicidality, especially with completed suicide, regardless of age. However, far too little is known about the relationship for clinicians to be able to use it as research evidence, as almost all the findings on suicidal behaviour came from cross-sectional studies, whether epidemiological or clinical. Therefore, the conclusion calls for research studies with a prospective design. Chapter X - Nocturnal frequency of urination (nocturia) is common in the elderly, and it is one of the most troublesome urologic symptoms. Urinary frequency interferes with daily activities, while nocturia may also result in sleep disturbance that can cause daytime fatigue as well as worsening the quality of life (QOL). Multiple factors may contribute to the occurrence of nocturia, including pathological conditions such as cardiovascular disease, diabetes mellitus, lower urinary tract obstruction, anxiety disorders or primary sleep disorders, and various other behavioral and environmental factors. Recently published guidelines have attributed the occurrence of nocturia to nocturnal polyuria and/or diminished nocturnal bladder capacity. However, since these factors may express the states of nocturia rather than the causes, it remains difficult to develop effective treatments for nocturia if the underlying etiology is not determined. Accordingly, in order to investigate which factors are strongly related to occurrence of nocturia, we performed a suite of examinations in elderly persons who had nocturia without any other diseases (elderly nocturia group) and two (young adult and elderly) control groups. As the results, sleep disturbance (a decrease of the nighttime plasma melatonin level),

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hypertension (an increase of nighttime plasma catecholamine levels), and excessive fluid intake (an increase of total urine volume) were major factors contributing to nocturia in the elderly. On the other hand, some elderly persons do not consider nocturnal urination to be bothersome even if they have a number of episodes. So, as a next step, the factors related to nocturnal urination that was not considered bothersome by comparing biochemistry tests were investigated between subjects who felt nocturnal urination ( twice per night) as bothersome and those who did not. As the results, the plasma melatonin level was lower in the bothersome group than in the non-bothersome group. Therefore, nocturnal urination might be not considered bothersome when subjects maintain sufficient levels of melatonin. As the third step, the effects of melatonin and the hypnotic, rilmazafone, on nocturia were compared in the elderly patients. After 4 weeks‘ treatment, the number of nocturnal urinations was decreased and the QOL score was improved in both groups. Melatonin and rilmazafone were equally effective for nocturia in the elderly, and the plasma melatonin level was increased in the melatonin-treated group. Therefore, the decrease of the plasma melatonin level may be one of the most important causes of nocturia, and sleep disturbance should be considered when choosing a therapy for nocturia. Chapter XI - In humans and other diurnally active mammals, melatonin acts as a sleeppromoting agent, but, for practical purposes, its short half-life in the circulation has been a major obstacle. Two different approaches have intended to overcome this problem, the development of slow-release pills and of other melatoninergic agonists, such as ramelteon and agomelatine, representing two non-indolic analogs of melatonin. With regard to sleep, melatonin and these analogs are acting in the same way, via the membrane-bound, highaffinity melatonin receptors MT1 and MT2 in the suprachiasmatic nucleus, which controls the hypothalamic sleep switch. Ramelteon displays a considerably higher receptor affinity, in conjunction with a much longer lifetime in the circulation, plus a contribution of one of its metabolites, M-II, to the melatoninergic actions. The affinities of agomelatine are close to those of melatonin, but the half-life of the analog is longer. In addition, agomelatine was shown to inhibit the serotonin receptor subtype 5-HT2C, an effect associated with additional antidepressive actions. In spite of the similarities with regard to sleep, several profound differences between the three compounds may be of importance. The use of slow-release melatonin should exert a much broader spectrum of effects, since this indoleamine acts, in addition to MT1 and MT2, via other binding sites, too, such as subtypes of the nuclear receptors ROR and RZR, quinone reductase 2, calmodulin, calreticulin and mitochondrial binding proteins. The actions of ramelteon and agomelatonine seem to be much more specific for the membrane receptors, although binding to the last-mentioned proteins has not yet been tested. Another profound difference concerns the metabolism of the agonists. The non-indolic compounds are hydroxylated, dealkylated or further oxidized in positions not homologous to those of the natural indoleamine. The entire kynuric pathway of melatonin metabolism is absent in ramelteon and agomelatine. Since biological effects have been ascribed to the melatonin-derived kynuramines AFMK (N1-acetyl-N2-formyl-5-methoxykynuramine) and AMK (N1-acetyl-5-methoxykynuramine), this sector of melatonin‘s actions is missing. To date it is difficult to judge whether the full spectrum of melatonin‘s effects represents an

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advantage of the parental compound, when only sleep promotion is intended, or whether the higher selectivity of the analogs for membrane receptors will turn out to be a favorable property. However, the poorly understood actions of metabolites from ramelteon and agomelatine, including disproof or proof of toxicity, may be relevant for a future decision on the most suitable compound. Chapter XII - Sleep disorders in childhood and adolescence are regarded as a common manifestation of symptoms of a disorder, mostly transitory in nature and in many cases caused by unsatisfactory sleep hygiene or maladjusted parent-child interaction during the falling asleep and sleeping through the night process. Furthermore, sleep disorders could exhibit comorbid symptoms with manifestations of psychiatric and neurological diseases [16, 17]. In these cases, they are often chronic and partially also serious in nature. In most cases, during consultation behaviorial therapeutic measues are indicated and are also sufficient. With manifestations of chronic disorders, medicinal measures play an important role [45]. Thus far, the use of an antihistamine, benzodiazepine or a neuroleptic can only be used with reservation or at least in the short term due to long-term side effects, the potential for dependency and substantial negative impacts on daytime alertness and memory functions [45]. With melatonin as an endogenous sleep-inducing hormone, for the first time a pharmacological treatment method essentially free of side effects could be offered for children. This paper summarizes the current, however still relatively narrow-based findings. The literature search is based on Medline-Search, in which substantial papers have been stored since 1985. Due to the still very provisional study status however, this could not consider exclusively randomized studies. Chapter XIII - Melatonin has been used to relief preoperative anxiety and stress. Several investigators reported that melatonin produces preoperatively anxiolysis and sedation. Patients undergoing laparoscopic cholecystectomy and pretreated with melatonin or midazolam exhibited less anxiety and increased sedation preoperatively compared with the controls. Similarly, patients undergoing gynecological laparoscopic surgery and premedicated with 5 mg of melatonin or with 15 mg of midazolam, or placebo were sedated in contrast to the control group. Psychomotor impairment after premedication was observed only in patients treated with midazolam. However, these effects are not reproducible by other studies. In elderly patients undergoing elective surgery 5 mg of melatonin or placebo given by mouth decreased anxiety scores to a similar degree. Melatonin premedication did not enhance the induction of anesthesia with sevoflurane as assessed by the bispectral index (BIS) monitor. Regarding the effect of sedative interventions and anesthesia on the endogenous melatonin release, acupuncture and acupressure may or may not affect melatonin levels. Also the inhalation anesthetic sevoflurane has been reported to decrease or to have no effect on endogenous melatonin. The different results may be attributed to the great variability associated with the measurements in melatonin levels, the different anesthetic techniques and co-administration of other agents, different populations in the relevant studies and other undetermined factors. Nevertheless, the interaction of sedative and anesthetic techniques with melatonin and vice versa is challenging and provocative in understanding the underlying mechanisms of sedation and anesthesia.

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Chapter XIV - Introduction: Obsessive-Compulsive Disorder (OCD) is a common, chronic disorder which results in marked distress and impairment of social and occupational functioning. Sleep disturbance often accompanies mental disorders, but there have been few studies of sleep disturbance in OCD. These have produced contradictory findings, with some reporting sleep disruption, and others a normal sleep pattern. The aim of the present study is to examine sleep patterns in OCD, to establish the frequency of the different types of insomnia (early, middle and late insomnia) in a sample of patients with OCD. The study also intends to determine whether the presence of a comorbid mood disorder influence frequency and type of insomnia. Methods: all patients with a primary diagnosis of OCD (according to DSM-IV criteria) consecutively referred to the Mood and Anxiety Disorder Unit, Department of Neuroscience, University of Turin, from January 2003 to June 2008, were recruited. Frequency and severity of the different types of insomnia were evaluated on the basis of the Hamilton Depression Rating Scale (HDRS) specific items score (item 4-5-6). A statistical comparison between OCD patients with and without insomnia was performed to examine whether there was any difference in clinical features. Then a statistical comparison between patients with and without depressive comorbidity was performed to examine whether there was any difference in prevalence and type of insomnia. Results: The sample included 315 OCD patients. More than a half of the sample suffered from any type of insomnia. The most frequent type of insomnia was early insomnia (about 44,8%). We didn‘t find a positive correlation between the severity measured with total YBOCS score or obsessions and compulsions sub-score clinical and socio-demographic features and insomnia. The presence of any comorbid depressive disorder increased the frequency of insomnia. Chapter XV - It has been suggested that sunbathing may increase the amplitude of the sleep-wake rhythm and nocturnal serum melatonin secretion, and have effects on insomnia as well. A case report of a patients with epilepsy, cerebral palsy, and severe mental and intellectual disabilities (SMID) with severe behavioral disturbance is presented, in which the sleep-wake-cycle (SWC) was markedly improved by a sunbathing for seven months. The schedule included a sunbathing for 30 minutes in the morning, and a walk with a sunbathing for 10～30 minutes in the afternoon. Reduction of frequency of excitement and pyrexia was also observed, and the latter effect persisted for more than six months after the completion of this schedule. In the present case, being similar to the effects of light therapy for insomnia in elderly persons, low level of nocturnal melatonin level exhibited a tendency toward normalization. These findings show that a sunbathing is an effective and simple method for the treatment of insomnia and behavioral disturbance associated with severe mental retardation. The effects of light therapy and / or a sunbathing on insomnia and serum melatonin level, particularly in individuals with brain damages, are reviewed based on the literatures. Chapter XVI – Insomnia is a frequent symptom or syndrome defined by complaints of trouble in initiating or maintaining sleep or of nonrestorative sleep. This causes significant impairments in several areas of daytime functioning including mood, motivation, attention and vigilance.

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Significant advances in our neurobiological knowledge of insomnia have been brought by electrophysiological data (e.g. electroencephalography (EEG) and by functional neuroimaging data (e.g. single photon emission computed tomography (SPECT), positron emission tomography (PET) acquired during wakefulness, transition from waking to non rapid-eye-movement (NREM) sleep and REM sleep itself. Indeed it has been shown that idiopathic insomnia is characterized by a specific pattern of regional brain activity: (i) during the transition from waking to NREM sleep: failure to decrease brain activity in the ascending reticular activating system, medial prefrontal cortex, limbic/paralimbic areas (including insular cortex, amygdala, hippocampus, anterior cingulate), thalamus and hypothalamus, (ii) during NREM sleep: deactivation of the parietal and occipital cortices, and basal ganglia, and (iii) during wakefulness: deactivation in brainstem reticular formation, thalamus, hypothalamus, prefrontal, left superior temporal, parietal and occipital cortices. This specific distribution of brain activity might relate to (i) specific impairments in daytime functioning (e.g. hypoactivity in prefrontal cortex during wakefulness is consistent with reduced attentional abilities), (ii) hyperarousal hypothesis as a common pathway in the pathophysiology of insomnia (e.g. overall cortical hyperarousal characterized by an increase in EEG beta/gamma activity (14-35 / 35-45 Hz) at sleep onset and during NREM sleep) and (iii) the potentially overlapping pathophysiology with major depressive disorder as this illness has shown similarly altered cortical patterns (e.g. both illnesses have impairments in limbic/paralimbic areas as well as in basal ganglia). The goal of this chapter is to show that combining recent neurophysiological and neuroimaging data on human sleep offers new insights into the pathophysiological mechanisms of insomnia and potentially opens new therapeutic perspectives. Chapter XVII - Dreams are sensory, cognitive, and emotional experiences that occur spontaneously during sleep. Dream reports tend to be more frequent, vivid, and longer during rapid eye movement (REM) sleep than during non-REM sleep. This is why our current neurobiological knowledge about dreaming primarily derives from functional neuroimaging data acquired during REM sleep (e.g. electroencephalography, positron emission tomography, and functional magnetic resonance imaging). Recent neuroimaging results showed that REM sleep is characterized by a specific pattern of regional brain activity: (i) activation of the thalamus, pons, temporo-occipital and limbic/paralimbic areas (encompassing amygdala, hippocampal formation and anterior cingulate cortex), and (ii) deactivation of the dorsolateral prefrontal and inferior parietal cortices. This heterogenous distribution of brain activity might relate to some characteristic dream features (e.g. amygdala activation is consistent with frequent threat-related emotions in dream reports). Reciprocally, specific dream features suggest the activation of specific brain regions during sleep. Based on these observations, we previously proposed that a neuropsychological or cognitive neuroscience approach to dreaming can usefully contribute to the interpretation of neuroimaging maps of sleep. The goal of this chapter is to show that connecting recent neurophysiological and neuroimaging data on human sleep and the content of dreams offers new insights into the brain correlates of dreaming and possibly into dream functions.

In: Melatonin, Sleep and Insomnia Editor: Yolanda E. Soriento

ISBN: 978-1-60741-859-7 ©2010 Nova Science Publishers, Inc.

Chapter I

Conditioned Arousal in Insomnia Patients: Physiological, Cognitive, Cortical—An and/or Question? Aisha Cortoos, Elke De Valck and Raymond Cluydts Unit of Biological Psychology, Vrije Universiteit Brussel, Belgium

Abstract Insomnia has become fully recognized as one of the most prevalent sleep disorders in society with a profound impact on multiple aspects of daytime functioning and quality of life. Major advances in the non-pharmacological approach to insomnia include the work of Morin and colleagues on the behavioral and cognitive treatment of insomnia and the introduction of the behavioral model published by Spielman and Glovinsky (1991). Other researchers quickly followed resulting in an increasing amount of studies validating this perspective with its separate components. In the last 15 years, the nature of the conditioned arousal as one of the components in this model has been a major topic of interest. In this context, the neurocognitive model, published by Perlis and colleagues in 1997, argues for the extension of the arousal concept with a third component: cortical arousal. The latter is reflected by high frequency EEG activity during sleep, which is thought to mirror the lack of cognitive deactivation, resulting in a disruption of the normal sleep onset and maintenance processes. Some studies have shown the presence of high frequency EEG activity during the sleep onset period, NREM and REM sleep. Furthermore, beta and gamma EEG activity seem to be related to the subjective misperception of sleep, so often seen in insomnia patients. However, other studies revealed no significant differences in the sleep EEG between insomnia patients and controls. In addition to the theoretical overview, this chapter includes a study exploring the different arousal components in a group of selected insomnia patients with objective findings. 17 insomnia patients diagnosed according to DSM-IV criteria and 12 healthy controls were included in our study. Next to a general assessment of hyperarousal through the use of cortisol assay and questionnaires, a wake EEG and polysomnography

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Aisha Cortoos, Elke De Valck and Raymond Cluydts were performed to evaluate the presence of cortical hyperarousal both during wakefulness and sleep. In comparison to a control group, insomnia patients experienced more cognitive and emotional arousal, but no increase in physiological arousal, both subjectively as well as objectively. Indications of cortical arousal were only present during the sleep onset period, reflected by a stable alpha EEG level and slower increase of delta power, related to longer sleep onset latencies. Furthermore, the cortical arousal variables were correlated significantly with objective sleep disruption, not with sleep perception. Together with previous studies, these results point to a large variability in insomnia patients as to the expression of hyperarousal and its different components.

Introduction Sleep is a behavior we engage in approximately one third of our lives. Falling asleep and staying asleep is a natural phenomenon for most people. However, approximately 10 to 20% of the population report difficulties initiating or maintaining sleep, accompanied by impairment of one or more aspects of daytime functioning [1]. When facing the fact that sleep initiation is delayed or has to be repeated several times during the night, the process of falling asleep loses its obvious characteristics and becomes a conscious and often frustrating task. Most people encounter this kind of situation at least once in their lives. Often a stressful or disruptive event causes the temporary sleep difficulties, which in turn will disappear when the stressor fades away. However, some people are more sensitive to a disruption of their sleep-wake rhythm and will continue having sleep problems even when the initial cause has disappeared. Often reported characteristics of sleep initiation or reinitiating problems are the presence of ‗racing thoughts, rumination and a state of alertness‘ at a time and place when relaxation is necessary [2, 3]. In reaction to the resulting sleep difficulties, behavioral coping strategies are developed, aiming at an increase of sleep time. When this process is repeated for a period of time, it becomes connected or linked to the specific environment within which it occurs; a phenomenon called conditioned arousal. The development of this subtype of insomnia is well described and widely known as the behavioral model [4]. Sleep is considered a complex behavior, partially dependant on daytime stimuli. The focus lies on the conditioned arousal, manifesting itself on different levels, such as anxiety, muscle tension, destructive and/or obsessive cognitions about sleep, and the consequences of sleep shortage. Within this model, the so-called 3 Ps (predisposing, precipitating and perpetuating factors) describe the 3 most important factors playing a key role in the development of insomnia [5]. First of all, it is suggested that insomnia patients are characterized by predisposing factors, making them more sensitive to sleep disruptive phenomena. These trait or predisposing factors can be related to personality traits, biological and/or psychological factors. At this point, however, a significant sleep disruption should not be present. It is only with the occurrence of a precipitating factor, mostly a stressful life event, that an interference of normal sleep processes takes place. As a reaction to the delayed and/or fragmented sleep period certain behavioral strategies, such as an extended time in bed, are employed as a way of ‗catching up‘ on sleep. These strategies or perpetuating factors, however, reinforce the relationship between wakefulness and the bedroom, which in turn will

Conditioned Arousal in Insomnia Patients

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result in conditioned arousal, and finally in a more severe sleeping problem. At this point a negative vicious cycle is installed, maintaining the sleep disruption and its facilitating processes. Within this model it is assumed that the sleep disturbances in chronic insomnia are maintained because of these perpetuating factors, which in turn form the focus of attention for treatment interventions.

The Concept of Arousal: Validation of the Behavioral Model Arousal mechanisms are essential for surviving and have an adaptive function enabling our most basic behaviors, such as movement, sleep, rest, wakefulness, and danger orientation. As such, arousal is part of our daily life and makes it possible to perform certain physical and/or mental tasks. However, the perception of arousal may vary according to the possible presence of emotions related to the situation [6]. Performing sports after work will often not be recognized as a situation of arousal, although all characteristics of physical arousal are present, such as muscle activation, increased heart rate and ventilation. However, when confronted with a possible dangerous situation, we are more aware of the changes inducing a state of arousal. Together with the physical preparation, our cognitive system reacts as well, by scanning the environment for dangerous cues, and as such selective attentional processes are activated. Chronic insomnia patients tend to perceive sleep-related situations, such as the bedroom and bedtime, as stressors, as such inducing an arousal response, as proposed by the behavioral model. This theoretical perspective has given rise to a growing amount of research concentrating on the assessment of different arousal components in insomnia patients. One of the major difficulties in these studies, however, is the differentiation of the different arousal components involved, because of possible similarities in the underlying etiologies [7].

Physiological Arousal The process of falling asleep is accompanied by a series of events indicating a deactivation of several bodily systems, as such reflecting a state of physiological de-arousal [8]. During sleep onset, a decrease in muscle activation of the upper airway dilator muscles and respiratory pump muscles result in a fall in ventilation [9], which is also accompanied by a gradual decrease in heart rate [10]. Although EMG changes during sleep onset are not often studied in detail, findings regarding other related topics of sleep onset, such as passive behavioural sleep devices or changes in respiratory activity, suggest a decrease in overall EMG activity during sleep onset. In light of these findings, it is obvious that an interference of physiological deactivation can result in an impairment of sleep onset processes, a phenomenon called physiological arousal. This can be often observed in insomnia patients. One of the first studies assessing aspects of physiological arousal [11] showed that insomnia patients were characterized by elevated rectal temperature, skin resistance, and phasic vasoconstrictions. Hyperarousal was present half an hour before bedtime, as well as during sleep. This study was the starting point for many other researchers evaluating the

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Aisha Cortoos, Elke De Valck and Raymond Cluydts

possible link between physiological arousal and sleep disturbances. Freedman and Sattler [12] and Freedman [13], for example, revealed that insomnia patients dominantly suffering from sleep onset problems, featured increased facial muscle activity during the sleep onset period, as well as increased beta and decreased alpha EEG activity during wakefulness, phase 1 and REM sleep. Other studies reported increased heart rate in insomnia patients during the night [14, 15], as well as in the morning when confronted with a stressful event [14]. Moreover, there appears to be a correlation between specific alterations in body temperature, related to impairments of the circadian rhythm, and different types of insomnia [16]. Sleep onset insomnia might partially be associated with a delay in temperature rhythm. As such, they try to fall asleep during their ―wake maintenance zone‖ [17] resulting in increased sleep latencies. Early morning awakening insomniacs, on the other hand, appear to be characterized by a phase advanced temperature rhythm, causing an early circadian wake up time. Sleep maintenance insomnia apparently is not associated with a temperature rhythm impairment, but with overall nocturnal elevated body temperature [18]. Finally, it is suggested that insomnia patients suffering from a combination of sleep-onset and maintenance problems are associated with a 24-hour elevated core body temperature [16]. The mediating role of the hypothalamic-pituitary-adrenal (HPA) axis has been another main focus in arousal studies in insomnia patients. Some studies have shown that insomnia patients have increased levels of evening cortisol, which are also correlated with the amount of awakenings during the night [19-21]. Backhaus et al. [22], on the other hand, only found decreased cortisol levels in the morning, negatively correlated with the reported subjective sleep quality. Although these studies report different results, they all mention some impairment of hormones related to the HPA axis. Therefore, it can be proposed that the hypothalamic-pituitary-adrenal (HPA) axis is overactivated, mostly due to stress and anxiety, keeping the cortisol levels high en thus interfering with normal sleep onset and maintenance processes [23, 24]. Despite these impressive results, other studies failed to find significant differences in the mentioned parameters of physiological arousal. Riemann and colleagues [25] for example, did not found elevated levels of evening cortisol, but only decreased levels of melatonin. No increased heart rate was found in the study by Monroe (1967). Varkevisser and colleagues [26] performed a 24-hour sleep deprivation protocol in insomnia patients and evaluated several indicators of physiological arousal (cardiovascular parameters, cortisol, and body temperature) but found no significant differences in comparison to healthy controls. These mixed results suggest a vast heterogeneity in regard to the presence and expression of physiological arousal in insomnia patients.

Cognitive Arousal As discussed above, falling asleep is accompanied by relaxation and deactivation of several bodily functions, which can be impaired at several levels in insomnia patients. However, a reduction in physiological processes is not the only requirement for a rapid sleep onset. The mind is a powerful and sometimes uncontrollable entity, processing all incoming information from external and internal stimuli during the day, which can also interfere with sleep onset. Increased presleep cognitive activity has been consistently associated with the


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maintenance of insomnia. Studies have repeatedly shown that insomnia patients experience intrusive thoughts, which are mostly negatively toned, as well as excessive worry, typically about sleep, the lack of sleep and its consequences on daytime functioning [27-29]. Studies evaluating self-reported attributions showed that insomnia patients report more presleep cognitive activity during the sleep onset period in comparison to healthy sleepers, and experience more sleep disturbances from presleep cognitive activity [30]. Furthermore, cognitive arousal appears to be more dominantly present as opposed to physiological arousal [3]. Besides the plain existence or presence of disruptive cognitive activity, it is also very interesting to evaluate its specific content in patients suffering from insomnia, especially in light of therapeutic interventions. Regarding the nature of cognitive activity, it has been reported that problem solving, worries and concerns, and listening to noises are a major focus of attention when trying to fall asleep [30]. Furthermore, thoughts about sleep shortage and re-evaluating the day are often reported. Another characteristic of insomniacs in comparison to healthy sleepers is the perceived control over presleep thoughts and worries. Whereas normal sleepers report that their presleep cognitive activity is intentionally, insomniacs describe this as being uncontrollable. Wicklow and Espie [31] conducted a study were they evaluated the content of intrusive thoughts and their relationship with actigraphic measured sleep and self report. Through the use of Principal Component Analysis, they were able to derive three major factors of intrusive thoughts. The first factor was referred to as ‗active problem solving‘, which correlated with objective sleep latency and was relatively unaffected by emotional tone. The second factor was ‗present state monitoring‘, reflecting selfawareness and self-monitoring. No connection was found with the objective sleep latency, but an inverse correlation was present with emotional tone. ‗Environmental reactivity‘ was the third factor, but no relations were found with any sleep parameter. Regarding the subjective sleep report, none of the factors apparently correlated with perception of sleep. The role of cognition in insomnia has been elegantly described by Harvey [32] in her paper ‗the cognitive model of insomnia‘. It is suggested that insomnia patients are overly worried about their sleep and the possible consequences of sleep shortage on daytime functioning, which results in ‗excessively negatively toned cognitive activity‘. This in turn leads to an arousal response and emotional distress, triggering selective attention towards all kinds of stimuli that are perceived as threads for a good night sleep. The combination of arousal and distress, as well as specific selective attentional processes cause a distortion in the perception of the sleep complaints and impairments in daytime functioning. This in turn fuels again the negatively toned cognitive activity, and is the starting point for a negative vicious cycle. In line with the behavioral perspective described earlier, this negative cognitive activity gives rise to certain beliefs about sleep and their sleep problem, as well as safety behaviors, comparable with the perpetuating factors of the behavioral model. Other researchers have also demonstrated the presence of a sleep related attentional bias. Taylor et al. [33] compared two groups of cancer patients with insomnia, the first group at 0-3 months and the second at 12-18 months after cancer diagnosis. All patients had been good sleepers before the diagnosis. Results from the Stroop paradigm showed that both groups presented an attentional bias for cancer words, but only the persistent insomnia patients who still experienced sleep disturbances a year after their diagnosis, demonstrated attention bias for sleep-related words. In a recent study, Spiegelhalder and colleagues [34] for example,

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compared insomnia patients, sleep experts and healthy controls using an emotional Stroop task. They found significant higher attentional bias scores in the insomnia group in comparison to the sleep expert group, suggesting that the attentional bias for sleep-related words is due to specific emotional, cognitive or procedural processing rather than differences in habitual exposure to these concepts. In summary, these results suggest that insomnia patients are characterized by some form of cognitive arousal, mainly consisting of thoughts concerning problem solving and monitoring. As is shown by Harvey‘s cognitive model of insomnia, specific selective attentional processes play an important role in the maintenance of insomnia, which in turn has been repeatedly shown by studies who found an attentional bias in insomnia patients for sleep related words or cues. Espie and colleagues [35] reviewed literature about attentional bias in insomnia patients and introduced an important sleep inhibitory process, namely the attention-intention-effort pathway. They point out that the automaticity of the sleep system in insomnia patients is inhibited by three factors: first, the selective attention to sleep; secondly, the explicit intention to sleep; and finally, a dysregulation by both direct and indirect sleep effort. As such, when considering therapeutic intervention, the cognitive processes and attentional bias should be an important focus of attention.

Clinical Applications: Cognitive and Behavioral Interventions for Insomnia The growing literature regarding physiological and cognitive arousal in insomnia patients resulted in studies evaluating different interventions aiming at a reduction of these arousal components. Since the 1970‘s the impact of different relaxation techniques on physiological arousal and sleep quality were examined. Borkovec and Fowles [36] for example, evaluated three different relaxation trainings as well as a waiting list no-treatment control group. They used progressive relaxation, hypnotic relaxation and self-relaxation as a way to influence physiological arousal in insomnia patients. They hypothesized that only the progressive and hypnotic relaxation groups would demonstrate significant improvement after training. However, results showed an equal improvement in sleep onset latency, number of awakenings and waking up refreshed in all three training groups. Surprisingly, the reduction in physiological arousal reflected by skin conductance, heart rate and respiration was not related to treatment outcome. The authors suggested that the general instruction in all groups to relax and focus on pleasant internal feelings might be the mediating factor responsible for the general improvement in all groups. As such they hypothesized that attention focusing may be enough as treatment intervention for moderate insomnia patients. A similar study was performed by Nicassio and Bootzin [37] using progressive relaxation and autogenic training as active treatment groups, and a self-relaxation and waiting list group as control groups. In contradiction with Borkovec and Fowles [36] they only found significant improvement after progressive relaxation and autogenic training, suggesting that the mere instruction to relax at a scheduled time is not enough to result in significant improvements in sleep. As their sample of insomnia patients had more severe sleep problems, it was also suggested that the selfrelaxation instruction may lose its value with increasing severity of the sleep complaints.


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In addition to this line of research, much attention has been paid to other behavioral interventions, mostly based on operant or instrumental conditioning. The use of ‗stimulus control‘ [38], for example, was one of the first interventions successfully applied in insomnia patients, which is based on the fact that spending to much time in bed is an important perpetuating factor playing a key role in the maintenance of the sleep complaints [4]. It has been shown that avoiding wakefulness in bed during the night as well as daytime napping results in a significant improvement of total sleep time, wake after sleep onset, sleep efficiency and sleep onset. The main objective of this intervention technique is to reassociate the sleep environment with relaxation and fast sleep onset, resulting in a new conditioned response as opposed to the arousal response leading to the reported sleep complaints. The American Academy of Sleep Medicine has recommended stimulus control instructions as a ‗standard‘ treatment for primary insomnia [39]. A second behavioral intervention that has received much attention is the use of ‗sleep restriction therapy‘ [40] were the time in bed is restricted to the reported total sleep time, as such that a mild sleep deprivation results in fast sleep onset latencies and increased sleep efficiency. In addition to these two major behavioral interventions, sleep hygiene instructions [29, 41] are recommended to ensure that poor sleep habits do not interfere with the beneficial effects of other interventions. Finally, in the 1990‘s cognitive therapy was introduced in order to directly intervene on the level of dysfunctional beliefs and attitudes about sleep [29]. These different components were then integrated into a multi-component treatment for insomnia, widely known as Cognitive Behavioral Therapy for Insomnia (CBT-I) [42]. The use of these different components in one integrated training program results in better outcome in comparison to single component treatment, and the addition of cognitive restructuring to the behavioral components causes slightly greater benefits than behavioral treatment alone [43]. Furthermore, it has been shown that CBT-I does induce a greater decrease in maladaptive beliefs and attitudes about sleep in comparison to relaxation therapy and placebo [44]. This effect is maintained at follow-up 6 months after completing the training program. Morin and colleagues [45] performed a similar study comparing a CBT-I group, pharmacotherapy, combined therapy of CBT-I and pharmaco and a placebo medication group. Again they showed that CBT-I or the combination of CBT-I with medication resulted in greater improvements of beliefs and attitudes about sleep. Furthermore, both studies showed that a decrease in maladaptive beliefs and attitudes were correlated with objective and subjective sleep improvement. Although CBT-I is regarded the gold standard for psychological management of insomnia, there are limitations, suggesting that a further exploration of additional interventions or treatments is still required [46]. First of all, the majority of insomnia patients following CBT-I show an average improvement that does not bring them into the good sleeper range, which means that they still show some impairment after treatment [46-48]. Secondly, the effect sizes after CBT-I training are markedly lower in insomnia patients in comparison to the effect sizes resulting from CBT in other psychophysiological disorders [46]. Thirdly, although the combination of CBT-I with pharmacotherapy might result in better improvements on the short term, Hauri [49] also showed that the progress obtained after a combined therapy are not maintained over a follow-up period of 10 months in

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comparison to the use of CBT-I alone. Fourthly, the different components of CBT-I, such as sleep restriction and stimulus control, require a certain amount of dedication and the will to make some changes in habitual life style to produce the desired effects, which is not always obvious [48]. Finally, it has to be noted that about 19% to 26% of patients do not respond to CBT-I [46, 48]. These observations suggest that a focus on physiological and/or cognitive/behavioral components of arousal might not be enough for a substantial group of insomnia patients, and other factors may be in play causing sleep disruption.

The Neurocognitive Model: Introduction of a New Arousal Component As a theoretical perspective on insomnia the behavioral model has been dominantly used since the 1980‘s, and it has given rise to new and efficient therapeutic interventions. However, some characteristics or paradoxes observed in insomnia patients can not be fully explained by this model [50]. A first paradox refers to the phenomenon perceiving ‗sleep‘ as ‗wakefulness‘. There appears to be a misperception of sleep resulting in a discrepancy between polysomnographically measured sleep and the subjective report through sleep logs [51-54]. Secondly, insomnia patients tend to overestimate the time needed to fall asleep and underestimate their total sleep time [11, 52, 55]. Thirdly, when using hypnotic medication there appears to be a discrepancy between the benefits reported by the patients and the objective gains [53, 56]. Furthermore, it has been shown that the administration of benzodiazepines does not normalize sleep; in fact it decreases SWS, while insomnia patients tend to report great benefits of them. In 1997, Perlis and colleagues introduced the neurocognitive perspective, an extension of the previous discussed behavioral model, which focuses on a third arousal component, namely cortical arousal [50]. They hypothesize that the presence of high frequency EEG activity during sleep reflects a state of hyperarousal, interfering with the normal sleep onset and maintenance processes. The presence of cortical arousal makes it possible to explain some of the mentioned paradoxes as cognitive alterations may result from high frequency EEG activity. It is suggested by the authors that cortical arousal results in heightened sensory and information processing. These cognitive alterations in turn are able to clarify certain characteristics of insomnia, such as the complaint of not falling asleep, the perceived misperception between wakefulness and sleep and the overestimation of wakefulness. The past decade research concerning cortical arousal in insomnia patients has received much attention and suggests that this sleeping disorder is characterized by the presence of high frequency EEG activity during sleep onset and sleep. Nevertheless, results are still inconsistent, probably due to different methodologies and inclusion criteria. On the other hand, literature shows that the presence of physiological and/or cognitive arousal is not a uniform phenomenon as well. Indeed, the insomnia population appears to be quite heterogeneous, which might also be the case for cortical arousal.


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Cortical Arousal As discussed in the previous sections, the concept of arousal in insomnia patients has traditionally been explained in terms of physiological and/or psychological processes. However, arousal can also be seen as a brain process reflected by changes in specific EEG frequency rhythms, referred to as cortical arousal. A state of arousal or high vigilance means that the brain is open to signals from the outside world, ready to process and react on these stimuli [57]. One of the most important structures in the brain involved in the control of information flow to the cerebral cortex is the thalamus. During sleep, synaptic inhibition occurs, blocking the incoming signals of being processed by the thalamus, as such the brain closes of from irrelevant external cues. The specific functions of the thalamus can be related to the EEG frequencies produced by this structure and measured on the scalp. The process of falling is asleep is normally characterized by a decrease of high frequency and an increase of slow frequency EEG activity [58, 59], reflecting the inhibition of incoming stimuli by the thalamus resulting in a slowing down of general brain EEG activity. Several studies have shown a different EEG pattern in insomnia patients during sleep onset and sleep, suggesting higher arousal levels in comparison to healthy sleepers. Freedman [13] was the first to investigate possible differences in EEG frequencies between insomnia patients and healthy controls. He examined the first minute of every sleep stage and found increased beta and decreased alpha EEG activity during wakefulness, stage 1 and REM sleep. Since possible EMG interferences were not taken into account, and patients were not screened for psychiatric disorders, these results should be interpreted with caution. Two other studies evaluated the specific EEG changes during sleep onset in insomnia patients [60, 61] and found decreased delta and alpha EEG power, as well as increased beta EEG power in comparison to healthy controls and even psychiatric insomniacs [60]. These results suggest an impairment of normal sleep onset processes, possible related to heightened cortical arousal. Moreover, the authors posit that the presence of beta EEG activity during sleep onset might also be related to the tendency in insomnia patients of overestimating sleep onset latency [60]. Finally, Staner et al. [62] assessed the sleep onset period and first NREM cycle in 21 controls, primary insomniacs and depressives. In contrast to the other studies, they found that insomnia patients were characterised by lower beta1 (13-21.5 Hz) EEG activity at the beginning of sleep onset, resulting in a relatively stable evolution during the sleep onset period. However, in line with the research of Lamarche and Ogilvie [60] they found decreased levels of alpha power. Both EEG frequencies however, are supposed to show a progressive decline during sleep onset. As such these results are interpreted as reflecting an impairment of the wakefulness propensity or a state of hyperarousal, interfering with normal sleep onset processes. Besides the EEG differences during the sleep onset period, there have also been some studies evaluating sleep EEG profiles during NREM and REM sleep. Merica, Blois and Gaillard [63] examined the first 4 NREM/REM cycles and found significant EEG difference in NREM, as well as in REM sleep. Decreased delta and theta and increased beta EEG activity were present in both NREM and REM stages. For alpha power a different pattern was found: this EEG rhythm was reduced during NREM and elevated during REM sleep. It is suggested that these results indicate on the one hand presence of cortical arousal reflected by

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heightened levels of beta activity during sleep, and on the other hand a slow wave sleep deficiency reflected by the lack of slow frequencies during NREM sleep, more specifically delta power. They proposed a neurophysiological interpretation combining two related theories, namely the neuronal group theory of sleep function [64] and the Neuronal Transition Probability (NTP) model [65] to clarify and combine both results. First of all, the neuronal group theory posits that alertness and sleepiness are two concepts of a continuum, in which the varying degree of these two states are dependent on the amount of sleep intensity. The perception of sleep, in turn, is dependant on the amount of neuronal groups being in a sleep (or disjunctive) state. As such, a lesser number of neuronal groups entering the disjunctive state might be a characteristic of insomnia patients, resulting in a part of the brain that remains alert or awake, reflected by higher levels of beta EEG activity. Secondly, the Neuronal Transition Probability model [65] makes use of the work of Steriade et al. [57] who showed that the hyperpolarisation of thalamocortical neurons produce delta oscillatory modes, resulting in SWA and deep sleep, and subsequent depolarization creating a disappearance of the delta oscillations leading to a transition to light sleep. This process is accompanied by oscillation changes of the neurons, following a sequence: beta – sigma – delta – sigma – beta [65]. In light of this model, their observation of a broader sigma peak and delayed delta peak in insomnia patients would suggest that the thalamocortical neurons become hyperpolarized at a slower rate, resulting in a slower transition from the sigma to the delta oscillatory mode [63]. Two more studies performed by Perlis and colleagues [66, 67] found increased beta1 (1420 Hz), beta2 (20-35 Hz) and gamma (35-45 Hz) EEG power during NREM sleep, as well as heightened levels of beta2 activity during REM sleep in insomnia patients compared to psychiatric insomniacs and good sleepers. Furthermore, the increased beta activity was correlated with the tendency to underestimate total sleep time. By analyzing the temporal and stagewise distribution of high frequency activity, they found an inverse relationship between delta and beta EEG activity in healthy controls, which disappeared in insomnia patients during the second part of the night. All these studies, however, did not take into account the amount of discrepancy between objective and subjective sleep complaints and thus possible subtypes of primary insomnia. Krystal et al. [68] evaluated NREM sleep EEG spectral analysis between ―subjective‖ and ―objective‖ insomnia patients and healthy controls. Results showed distinctive different EEG patterns between both insomnia groups. Diminished delta and greater alpha, sigma and beta EEG relative spectral power during NREM sleep were observed and more prominent in the ―subjective‖ insomnia patients. These EEG differences were also correlated with the subjective sleep complaints of the ―subjective‖ group, but not with the ―objective‖ insomniacs. A correlation was found between the lower relative delta power during NREM sleep and the discrepancy between subjective and objective sleep measures. This result seemingly contrasts the finding of Perlis et al. [67] who found a positive correlation between the presence of beta power and the underestimation of TST. However, the authors suggest that since delta and beta EEG power appear to be negatively correlated, both findings might be related. Finally, a very recent study by Buysse and coworkers [69] performed an interesting study on EEG profiles during NREM sleep, examining the possible effects of gender on sleep EEG. Surprisingly, they did found a significant impact of gender on the sleep EEG profiles, namely women were characterised by elevated high


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frequency EEG activity, as well as increased low frequency EEG activity. These differences were not found in men suffering from insomnia compared to healthy men. These results raise the question whether the earlier findings on heightened beta EEG activity might be related to gender as opposed to the sleep complaints, especially since insomnia complaints are more prevalent in woman? Moreover, they found no relationship between high frequency EEG activity and clinical characteristics of insomnia in both men and woman. Overall, it is obvious that although certain studies report evidence for cortical arousal during sleep in insomnia patients, the results are still inconclusive. There have been reports of increased beta EEG activity in primary insomniacs [63, 66, 67, 70] or only in subjective insomniacs [68] or only in women suffering from insomnia [69] or even no differences during NREM [13]. The same picture is found for the sleep onset period. Further research is necessary to clarify these mixed results on cortical arousal during sleep in insomnia patients.

The Concept of Arousal: Interrelationships between the 3 Components By reviewing the literature on the presence of arousal in insomnia patients, it is clear that there exists a certain amount of variability. Hyperarousal, if present, can manifest itself in different ways, such as elevated heart rate, EMG, cortisol levels, cognitive activity, high frequency EEG activity, but as to why it expresses itself in different manners has not been explained yet. The neurocognitive model [50] posits that conditioned arousal can present itself in three different modalities, being physiological, cognitive and/or cortical. However, few studies have evaluated the expression of hyperarousal in these three systems at the same time. Furthermore, one can ask to what extend these three components are (in)dependent of each other and what are their interrelationships? An important question not yet received much attention. In a recent review by Perlis and colleagues [71] the same question has been put forward. In line of the neurocognitive perspective, they posit that the three arousal components are relatively distinct and rather independent from one another, as such that heightened arousal in one component does not necessarily lead to an increase in the other components. One of the arguments put forward to ground this hypothesis, is the disconnection between the peripheral nervous system and the brain during REM sleep; muscle activity is practically shut down at the same time that the brain shows signs of arousal in the EEG. On the other hand, it has been shown that the sympathetic activation during wakefulness reflected by heart rate, decreases entering NREM sleep, and rises again towards mean awake levels during REM sleep [72]. Interestingly, here we see an example were two parameters reflecting physiological (de)arousal suggesting different states of arousal. A second consequence of viewing arousal as a three-construct system with limited interrelations, is the lack of knowledge to know which component might be elevated reflected by which parameter and under which conditions? This might also explain the mixed results concerning the different arousal components in insomnia. To clarify this rather complex question can be seen as a challenge. A few studies have tried to clarify the interrelationship between different arousal components. One of the main objections against the presence of high frequency EEG activity in insomnia patients is the possible influence of increased EMG levels on the EEG spectrum.

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Indeed, it has been suggested that the raise of beta EEG activity under stress or arousal conditions, might be related to the raise in muscle tension, as such not exclusively reflecting a change in brain activity [73], but rather a expression of physiological arousal. Bonnet and Arand [74] targeted this question by evaluating the effect of different states of physiological arousal and increased EMG upon spectral EEG measures in healthy sleepers. The different conditions used were sitting, standing, walking, a mathematical task, gritting teeth and clenching fists. Indeed, it was shown that the production of physiological arousal resulted in an increase in high frequency EEG activity. Heightened levels of EMG produced EEG changes above 24 Hz, which includes the beta EEG band often referred to in insomnia studies. At the same level, an increase in heart rate was observed during arousal condition, which in turn was related to changes in the EEG spectrum. As such, it is hypothesized that increased high frequency EEG activity may not be a sign of cortical arousal, but might just be a reflection of physiological arousal such as heart rate or tension. A second study by De Valck et al. [75] evaluated the effect of experimentally induced cognitive arousal on the subsequent physiological and cortical arousal components in healthy sleepers. The unannounced visit of a camera crew filming a documentary on sleep and related issues was used as a trigger for cognitive arousal. Cognitive, physiological and cortical arousal were assessed using respectively the POMS tension subscale, heart rate (HR) and HRV, and beta EEG activity during the first and last 5 minutes of an MSLT. All subjects were exposed to an arousal and neutral condition during a 2-day partial sleep deprivation protocol. The arousal condition resulted in significant increases in cognitive subjective arousal and physiological arousal reflected by higher scores on the POMS and an increase in heart rate, which in turn gave rise to increased sleep latency during the MSLT. In regard to the impact on cortical arousal, a trend was found for increased beta2 (20-35 Hz) EEG activity during the first and last 5 minutes of the MSLT. None of these changes were observed during the neutral condition. Surprisingly, none of the arousal parameters correlated with objective sleep latency. These findings suggest a partial interrelationship between the three arousal components, with a more pronounced connection between cognitive and physiological arousal, as opposed to cortical arousal. Furthermore, since the increase in physiological arousal did not result in a similar magnitude of increased cortical arousal, this might suggest that heightened levels of beta EEG activity are not solely the result of increased physiological arousal. Methodological difference between the former and latter study are related to the experimentally provoked arousal component used. Bonnet and Arand induced physiological arousal and evaluated its impact on cortical arousal, whereas De Valck and colleagues used cognitive arousal as a starting point. Thirdly, Tang and Harvey [76] performed two napping experiments in order to clarify the different effects of physiological versus cognitive and emotional arousal, and their impact on perception of sleep. The first experiment aimed at evaluating the specific influence of presleep cognitive arousal on the distortion of sleep perception, reflected by the SOL and TST discrepancy, during an afternoon nap. Secondly, the cognitive arousal group was divided in two subgroups, the first being the anxious cognitive arousal and the second the neutral cognitive arousal group. It was hypothesized that both anxious and neutral cognitive arousal would lead to a prolonged sleep latency and an increase in the discrepancy between self reported sleep and actigraphy-defined sleep in comparison to a ‗no manipulation‘ group.


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Indeed, analysis showed an increase in self reported cognitive arousal in both groups, but only the anxiety group reported a significant increase in anxiety during the sleep onset period. Regarding the objective sleep parameters, only the cognitive anxious arousal group showed a significant increase in sleep onset latency, as opposed to the neutral cognitive arousal group. However, both arousal groups did show an overestimation in reported sleep onset latency compared to the no manipulation group, supporting the hypothesis that the amount of presleep cognitive arousal is related to the discrepancy in sleep perception. A second experiment compared the relative effects of an anxious cognitive arousal group with a physiological arousal group, induced by caffeine intake, in relation to the objective measures of sleep quality by means of actigraphy, as well as distortion of sleep perception. Results showed that both arousal groups resulted in a distorted perception of sleep. In regard to the objective sleep parameters, only the anxious cognitive arousal group showed increased sleep latencies. Summarizing, these studies have resulted in some preliminary insights into the different arousal components and their specific influences on sleep parameters, perception and other arousal dimensions. Inducing physiological arousal by means of physical activity and additional raises in EMG level, results in parallel increases in beta EEG activity, probably due to the specific effects of EMG on the EEG spectrum. On the other hand, when using a protocol that induces cognitive arousal, a similar increase in physiological arousal is produced, but not in cortical arousal, suggesting that this methodology might avoid to some extent the confounding effect of muscle tension on the EEG. Furthermore, when using an experimentally induced cognitive arousal protocol, attention must be paid to the possible occurrence of emotions, such as anxiety. As Tang and Harvey [76] showed, combined occurrence of emotion and cognitive arousal, will have a greater impact on objective sleep variables.

Conditioned Arousal or a Predisposing Factor? Based on the many studies regarding this topic during the last decade, hyperarousal is recognized as an important characteristic in primary insomnia today. However, the specific nature of this arousal remains unclear: is it a conditioned response or a predisposing factor? Furthermore, the two are not mutually exclusive. More specifically, the basic level of arousal that predisposes people to develop insomnia may be another key factor [7]. According to the neurocognitive perspective [50], arousal in insomnia patients is a conditioned response as a results of the presence of predisposing factors in combination with a precipitating event and perpetuating factors. As such, arousal responses should only occur in situations that have become associated with threatening sleep-related environments or contexts or as a result of such responses. Most studies on arousal assessed its presence in sleep-related contexts or environments, such as the bedroom, the sleep onset period, during the entire night or in the morning. Indeed, indications for hyperarousal such as increased muscle activity, beta EEG activity, cortisol levels, temperature or HR during the sleep onset period or during sleep could be interpreted as being a conditioned arousal in response to the sleep environment. However, if considered a conditioned response, these increases in arousal should not be present in situations not related to sleep. As mentioned before, there exists a

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certain amount of variability and not all studies found the same increased arousal in insomnia patients, suggesting that the arousal response may vary between subjects. Another explanation is that the conditioned response is triggered in different situations, being bedtime or during awakenings or in the morning after a bad night sleep, which might clarify to some extend the mixed results mentioned before. A way of examining this is to evaluate specific measurements of arousal during a longer period, such as 24 hour protocol. Indeed, Bonnet and Arand [77] performed a study targeting these limitations of previous studies by arguing that the mixed results concerning hyperarousal in insomnia might be related to the fact that the involved physiological systems differ between insomnia patients and that the measurements were limited in time to a specific moment. As such, a more general measure of physiological arousal, for example metabolic rate reflected by whole body oxygen use, would give more consistent and accurate results. Insomnia patients showed increased metabolic rate during the day and the night, suggesting a general 24-hour hyperarousal disorder, which in turn is responsible for the reported sleep impairments. This surprising result lead to the suggestion that the presence of such a general hyperarousal could also be considered as a predisposing factor, making a person more prone to emotional and/or cognitive arousal and the resulting sleep impairments, and not as a conditioned arousal response. This conclusion can be considered a very important and topical subject. The presence of a predisposing arousal factor is not present in all insomnia patients however, as was shown by the study of Varkevisser et al. [26] who found no significant difference in 24-hour cardiovascular parameters, free cortisol, and body temperature. It was suggested that their insomnia sample was not characterised by a general hyperarousal disorder on the level of physiological arousal. These results imply the possible presence of two distinct categories of insomnia patients, namely a group characterised by a predisposing arousal disorder, and a second group distinguished by specific conditioned arousal responses related to sleep and sleep difficulties. Recent research on the possible influence of specific genes on sleep propensity and waking performance has given preliminary evidence for a predisposing factor with an impact on the sleep and wake EEG in healthy sleepers [78]. The presence of PER34/4 or PER35/5 in healthy sleepers results in different SWS, SWA and waking performance. It has been shown that people with PER35/5 are characterised by a greater sleep propensity during NREM sleep, reflected by faster sleep onset and higher SWA during NREM sleep, in comparison to subjects characterized by PER34/4. The differential effects of both genes was even more apparent after sleep deprivation, since the presence of PER34/4 resulted in less inhibition of REM sleep during recovery, no increase in theta EEG power and less decrements in waking performance during sustained wakefulness. Future research evaluating PER3 VNTR polymorphism in insomnia patients might clarify some of the unanswered questions regarding arousal and predisposing factors.

Arousability and Habituation A final relevant question regarding arousal and its role in the development of insomnia, is related to the degree of arousal that insomnia patients develop when confronted with new or emotional stimuli [7]. It has been shown that a higher arousability reflected by higher


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scores on the Arousal Predisposition Scale (APS) in healthy individuals is associated with stronger electrodermal and EMG responses, e.g. physiological arousal [79]. Lundh et al. [80] performed a study evaluating personality profiles as an indication of predisposing factors in the development of insomnia. Their patient sample was characterized by higher emotional sensitivity, slow recuperation after stress, and worrying. When confronted with new/emotional stimuli, a greater arousal response is produced, which in combination with the slow recuperation will remain present for a longer period in comparison to healthy sleepers. This situation in turn, might increase the possibility of creating negative associations or conditioned responses to sleep related cues. Furthermore, the predisposition of excessive worry will lead to more negative cognitions about the sleep disruption. The presence of these predisposing factors can be the starting point for the onset of the behavioral/neurocognitive model, resulting in a negative vicious cycle. In this situation, it is a matter of being prone to react with higher arousal levels on a stressful or emotional situation and the slow habituation from stress that make up the predisposition to insomnia, and not per se the presence of a general 24-hour hyperarousal.

Current Study The aim of the current observational study is to assess the presence of physiological, cognitive and/or cortical arousal within a sample of primary insomnia patients in comparison to healthy controls. In line of current knowledge, we hypothesize that insomnia patients are characterized by some form of hyperarousal, being physiological, cognitive and/or cortical. As to which component of the arousal system will be elevated, no hypotheses are put forward. Furthermore, possible correlations between hyperarousal and subjective or objective sleep parameters will be explored. In addition to differences in sleep macrostructure, we hypothesize to find significant differences in microstructural parameters of sleep, as well as reported sleep reflected by the sleep logs. In accordance with the literature, we hypothesize that our insomnia group will show greater discrepancy between objective and subjective sleep variables than good sleepers.

Method Subjects Primary insomnia patients were recruited through clinical sleep centers and primary care physicians. After a short screening interview by phone to check for possible medical conditions and medication use, eligible candidates were invited for a full screening session. In addition to a comprehensive sleep history and the Mini International Neuropsychiatric Interview (M.I.N.I.) [81], the following questionnaires were used: Pittsburgh Sleep Quality Index (PSQI) [82], Epworth Sleepiness Scale (ESS) [83], Athens Insomnia Scale (AIS) [84], State Trait Anxiety Index (STAI) [85], Beck Depression Inventory (BDI) [86], Presleep Arousal Scale (PSAS) [87] with a somatic (PSAS SOM) and a cognitive (PSAS COG)

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subscale. Once enrolled in the study subjects received an explanation of the complete procedure and signed an informed consent. Of the 158 subjects with sleep complaints who wanted to join the study, 56 subjects were invited for an interview. 27 insomnia patients fulfilled the in- and exclusion criteria (see below) and came to our lab for a polysomnography. 20 insomnia patients were enrolled in this study, but 3 more patients cancelled their participation. A total of 17 insomnia patients, 11 men and 6 women (mean age 42.6) were finally included in this study. 13 of them already underwent a polysomnography in a clinical sleep centre the past year. 16 out of 17 insomnia patients reported a combination of sleep onset and sleep maintenance problems with a dominance of the latter type. Only 1 patient reported an exclusive sleep onset disruption. Twelve healthy sleepers, 7 men and 5 women (mean age 44.4), participated in the study as a control group for baseline sleep comparisons. They underwent a similar screening session. This study was evaluated and approved by the Medical Ethics Committee of the Brussels University Hospital.

Inclusion and Exclusion Criteria Insomnia patients between 18 and 60 years of age had to present either a sleep onset problem (latency > 30 minutes) or a sleep maintenance problem (wake after sleep onset > 30 minutes) based on a polysomnography. In addition they had to report sleep complaints with a minimum of 3 times per week, and duration of the insomnia complaints of more then 6 months. Impairment in daytime functioning had to be present and all participants had to be medication-free for at least 4 weeks before the start of the study, as well as during the whole study. All psychiatric or medical disorders were excluded, except for a positive response in the M.I.N.I. on dysthymia and/or generalized anxiety disorder when it was clearly related to their sleep complaints. Table 1. Clinical characteristics Insomnia

Duration insomnia (years) Age STAI 1 STAI 2 BECK AIS PSQI PSAS SOM PSAS COG ESS

n=17 ♂=11;♀=6) 12.41 (10.15) 42.65 (9.35) 34.12 (5.56) 42.18 (7.19) 5.65 (5.23) 12.24 (3.53) 11.53 (2.00) 11.41 (4.58) 20.88 (8.53) 7.65 (4.96)

Controls n=12 (♂=7;♀=5) 0 (0) 44.42 (7.68) 27.67 (6.3) 34.58 (9.03) 2.67 (3.08) 2.17 (1.47) 4.00 (1.76) 9.50 (1.62) 11.75 (2.30) 7.08 (2.35)

*indicates significant difference with control group (p. < .05)

Effect size (r)

0.85* 0.09 0.52* 0.39* 0.25 0.83* 0.83* 0.15 0.41* 0.11


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Further exclusion criteria for all subjects: students, shift workers, pregnancy, consumption of more than two alcohol units/ day for woman and three alcohol units/day for men, consumption of more than five caffeine beverages/day, phase delayed or phase advanced syndrome, abnormal bedtime hours (< 09:30 PM) or irregular sleep-wake schedule, parents with newborns, excessive daytime sleepiness (ESS>13 and subjective report of difficulty staying awake during the day), presence of other primary sleep disorders (RLL, PLM, sleep apnea,…), BMI > 30.

Sleep Diary and Actigraphy Before the polysomnography, participants were asked to fill in a sleep diary and wear an actigraphy during the night for 2 weeks, to check for irregular sleep-wake schedules. The morning after the polysomnography, all participants were asked to fill in a morning questionnaire evaluating their night in the sleep lab, consisting of the Brussels Indices of Sleep Quality (BISQ) and a PSAS. Following variables were calculated from the sleep diary: Total Sleep Time (TST), Sleep Latency (SOL), Wake after sleep onset (WASO), Sleep Efficiency (SE), and Time in Bed (TIB).

Wake EEG All participants underwent a full-cap EEG measurement using the Cognitrace (A.N.T.) the evening they came to the laboratory for their sleep night. 19 electrodes were placed according to the international 10-20 system (Fp1, Fp2, F3, F4, F7, F8, Fz, C3, C4, Cz, P3, P4, Pz, T3, T4, T5, T6, O1, O2) and were averaged referenced online. An EOG and EMG submentalis were added to exclude artifacts of eye movements or muscle activity. Sampling rate was 256 Hz and impedances were kept below 10 kOhm. A 5 minute measurement with eyes open and eyes closed was performed. A Fast Fourier Transformation (FFT) Analysis was performed on the wake EEG on a minimum of 90 seconds artefact-free data using Neuroguide software (Applied Neuroscience, Inc.). The spectrum was divided into the following EEG frequency bands: delta (1-3.5 Hz), theta (4-7.5 Hz), alpha (8-12 Hz), beta1 (12-15 Hz), beta2 (15-17.5 Hz), beta3 (18-25 Hz), and high beta (25.5-30 Hz). Both absolute and relative values were calculated and a log transformation was performed to counter normality issues.

Polysomnography A polysomnography was performed at the experimental sleep laboratory at the Vrije Universiteit Brussel. In accordance with the studies of Perlis et al. [66, 67] analysis were performed on the first screening night. The recording montage consisted of 3 EEG electrodes referenced to a single mastoid (F3-A2, C4-A1, O1-A2), 2 EOG electrodes referenced to a single mastoid (LOC, ROC), a bipolar submentalis EMG, tibialis EMG, and EKG. A 32

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channel Embla N7000 recording system was used (Medcare) with a DC offset of 500 mV max and a fixed DC low cut filter at 0.3 Hz. The signal was digitized at a sampling rate of 500Hz using Somnologica Software. The EEG and EOG signals were high pass filtered at 0.5 Hz and low pass filtered at 40 Hz, EMG channels were high pass filtered at 5 Hz and low pass filtered at 70 Hz. All data was scored in 30-second epochs according to the Rechtschaffen & Kales [88] rules by a trained specialist, unaware of group allocation. Outcome variables were Total Sleep Time (TST), Sleep Onset Latency (SOL) defined as lights out to the first minute of stage 1 sleep, Wake After Sleep Onset (WASO), Sleep Efficiency (SE), % Slow Wave Sleep (SWS) of the Sleep Period Time (SPT), % REM sleep of the SPT, % Stage 1 sleep (S1) of the SPT and % Stage 2 sleep (S2) of the SPT. Furthermore, the arousal index defined as the amount of arousals (3-15 seconds) per hour and number of awakenings was calculated. Additionally, the EMG level (Root Mean Square µV) of the first period of wakefulness during the sleep onset period was also analyzed as a measure of baseline tension level. Movement artefacts were excluded from analysis. Spectral analysis was performed on C4-A1 to evaluate both the sleep onset period (SOP) and NREM and REM sleep. SOP was defined as lights-out to the first 5 minutes of stage 2 sleep [60]. Artefacts were removed and the SOP was divided into four quartiles to evaluate the EEG dynamics. FFT analysis was performed using Neuroguide software (Applied Neuroscience, Inc.), in which standard EEG frequency bands were defined: delta (1-3.5 Hz), theta (4-7.5 Hz), alpha (8-12 Hz), beta1 (12-15 Hz), beta2 (15-17.5 Hz), beta3 (18-25 Hz), and high beta (25.5-30 Hz). Regarding the sleep EEG, all epochs containing movements, EMG artefacts, sleep stage transitions or arousals (3-15sec) were excluded from analysis. All artefact-free epochs underwent high-pass filtering and hanning windowing followed by Fast Fourier Transformation in 2-second epochs. Delta (0.5 – 3.5 Hz), theta (4 – 8 Hz), alpha (8.5 – 12 Hz), sigma (12.5 – 16 Hz), beta (16.5 – 30 Hz) and gamma (30.5 – 60 Hz) were the analysed frequency bands. Analyses were performed using Somnologica Science software and data was exported to an excel file. The definition of NREM and REM cycles was adopted from the study of Perlis and colleagues [67]. Relative power spectra were calculated by dividing each frequency band by the calculated total power (sum of power of all frequency bands).

Arousal Parameters The somatic subscale of the PSAS will be used as a measure of subjective physiological arousal, both retrospective, as well as during their stay in our sleep laboratory. Secondly, EMG levels during sleep onset, as well as a cortisol sample the evening of the scheduled polysomnography will be used as an objective measure of physiological arousal. The cognitive subscale of the PSAS will be used as a measure of subjective cognitive arousal. Finally, an evaluation of cortical arousal reflected by the spectral profile of the wake and sleep EEG (SOP-NREM-REM) will be performed.


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Procedure Before the polysomnography, participants were asked to fill in a sleep diary and wear an actigraphy during the night for 2 weeks, to check for irregular sleep-wake schedules. Subjects came to our sleep lab for the first PSG measurement at the Vrije Universiteit Brussel. They came in around 8:00 pm and received information on the procedure of the evening and purpose of the measurement. Around 8:15 pm the EEG measurement in an experimental room was started. During the eyes open condition, subjects were asked to keep their eyes fixed on a white dot on the floor, approximately 1.5 m from their seat to minimize eye movements. In the eyes closed condition, subjects were asked to visualize the same white dot and try to keep their eyes as still as possible. Afterward the electrodes for the night were applied. Around 10:30 pm cortisol measurement was performed through a saliva sample. Subjects went to bed between 10:30 pm and 12:00 pm, depending on their usual bedtime. Time in bed was approximately 7 hours and 30 minutes and was kept stable for every subject. The next morning they were asked to fill in the Brussels Indices of Sleep Quality (BISQ) and PSAS to monitor their subjective sleep quality.

Statistical Analysis Statistical analysis was performed using STATISTICA 8.0 software. Normality and homogeneity of variances were checked before analysis. To evaluate differences regarding clinical, demographical, PSG and sleep diary data an independent samples t-test was performed. If one of the assumptions was violated, a Mann-Whitney U test was used. The wake EEG was evaluated using a 2x19 repeated measures ANOVA for every EEG frequency band, using group (insomnia vs. controls) as a between subject variable and electrode location (19 locations) as a within subject variable. A 2x4 repeated Measures ANOVA was used for the SOP, with group (insomnia vs. controls) as a between subject variable and quartile as a within subject variable. The first 3 NREM and REM cycles were also examined using an 2x3 repeated measures ANOVA with group (insomnia vs. controls) as a between subject variable and NREM/REM cycle as a within subject variable. The calculated effect size for the repeated measures ANOVA is partial-eta squared (ηp2). Finally, in order to examine possible associations between sleep and arousal, a Spearman Rank correlational analysis was performed.

Results Clinical Characteristics In addition to the data presented in table 1, our insomnia subjects reported significantly more anxiety, both as a state and trait characteristic (STAI-1: z = 2.81; p.<.005; STAI-2: z = 2.13; p.<.05). They reported increased presleep cognitive arousal during the past month in comparison to the control group (z = 2.24; p.<.05). No difference was found for somatic

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presleep arousal. Furthermore, state anxiety correlated significantly with PSAS-SOM (rs=.60) and PSAS-COG (rs=.51) in insomniacs, which was absent in healthy sleepers.

Objective and Subjective Sleep Parameters Results from the polysomnography and sleep diaries are displayed in Table 2 (A). Objective sleep parameters show that the group of insomnia patients was characterized by significant objective disruptions of sleep. Table 2. Objective and subjective sleep parameters A. PSG

Insomnia n=17 (♂=11;♀=6) 22.11 (15.48) 78.44 (48.17) 373.01 (47.03) 82.74 (10.5) 14.98 (5.11) 18.31 (4.16) 6.38 (3.13) 42.98 (8.34) 11.29 (7.56) 14.30 (5.24) 473.57 (21.71)

SL (min.) WASO (min.) TST (min.) SE (%) SWS (%SPT) REM (%SPT) F1 (%SPT) F2 (%SPT) Awakenings (#) Arousal index (#/hour) TIB (min.) B. Sleep diary SL (min.) 76.17 (97.36) WASO (min.) 119.70 (92.86) TST (min.) 300.00 (102.81) SE (%) 63.68 (21.52) C. Discrepancy between objective and subjective sleep SOL (min.) 54.05 (94.14) WASO (min.) 41.26 (68.45) TST (min.) -73.01 (74.23)

Controls n=12 (♂=7;♀=5) 9.24 (4.54) 32.7 (21.55) 412.25 (31.51) 92.8 (4.74) 16.86 (8.27) 23.03 (4.74) 5.77 (1.61) 42.70 (13.39) 6.00 (2.69) 6.94 (2.90) 454.19 (38.8)

Effect size (r)

10.75 (8.04) 18.66 (17.24) 421.66 (32.49) 92.73 (5.25)

.80* .73* .71* .77*

1.50 (6.13) -14.03 (16.92) 9.41 (28.11)

.50* .52* .67*

.51* .50* .43* .50* .13 .47* .11 .01 .38* .68* .22


It took them longer to fall asleep (z = 2.79; p.<.01; r = .51), they spend more time awake during the night (t(27)=3.06; p.<.005; r = .50), had less TST (t(27)=-2.51; p.<.05; r = .43) and a decreased SE (t(27)=-3.07; p.<.005; r = .50). Regarding sleep architecture, no significant differences were observed, except for a decreased REM sleep % (t(27)=-2.83; p.<.01; r = .47) in comparison to the group of healthy sleepers. Sleep was more fragmented in insomnia patients reflected by more awakenings (z = 2.09; p.<.05; r = .38) and a higher arousal index (z = 3.70; p.<.0005; r = .68). The morning after the PSG, subjects were asked to evaluate their sleep by filling in the BISQ, which revealed significant differences between both groups (Table 2 B). Insomnia patients reported longer SOL (z = 4.13; p.<.00005; r = .80), more WASO (z = 3.96; p.<.0001; r = .73), less TST (z = -3.85; p.<.0005; r = .71) and a decreased SE (z = -4.18; p.<.00005; r = .77). As was hypothesized, insomnia patients were characterized by a greater discrepancy between objective sleep parameters and perception of sleep (Table 2 C). They overestimated SOL by approximately 55 minutes (z = 2.74; p.<.01; r


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= .50) and WASO by an average of 41 minutes (z = 3.96; p.<.005; r = .52), while TST was underestimated by an average of 73 minutes (z = -3.63; p.<.0005; r = .67).

Cognitive and Physiological Arousal To evaluate the two arousal components described by the behavioral model, our subjects completed the PSAS the morning after the PSG recording as a measure of subjective cognitive and physiological arousal. Results show that our insomnia sample reported significantly more cognitive arousal (z = 2.91; p.<.005; r = .54) during the SOP, but no increased physiological arousal was indicated. Markers for objective physiological arousal were obtained by a cortisol sample the evening of their stay in our laboratory, and analysis of the EMG level during the SOP. No indications of objective physiological arousal were found (table 3). Table 3. Cognitive and physiological arousal. Cognitive arousal PSAS COG Physiological arousal PSAS SOM EMG (RMS µV) Cortisol

Insomnia n=17 (♂=11;♀=6) 15.52 (5.26)

Controls n=12 (♂=7;♀=5) 10.50 (1.97)

9.70 (2.36) 3.76 (1.18) 2.34 (1.89)

8.58 (1.08) 3.48 (1.11) 1.74 (0.46)

Effect size (r) .54* .24 .01 .02


Cortical Arousal: Wake EEG, SOP and NREM/REM Wake EEG To assess the possibility of increased cortical arousal in the evening outside the bedroom, a wake EEG was performed. A 2x19 repeated measures ANOVA revealed no differences between insomnia patients and healthy controls. The SOP The SOP defined starting from lights-off to the first 5 minutes of stage 2 sleep was divided into 4 quartiles to evaluate the specific EEG dynamics between insomniacs and healthy controls. A 2x4 repeated measures ANOVA was performed for both relative and absolute power in 7 frequency bands. For all frequency bands, a main effect for quartile was observed. Absolute delta (F(27)=105.74; p.<.0000001; ηp2 = .79) and theta (F(27)=41.67; p.<.0000001; ηp2 = .60) and beta1 (F(27)=13.27; p.<.0000001; ηp2 = .32) power increased from the first to the last quartile, alpha (F(27)=9.20; p.<.00005; ηp2 = .25) , beta2 (F(27)=8.29; p.<.0001; ηp2 = .23), beta3 (F(27)=40.10; p.<.0000001; ηp2 = .59) and high beta (F(27)=26.26; p.<.0000001; ηp2 = .49) decreased. A small but significant group x quartile

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interaction effect was found for absolute delta (F(27)=3.64; p.<.05; ηp2 = .11) and alpha (F(27)=3.12; p.<.05; ηp2 = .10) EEG power (figure 1 and 2).

Figure 1. Evolution of the absolute delta power during the sleep onset period. A log transformation (ln) was performed.

Post-hoc Tukey showed that the controls had a steeper and faster increase in delta power (quartile 2 vs. quartile 3: p.<.0005; no significant difference between third and fourth quartile) in comparison to the insomnia group (significant difference between quartile 2 and 3: p.<..005; quartile 3 and 4: p.<.0005). In regard to the absolute alpha power, no significant difference between all quartiles was found for the insomnia group, whereas the controls showed a gradual significant decrease (quartile 1 versus quartile 3 and 4: p.<0005). No significant differences were found for the beta EEG frequency bands. Regarding the relative power, similar results were found: a significant main effect for quartile were delta (F(27)=74.44; p.<.0000001; ηp2 = .73) and theta (F(27)=17.17; p.<.0000001; ηp2 = .39) power increases during SOP, while all other frequencies showed a decrease (alpha: F(27)=53.70; p.<.0000001; ηp2 = .67; beta1: F(27)=3.91; p.<.05; ηp2 = .13; beta2: F(27)=45.14; p.<.0000001; ηp2 = .63; beta3: F(27)=81.28; p.<.0000001; ηp2 = .75; high beta: F(27)=57.62; p.<.0000001; ηp2 = .68). Again, a significant interaction effect was found for relative delta (F(27)=3.35; p.<.05; ηp2 = .11) and alpha (F(27)=5.17; p.<.005; ηp2 = .16) EEG power (figure 3 and 4).


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Figure 2. Evolution of the absolute alpha power during the sleep onset period. A log transformation (ln) was performed.

Figure 3. Evolution of relative delta power (%) during the sleep onset period. Log transformation (ln) was performed.

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Post-hoc Tukey analysis showed a faster and steeper increase in relative delta power in the healthy sleepers (quartile 2 vs. 3: p.<.0005) in comparison to insomniacs (quartile 3 vs. 4: p.<.005). The results for the relative alpha power show a gradual decrease for both groups, but this process is faster and steeper for controls (quartile 2 vs. 3: p.<.0005) in comparison to the insomnia group (quartile 3 vs. 4: p.<.05). The difference between absolute and relative alpha power, suggests that the decrease in relative alpha power is due to an increase in absolute power of one of the other frequency bands, as opposed to an actual decrease of absolute alpha power.

Figure 4. Evolution of relative alpha power during the sleep onset period. Log transformation (ln) was performed.

No significant interaction effects were found for the other frequency bands. The Sleep EEG: NREM/REM First, the average of all the previously defined relative frequency bands during NREM and REM sleep of the entire night was calculated (figure 5). No significant differences were found between both groups.

Figure 5. Relative spectral power profiles during NREM and REM sleep. An average of the entire night was calculated for each frequency band. Error bars denote standard error.


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Since the number of sleep cycles was not equal for all participants, an average of NREM and REM sleep was calculated for the first three sleep cycles. Again, no significant differences were found between insomnia patients and healthy sleepers. Furthermore, an assessment was made of the evolution of all described EEG frequencies from the first to the third NREM and REM cycle, but no significant differences were found.

Correlational Analysis of Arousal and Sleep Parameters As previous studies have shown that arousal and sleep disruptions are interrelated, a correlational analysis was performed to evaluate possible links between objective and subjective sleep parameters and arousal components. Given the risk for multiple comparisons and chance hits, only the following correlations were analyzed: objective SOL and arousal components, discrepancy between objective and subjective SOL and arousal components, and cortisol and sleep fragmentation parameters. More specific it was hypothesized that specific sleep EEG frequencies are related to objective sleep disruption and sleep misperception: delta and beta EEG activity during the SOP and NREM sleep were compared to the arousal index and TST discrepancy. Objective Sleep Parameters and Arousal A Spearman Rank correlational analysis was performed for each group to evaluate the possible associations between objective sleep parameters and arousal components. The objective SOL was negatively correlated with the average absolute delta (rs=-.77) EEG activity during the SOP in insomnia patients. Evening cortisol level was positively correlated with the arousal index (rs=.55) and number of awakenings (rs=.70) during the night. Relative beta EEG activity during NREM sleep was positively correlated with WASO (rs=.66) and the arousal index (rs=.55), and negatively correlated with TST (rs=-.49) and SE (rs=-.68). Relative beta power during REM sleep was also positively correlated with the arousal index (rs=.64) (all p‘s <.05). Within our group of healthy sleepers, the objective SOL was negatively correlated with absolute delta power (rs=-.64). Furthermore, a positive correlation was found between cortisol and PSAS-SOM (rs=.66). Relative beta EEG activity during NREM sleep was positively correlated with WASO (rs=.59), number of awakenings (rs=.64), and the discrepancy of TST (rs=.60) (all p‘s <.05). The only correlation observed in both groups, as well as in the total sample of subjects (insomnia and controls as one group) was the negative correlation between objective SOL and the amount of absolute delta power (rs=-.70). Subjective Sleep Parameters and Arousal A Spearman Rank correlational analysis was performed for each group to evaluate the possible associations between subjective sleep parameters and arousal components. The SOL discrepancy in insomnia patients was positively correlated with the PSAS-SOM (rs=.49) and cortisol level (rs=.51).

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The SOL discrepancy in the control group was positively correlated with the EMG level (rs=.60) during the SOP. Relative beta EEG activity during NREM sleep was positively correlated with the discrepancy of TST (rs=.60) (all p‘s <.05).

Conclusion Clinical Data In this study, a relatively homogenous group of ‗objective‘ insomnia patients was targeted and compared to a matched control group of good sleepers. Indeed, our insomniacs were clearly characterized by sleep disruption as reflected by the PSG data. They tended to take more time to fall asleep, were more awake during the night, had less TST and a decreased SE. Moreover, both the macro- and microstructure of sleep were significantly fragmented, reflected by more awakenings and a higher arousal index in comparison to controls. Interestingly, when evaluating the effect sizes for all objective sleep parameters, the highest effect was found for the arousal index, which is a strong argument for including this parameter in standard sleep evaluation. An often reported phenomenon in insomnia patients is the fact that perception of sleep quality is not in accordance with objective findings, a result also present in our insomnia group. In line with former research [51-53, 56], our group of insomniacs—although characterized by objective sleep disruption—tended to overestimate SOL and WASO, as well as underestimate TST and SE. The discrepancy between perception and polysomnography has been related to the occurrence of arousals [89]; however, our results did not show a positive correlation between the arousal index and perception of sleep within the insomnia group, suggesting that another factor might be in play. The insomnia patients were also characterized by higher levels of trait and state anxiety, as well as more cognitive arousal instead of physiological arousal, a finding previously reported by Lichstein and Rosenthal [3]. Furthermore, trait anxiety was related to the perception of the SOL, while this was not the case in the control group. Moreover, there appeared to be a relationship between state anxiety and presleep arousal in insomnia patients. Tang and Harvey [76] showed in a napping experiment that the presence of both anxiety and cognitive arousal have a greater impact on sleep and perception of sleep. Indeed, in their study only the anxious cognitive arousal group showed a greater discrepancy in TST, as opposed to a neutral cognitive arousal group in comparison to a no manipulation group.

Arousal in Insomnia: A Dynamic and Transitional Concept? Our results confirm the presence of arousal in insomnia patients. First of all, the heightened scores on the trait anxiety subscale of the STAI questionnaire suggests that our insomnia patients were characterized by a predisposition to react with an emotional arousal response in stressful situations, which corresponds with the behavioral perspective and neurocognitive model of insomnia. Furthermore, the results of the STAI-2 subscale confirm the presence of anxiety in stressful situations. During the presleep period, they also reported


27

more cognitive arousal, a result in line with previous studies [27, 28, 30, 42]. As in the study of Lichstein and Rosenthal [3], presleep physiological arousal was also absent in our study sample. As discussed previously, research regarding the presence of physiological arousal reflected by EMG levels or cortisol show mixed results. Besides the subjective physiological arousal, muscle tension during the SOP and evening cortisol were measured to evaluate the objective physiological arousal related to the sleep environment and sleep time, but no effects were found. This corresponds to the studies performed by Riemann et al. [25], as well as Varkevisser et al. [26], who also found no indication of physiological arousal whatsoever. As the insomnia group also failed to report a significant increased physiological presleep arousal over the last month during the screening period, it could be suggested that this was just a characteristic of this patient sample. Next, an indication was found for an impairment of cortical sleep initiation processes during the SOP. The absence of a decrease in alpha power in combination with the slower increase in delta power, suggests that normal sleep onset processes were delayed, resulting in longer sleep onset latencies. This result is in agreement with previous studies evaluating the sleep onset period [60, 61]. We did not find, however, any significant differences for beta EEG activity, both during wakefulness and sleep. Again, these results emphasize the fact that hyperarousal in all three systems studied is apparently not always simultaneously present in insomnia. Arousal most probably should not be seen as a static phenomenon. When reviewing the process of falling asleep at the level of EEG changes, we see that two shifts need to occur before sleep onset is achieved. First, high frequency EEG activity needs to decrease, and secondly low frequency EEG activity needs to increase [58, 59]. According to the neuronal group theory [64, 90] maximal alertness and maximal sleepiness are part of a continuum, suggesting that transitional states are possible as well. Furthermore, the Neuronal Transition Probability model [65] posits that oscillatory modes of the thalamocortical neurons responsible for the beta, sigma and delta oscillations clearly show this transitional character of arousal and sleepiness. Therefore, it might be suggested that maximal alertness is equal to hyperarousal, reflected by both increased levels of beta EEG activity and decreased levels of slow wave activity in the delta range. A second phase could be referred to as arousal; it is a condition in which hyperarousal is not present anymore, but complete de-arousal is still not reached, reflected by normal levels of beta EEG activity and slower increase of delta power. Finally, when complete de-arousal is reached, a normal transition from wake to sleep can occur. In light of this perspective, it can be assumed that our insomnia patients were characterized by a lack of complete de-arousal, reflected by impairment in sleep initiation processes as seen in the slower EEG frequencies during the SOP. The strong correlation found between the sleep onset latency and the amount of delta power both in healthy sleepers and insomnia patients strengthens the hypothesis that the depolarization to the delta mode of the TC neurons, and thus the speed of transition from wake to sleep is the key factor, and not the beta EEG power. This perspective can also be used to explain the lack of hyperarousal during NREM and REM sleep. If, according to this theory, our insomniacs were not characterized by hyperarousal, but by a lack of complete dearousal, heightened levels of beta EEG activity were not expected. Moreover, the frequent awakenings and arousals may be an indication of a certain degree of instability of the sleep system because of the arousal condition, since these intrusions are defined by the presence of

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higher frequencies such as alpha or beta EEG activity. When arousal is considered as a varying construct on a continuum, the mixed results regarding hyperarousal in insomnia can be better interpreted. Assuming that the maximal state of hyperarousal is accompanied by increased levels on all 3 components of the multidimensional arousal construct, the gradual decrease in hyperarousal will lead to a normalization of some arousal components. For example, our insomnia patient sample apparently was only characterized by presleep cognitive arousal, state anxiety, impairment of sleep initiation processes and instability of the sleep maintenance processes. As such, it could be hypothesized that physiological and cortical hyperarousal will be more apparent when reaching the upper level (hyperarousal) of the continuum, while cognitive arousal is a sign of a minimal arousal level. Indeed, cognitive arousal is much more prevalent in insomnia studies than physiological arousal [3] and is often regarded as the starting point for the development and maintenance of insomnia and related arousal changes [32, 35]. Of course, the recruitment of our patient sample on the basis of their polysomnographical sleep distortions might have influenced the cortical arousal data, given the fact that Krystal and coworkers [68] found that specific EEG correlates of cortical arousal were more pronounced within a group of ‗subjective‘ insomnia patients in comparison to ‗objective‘ insomniacs and controls. However, our insomnia patient group showed a high degree of underestimation of TST (19.5%), but this was not accompanied by increased high frequency EEG activity, as would be expected by the theory posited by Krystal and colleagues. Furthermore, Buysse et al. [69] found that only women are characterized by heightened levels of beta EEG activity during sleep. Given that our insomnia and control groups consisted of more men than women, it is possible that cortical arousal reflected by beta EEG activity was not a predominant feature.

Sleep and Arousal Based on these results and recent literature, we propose to conceptualize arousal as a multidimensional construct, expressing itself in different systems with varying degrees. To what extent is arousal associated with the specific sleep impairments, both objectively and subjectively? Previous studies have found different correlations between arousal and sleep disruption, again pointing out the heterogeneity of this construct and its role in sleep. On the one hand, we found a correlation between evening cortisol and number of awakenings and arousal index, a finding in accordance with Vgontzas et al. (1998, 2001) and Rodenbeck et al. (2002). Also, cortisol levels were associated with the misperception of the SOL. These results suggest that physiological arousal reflected by evening cortisol is associated with a significant fragmentation of sleep macro- and microstructure, as well as a misperception of the time needed to fall asleep. On the other hand, the subjective physiological presleep arousal component seemed to be related with the discrepancy of SOL. Although our insomnia patients were not characterized by increased levels of beta EEG power during wakefulness and sleep, correlations have been found with objective sleep parameters. It seems that the presence of beta EEG power, both during NREM and REM sleep, is related to sleep fragmentation, reflected by the arousal index. An important remark related to this issue is the


29

fact that all awakenings and arousals were excluded from spectral analysis, which means that this correlation can not be due to the mere presence of arousals in insomnia patients. Furthermore, NREM beta EEG activity was also correlated with objective WASO, TST and SE. This seems not to be in accordance with previous research suggesting that beta EEG activity is specifically related to subjective insomnia and the perception of sleep [66-68]. Our insomnia sample seemed to be characterized by a discrepancy of sleep perception, in combination with a lack of cortical hyperarousal reflected by high frequency EEG activity. Could it be that this was a specific subtype of arousal-related insomnia, in which the beta EEG activity is more associated with objective PSG disruption both at the level of macroand microstructure? Misperception of TST was associated with the amount of alpha EEG power during REM sleep, a result not mentioned before. Furthermore, misperception of SOL in our study was related to the somatic component of the PSAS, and not the cognitive arousal component as was previously shown by Tang and Harvey [76]. The fact that they experimentally induced arousal in healthy sleepers might be an important factor. However, De Valck et al. [75] did not find any correlations between the experimentally induced arousal and increased sleep onset latencies measured by an MSLT. Could it be due to individual differences in predisposing factors? In summary, the insomnia group was characterized by more cognitive presleep arousal, but no association was found with any sleep variable. Instead, the physiological component of arousal appeared to play an important role in influencing both objective and subjective sleep, reflected by the correlation between cortisol and sleep fragmentation and somatic presleep arousal and perception.

Conclusion In this study we used a relatively homogenous sample of insomnia patients characterized by objective sleep distortions as shown by a polysomnography. They reported sleep maintenance problems in combination with sleep onset difficulties with a dominance of the first type. In accordance with previous studies evaluating NREM/REM EEG profiles in insomnia patients [66, 67], analyses were performed on the first PSG recording. Summarizing, this group experienced more cognitive and emotional arousal, but no increase in physiological arousal, both subjectively as well as objectively, in comparison with a control group. Indications of cortical arousal were only present during the sleep onset period, reflected by a stable alpha EEG level and slower increase of delta power, resulting in longer sleep onset latencies. Correlational analysis on the other hand, revealed a stronger association between physiological parameters of arousal with sleep, in comparison to the cognitive arousal component. Furthermore, the cortical arousal variables were correlated with objective sleep disruption, not with sleep perception. Together with literature, these results point to a large variability in insomnia patients as to the expression of hyperarousal and the different arousal components. It is suggested to regard hyperarousal as a more transitional state that can vary on a continuum going from maximal alertness/hyperarousal to maximal sleepiness/de-arousal. Future research should take into account the possible variation within the insomnia population of this construct and the role of specific predisposing factors, and

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examine the specific effects of different degrees of hyperarousal through experimentally induced arousal studies as to further clarify the role of this concept in insomnia and its different subtypes.

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Chapter II

Neuropathology of Insomnia in the Adult: Still an Enigma! Jean-Jacques Hauw*1 and Chantal Hausser-Hauw2 APHP, Hôpital de la Salpêtrière, Université Pierre et Marie Curie, Laboratoire de 1 Neuropathologie Raymond Escourolle, Paris, France Laboratoire du sommeil, Hôpital Foch, Suresnes, France2

Abstract Insomnia Insomniais a very frequent symptom, usually due to non organic brain diseases. In some organic brain disorders, however, sleep impairment occurs through a series of mechanisms: structures responsible for need for sleep are lesionned ; the biological clock doesn‘t give the start for sleep; sleep networks responsible for inhibition of waking structures are not efficient; mechanisms carrying on sleep or responsible for waking stages are damaged. In each case, examples of those brain disorders leading to insomnia (tumors, strokes, traumas, neurodegenerative disorders) are reviewed, focusing on the neuropathological description of structures involved in sleep network. When possible, clinicopathological correlates are suggested.

Introduction Whatever the cause, insomnia is usually related to a stress-induced hyperarousal state thought to be mainly mediated by the limbic system and forebrain areas. This hyperarousal state leads to an over-stimulation of the hypothalamo-hypophyseal axis, inducing chronic *

Correspondence: Pr J.-J. Hauw, Laboratoire de Neuropathologie Raymond Escourolle, La Salpêtrière, 47 Bd de l‘Hôpital, 75651, Paris Cedex 13, Tel :33 1 42 16 1881, FAX :-33 1 42 16 1899, [email protected]

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Jean-Jacques Hauw and Chantal Hausser-Hauw

insomnia. (Vgontzas A, 2001; Buckley R et al, 2008). No organic brain lesion is seen, but functional neuroimaging shows an increased brain metabolism associated with inability to get asleep. In contrast, it has been suggested that decreased activity in the prefrontal cortex may be related to sleep deprivation effect (Nofzinger EA et al, 2004). In a few occurrences, however, insomnia is associated with identified brain lesions. This may occur when the hypothalamic suprachiasmatic nucleus doesn‘t give the start for sleep, when waking structures are not inhibited by sleeping structures, when thalamocortical bundles that carry on sleep are lesionned, or even when some waking structures are impaired. In addition, it may be due to a dysfunction of structures responsible for need for sleep. Some strategically located brain tumours, strokes, and consequences of brain traumas are characterized by insomnia. Several neurodegenerative diseases such as Steele-Richardson, Alzheimer, Parkinson or Huntington diseases may also lead to insomnia. A series of different disorders, Fatal insomnia, rare cases of Creutzfeldt-Jakob disease, Morvan‘s chorea, limbic encephalitis and delirium tremens, often associated with severe insomnia, have been grouped together under the name ―agrypnia excitata‖(Montagna P and Lugaresi E, 2002). Most of the time, on the other hand, when recognised, the lesions in these disorders are widespread, making definite correlations difficult. In addition, combined factors (organic, psychic, cognitive or therapeutic) are often associated. In some cases, however, the lesions involve various regions, some of which are responsible for sleep organisation, which makes clinico-pathological correlations possible. In addition, in a few selected cases, organic brain lesions are localized enough to throw light on the mechanism of associated sleep disorders.

1. The Biological Clock Hypothalamic suprachiasmatic nucleus is supposed to start sleep. Cells of this ―pacemaker‖ contain a series of clock genes with rhythmic expression. It is influenced by light stimulation from the retina through the retinohypothalamic tract (glutamatergic), and indirectly from the geniculohypothalamic tract (GABAergic) and projects widely (among other regions) towards the pineal gland which secretes melatonin. Circadian synthesis of melatonin in the pineal gland is part of the rhythmic controls set up by the suprachiasmatic nucleus. The neuronal inputs originate in the retina which project fibers to the suprachiamatic nucleus; then the signal passes through the paraventricular nucleus, follows the medial forebrain bundle, and ends in the intermediolateral cell column of the upper thoracic spinal cord, from where it projects to the superior cervical ganglion, which sympathetic neurons innervate the pineal gland (Møller M and Baeres FM, 2002). The signal to the pineal gland is mediated by norepinephrine, which is inhibited by light. Melatonin is implicated in numerous physiological processes, including circadian rhythms, stress and reproduction, many of which are mediated by the hypothalamus and pituitary gland. Melatonin receptors MT1 immunoreactivity is seen in the suprachiasmatic nucleus, paraventricular nucleus, periventricular nucleus, supraoptic nucleus, sexually dimorphic nucleus, the nucleus of the diagonal band of Broca and the nucleus basalis of Meynert, infundibular, tuberomamillary nuclei and the mamillary body, thalamic ventromedial, dorsomedial nuclei and paraventricular nuclei (Wu YH et al, 2006).

Neuropathology of Insomnia in the Adult: Still an Enigma!

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The suprachiasmatic nucleus, optic tracts, retinohypothalamic pineal gland and MT1 receptors are crucial to induce sleep. Lesions of this circuit may induce insomnia characterized by delayed sleep onset, eventually leading to day-night reversal : a) Tumors of the anterior hypothalamus occur more frequently in children. The anterior hypothalamic syndrome consists of insomnia and loss of thirst regulatory mechanisms (Carmel PW 1980). In occasional larger lesions which interrupt the output from the supraoptic and paraventricular nuclei, diabetes insipidus is noticed. Tumors or cyst of the pineal gland may also lead to delayed sleep onset (Etzioni A et al, 1996; Taraszweska A et al, 2008). A 17-year-old boy, presented with severe headaches, associated with insomnia. Preoperative MR imaging suggested tumour of the pineal gland. Histopathological and immunohistochemical examination of the specimens from this surgical case revealed a characteristic pattern of cystic structures within the pineal gland, surrounded by layers of a dense fibrillar glial tissue and pineal parenchyma, consistent with non-neoplastic glial cysts (Taraszweska A et al, 2008). b) Delayed sleep phase syndrome is also frequently associated to brain injury. It probably results from alterations either of the suprachiasmatic nucleus, or of its connecting fibers (Quinto C et al, 2000), which could imply basal contusion or diffuse axonal injury (Wang JY et al, 2008 ; Kumar R et al, 2009) c) In the ―normal old‖aged persons, who pathologically may correspond to pre-clinical stages I and II of Braak‘s classification of abnormal tau-associated lesions of Alzheimer disease (Braak H and Braak E, 1991), sleep initiation can be much delayed. In Alzheimer disease (AD), sleep disorders consist mainly in hypersomnia at the onset of the disease. Then, insomnia and inversion of circadian rhythm take place, the patient wandering during the night and sleeping during the day. Melatonin, which inhibits neurons mediated by receptor MT1, may regulate neuronal sensitivity to stimuli that set biological clock in phase with environmental pressures (Wu YH et al, 2006). Melatonin has been reported to be low in old persons, but much variations were found: some have high levels, others have low levels and a few have even no evidence of melatonin secretion, whatever the differences in self reported quality of sleep (Baskett et al, 2001). It may be emphasized, however, that these data have been found in aged persons in the absence of neuropathological data. Melatonin levels in the cerebrospinal fluid decrease during the progression of AD associated tau neuropathology, tightly linked to neuronal loss (as assessed by the Braak‘s stages), and this is already observed in cognitively intact subjects with the earliest AD neuropathology (Braak stages I-II), the so-called preclinical AD (Wu YH et al, 2003). It has been shown that dysfunction of the sympathetic regulation of pineal melatonin synthesis by the suprachiasmatic nucleus is responsible for melatonin changes during the early AD stages (Wu YH, 2005). In neuropathologicaly assessed Alzheimer‘s disease, two main lesions (already found in some aging ―normal‖ brain) are seen: essentially extracellular deposits of Abeta (diffuse and focal deposits, including the core of senile plaques) and mostly intraneuronal inclusions of hyperphosphorylated tau, including neurofibrillary tangles, neuropil threads and the corona of

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senile plaques. The latter are highly linked to neuronal loss (Duyckaerts C, 2008 ; Dixon DW, 2008). The regions implicated in circadian rhythms (hypothalamus and pineal gland) have been thoroughly studied in AD by Dick Swaab‘s group (2004) using early postmortem samples from the Amsterdam tissue bank. In 68 pineal glands, some clock genes (hBmal1, hCry1and hPer1) were found rhythmically expressed in aged control cases (stage 0 of Braak), and there were some correlations between hPerl expression and adrenergic beta1 (hbeta1ADR) receptors. These data were linked to the hour of death. In AD (late stages V-VI of Braak), and even at pre-clinical stages I-II, (―old aged‖persons), rhythmic expression of clock genes was no longer found and the correlations disappeared. Surprisingly, hCryl mRNA was increased in AD. The authors suggest that brain control upon pineal gland is lost, in reference to similar results obtained in the pineal gland of de-afferented rats (Wu YH et al, 2006). These data may be match up to the reduction of the hypothalamic neurons that express melatonin MT1 receptors, vasopressin and VIP (vasoactive intestinal peptide) at stages V-VI of Braak, whereas in aged controls (Braak‘s stage 0) and at early stages I-II, the reduction of neurons concerns only those expressing melatonin receptors. d) In Parkinson disease (PD), characterised by a synucleinopathy (Lewy bodies and Lewy neuritis) involving progressively some selected areas of the peripheral and the central nervous system (Hauw JJ et al, 2008 ; Braak H and Del Tredici K, 2008), as expanded later on, insomnia is the most common of the sleep disorders: 67% of patients have problem initiating sleep and 88% have sleep maintenance impairment (Factor SA et al, 1990). The number of neurons expressing melanoconcentrating hormone (MCH) is reduced from 12% at stage I to 74% at stage V, at the same time as their size increases significantly. Hypothalamic neuronal loss may play a more significant role in this disease than previously thought (Braak H and Del Tredici K, 2008). e) Huntington disease (HD) is characterized by dementia, chorea and a dominant mode of inheritance. It is caused by an abnormal expansion of CAG repeats in the gene encoding Huntingtin. Sleep disturbances have been described in about 20% of patients with late-onset HD. Insomnia with impaired initiation and maintenance of sleep is a common complaint particularly in moderate to severe cases. With progression of the disease, sleep fragmentation increases (Myers RH et al, 1985). Sleep records used to show increased spindle density (Emser W et al, 1988). More recent sleep records showed low sleep efficiency, increased stage 1, delayed and shortened REM sleep and increased periodic leg movements (Arnulf I et al, 2008). On cerebral imagery, global cerebral atrophy did not significantly correlate with sleep parameters while atrophy of caudate nuclei was associated with reduced slow wave sleep and increased periods of awakeness (Wiegand M et al, 1991). Hypothalamic atrophy occurs at early stages, associated with loss of orexin (hypocretin) and somatostatin-containing cell populations. Endocrine changes including increased cortisol levels, reduced testosterone levels and increased prevalence of diabetes are also found in HD patients. In HD mice, alterations in the hypothalamic-pituitary-adrenal axis occurs, as well as pancreatic beta-cell and adipocyte dysfunction (Petersen A and Björkqvist M, 2006).


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2. The Structures Inhibiting Waking Systems Sleep is set on only when structures responsible for waking state are inhibited: the ventrolateral preoptic area, which is in charge of sleep, inhibits the lateral hypothalamus (orexin/hypocretin system), Meynert nucleus, posterior hypothalamus and periaqueductal grey matter (Mignot E et al, 2002; McGinty D and Szymusiak R, 2003; Swaab D, 2004; Saper C et al, 2005; Sakurai T, 2007). Stress, which stimulates CRF and orexin/hypocretin system is the usual cause of lack of inhibition of the waking structures. Lesions of the ventrolateral preoptic area or its connecting fibers to the waking structures may also impair the setting of sleep and lead to initiation of sleep insomnia: a) Tumors of the anterior hypothalamus that impair biological clock, may also impair ventrolateral preoptic areas, when they are large enough. b) In Parkinson‘s disease, ventrolateral preoptic areas is involved at an early stage (Braak H and Del Tredici K, 2008). That could account for the severe insomnia occurring in this disease. c) Whipple disease is a rare infectious disease that typically infects the bowel. It is caused by a bacteria named Tropheryma whippelii. It can affect any system of the body. At times, brain is the only organ affected. Symptoms include diarrhea, intestinal bleeding, abdominal pain, loss of appetite, weight loss, fatigue, weakness, arthritis and neurological signs and symptoms. Patients could suffer from hypersomnia or insomnia. Hypothalamic manifestations occur in 31% of Whipple encephalopathies, including polydipsia, hyperphagia, change in libido and insomnia (Papadopoulou M et al, 2005). Cerebral lesions of Whipple disease are disseminated throughout hemispheric and brain stem grey matter much more than in the white matter. They are more prominent in the hypothalamo-hypophyseal region and the upper brain stem especially in the periaqueductal grey matter (Powers J and Rawe SI, 1979). In a well-studied case of Whipple disease, progressive and almost complete sleep loss was the initial and predominant symptom. Polysomnographic recording over 24 h, and during several consecutive nights, showed a complete abolition of the sleep-wake cycle with nocturnal sleep duration of less than 15 min. Hypothalamic dysfunction occurred, with flattening of circadian rhythmicity of cortisol, TSH, GH and melatonin, and hypocretin was reduced in CSF. However, FDG-PET scan revealed hypermetabolic zones in cortical and subcortical areas, including the brainstem. In this case, hypothalamic dysfunction was probably not the only cause of insomnia (Vodeholzer U et al, 2002).

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3. The Structures Carrying on Sleep 3.1 Slow Wave Sleep After the two previous steps have been achieved, thalamus switches to sleep (Akire MT et al, 2000). Slow sleep is the product of synchronized rhythmic activity of the thalamic reticular nuclei projecting to the cortex (thalamocortical activity) and hyperpolarizing cortical layer V. Sleep spindle and delta waves are thought to be due to these thalamocortical networks (Steriade M et Timofeev I, 2003). The main neurotransmittor is GABA. Deactivation of the orbital, dorsolateral prefrontal and inferior parietal cortices occurs during slow wave sleep and REM sleep, as shown by PET study (Braun AR, 1997). Various brain lesions may involve the thalamocortical network and induce insomnia: stroke, trauma, normal aging and Alzheimer disease, and prion infection, a) Insomnia is associated with acute stroke, whatever the location, and sleep duration is reduced proportionally to the size of the stroke (Müller C et al, 2002). When stroke involves the middle cerebral artery territory, stages 2 and 3 and spindle density decrease during the few days following stroke. Following a thalamic infarct involving postero-lateral, ventral postero-lateral, dorso-medial and centromedial nuclei (a mixture of reticular/intralaminar, limbic and specific sensory nuclei) a 48hour insomnia has been reported (Garrel S et al, 1966). Surprisingly, thalamic infarcts are seldom reported as a cause of insomnia, since thalamus plays an important role in generating sleep spindles. As thalamocortical activity is also involved in waking state, patients are frequently neither asleep nor totally awake. Actually, thalamic infarcts are more responsible for hypersomnia or altered states of consciousness than for insomnia (Castaigne P et al; 1981; Schmahmann JD, 2003). The clinical presentations of thalamic stroke is not specific to individual nuclei because even small, focal ischemic lesions are seldom confined within nuclear boundaries. For instance, there is nothing such as an ―infarct of the reticular/intralaminar nuclei‖, that would be the best candidate to produce insomnia (De Girolami U et al, 2009). b) Insomnia is a frequent consequence of brain injury. It is attributed to shearing mechanism that induces diffuse axonal injury, as already mentionned. Most of the time it is associated to depressive mood and is usually reversible (Fichtenberg NL et al, 2002). Very few cases of localised brain injury leading to persistent insomnia are available. A case of total insomnia during 6 days was reported after right thalamotomy in a Parkinsonian patient who had benefited from a left sided alcoholic thalamotomy in the past (Bricolo A,1967). The right lesion involved ventral lateral, ventral intermedial and anterior part of the ventral intermedial nuclei, medial center and the subthalamic area, the dento-rubro-thalamic bundle and the H1 Forel region. The left sided lesion involved the medioventral part of the lateral ventral nucleus, ventral intermedial nucleus and anterior part of the ventral intermedial, median center and dorsal subthalamic bundles.


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c) In old persons, sleep is interrupted by frequent awakenings. There is age-dependent changes in sleep EEG, with a shift of power from the anterior towards the central regions (Landolt HP and Borbély AA, 2001). In Alzheimer‘s disease, sleep records show reduced sleep efficiency, increased amounts of stage I and increased numbers of awakenings. The typical lesions of tauopathy in clinical AD involve limbic, then hemispheric cortex with associative areas being predominantly injured. A number of nuclei that give projections to the cortex (involving mainly cholinergic, serotoninergic and histaminergic systems), are also injured (Duyckaerts C and Dickson DW, 2003), although initial tauopathy occurs in the peri-rhinal and entorhinal areas in presymptomatic patients. As a matter of fact, the development of abnormally phosphorylated tau occurs typically as described by Braak (I and II: preclinical stages, thus including ―normal aged people‖; III and IV: limbic stages: Ammon horn involvement ; V and VI : isocortex involvement) (Braak H and Braak E, 1991). The ventro-medial amygdala (Tsuchiya K and Kosaka K, 1990), and the basal nucleus of Meynert are involved precociously (Sassin I et al, 2000). On the contrary, the striatum and the thalamus are usually spared, with the exception of thalamic limbic nuclei which are also affected early (Braak H and Braak E, 1991). d) Prion diseases, or transmissible spongiform encephalopathies (Creutzfeldt-Jakob diseases, fatal insomnias, Gerstmann-Strausler-Scheinker disease…) are due to a misfolded isoform enriched in beta-sheet of a normal protein (PrP). We will call PrPres this abnormally conformed protein for it is partly resistant to proteinases. In addition, it is transmissible to some animal species, including human. In PrP knockout mice devoid of prion protein, there is an alteration in both circadian activity rhythms and patterns. This could imply that prion protein is strongly involved in sleep regulation (Tobler I et al, 1996). However, in humans affected by Prion disorders, sleep disturbances are related more to the localisation of lesions than to prion infection by itself. For instance, in fatal insomnias, insomnia is constant; in Creutzfeldt-Jakob diseases, sleep disorders are a variable feature and in GerstmanSträussler-Scheinker disease, sleep is usually normal. These different phenotypes are likely related to different conformations of PrPres. The distinct localization of neuronal loss or systems that could explain the different phenotypes may be difficult to assess, however, unless specific markers (such as enzymes of neurotransmitter metabolism) allow numerating definite neuronal classes. The classical triad of lesions in prion diseases is not always easily recognisable: in contrast to spongiform change and gliosis involving both astrocytes and, at a lesser degree, microglial cells, neuronal loss is often difficult to detect in the early lesions. However, it is conspicuous in the severe lesions where it induces gross atrophy. Early, severe, and selective neuronal loss affects a subset of parvalbumin positive GABAergic inhibitory interneurons both in human and experimental prion diseases, except in FFI (Guentchev M et al., 1997; Budka H et al, 2003). Electron microscopy does not disclose any known infectious agents, but tubulovesicular structures, particles of unknown origin and chemical composition which seem to occur only in prion diseases (Liberski PP et al, 2008). These lesions are associated with various types of

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Jean-Jacques Hauw and Chantal Hausser-Hauw PrPres deposits seen by immunohistochemistry (Privat N et al, 2008) or immunobloting. Western blotting provides most sensitive, but less precise data.

Fatal insomnia (FI) is a rare prion disease which affects as well men as women, at an age ranging from 36 to 62 years (Lugaresi E et al, 1986 ; Manetto V et al, 1992 ; Krasnianski et al, 2008). Most FI have a genetic autosomic dominant aetiology (Montagna P et al, 1998), usually linked to a mutation at codon 178 (D178N) of the gene of prion protein (PRNP). Interestingly enough, in the very same family, fatal familial insomnia (FFI) phenotype usually occurs only when there is a methionine (M) on the mutated allele at the polymorphism methionine-valine (MV) of codon 129 of the PRNP. When a valine (V) is present on this allele, a genetic disease with Creutzfeldt-Jakob phenotype occurs. Variants of this scheme have been reported, however, including typical Creutzfeldt-Jakob disease, FFI, and what was thought to be an autosomal dominant cerebellar ataxia in the same family (McLean CA et al, 1997) and different involvement of thalami and frontal lobes on PET scan in half-brothers (Johnson MD et al, 1998), suggesting that other genetic or environmental factors may play a role in the disease process. Mutations at codon 200 (E200K-129M), classified usually as familial Creutzfeldt-Jakob disease (Parchi P et al., 2003) have also lead to FFI phenotypes in cases with homozygoty VV at codon 129 (Taratuto AL et al, 2002). In sporadic fatal insomnia (sFI), also called the MM2-T subtype of sporadic Creutzfeldt-Jakob, PRNP shows no mutation. MM homozygosity at codon 129 polymorphism is also found (Scaravilli F et al, 2000). In FI, disease onset is characterized by subtle personality changes, indifference and unability to express emotions and feelings, hallucinations and depression (87%). Cognitive dysfunction (87%) is characterized by lack of attention and hypovigilance. Myoclonus (70%), ataxia, dysarthria (61%), dysphagia (13%), pyramidal (43%) and extra-pyramidal (35%) signs occur. Profuse vegetative signs including perspiration and salivation, tachycardia, hypertension, fever, impotence, are present at the onset or a few weeks later (83%) (Krasnianski A et al, 2008). Hypovigilance is often prominent. Peudohypersomnia could also happen with profound alteration in the sleep-wake cycle (Dauvilliers Y et al, 2004). However, the hallmark of the disease is sleep loss with inability to produce the physiological patterns of slow sleep and REM sleep (96%) as well as hormonal and vegetative circadian fluctuations. Sleep records in 5 cases showed REM sleep reduction (100%), reduced efficiency of sleep (80%), deep sleep reduction (80%), periodic limb movements (60%), central apneas (40%) (Krasnianski A et al, 2008). Hypnograms of an italian case fluctuated between stage 1 and REM sleep (Provini F et al, 2008). CT and MRI are normal except for slight atrophy of the cerebrum and the cerebellum in the most advanced cases. A mild hypometabolism initiating in the thalamus, then extending to the mesial frontal areas and the whole hemispheres and basal ganglia, could be observed as soon as 13 months before the disease onset in a longitudinal 18FDT-PET scan study performed in carriers of the D178N mutation of PRNP (Cortelli P et al, 2006). Magnetic resonance spectroscopy combined with the measurement of apparent diffusion coefficient of water in different brain areas were performed 4 days before death in a 55-year-old man with familial fatal insomnia linked to D178N mutation. They showed an increase of apparent


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diffusion coefficient of water, and a metabolic pattern indicating gliosis in the thalamus but not in the other brain regions studied (Haïk S et al, 2008). In FI, the neuropathological lesions include mainly gliosis and neuronal loss, due to apoptosis (Daurandeu A et al., 1998) which is difficult to detect, as mentioned, in the early lesions. It is associated with gross atrophy in the severe lesions only. Spongiform change is mild or lacking, except in cases with very long duration (Hirose K et al, 2006). Some gliosis of the hypothalamus and periaqueductal gray matter is a common finding. In contrast, there is a severe bilateral and symmetrical thalamic degeneration with marked gliosis, neuronal loss, and usually lack of spongiform change. Gross atrophy is seen in the most affected areas, i. e. the anteroventral, mediodorsal and pulvinar nuclei. Other thalamic nuclei are usually less damaged, but intralaminar nuclei can be severely injured, especially in long duration cases. A morphometric investigation showed, indeed, that most thalamic nuclei had severely degenerated in two patients with FFI. Associative and motor nuclei lost 90% neurons, and limbic-paralimbic, intralaminar and reticular nuclei lost 60%. Although PrP immunohistochemistry shows various demonstrable deposits of PrP, biochemical studies usually detect PrPres at highest levels in the thalamus, and at lower levels in the brain stem and limbic structures (Gambetti P et al, 2003 ; Sazaki K et al, 2005 ; Ironside JW and Head MW, 2008). Serotoninergic neurons are selectively decreased in the raphe nuclei (Wanschitz J et al, 2000). It may be mentioned that in mutations at codon 200 (E200K-129M), which may also lead to FFI phenotype, the usual lesions are alike those of sporadic Creutzfeldt-Jakob of the MM1 type (Parchi P et al, 1999; Parchi P et al, 2003), affecting the cerebral cortex, striatum, medial thalamus, and cerebellum. There is severe gliosis and moderate to severe neuronal loss in the thalamic nuclei and the inferior olivary nuclei, and spongiform change is particularly evident in the medio-dorsal nucleus of the thalamus, with rare and coarse spongiform degeneration in the isocortex and the putamen in a case with severe insomnia. In a E200K-129M case of CJD with thalamic involvement, insomnia occurred as the initial symptom, and was severe and intractable. Polysomnographic studies showed an absence of deep sleep and of REM sleep. On neuropathological examination, there was major involvement of the thalamus and of the inferior olivary nucleus, as could be seen in D178N mutation. Spongiform changes were mild in the neocortex and not patent in the cerebellum (Taratuto AL et al, 2002). ). In sporadic fatal insomnia (sFI), also called the MM2-T subtype of sporadic CreutzfeldtJakob, there is a marked atrophy of the thalamus and inferior olive, with mild lesions in other areas (Scaravilli F et al, 2000, Piao YS et al, 2005). In summary, thalamus is always involved in FI and thalamic lesions appear responsible for disappearance of deep stages of sleep, delta waves and spindles. Degeneration of mediodorsal, anteroventral and pulvinar nuclei of the thalamus is prominent. The disorganization of most thalamic circuits is a condition necessary for the sleep-wake rhythm being affected (Macchi G et al, 1997). This could be confirmed when comparing with the mild hypometabolism initiating in the thalamus observed as soon as 13 months before the disease onset when sleep was normal (Cortelli P et al, 2006). Mediodorsal nucleus has important connections both with reticular nucleus of the thalamus and cerebral cortex. Its lesion, or the frequent lesions of the intralaminar nuclei, are thus likely responsible for disappearance of spindles and delta sleep. By contrast, REM sleep often (but not always)

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persists because the tegmentum pontis sublaterodorsal nucleus and precoereuleus area, ventrolateral periaqueductal grey matter and tegmentum latero-pontis are not always severely affected. Hypovigilance and sleepiness could depend on damage of other thalamic structures, i.e. reticular nuclei for instance. In sporadic Creutzfeldt-Jakob disease (sCJD), PrPres seems to occur in the brain for no obvious reason (―natural stochastic conversion‖) and the disease manifests as a rapidly evolving dementia. A number of clinical criteria for suspicion of sCJD have been proposed (Brandel JP et al., 2000; Zerr I, 2008); every one includes myoclonus, cerebellar signs, pyramidal or/and extrapyramidal signs, and some akinetic mutism or lower motor neuron involvement. None of them, however, mention insomnia or other sleep alteration. Typical EEG (pseudoperiodic sharp waves) and detection of 14-3-3 protein in the CSF are also considered in some criteria. Even if insomnia is rare, sleep disturbances are frequent, however, and night-time behaviour disorders have been noted in 37% of 30 cases of sCJD (Zerr I, 2008). Sleep disorders can sometimes be similar to those found in FFI (Landolt HP et al, 2006). These authors followed seven consecutive patients with definite sCJD who underwent a systematic assessment of sleep-wake disturbances, including clinical history, video-polysomnography, and actigraphy. Sleep-wake symptoms were observed in all patients, and were prominent in four of them. All patients had severe sleep EEG abnormalities with loss of sleep spindles, vertex sharp waves, K-complexes, and slow sleep, very low sleep efficiency, and virtual absence of REM sleep. The EEGs were similar to that of wakening state, at times interrupted by muscular atonia without the other characteristics of REM sleep. Neuropathological examination (Budka H et al., 2003; Landolt HP et al., 2006; Ironside JW and Head MW, 2008) show that, macroscopically, there may be either no gross alteration or a diffuse cerebral and cerebellar atrophy. The lesions typical of sCJD are patent spongiform change, gliosis, neuronal loss, and deposits of PrP. In about 10% of cases, these deposits aggregate into amyloid plaques of the ―kuru‖ type. Several regional involvements could occur, in relation to the type of mutation or, in sporadic cases, to the M/V distribution at polymorphic codon 129 of the PrP gene in combination with the migration pattern of PrPres on Western blotting:1 or 2 following the classification of Parchi P et al. (1999). Six main molecular subtypes can thus been recognized (Parchi P et al., 1999; Zerr I, 2008). Whatever either the prominent types of lesions (spongiform change, gliosis, marked neuronal loss, plaques, type of immunodeposit) or their localisation (cortical, basal ganglia, cerebellum, brain stem nuclei), no insomnia was expressly described (Zerr I, 2008), but insomnia is not a systematically noticed symptom. It must be stressed upon that in Landolt HP et al (2006) patients with definite sCJD who underwent a systematic assessment of sleep-wake disturbances, and had severe sleep EEG abnormalities with loss of sleep spindles, very low sleep efficiency, and virtual absence of REM sleep, autopsy revealed prominent changes in cortical areas, and only mild changes in the thalamus. A severe involvement of the thalamus can be observed in some cases of CJD (Nagashima T et al, 1999, Yamashita M et al, 2001). The MV2 subtype, where the thalamus is predominantly affected, is easily distinguished from FI, always MM at codon 129 polymorphism.


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Studies concerning hypothalamus have mainly concerned pituitary infectivity. Hypothalamus per se is seldom mentioned. In summary: In CJD, insomnia is frequent, but is not a constant symptom. It appears to be associated with involvement of the thalamus in some cases, of the cortex in others. Variant CJD (Ironside JW and Head MW, 2008), iatrogenic CJD (Brown P et al, 2001) and Gerstman-Sträussler-Scheinker disease (GSS) have quite different clinical and pathological characteristics, but in none of them insomnia is a salient feature even if variant CJD is characterised by severe thalamic lesions. A few exceptions are provided, however, for example by P102L GGS, where two sisters showed protracted awakenings, reduced sleep efficiency, brief daytime naps. Slow wave sleep and REM sleep were preserved (Provini F et al, 2008), or in a case of variant CJD (Limousin N et al, 2008). e) In Progressive supranuclear palsy (PSP), insomnia is a frequent and important feature (Petit D et al., 2004; Sixel-Döring F et al., 2008; Hauw JJ et al., 2008). Polysomnographic studies show short total sleep time, lower sleep efficiency, drastic reduction in sleep spindles, atonic slow-wave sleep. Standard EEG shows slowing in the frontal lobes (Montplaisir J et al., 1997). Although described as normal in the seminal descriptions, the isocortex is commonly affected by lesions of glial cells and neurons predominating in the motor and temporal cortex (Hauw JJ and Agid Y, 2003; Dickson DW, 2008). Some degree of neuronal loss is seen in the striatum and thalamus, especially ventral anterior and lateral thalamic nuclei. Thalamic intralaminar caudal nuclei are often involved (Henderson J et al, 2000).Other lesions will be described later on.

f)

In Huntington disease (HD), there is usually a cortical atrophy in the frontal lobes, and significant neuronal loss has been found by morphometric studies, notably in layer VI of HD brains at stages 3 or 4 of the disease. These cells project principally to the thalamus, the claustrum and other regions of cerebral cortex. Layer V neurons have also be found in decreased densities (Hedreen JC et al, 1991). Using anti huntingtin and antipolyglutamin immunohistochemistry, neuronal intranuclear ubiquitinated inclusions can be detected long before the onset of symptoms. An increase of CD15 (carbohydrate epitope 3-fucosyl-N-acetyl-lactosamine)-positive astrocytes has been described in the lateral part of the nucleus basalis of Meynert (Morres SA et al, 1992). The most striking neuronal loss and astrocytic gliosis in the brains of HD occurs in the striatum, predominant in the caudate nucleus. However only 1-4% of striatal neurons in all grades of HD have huntingtin nuclear inclusions (Gutekunst CA et al, 1999). Medium spiny projection neurons containing GABA colocalized with substance P and especially with enkephalin degenerate first. The most severe lesions of the thalamus are seen in the centrum medianum. In seven cases, the ventrolateral thalamus was studied by quantitative cytometry. A selective 50% atrophy of microneurons (internuncial cells) was found while the macro neurons did not show significant atrophy (Dom R et al, 1976). There is also a loss of neurons of the substantia nigra and the subthalamicus nucleus.

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In summary: In HD, insomnia seems to be related to the involvement of the thalamus and even more to the involvement of the layers V and VI of the cortex. The role of the caudate nuclei in the occurrence of sleep disorders in HD is unknown.

3.2 REM Sleep REM sleep system remains hypothetical. It is also due to thalamocortical activity, like slow wave sleep, but in a desynchronised pattern, as it occurs during waking state (McCormick DA and Bal T, 1997; Wehrle R et al, 2007), under the influences of several upper brain stem nuclei. Mechanisms for tonic REM sleep and phasic REM sleep are probably somewhat different : during phasic REM periods, thalamocortical network includes basal forebrain, limbic and parahippocampal areas activity (Nofzinger EA et al, 1997; Wehrle R et al, 2007). The mechanisms that set on and set off REM sleep have been recently debated, their dysfunction being responsible for several disorders. Reciprocal inhibitory interactions between cholinergic brain stem neurons promoting REM (« REM-on ») and monoaminergic inhibitors « REM-off ») were up to now largely accepted (Siegel J, 2004). Selective lesions of these systems, however, do not seem to affect significantly REM sleep. Cholinergic system may, in fact, modulate rather than initiate this stage. Actually, recent studies in rats showed the existence of mutually inhibitor neurons, « REM-on » in the tegmentum pontis sublaterodorsal nucleus and precoereuleus area, and « REM-off » in ventrolateral periaqueductal grey matter and tegmentum latero-pontis. Each of these two neuronal populations contains interconnected GABAergic neurons. This system of reciprocal inhibition has been called ― flip-flop switch ‖, from electronic binar switch used to proceed quickly from a state to the other (Lu J et al, 2006). The existence, in human, of similar structures as ―REM-on‖ and ―REM-off‖ found in rats is highly probable. Their precise topography remains hypothetical. However, it has been possible to suggest a human equivalent of the rat sublaterodorsal nucleus and precoeruleus area « REM-on » which needs to be confirmed. The ventrolateral regions of the periaqueductal grey matter and tegmentum lateroponti may correspond to « REM-on » regions (Boeve B et al, 2007). Two ―REM-on‖ glutamatergic neuronal groups may be activated, one projecting toward the basal telencephalon, setting EEG pattern ; the other one projecting to the ventromedial medulla and spinal cord, setting muscle atonia. Ponto-geniculo-occipital sharp waves (PGO) which precede and accompany rapid eye movements are related to neurons of the mesencephalon tegmentum (rostral part of the alpha locus coeruleus and of the mesopontine nuclei). They project on the lateral geniculate nucleus of the thalamus which is a cortical relay. In human, they are assumed to be located at the pedunculopontine nucleus (Lim AS et al, 2007). Two motor systems appear implicated. One is responsible for muscular atonia, the other for suppression of motor activity (the last relay being the bulbar gigantocellularis nucleus). The former is characterised by the activation of two neuronal groups, some bearing cholinergic receptors in the locus coeruleus/subcoeruleus areas, the other glycinergic receptors in the magnocellular reticular nucleus (Fuller P et al, 2007; Luppi H et al, 2007).


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Sublaterodorsal nucleus could be at the origin of the common final pathway towards spinal interneurons which inhibit muscular tonus. This hypothesis remains to be confirmed (Boeve et al, 2007). The latter system responsible for suppression of nocturnal movements appears to be influenced by indirect pathways linking midbrain dopamine neurons with pre-motor structures in the mesopontine tegmentum and ventromedial medulla (Rye DB, 2004). Descending dopaminergic neurons from the telencephalon (A11) to the spinal cord may contribute to abnormal movements during sleep. Schematically, during REM sleep, cholinergic system is active, as it is during waking state, whereas monoaminergic systems are silent, as they are during slow stages of sleep. In summary: Lesions, in the brain stem, of sublaterodorsal nucleus, rostral part of the alpha locus coeruleus and of the mesopontine nuclei, could affect REM sleep organisation. (Dysfunction of thalamocortical loops or limbic system may also play a role in reducing the amount of REM sleep). Lesions of the noradrenergic locus coeruleus/subcoeruleus, cholinergic pedunculo-pontine nucleus and tegmentum laterodorsal, impair atonia during REM sleep. Lesions are mainly neurodegenerative in nature: progressive supra-nuclear palsy (PSP), Parkinson disease (PD) and Alzheimer disease (AD): a) In Progressive supra-nuclear palsy (PSP), apart from insomnia, the other sleep disorders include REM sleep behaviour disorder (RBD), and, less frequently, hypersomnia and pseudo-narcolepsia. On sleep records there is a lower percentage of REM sleep (Montplaisir J et al, 1997). Neuropathological gross findings include severe atrophy in midbrain where it predominates on the tectum, extending to a lesser degree to the pons. Other lesions include loss of pigment in the substantia nigra, and atrophy of the subthalamic nucleus and the superior cerebellar peduncle. Microscopic lesions, which are tauopathies, affect as well some neurons (neurofibrillary tangles in the cell body, neuropil threads in the dendrites) as some glial cells (tufted astrocytes and oligodendrocytic coiled bodies). They widely spread in brain stem and basal telencephalon where they involve several systems implicated in sleep organisation. were unchanged compared with controls. Regions severely involved include substantia nigra (more than 80% of the reported cases), then periaqueductal grey matter, locus coeruleus, and central pontine nuclei (more than 50% of reported cases). Pedunculopontine nuclei involvement is variable (Verny M et al, 1996 ; Hauw JJ et Agid Y, 2003). Other injured nuclei are superior colliculi, oculomotor nuclei, locus ceruleus, pontine nuclei, vestibular nuclei, medullary tegmentum, inferior olives and cerebellar dentate nucleus. Nuclei responsible for autonomic regulation, intermediate zone of bulbar reticular formation and gigantocellularis nucleus are the most lesionned area. Other very markedly affected regions include the pontine reticular formation, medial parabrachial nucleus, and nuclei raphe magnus and obscurus. Lateral parabrachial nucleus is less injured (Rüb U et al, 2002a). Meso-cortico-limbic dopaminergic projections are relatively spared, which contrasts with the extreme severity of nigro-striatal system lesions, especially for its ventral part (Oyanagi K, 2001). The lesions of REM ―on‖ and ―off‖ systems in the brain stem, could explain the

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reduction of REM percentage on sleep records and REM sleep behaviour disorders and episodes of pseudo-narcolepsy, occurring in the late stages of the disease (Boeve B et al, 2001; Arnulf I et al, 2005). b) In Parkinson‘s disease (PD), REM sleep is often reduced. Other sleep disorders include REM sleep behaviour disorders (RBD), restless legs and periodic limb movement syndrome, hypersomnia and pseudo-narcolepsy (Arnulf I et al, 2005 ; Park M et al, 2006 ; Hausser-Hauw C, 2007). PD is a synucleinopathy (Duyckaerts C et Hauw JJ, 2003), the spectrum of which comprises Parkinson disease and dementia with Lewy bodies, according to the predominance of signs and topography of the lesions. The lesions (Lewy bodies and fibers immunolabelled by synuclein directed antibodies) involve preferentially the brain stem in Parkinson disease, and the cortex in Lewy body dementia. Immunohistochemistry of alpha-synuclein allowed Heiko Braak et al (2003) to suggest that the synucleinopathy occurs according to a stereotyped hierarchic temporo-spatial fashion, similar to that described for neurofibrillary degeneration and other tau-associated lesions in Alzheimer disease. They first studied the topography of lesions labelled by antisynuclein antibody in two series of autopsied cases: i.: clinically characterized Parkinson disease, and ii. brains from people free from neurological symptoms and signs. The synucleinopathy could be restricted either to the olfactory bulb and peduncle or to the medulla. In the former case, the lesions remained confined to the olfactory bulb and had no tendency to spread to adjacent regions. At the opposite, brain stem synucleinopathies always involved the medulla, from which they seemed to spread progressively toward the pons, then ventral mesencephalon, diencephalon, and antero-medial mesocortex of the temporal lobe. The brain stem is affected very early: At stage I, besides dorsal nucleus of IXth and Xth nucleus, dorsal spinal cord intermediolateral horn, gastro-intestinal nervous system are involved; at stage II, inferior raphe nuclei, magnocellularis reticular formation, among which bulbar gigantocellularis nucleus, and coeruleus-precoeruleus complex are involved. Substantia nigra and ventral tegmental area are involved at stage III (Braak H et al, 2008). In summary: in PD, Pedunculo-pontine nuclei, Meynert basal nucleus, tubero-mamillary nucleus and oral raphe nuclei involvement could explain REM sleep disorders. c) In Alzheimer‘s disease (AD), REM sleep alterations may not be present early in the disease, and a relationship between the severity of sleep disturbance and the severity of dementia is found (Montplaisir J et al, 1995). Superior and dorsal brain stem regions involvement could explain REM sleep disorders (Parvizi J et al, 2001).

4. The Structures Responsible for Waking State Sleep-wake organisation depends on oscillatory connections between sleep and arousal structures through feedback and reentry mechanisms. Thus lesions of structures related to arousal may impair sleep.


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The waking state is the result of a depolarisation of thalamocortical and thalamic reticular neurons and enhanced excitability in many pyramidal cells under the release of several different neurotransmitters from limbic system and brain stem nuclei (Steriade M and Timofeev I, 2003). The cholinergic systems are issued from two main pathways: the basal forebrain (magnocellular formations of the base, among which the basal nucleus of Meynert is the best known), and from the brain stem, originating from the tegmentum laterodorsal and pedunculo-pontine nuclei (also called ―meso-pontine‖ or ―peri-brachial‖) and from the bulbar gigantocellularis nucleus. It stimulates the cortex directly or through the mesencephalon reticular formation or the thalamocortical diffusely projecting nuclei, i.e. intralaminar formations (aspartate/glutamate). It could also stimulate the hypothalamic tubero-mamillary nucleus. Monoaminergic systems include: histaminergic pathways from the hypothalamic tuberomamillary nucleus, noradrenergic projections from the locus coeruleus, and serotoninergic pathways from the pontine raphe nuclei. They project directly to the cortex. The role of dopamine is uncertain. However pharmacological, biochemical and physiological studies suggest that mesocorticolimbic dopamine may help maintain wakefulness (Rye DB, 2004). Pharmacological evidence suggests the involvement of dopamine neurons, especially in the ventral tegmental area (A10), for the control of alertness (Lu J et al, 2002). On the other hand, L-DOPA and dopamine agonists induce sleepiness! Orexin/hypocretin system: Orexin (or hypocretin) is secreted in neurons of the lateral and posterior hypothalamus, and this system gives projections to the locus coeruleus, tuberomamillary nucleus and raphe nuclei, among others. They are highly excitatory neuropeptide hormones. They strongly stimulate the various brain nuclei including dopamine, norepinephrine, histamine and acetylcholine systems and appear to play an important role in stabilising wakefulness and sleep (Mignot E et al, 2002). All these systems also give descending projections for control in variations of breathing and muscle tonus associated with the different stages of sleep and wakefulness. During wakefulness, cholinergic afferent system to the thalamus, monoaminergic afferent systems to the cortex, orexin/hypocretin system widespread afferences, are active ; during slow stages of sleep, they are supposed to be inactive, or strongly inhibited. Lesions of the waking structures may produce hypersomnia, insomnia or both disorders. Some strokes, brain trauma, limbic encephalitides and Morvan‘s fibrillary chorea, several neurodegenerative disorders and prion diseases are examples of sleep and wake disorders occurring after arousal system lesions. a) Insomnia has been reported, though rarely, with ventral pons and mesencephalon strokes (Garrel S, 1966; Baldy-Moulinier M et al, 1977).Insomnia and hallucinations were also present in 7 patients in association with small vascular lesions of the pontine tegmentum. Insomnia affected both non-REM and REM sleep, appeared in the acute phase and tended to improve with time. Autopsy of one case revealed lesions of the pontis centralis caudalis and pontis centralis oralis nuclei (Forcadas MI and Zarraz JJ, 1994). In another case, sleep and dream suppression followed a lateral medullary infarct (Hobson A J 2002). As a matter of fact, medullary infarcts are

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Jean-Jacques Hauw and Chantal Hausser-Hauw exceptionally responsible for insomnia. To our knowledge, it is the only reported case. b) In severe brain injury responsible for lesions located caudally to the mesencephalon, there is no longer any EEG activity corresponding to sleep (Mangin P et al, 1979). If patients recover from coma, they may suffer from insomnia. A case of insomnia related to post-traumatic pontine lesions was reversed by 5HTP(Guilleminault C et al,1973). c) Limbic encephalitis is a clinico-pathologic complex of symptoms which merged half a century ago, and the aetiology of which progressively diversified. Initially characterized by symptoms and signs indicating lesions predominant in the limbic system (memory and behaviour troubles, temporal seizures) and by neuropathological lesions suggesting an immunopathologic mechanism in the same territory, it went through many, diversely intricated, periods: viral, paraneoplasic and dysmetabolic.

Corsellis JAN et al (1968) described a paraneoplastic encephalitis of the limbic system developing in patients with systemic cancers, among encephalitides affecting mainly the temporo-cingular areas, the large majority of which were necrotic and of herpetic aetiology. Soon, however, the lesions revealed to be more diffuse than initially thought (extending to other brain areas, and mostly to the diencephalon, cerebellum, brain stem and spinal cord), which allowed to unify a number of clinico-pathologic descriptions («paraneoplastic polioencephalomyelitides ») (Goldbert GJ and Norton AR, 1968 ; Dubas F et al, 1982 ; Rosenfeld MR et al, 2001 ; Dalmau J et al, 2004). Lymphoid cells were found in the cerebral tissue where necrotic lesions were rare or absent. Multiple antibodies against onco-neural antigens (neuromuscular junction proteins, nerve terminal/vesicle-associated proteins, neuronal RNA binding proteins, or neuronal signal-transduction proteins) were found in the blood and the CSF, and were called for example anti HU, anti Yo … (Seeger RC et al, 1979 ; Darnell RB, 1996). On neuropathologic criteria, these encephalitides were grouped together with similar disorders arising in the absence of cancer (Dubas F et al, 1982). In 2004, indeed, Vincent A et al. showed that analogous encephalitides, often unrelated to systemic cancers, were associated with antibodies against either voltage-gated potassium channel or other neuronal membrane antigens. In most cases, MRI abnormalities were seen in the temporal lobe only. In a few cases, however, more diffuse lesions (frontal lobes, insula, cerebellum) were seen. These affections could be improved by reduction of the antibody levels. More recently, it was shown that encephalitides related to ovarian cancer were associated with antibodies to some membrane receptors of N-methyl-D-aspartate, NR1 and 2, and had a favourable outcome under plasma exchange and corticosteroids (Seki M et al, 2008). Limbic encephalitis, which could be linked also to the as yet not understood Rasmussen‘s encephalitis and maybe Morvan‘s fibrillary chorea, is an expanding concept (Graus F et al, 2008). Among 130 000 suspected paraneoplastic autoimmunity patients, 80 cases were positive for voltage-gated potassium channel (VGKC) autoantibodies (Tan KM et al, 2008). The


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pathogenic role of anti VGKC IgG is well known and intravenous immunoglobulins or plasmapheresis are most of the times efficient treatments. For these patients, clinical signs and symptoms included: cognitive alteration, with or without hallucinations, agitation and depression (71%); temporal lobe seizures or extra-temporal seizures, partial or generalized (38%); hypothalamic involvement: hyponatremia and hyperphagia (38%); dysautonomia (33%); myoclonus (29%); peripheral nervous system involvement (neuromyotonia, myokimia, cramps, sensitive or motor neuropathy, Morvan‘s syndrome (25%) ; extrapyramidal signs, tremor, rigidity, akinesia, chorea (21%); cranial nerves involvement, diplopia, dysarthria, dysphagia, facial palsy, facial hemispasm (19%). A cancer occurred in 33% of the cases, another autoimmune disorder in 33% (thyroïditis and diabetes). Sleep disorders occurred in 26% of the cases, including hypersomnia (13%) and insomnia (14%).Brain MRI showed T2/FLAIR hyperintensity in mesial temporal regions, unilateral in 8 cases or bilateral (12 cases), hyperintensity of the corpus callosum (1 case) and multifocal cortical hyperintensity (1 case) or generalised cortical atrophy (4 cases). The lesions of limbic encephalitis, whatever the mechanism (paraneoplastic or not) may be quite inconspicuous at gross examination, but, when severe, they can induce brain atrophy. They are often most pronounced in the limbic system, being bilaterally located in the hippocampus, medial temporal lobes, amygdaloid nuclei, mamillary bodies and orbital cortex. Histologic study reveals an interstitial infiltration of T-cells which can be grouped into clusters, cuffing the small vessels or dispersed in the grey mater. The T cells may be immunolabelled with antibodies against various antigens. The white matter is characteristically spared, and demyelination is not conspicuous. The remainder of the hemispheres is usually spared. (for review, see Dalmau J, 2008 ; Graus F et al, 2008) Other causes of limbic encephalitis, such as viral encephalitis (herpesvirus 6) in stem cell transplant recipients have been observed also. In five cases, clinical signs were short-term memory loss, insomnia and seizure activity in the temporo-basal areas. MRI showed increased hippocampal T2 and FDG-PET showed increased hippocampal glucose uptake (Wainwright MS et al, 2001). In summary: In limbic encephalitis, insomnia seems to be related to involvement of the limbic system, but the exact mechanism remains unexplained. d) Morvans‘s fibrillary chorea is a rare autoimmune disorder clinically characterized by acute and severe insomnia associated with anxiety, tachycardia, profuse perspiration and neuromyotonia (Serratrice G and Azulay JP, 1994 ; Hudson LA et al., 2008). The clinical course is benign in about 90% of the cases. In the remainder, the disease evolves into death in several weeks or months. Sleep is absent in the four months preceding death in malignant cases (Fisher-Perroudon et al, 1974) or is severely impaired if the evolution is more benign (Silber et al, 1995). A case of Morvan‘s syndrome occurred in a 76-year-old patient suffering from pulmonary adenocarcinoma and antibodies to VGKC. He was confused, restless and disoriented in time and space. When left alone, he would slowly lapse into a stuporous state with dreamlike episodes (enacted dreams) but was never asleep. Marked hyperhidrosis and excessive salivation and lacrimation were present as well as diffuse muscle twitching and spontaneous myoclonus. A 24-hour-video polysomnography showed


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that spindles, K complexes and delta waves were absent. EEG was dominated by ―wakefulness‖ and ―subwakefulness‖ alternating or intermingled with short atypical REM sleep phases, characterized by loss of muscle atonia (Liguori R et al, 2001). Actually, sleep records show similarities between Morvan‘s chorea and fatal familial insomnia (Provini F et al, 2008). Fundamentally, the neuropathology of Morvan‘s chorea is not understood. It could be related to an humoral immunopathologic disorder. In the case of Liguori R (2001) the brain was grossly unremarkable. Histological examination was also unremarkable. Direct immunohistochemistry on frozen sections of the post-mortem brain tissue showed areas of substantial leakage of IgG in the thalamus and striatum and diffusion into the parenchyma of antibodies bound to neuronal cells. In sections of cortex, there was evidence of antibodies in the blood vessels with only mild leakage into the surrounding tissue. However, these findings are non specific, and no control case was studied (Liguori R et al, 2001). e) In Fatal Insomnia, involvement of the cortex, when seen, is remarkably mild. When present, it includes slight spongiform change and gliosis often confined to the limbic cortex: orbitofrontal cortex, anterior gyrus cingulus and the entorhinal cortex, in short duration cases. In long duration cases, isocortical spongiform change and gliosis may be widespread, and even seen in the cerebellum, but they are always most prominent in the corticolimbic regions, including hippocampus and entorhinal cortex. According to Lugaresi E (1998), the degeneration of the thalamic nuclei, involved in the circuit of gyrus cinguli and orbitofrontal cortex to hypothalamus and reticular brainstem formation, releases hypothalamus and brainstem from corticolimbic control, and may result in loss of sleep. f)

In neurodegenerative disorders, waking structures as well as sleeping structures are involved so that hypersomnia as well as insomnia are frequent. The part played by lesions of the waking structures is difficult to assess. In PSP lesions of waking network, either cholinergic (Javoy-Agid F, 1994) or adrenergic, are precocious. Cholinergic nuclei of the brain stem are severely affected (Warren NM et al, 2005). In PD there is massive neuronal loss in intra-laminar thalamic nuclei, which are important relays of the cholinergic network for waking state (Henderson J et al., 2000) and in the thalamo-limbic nuclei (Rüb U et al, 2002b). The limbic system is affected earlier, at Braak‘ stage III, where the amygdala, the limbic cortex (entorhinal cortex and ammonian fields) are involved. In contrast, the cingular cortex is spared until stages V and VI. Lateral hypothalamic areas are involved at a precocious stage with orexin/hypocretin neuronal loss, as seen by immunohistochemistry, starting at stage I (23%) and being at its zenith at stage V (62%) (Thannickal TC et al, 2007). In AD, various structures in the brain stem implicated in waking network and ―allostatic‖ influences are precociously injured : initial tauopathy occurs in the peri-rhinal and entorhinal areas, locus coeruleus (German DC et al, 1992),


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raphe pontine nuclei (Rüb U et al, 2000), medial part of the substantia nigra (Uchihara T et al, 1992), and tegmento-pontine reticular nuclei. In HD, in the limbic system, the neuronal density in the granule cells of the CA1 area of the hippocampus is significantly reduced (Braak H and Braak E, 1982 ; Spargo E et al, 1993). The cellular expression of dopamine D1 and D2 receptor mRNAs was investigated in the post-mortem human caudate nucleus of control cases and pathologically confirmed cases of HD. For D2 receptor mRNA, the number of detectable D2-positive medium-sized cells decreased with increasing pathology. By contrast, for D1 receptor mRNA, despite a decrease in the number of D1 mRNA-positive cells detected, the average cellular expression of D1 mRNA was markedly reduced only in grade 1 HD and then increased with increasing pathology, presumably reflecting the relative survival of D1expressing striatal interneurons (Augood SJ et al, 1997). In the brain stem, in situ hybridation revealed extensive loss of tyrosine hydroxylase (TH) mRNA, the rate-limiting enzyme for dopamine biosynthesis, and decreased dopaminergic cell size in the substantia nigra. TH-immunoreactive protein was reduced in human grade 4 HHD substantia nigra by 32% compared to agematched controls (Yohrling GJ et al, 2003). In summary, in HD limbic system involvement and reduced striatal and nigral dopamine may play a role in insomnia.

4.1 The Structures Responsible for “Need for Sleep” There is a representation of motivational drives, especially for sleep and food intake, in mesial cortex, medial thalamus, hypothalamus and midbrain (Sewards RV and Sewards MA, 2003). Motivational drives could be impaired by numerous allostatic factors and by organic lesions. Actually we don‘t know why we need to sleep but there is an homeostatic system that fix sleep-wake cycles. The homeostatic facet of sleep-wake regulation correspond to regulation of ―sleep need‖ which increases during wakefulness and decreases during sleep. The neurochemical mechanisms underlying sleep homeostasis are poorly understood, but there is compelling and convergent evidence that adenosinergic neurotransmission plays a role in nonREM homeostasis in human (Landolt HP, 2008). Adenosine release in the brain may occur when energy-storing molecules containing adenosine triphosphate (ATP) are broken down to provide energy for cell activity. When brain cells burn ATP, adenosine builds up. During long sleep deprivation periods, the over regulation of A1 adenosine receptors takes place not only at the basal telencephalon level but also over the whole cortex (McCarley R, 2007). Some other regions react to sleep deprivation. These structures, the lesions of which causes insomnia in rats (Lu J et al, 2000), include ventrolateral preoptic area, as shown in rats and cats using the c-fos protein immunohistochemical method (Semba K et al, 2001). It has to be recalled that when a gene called c-fos, present in people and mice, is knocked out by genetic engineering, the mice act like human insomniacs, they have difficulty getting to sleep and staying asleep. Ventrolateral periacqueductal grey matter (Landis CA et al, 1993) and an

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area within anterior cingulated/medial prefrontal cortex are also activated after prolonged sleep deprivation (Cirelli C et al, 1995). In human, sleep deprivation causes the activation of a site within area 32 of medial prefrontal cortex (Clark CP et al, 2001). The thalamic representation of the need for sleep is probably located in the posterior part of the paraventricular thalamic nucleus, since neurons in this part of the nucleus are activated by sleep deprivation (Cirelli C et al, 1995; Semba K et al, 2001). In rats, this nucleus receives afferent projections from the suprachiasmatic nucleus, ventrolateral preoptic area, and ventrolateral periacqueductal grey matter (Krout KE et al, 2000). The regions responsible for need for sleep in human are not totally established. Some of them correspond to structures involved in sleep onset and maintenance, other to structures more related to waking state (limbic system and frontal cortex). They may thus give explanation for the occurrence of insomnia related to waking state related structures lesions. Some frontal tumors, maybe restless legs syndrome and basal ganglia disorders responsible for a reduction in adenosine could be cited as examples of insomnia related to loss of need for sleep. a) Rare cases of insomnia related to frontal tumors have been described. A 53-year-old man presented with insomnia for the previous 3 months. Psychological tests showed regression and schizophreniform and moderate organic deterioration signs. Neuropsychological testing revealed no deficit. MRI disclosed a presumed low-grade glioma or a dysgenetic tumor in the posterior part of the left gyrus rectus extending to the subcallosal area and the septal region, displacing the anterior cerebral artery. Polysomnography showed fragmented sleep with short deep slow wave sleep and no or little REM sleep. K-complexes and sleep spindles were present. Majority of sleep was unstable with high rate of cyclic alternating pattern (Szücs A et al, 2001). In another case, a right frontal lobe gliosarcoma induced sleep disturbance for 4 months and some headache and memory changes in a 79 year-old woman. The precise localisation of the tumor is unknown (Paueksakon P et al, 2003). In a case of nasalsubfrontal giant schwannoma, the patient presented with a year-long history of increasingly severe headache associated with insomnia. No neurological deficit was recorded except for anosmia (Bezircioglu H et al, 2008). b) Restless legs syndrome (RLS) is a sensorimotor disorder with a profound impact on sleep, inducing refractory insomnia, fatigue and sleepiness during the day. It affects both men and women, with a prevalence in the general population of 5% to10% (Berger K et al, 2004). RLS is characterized by an urge to move the legs or other parts of the body, accompanied by uncomfortable sensations. Symptoms occur during periods of rest and have a circadian peak of expression in the evening and at night. RLS is at times genetic autosomal dominant.The pathophysiology of RLS remains unclear, but there is evidence that impairment of brain iron availability and hypofunctioning of the brain dopaminergic system, play an important role. MRI metrics are suggestive of subnormal iron content in the substantia nigra (SN). T2 relaxation time values are higher in SNr than in SNc suggesting a higher iron content in SNc. The whole brain fMRI study evaluating patients with RLS during active


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dorsiflexion-plantar flexion of the foot show that only patients, and not controls, activate the thalamus, putamen, middle frontal gyrus and cingulated gyrus. Patients have higher activation of the dorso-lateral prefrontal cortex (Astrakas LG et al, 2008).TEMP and SPECT brain imagery did not show difference in presynaptic dopamine fixation in basal ganglions in RLS patients as compared to control group (Mrowkra M et al, 2005). TEP scan showed only slight reduction of presynaptic dopamine in the caudate nucleus and putamen (Ruottinen HM et al, 2000) or no difference at all (Trenkwalder C et al, 1999). The diencephalo-spinal dopaminergic pathway A11 is probably more important than the striatal dopamine in RLS physiology (Trenkwalder C et al, 2005).The genetic studies showed the association of several variants of the NOS1 (located at the level of the locus RLS1) with RLS. This result implicates that the system NO/arginine plays a role in RLS physiopathology. NOS1 gene is involved in the control of sleep-wake cycles and in the modulation of dopaminergic transmission (Winkelmann J et al, 2008).Autopsy studies in patients with early-onset RLS have demonstrated decreased H-ferritin and normal L-ferritin (usually stocked in oligodendrocytes) in the SN. Moreover transferrine fixation is increased in neuromelanine cells at the same times as transferrine receptors are reduces in theses cells, which suggests redistribution of iron toward cells that do not feed neurons (Connor JR and al, 2003). No autopsy in patients with late-onset RLS are available.In summary, insomnia occurring in RLS syndrome may be due to the activation of the dorso-lateral prefrontal cortex. It also could be related to an hypofunction of brain dopamine which is probably involved in sleep-wake cycles. c) A case of bilateral globus pallidus lesion due to hypoxia induced severe chronic insomnia. Acute mountain sickness occurs when someone move quickly to high altitude. Low oxygen partial pressure induces cerebral oedema responsible for loss of consciousness and coma. In one case, a 56-year-old female patient suffered severe chronic insomnia as the unique symptom following acute mountain sickness. MRI showed bilateral pallidus lesions (Shiota J et al, 1990). Globus pallidus is a part of the basal ganglia mainly involved in motor control, it is not traditionally associated with sleep organisation. Bilateral globus pallidus lesion usually change emotional and motivation but not sleep (Vijayaraghavan L et al, 2008). However, it may play a role in motor control of non-REM sleep through its connection with the frontocentral cortex during sleep (Salih F et al, 2009). The distribution of adenosine A2A, involved in sleep homeostasis is restricted in the basal ganglia (Kase H, 2001) so that a lesion to globus pallidus may theoretically reduce need for sleep.

5. General Influences (« Allostatic ») Various factors could overwhelm these regulatory systems. They include multiple stimuli, the best known being stress. Depression, systemic diseases and illness-related discomfort, drugs, alcohol, lack of light, are other very frequent factors inducing insomnia.

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Visceral sensory systems and autonomic regulatory neurons are clearly implicated, but a lot remains to be clarified in this field. Projections toward supra-chiasmatic nucleus, ventrolateral preoptic nucleus and orexin neurons of the cortical limbic system, for instance, have been advocated (Saper C et al, 2005). The role of the thalamic limbic system (anterior and dorso-medial areas), part of the ―central autonomic network‖ is also obvious. It is especially important in FFI (Provini F et al, 2005). Hormonal influences, the network of hypnogenic substances (VIP, somatostatine, CLIP or ACTH 18-39) and other molecules (prostaglandine D2, adenosine) (Huang Z et al, 2007; Bennaroch E, 2008) are implicated in these regulatory systems. These influences are not easy to illustrate but may play an important role in the occurrence of insomnia in normal persons and in those suffering from brain lesions, making clinicopathological correlations difficult.

Discussion and Conclusion Insomnia is theoretically induced by lesions of the structures implicated in sleep. However, structures involved in sleep and wake are so intimately interconnected that insomnia related to a brain lesion is rare and almost never an isolated symptom (Autret A et al, 2001). One methodological problem related to insomnia is the lack of sleep records. Sleep records are more often prescribed for hypersomnia or parasomnias than for insomnia. The symptom of insomnia is even not mentioned in many patients charts. Insomnia is considered as a ―soft sign‖, related to so many allostatic factors that its description doesn‘t bring much interest. At the opposite, hypersomnia, REM-sleep behaviour disorders, periodic limb movements are much more taken into consideration. Clinicopathological correlations are done according to the current knowledge about sleep and wake mechanisms. This knowledge is far from being accurate and is in constant evolution. For instance, the discovery of orexin/hypocretin system, few years ago, modified the known pathways of waking network and threw light on narcolepsy mechanisms. In the present paper, several levels or sleep organisation were considered in a classical hierachic manner : hypothalamus that sets schedule for sleep, thalamocortical bundles that set slow waves sleep, limbic system and frontal areas more involved in waking state and need for sleep, and brain stem nuclei responsible for REM-sleep organisation. With hypothalamic lesions, insomnia and delayed sleep syndrome occur when anterior hypothalamus is lesionned. Thalamo-cortical activity is modulated by limbic system and by several nuclei of the hypothalamus and brain stem, involved in sleep or in wakefulness. Thalamo-cortical activity is thus involved in alertness, waking state, slow sleep, and REM sleep, so that lesions involving thalamus, cortex, or thalamocortical bundles could induce altered states of consciousness, as well as insomnia and/or hypersomnia. Thalamic lesions, whether infectious, degenerative, ischemic, tumourous or others, never keep within the boundaries of selective thalamic nuclei, so that sleep related clinicopathological correlations are variable from patients to patients.


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The hypothesis of Lugaresi is that limbic cortex exerts an inhibitory control on the entire neuronal network regulating sleep and wakefulness (Lugaresi et al, 2004). According to the literature, the role of the limbic system is not so clear. It seems more involved in arousal and in phasic REM sleep than in sleep organisation. However fMRI shows significant BOLD signal changes in relation to slow wave sleep in specific brain areas including inferior and medial frontal gyrus, parahippocampal gyrus, precuneus, posterior cingulated cortex, pontomesencephalic tegmentum and cerebellum (Dang-Vu TT et al, 2008). Limbic system, inferior and medial frontal gyrus, and cerebellum may thus be implicated in sleep organisation, or at least, be strongly inhibited during slow wave sleep. Actually fMRI changes are dependant upon an hypermetabolism which could be inhibitory or excitatory in nature. The lesions of the limbic system could disorganise the sleep-wake circuit and induce insomnia (or hypersomnia). In the brain stem, the density of nuclei or tracts involved in sleeping or waking is so high that the risk that a lesion could impair only one group of nuclei is low. In Steele-Richardson‘s and Parkinson‘s diseases, insomnia is frequent but patients may also suffer from daytime hypersomnia and from several other sleep disorders. Strokes of the ventral pons and mesencephalon could lead to insomnia, probably by a dysfunction of the raphe nuclei (involved in arousal). With regard to traumatic lesion, clinicopathological correlations are poor for lesions are widespread and seldom localised. This schematic division is probably a caricature of genuine sleep organisation. A lot remains to discover. For instance, the role in sleep organisation of the striatum, and of several other structures, is still unknown.

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Chapter III

Non-Pharmacological Alternatives for the Treatment of Insomnia – Instrumental EEG Conditioning, a New Alternative?

1

Kerstin Hoedlmoser1, Thien Thanh Dang-Vu2,3,4, Martin Desseilles2,3,4 and Manuel Schabus1,2

University of Salzburg, Department of Psychology, Division of Physiological Psychology, Salzburg, Austria 2 Cyclotron Research Centre, University of Liège, Belgium 3 Psychiatry Department, Centre Hospitalier Universitaire (CHU), Liège, Belgium 4 Neurology Department, Centre Hospitalier Universitaire (CHU), Liège

1. Abstract There is already profound knowledge about the evidence that cognitive behavioral therapy (CBT) is effective for the treatment of insomnia (Benca, 2005; Morin et al., 1999; Morin, 2004; Morin et al., 2006). However, the characterization of nonpharmacological treatment effects like CBT on specific sleep parameters (e.g., sleep spindles, sleep architecture, electroencephalographic (EEG) power densities during sleep after CBT) are scarce (Cervena et al., 2004). In our approach we investigated if instrumental conditioning of 12-15Hz EEG oscillations would enhance sleep quality as well as declarative memory performance in healthy subjects. Additionally preliminary data indicating instrumental conditioning of 12-15Hz EEG oscillations as a promising treatment of insomnia will be presented. EEG recordings over the sensorimotor cortex show a very distinctive oscillatory pattern in a frequency range between 12-15Hz termed sensorimotor rhythm (SMR). SMR appears to be dominant during quiet but alert wakefulness, desynchronizes by the execution of movements and synchronizes by the inhibition of motor behavior. This frequency range is also known to be high during light

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K. Hoedlmoser, T. T. Dang-Vu, M. Desseilles et al. non-rapid eye movement (NREM) sleep, and represents the sleep spindle peak frequency. In the early 70ies Sterman, Howe, and MacDonald (1970) could demonstrate in cats that instrumental conditioning of SMR during wakefulness can influence subsequent sleep. Hauri (1981) was then the first to apply effectively a combination of biofeedback and neurofeedback to humans suffering from psychophysiologic insomnia. Results revealed that the patients benefited from the instrumental conditioning protocols. As research surprisingly stopped at that point, we intended to clarify the effects of instrumental SMR conditioning (ISC) on sleep quality as well as on declarative memory performance with today‘s technologies and by using a well controlled design which included a control group receiving the same amount of attention and training. Our results confirmed that within 10 sessions of ISC it is possible to increase 12-15Hz activity significantly. Interestingly, the increased SMR activity (i) was also expressed during subsequent sleep by eliciting positive changes in various sleep parameters like sleep spindle number or sleep onset latency and (ii) was associated with the enhancement of declarative learning. In addition to these fascinating results, preliminary data from our laboratory point to the possibility that people suffering from primary insomnia could likewise benefit from this conditioning protocol as indicated by improved measures of subjective and objective sleep quality.

2. Introduction Insomnia is characterized by difficulty in initiating sleep, maintaining sleep, and/or nonrestorative sleep that causes clinically significant distress or impairment in social, occupational or other important areas of functioning (Littner et al., 2003). From a psychological perspective insomnia patients typically complain of being unable to stop their reverberating thoughts and ―rest their mind‖ which prevents them from sleeping. Insomnia is associated with decreased quality of life, absenteeism, increased work and car accidents, as well as increased general health care utilization. Insomnia may arise directly from sleep/wake regulatory dysfunction or indirectly from comorbid behavioral, psychiatric, neurological or medical conditions. Finding the underlying cause of insomnia is crucial for curing an individual‘s symptom. In summary, insomnia is a prevalent and clinically important problem. In fact it is the most commonly reported sleep problem in industrialized nations worldwide (Sateia, Doghramji, Hauri, & Morin, 2000). Epidemiological research shows that the prevalence of insomnia lies somewhere between 10 and 35% in the general adult population (Angst, Vollrath, Koch, & Doblermikola, 1989; Benca, 2005; Gallup-Organization, 1995; Johnson, Roth, Schultz, & Breslau, 2006; Morin, LeBlanc, Daley, Gregoire, & Merette, 2006; Ohayon, 2002). Unfortunately, the recognition of the problem of insomnia is widely underestimated and often remains unrecognized and untreated. According to a 1995 survey (Gallup-Organization, 1995) almost 70% of patients with chronic insomnia never discussed their sleep problem with their physicians. Psychiatric conditions (above all anxiety and depressive disorders) are highly prevalent among insomnia sufferers suggesting that such conditions may play an important role in the etiology and perpetuation of insomnia symptoms. In addition to the high rates of past or present psychopathology insomnia patients also have an increased risk of the development of further psychiatric illnesses (Weissman, Greenwald, Nino-Murcia, & Dement, 1997). However, it is still discussed whether insomnia

Non-Pharmacological Alternatives for the Treatment of Insomnia

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is rather an early symptom than a cause of psychiatric conditions like depression or anxiety disorders (Buysse, 2004; Holbrook, Crowther, Lotter, Cheng, & King, 2000; Morawetz, 2003). Yet, it is well documented that insomnia gives rise to emotional distress and thus might itself be involved in the preservation, recurrence or even development of depression and anxiety disorders (Buysse, 2004; Morawetz, 2003). Empirical data demonstrates that insomnia is most often a chronic condition (defined as an inability to consistently sleep well for a period of at least one month). Retrospective studies of severely afflicted insomnia patients revealed that about 80% of the individuals had the problem for more than one year, with about 40% even reporting more than five years duration (Gallup-Organization, 1995). The consequences of chronic insomnia are severe. The most common adverse effects of sleep disturbances include fatigue/lethargy, mood disturbances, cognitive and motor impairments, social discomfort and non-specific physical complaints which often lead to seriously decreased quality of life, psychosocial discomfort, and economic repercussions including decreased work productivity (Gallup-Organization, 1995; Morin, 1993; Stepanski et al., 1989). Research indicates that already moderate levels of fatigue produce performance equivalents often greater than those observed at levels of alcohol intoxication deemed unacceptable when driving, working and/or operating dangerous equipment (Lamond & Dawson, 1999). It is thus not surprising that occupational and vehicular accidents secondary to poor sleep quality are consistently reported. Even more daunting is data suggesting that decreased sleep time (Kripke et al., 2002) and use of sleeping pills are associated with increased mortality (Kripke et al., 1998). According to a recent report by Kripke (2008) new hypnotics may increase cancer risk - especially the risk of skin cancer.

3. Diagnosis and Classification of Insomnia Depending on the chosen classification system insomnia patients are categorized somewhat differently. The ―International classification of sleep disorders‖ (ICSD-2; American Academy of Sleep Medicine, 2005) differentiates several subtypes of primary insomnia (e.g., psychophysiological, idiopathic, paradoxical, sleep state misperception). The more general classification systems ―International classification of diseases-10th revision‖ (ICD-10; World Health Organization, 2005) and ―Diagnostic and statistical manual of mental disorders-text revision, 4th edition‖ (DSM-IV-TR; American Psychiatric Association, 2000) classify ―nonorganic insomnia‖ (F51.0) and ―primary insomnia‖ (307.42), respectively. Since 2005 there are refined research diagnostic criteria for insomnia available which were developed by an American Academy of Sleep Medicine Work Group (Edinger et al., 2004) regarded as a starting point for improving insomnia research. As they provide the most homogeneous patient population, and satisfy traditional and cultural variations for the concept of a ―primary insomnia‖ it is recommended to identify study participants (as well as normal sleepers) by those criteria. Table 1 exemplarily lists research diagnostic criteria for insomnia disorder and primary insomnia, respectively. Additionally Edinger et al. (2004) provide research diagnostic criteria for the following Insomnia subtypes: insomnia due to a mental

K. Hoedlmoser, T. T. Dang-Vu, M. Desseilles et al.

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disorder, psychophysiological insomnia, paradoxical insomnia, idiopathic insomnia, insomnia related to periodic limb movement disorder, insomnia related to sleep apnea, insomnia due to medical condition, insomnia due to drug or substance. Furthermore, they offer universal criteria to identify normal sleepers for insomnia research. Table 1. Research Diagnostic Criteria (modified from Edinger et al., 2004).

Research Diagnostic Criteria for Insomnia Disorder

A.

The individual reports one or more of the following sleep related complaints: 1. difficulty initiating sleep, 2. difficulty maintaining sleep, 3. waking up too early, or 4. sleep that is chronically nonrestorative or

Research Diagnostic Criteria for Primary Insomnia

A.

disorder. B.

psychiatric disorder.

The above sleep difficulty occurs despite adequate

2. There is a current or past mental or psychiatric disorder, but the temporal course

At least one of the following forms of daytime

of the insomnia shows some independence

impairment related to the nighttime sleep difficulty is

from the temporal course of the mental or

reported by the individual: 1. fatigue/malaise; 2. attention, concentration, or memory impairment;

psychiatric condition. D.

medical condition.

performance;

2. There is a current or past sleep-disruptive

4. mood disturbance/irritability;

medical condition, but the temporal course of

5. daytime sleepiness;

the insomnia shows some independence from

6. motivation/energy/initiative reduction; driving;

the temporal course of the medical condition. E.

The insomnia cannot be attributed exclusively to another primary sleep disorder (e.g., sleep apnoea,

8. tension headaches, and/or Gastrointestinal

narcolepsy, or parasomnia) or to an unusual

symptoms in response to sleep loss; and 9. concerns or worries about sleep.

One of the following two conditions applies: 1. There is no current or past sleep-disruptive

3. social/vocational dysfunction or poor school

7. proneness for errors/accidents at work or while

One of the following two conditions applies: 1. There is no current or past mental or

opportunity and circumstances for sleep. C.

The insomnia noted in A has been present for at least one month.

C.

poor in quality. B.

The individual meets the criteria for insomnia

sleep/wake schedule or circadian rhythm disorder. F.

The insomnia cannot be attributed to a pattern of substance abuse or to use or withdrawal of psychoactive medications.


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4. Pathophysiology of Primary Insomnia Polysomnographic (PSG) sleep recordings of patients with insomnia show abnormalities such as prolonged sleep latency or frequent awakenings, more stage 1 and less slow wave sleep (e.g., Merica, Blois, & Gaillard, 1998; Reite, Buysse, Reynolds, & Mendelson, 1995). Krystal et al. (2001) found diminished delta and greater alpha, sigma, and beta EEG spectral power in NREM sleep, which may be an objective physiologic correlate of subjective sleep complaints. Furthermore, Parrino et al. (2004) investigated the role of sleep microstructures for insomnia and reported a more unstable sleep represented by a higher rate of cyclic alternating patterns (CAP). These activation patterns appear in NREM sleep and tend to recur in repetitive clusters with a periodicity of 20–40 s. CAPs are markers of arousal instability, composed of a phase A (activation pattern) and a phase B (interval between two consecutive A phases). CAP is the EEG translation of unstable sleep and accompanies the dynamic events of the sleep process (e.g., falling asleep, stage shifts, intrasleep awakenings). Based on rich experimental evidence from Perlis and colleagues (Perlis, Giles, Mendelson, Bootzin, & Wyatt, 1997; Perlis, Mercia, Smith, & Giles, 2001; Perlis, Kehr, Smith, Andrews, Orff, & Giles, 2001; Perlis, Smith, Andrews, Orff, & Giles, 2001) fast brain oscillations including beta and gamma activity are elevated at sleep onset and during shallow NREM sleep stages in insomnia patients. The authors interpreted these results in terms of increased cognitive arousal at sleep onset and relate the uncommon high frequency activity to the common misperception of insomnia patients of not being subjectively asleep while objective EEG parameters indicate otherwise. The ―Neurocognitive Model of Insomnia‖ (Perlis et al., 1997) proposes that the increase in central nervous system (CNS) tone results in increased and persistent sensory and cognitive processing where under normal circumstances (like sleep) such processes would be vastly attenuated or inhibited. According to the model the increased sensory processing and perception thus accounts for difficulties in sleep initiation and sleep maintenance. Our proposed ISC intervention builds upon these findings. Specifically, we assume that high frequency beta and gamma activity – usually elevated in insomnia patients – will be strongly diminished at sleep onset and during (early) NREM sleep after successful ISC (Hoedlmoser et al., 2008). The introduction of the neurocognitive model with its focus on cortical or CNS arousal, has renewed the interest in the neurophysiological characteristics of insomnia and as such, the use of a method like ISC directly targeting the altered brain activity has also been put forward by others (cf. Cortoos, Verstraeten, & Cluydts, 2006 for a current review) as a promising treatment modality deserving attention.

5. Treatment According to the National Institutes of Health (NIH) ―state-of-the science statement on chronic insomnia in adults‖ (2005) there is still a paucity of large randomized trials for any of the widely used insomnia treatments that include pharmacotherapy, CBT, over the counter products (OTCs), and herbal remedies. The NIH states that the most common treatments for chronic insomnia are OTCs, alcohol, and prescription of medications although CBT has been proven to be as effective as sedative-hypnotic pharmacotherapy. Furthermore, there is no

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evidence that OTCs, melatonin, or herbal remedies are more effective than a placebo. According to the NIH there is convincing evidence that the beneficial effects of CBT, in contrast to many of those produced by medications, last well beyond the termination of treatment. However, because few health professionals are experts in the use of psychotherapeutic interventions like CBT, it is still not a very widespread treatment. This is even more true for ISC which is methodologically complex and which has not been rigorously tested for efficacy in insomnia disorders.

5.1 Pharmacological Treatment A variety of drugs are available to treat insomnia. The following classes of drugs and individual agents are most commonly used: benzodiazepines and nonbenzodiazepines acting at benzodiazepine receptors, sedating antidepressants, antihistamines and antipsychotics (Walsh, Roehrs, & Roth, 2005). There are two pharmacological classes of hypnotics being approved by the United States Food and Drug Administration (FDA): benzodiazepinereceptor agonists (BRA; including the traditional benzodiazepines like flurazepam, temazepam as well as the non-benzodiazepine receptor agonists like zolpidem, eszopiclone, zaleplon) and melatonin-receptor agonists (e.g., ramelteon). BRA are occupying benzodiazepine receptors on the gamma-aminobutyric acid (GABA), type A, receptor complex, resulting in the opening of chloride ion channels and facilitation of GABA inhibition. All BRA hypnotics reduce sleep latency, most of them increase total sleep time, although decreasing the duration of SWS (Walsh, Roehrs, & Roth, 2005). However, even highly effective at reducing sleep latency, BRA are associated with varying degrees of residual daytime sedation, abuse liability, and toxicity (Griffiths & Johnson, 2005). Ramelteon is the first FDA-approved melatonin receptor (MT1, MT2) agonist. In patients with chronic insomnia, ramelteon reduces latency to persistent sleep and increases total sleep time. Although prescription of hypnotics is still the most widely used treatment for insomnia, it is sometimes inadvisable or contradicted. Some patients for example simply do not want to use hypnotics for various reasons (Morin, Gaulier, Barry, & Kowatch, 1992). For others hypnotic drugs do not alleviate their insomnia at all or gradually lose their efficacy after some initial relief. Furthermore, hypnotic medication may be contraindicated by the use of other medications, existing medical conditions, a patient‘s high risk to substance abuse or addiction and age (above all pediatric or geriatric patients). Adverse events that are associated with sedative use, such as ataxia, falls, or memory impairment are known to be particularly problematic for older people. However, there are additional variables (e.g., gender) that have to be considered when prescribing hypnotics (Toner et al., 1999). According to the NIH sedative-hypnotics have only been proven to be effective in the short-term management of insomnia (studies usually averaging 7 days) with adverse effects of these medications including daytime sleepiness, dizziness, cognitive impairment, motor incoordination, dependence, and rebound insomnia. However, it has to be mentioned that there are now three hypnotics approved by the FDA for indefinite use (eszopiclone, ramelteon, and zolpidem CR). Yet, empirical evidence suggests that daytime functioning of


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the suffering patients is often unchanged. That is, medication might sometimes only alter the perception of sleep (Perlis et al., 1997) but does not normalize sleep architecture. Therefore we believe that it is highly needed to assess new non-pharmacological alternatives directly aiming to produce more ―sleep-like‖ EEG patterns (e.g., by ISC treatment) and evaluate their effects on daytime variables such as subjective quality of life, attention and memory performance. For review and further discussion on the topic please refer to Perlis and colleagues (2003).

5.2 Non-Pharmacological Treatment of Insomnia Reports from patients with insomnia suggest that the disorder often starts as a stressrelated phenomenon (Hauri & Fisher, 1986) with the individual emotional and behavioral response to the condition playing an important role in the final outcome of the situation. We believe that these maladaptive cognitive, behavioral and emotional responses - precipitating and perpetuating insomnia - may be well dealt with non-pharmacological treatments (i.e., CBT and ISC). Indeed, there is already promising evidence that non-pharmacological methods besides hypnotics can be (i) efficient in treating insomnia symptoms (Morin et al., 2006; Morin, Colecchi, Stone, Sood, & Brink, 1999; Perlis et al., 2003) i.e., improving objective sleep measures such as sleep onset latency, wake after sleep onset, or total sleep time and can also (ii) lead to subjective improvement of patient complaints, with higher measurable quality of life after treatment.

5.3 Cognitive Behavioral Therapy (CBT) There is growing evidence that Cognitive Behavioral Therapy for Insomnia (CBT-I) is as effective as sedative hypnotics during acute treatment (4-8 weeks) and more effective even considering the long term efficacy. According to Morin (1999) between 70-80% of insomnia patients benefit from treatment, 50% achieve clinically meaningful outcomes and about one third become good sleepers. Until now there is little knowledge about effects of CBT-I on objective data like sleep architecture and sleep EEG power densities. Cervena et al. (2004) could show that after 8-weeks of CBT-I both subjective and objective sleep quality was improved: stages 2, REM sleep and SWS durations were significantly increased; slow wave activity (SWA) was increased and SWA decay shortened, beta and sigma activity during NREM sleep were reduced. Thereby they provided the first evidence that CBT-I may have a positive effect on CNS hyperarousal by decreasing high EEG frequencies and enhance sleep pressure and improve homeostatic sleep regulation by increasing SWA during NREM sleep. There are 3 main components of cognitive-behavioral management for insomnia complaints: behavioral, cognitive and educational modules (Morin, 2004). Interventions like ―Sleep Hygiene Education‖, ―Relaxation Training‖, ―Stimulus Control‖, ―Sleep Restriction‖ and ―Cognitive Therapy‖ can be administered effectively in a group or individual therapy setting. When applied correctly CBT-I has the potential to alleviate insomnia and to help


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patients understanding and eliminating probable causes for their condition. Table 2 gives an overview about current cognitive-behavioral treatment practices for primary insomnia. Table 2. Cognitive-Behavioral Interventions for Insomnia (CBT-I). CBT-I INTERVENTION Sleep Hygiene Education Relaxation Training Stimulus Control Sleep Restriction Cognitive Therapy

DESCRIPTION Education about sleep practices, habits and environmental factors that may affect sleep Inhibition of autonomic activity and physiological arousal; facilitation of mental de-arousal Sleep stimuli (e.g., bedroom, bed) have to become reassociated with sleep; temporal adjustment to a consistent sleep pattern Reduction of time in bed to approximate time spent in bed to the length of actual sleep time A psychotherapeutic method to identify and change dysfunctional cognitions about sleep and insomnia

Sleep hygiene education and relaxation training are often used as starting point in CBT-I. Sleep hygiene education refers to general guidelines about health practices and environmental factors that may affect sleep. The main external factors known to have an effect on sleep are: caffeine (―Avoid caffeine and all stimulants after dinner‖), nicotine (―Avoid smoking near bedtime and upon night wakings‖), alcohol (―Do not drink alcohol in the late evening‖), exercise (―Do not exercise too close to bedtime; regular exercise in the late afternoon or early evening may deepen sleep‖) as well as noise, light and room temperature (―Minimize noise light, and excessive temperatures‖). Relaxation training is the most commonly used non-pharmacological therapy for insomnia. Thereby ―standard progressive muscle relaxation‖ has been the most widely investigated relaxation technique for insomnia. Relaxation techniques require disciplined, daily training and practice. Relaxation-based treatments may inhibit two types of arousal that interfere with sleep: autonomic and cognitive. According to Morin et al. (1999, 2006) progressive muscle relaxation meets the American Psychological Association (APA) criteria for empiricallysupported psychological treatments for insomnia, whereas there is no evidence that sleep hygiene education has a detrimental effect on outcome. However, sleep hygiene education is a necessary treatment component and should be incorporated into the overall intervention. Another step within CBT-I is ―Sleep Scheduling‖ which comprises the interventions stimulus control and sleep restriction. According to Bootzin (1991) insomnia is the product of maladaptive sleep habits. Typical sleep stimuli do not cause drowsiness and sleep, but instead are associated with wakefulness. Morin (2004) recommends 5 simple instructions that can help patients to re-associate sleep stimuli with the proper behavior: i) Go to bed only when sleepy, ii) Use the bed or bedroom only for sleeping (sexual activity is the only exception to this rule), iii) Get out of bed when unable to sleep after 15 minutes spent in bed, iv) Arise at the same time every morning, and v) avoid daytime naps. On the other hand sleep restriction can be used parallel, to compress sleep toward greater continuity, reduced wakefulness in bed


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and increased sleep efficiency. This intervention was induced by Spielmann (1987) who encouraged his patients to limit the amount of time spent in bed to the amount of time spent sleeping. Thereby a mild state of sleep deprivation is induced and leads to a faster sleep onset as well as greater sleep continuity and quality. Both treatments stimulus control and sleep restriction meet the APA criteria for empirically-supported psychological treatments for insomnia (Morin et al., 2006). Finally CBT-I seeks to identify and to change dysfunctional cognitions (faulty or distorted beliefs, expectations, appraisals or attributions) in insomnia. Cognitive therapy targets these cognitions and attempts to alter them. According to Morin (2004) these cognitions are the dangerous insomnia-bolstering concomitant of the maladaptive behaviors that perpetuate insomnia. Patients have to learn to re-evaluate the accuracy of their thinking and to re-interpret events and situations they experience in a more realistic and rational way (Morin & Espie, 2003). The main targets of cognitive therapy are: i) unrealistic expectations about sleep needs and daytime functioning, ii) misconceptions and false attributions about the causes of insomnia, iii) distorted perceptions of its consequences and iv) faulty beliefs about sleep-promoting practices. In general cognitive therapy should guide patients to view insomnia and its consequences from a more realistic and rational perspective. Corresponding to APA criteria (Morin et al., 2006) cognitive therapy meets criteria for empirically-supported psychological treatments. Additionally there is evidence that paradoxical intention – an individual cognitive restructuring technique to alleviate performance anxiety – meets the APA criteria for empirically-supported psychological treatments for insomnia (Morin et al., 1999; 2006).

5.4 Biofeedback Biofeedback is a technique in which people learn how to self-control certain internal bodily processes that normally occur involuntarily, such as heart rate, blood pressure, muscle tension, skin temperature and brain activity. To provide biofeedback special computer hardware is required. Biofeedback instruments are supposed to i) monitor a physiological process of interest, ii) measure what is monitored and finally iii) present what is measured as meaningful information by translating the raw signal e.g., into a tone that varies in pitch, a visual meter that varies in brightness, or a computer screen that varies the lines moving across a grid. The patients have to find mental strategies to self-control the parameter of interest. Through trial and error participants learn to identify and control their mental activities that will bring about the desired physical changes. The three most commonly used forms of biofeedback are i) electromyography (EMG; muscle tension) biofeedback, ii) thermal biofeedback (skin temperature) and iii) EEG biofeedback (neurofeedback; brain activity). Concerning biofeedback as treatment for sleep disorders there are two types of biofeedback that have been effectively used: EMG and EEG biofeedback. According to the ―Practice Parameters for the Psychological and Behavioral Treatment of Insomnia‖ by Chesson et al. (1999) and Morgenthaler et al. (2006) biofeedback is an effective and recommended therapy in the treatment of chronic insomnia. It has been rated as probably efficacious indicating that multiple observational studies, clinical studies, wait list controlled studies, and within subject


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and intrasubject replication studies demonstrated efficacy. However, after receiving considerable attention in the 1970s and 1980s (cf. Table 3) there has been a big gap until today – only one study of biofeedback treatment for insomnia has been published in the last 20 years (Sanavio et al., 1990). This lack of research interest may be related to the fact that biofeedback requires more time than comparable forms of relaxations therapies with only little appreciable advantage. Additionally commercial hardware for detecting and managing psychophysiological parameters are needed and the biofeedback operator should understand the fundamental principles and methods for detecting and measuring physiological processes in depth. Despite this lack of research, biofeedback seems to be an efficacious treatment for insomnia. It is also to note that after the intense and promising research in the 1970s many people in the field applied the method rapidly to a variety of clinical disorders (e.g., migraine headache, anxiety disorders, epilepsy, tinnitus, attention deficit (hyperactivity) disorder, chronic pain) thereby skipping the much needed basic research documenting biofeedback efficacy convincingly. Therefore our starting point was to vigorously and objectively test the EEG biofeedback (or neurofeedback) methodology by conducting a highly controlled study using sensorimotor (12-15Hz, SMR) "instrumental conditioning" with the aim to influence brain patterns during waking as well as sleep (cf. chapter 5.5.1). Table 3. Overview of literature concerning Biofeedback and Insomnia. Reference

Subjects

Feedback protocol

Coursey et al. (1980)

22 subjects suffering sleep onset insomnia

EngelSittenfeld et al. (1980)

35 subjects suffering chronic insomnia

Freedman & Papsdorf (1976)


Hauri (1981)

48 subjects suffering primary Insomnia

EMG frontalis biofeedback; relaxation therapy (autogenic training); “Electrosleep Therapy”; PSG EMG frontalis biofeedback and EEG theta NFT; relaxation therapy (autogenic training); client-centred psychotherapy EMG frontalis biofeedback; relaxation therapy (progressive relaxation); control group: placebo (“relaxation” exercises); PSG 4 modalities: (i) EMG frontalis, (ii) EMGtheta, (iii) SMR (1214Hz) and (iv) no treatment; sleep logs, sleep recordings; PSG

Number and duration of sessions 12 (2 a week); 35-45min 1 month follow up 19 (2 a week); 1,5 hours 6 months follow up

Results

EMG biofeedback and relaxation therapy compared to “Electrosleep Therapy”: ↓ sleep onset latency; ↑ sleep efficiency ↓ hypnotic medication

6 (3 a week); 30 min 2 months follow up

EMG biofeedback and relaxation therapy: ↓ sleep onset latency

15 - 62 (2-4 a week); 1 hour 9 months follow up

amount of SMR-feedback-learning correlated significantly with sleep improvement

Non-Pharmacological Alternatives for the Treatment of Insomnia Hauri et al. (1982)

16 subjects suffering primary Insomnia

2 groups: (i) frontalis EMG and theta, (ii) frontalis EMG and SMR (12-14Hz); T7/T8, C3/C4; visual NFT; sleep logs, sleep recordings; PSG

32 (2-3 a week); 1 hour 6 x EMG 26 x theta/SMR 9 months follow up

Hughes & Hughes (1978)

36 subjects suffering chronic insomnia

1-5 1 hour 6 months follow up

Nicassio et al. (1982)


Sanavio (1988)

24 subjects suffering psychophysiological insomnia

EMG biofeedback; relaxation therapy; stimulus control; control group: pseudobiofeedback EMG frontalis biofeedback; relaxation therapy (progressive relaxation); control group: pseudobiofeedback; no treatment EMG frontalis biofeedback; cognitive behavioral therapy (CBT)

Sanavio et al. (1990)


VanderPlate & Eno (1983)


EMG biofeedback; CBT; stimulus control + relaxation therapy (progressive relaxation); control group: waitlist EMG biofeedback; pseudo-biofeedback; self-monitoring; control group: waitlist

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objective sleep recordings revealed that tense and anxious insomniacs benefited only from thetaNFT, while those who were relaxed only benefited from SMR-NFT; according to sleep logs both NFT groups seems to be effective ↓ sleep onset latency for patients of all four groups (no sign. group differences)

5 1 hour; 6 months follow up

relaxation therapy and EMG biofeedback: ↓ sleep onset latency

6 (3 a week); 1 hour 3 and 12 months follow up

EMG biofeedback and CBT: ↓ sleep onset latency; CBT: ↓ reverberating thoughts; EMG-biofeedback: ↑ relaxation before falling asleep EMG biofeedback; CBT; stimulus control + relaxation therapy: ↓ sleep onset latency, ↓ WASO; effects remain stable after 1 and 3 years follow up EMG biofeedback and pseudo-biofeedback: ↓ sleep onset latency

6 (3 a week); 1 hour 36 months follow up 3 1 hour 2 months follow up

Abbreviations: ↑ = increase; ↓ = decrease; WASO = wake after sleep onset; CBT = cognitive behavioral therapy; PSG = polysomnography; EMG = electromyography; NFT = neurofeedback-training; SMR = sensorimotor rhythm; EEG = electroencephalography

5.5 Instrumental EEG Conditioning (IEC) Instrumental conditioning of EEG parameters – often called neurofeedback or EEG biofeedback - is a very sophisticated type of biofeedback and refers to an operant conditioning paradigm (for review see Budzynski, Budzynski, Evans, & Abarbanel, 2009; Sterman, 1996). Participants are instructed to learn to self regulate distinct parameters of their cortical activity (e.g., amplitude, frequency or coherence) as assessed by the means of EEG. The aim of IEC is to teach individuals what specific states of cortical arousal feel like and

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how to activate such states voluntarily. During IEC - as depicted in Figure 1 - EEG is recorded and the relevant components are extracted and ―fed back‖ to the individual using an online feedback loop (audio, visual or combined audio-visual). The individual‘s task may then be to increase/decrease the respective cortical parameter. When the correct EEG-pattern is produced, the subject receives a positive response or reward by the computer.

Figure 1. Equipment requested for IEC. Scalp electrodes capture brain oscillations and transmit them to the amplifier. After amplification signals are transmitted to the computer where online calculations (e.g., Fast Fourier Transformation) are performed. Pre-processed data are presented to the subjects either visually (e.g., compass-needle) and/or acoustically (e.g., varying tone pitches). During IEC subjects permanently get realtime feedback of the parameters (e.g., SMR band power) intended to be changed (e.g., by relaxing). Additionally the researcher can supervise the session by a separate monitor.

It is proposed that IEC is not successful below 10 training sessions (Egner & Gruzelier, 2003) and there is a very high variability (from 1 up to 50) in the number of sessions used for training throughout literature (cf. Table 4). After an initially enormous research interest in the 60ies and 70ies and a dramatic decrease thereafter a kind of ―Neurofeedback Renaissance‖ seems to take place. Today IEC is mainly used as a therapeutic tool to treat different types of disorders like epilepsy (Lantz & Sterman, 1988; Kotchoubey, Strehl, Holzapfel, Blankenhorn, Fröscher, & Birbaumer, 1999; Sterman & Lantz, 2001; Strehl et al., 2006; for review see Sterman & Egner, 2006; Tan et al., 2009) or attention-deficit hyperactivity disorder (ADHD; Beauregard & Lévesque, 2006; Fuchs, Birbaumer, Lutzenberger, Gruzelier, & Kaiser, 2003; Gevensleben et al., 2009; Kaiser & Othmer, 2000; Leins et al., 2007; Lubar, Swartwood, Swartwood, & O‘Donnell, 1995; Lubar, Swartwood, Swartwood, & Timmermann, 1995; Strehl, Leins, Goth, Klinger, Hinterberger, & Birbaumer, 2006; for review see Arns, de Ridder, Strehl, Breteler, & Coenen, 2009; Heinrich et al., 2007;


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Monastra, 2005). Within the treatment of other clinical disorders such as depression (Rosenfeld, Baehr, Baehr, Gotlib, & Ranganath, 1996; for review see Hammond, 2005), tinnitus (Gosepath, Nafe, Ziegler, & Mann, 2001; for review see Dohrmann et al., 2007), anxiety (Hardt & Kamiya, 1977) and substance abuse (Moore, Trudeau, Thuras, Rubin, Stockley, & Dimond, 2000; for review see Peniston & Kulkosky, 1999; Sokhadze et al., 2008) IEC has also been reported to be a useful instrument. Furthermore, the exciting progress since the pioneering work of Nicolelis (for review see Nicolelis, 2003) in the field of brain-computer or brain-machine interface enabling ―locked-in‖ and partly paralysed patients to communicate or to produce movements, respectively, by voluntarily controlling neuronal activity (Birbaumer et al., 1999; Hinterberger et al., 2004; Pfurtscheller, Müller, Pfurtscheller, Gerner, & Rupp, 2003; for review see Birbaumer & Cohen, 2007; Birbaumer, Ramos Murguialday, Weber, & Montoya, 2009) benefits from this specific method. Of high interest for our approach are the early findings by Sterman et al. (1970) who could show that facilitation of sensorimotor rhythm (SMR) by IEC during wakefulness in cats (i) selectively enhances spindle activity during sleep and (ii) produces longer epochs of undisturbed sleep. EEG recordings over the sensorimotor cortex show a very distinctive oscillatory pattern in a frequency range between 12-15Hz termed SMR (Sterman & Wyrwicka, 1967; Chase & Harper, 1971; Howe & Sterman, 1972). These brain activities are also known as ―rolandic mu rhythms‖ or ―wicket rhythms‖ (Gastaut, 1952; Niedermeyer, 2005). SMR appears to be dominant during quiet but alert wakefulness (Roth, Sterman, & Clemente, 1967) and desynchronizes during planning, execution and also imagination of hand, finger, foot and tongue movements (Neuper, Wörtz, & Pfurtscheller, 2006; Pfurtscheller, Brunner, & Schlögl, 2006). Active inhibition of motor behavior on the other hand results in SMR synchronization (Howe & Sterman, 1972). Furthermore this frequency range is known to be abundant during light NREM sleep, and is representing the classical sleep spindle band. First spindles emerge at sleep onset, have a waxing-and-waning appearance and are known to be generated in thalamocortical circuits (Steriade, 1999). Sterman and colleagues postulated that instrumental SMR conditioning can transfer into sleep, inducing a facilitation of spindle burst sleep and decreased sleep fragmentation (i.e., reduced waking and movements during NREM sleep) in normal adult cats. By instrumental conditioning the occurrence of SMR and the related suppression of movement could be induced in cats (Wyrwicka & Sterman, 1968). EEG was recorded from lateral pericruciate cortex (on both sides) and posterior cortical sites in eight cats. The animals were placed in a recording chamber equipped with an automatic feeding device. After adaptation to this chamber, three independent recordings of sleep were obtained as baseline. At least two sleep cycles (quiet sleep being interrupted eventually by periods of active sleep or spontaneous shifts back to the waking or hypnagogic state). Subsequently the eight cats were split in two groups of four each and both groups were trained to produce specific patterns of EEG activity recorded over sensorimotor cortex (either SMR or low voltage [<20µV], fast [18-30Hz] activity [LVF]) during daily sessions to receive food. One training session consisted of 60 reinforcements by food for producing the desired activity. In the SMR-condition a signal containing at least 0.5sec 12-14Hz activity at a voltage 100% above background level produced a reward. Most animals received maximum performance after 2-4 weeks of daily training. In a first test session cats were allowed to obtain unlimited reinforcement and

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remained in the chamber until several complete sleep cycles were recorded. In a second run training (SMR, LVF) was reversed for the two groups. A final sleep recording 1 month after the end of the second training block served as a follow-up. Results show that instrumental conditioning of SMR activity in the waking cat produce significant changes in spindle-burst activity (number and duration of spindle bursts) and sleep duration. An increase in spindleburst activity during sleep following SMR was observed in both groups whereas spindleburst activity in the follow-up 1 month later was enhanced only in the group receiving SMRtraining in the second run, but was not sustained in the second group where intervening LVF conditioning was given. Additionally the mean duration of quiet-sleep epochs was significantly increased immediately after SMR conditioning, but not in the follow-up, supporting the findings by Roth et al. (1967) that phasic motor behavior suppression is related to SMR activity. Moreover at those early times, 12-14Hz IEC has already been effectively used in treating patients suffering from psychophysiologic insomnia (Hauri, 1981; Hauri, Percy, Hellekson, Hartmann, & Russ, 1982). In Hauri et al. (1982) sixteen subjects suffering from psychophysiologic insomnia were randomly assigned to either an EMG / theta-feedback or EMG/SMR-feedback treatment group. At first subjects were evaluated for 3 nights in a sleep laboratory, including different psychological questionnaires, sleep logs and a psychiatric interview. Patients who satisfied criteria for psychophysiological insomnia defined by chronic, serious and relentless sleeping problems for at least 2 years; insomnia has been shown for at least 8 of the 14 nights reported by home sleep logs; >30min sleep latency or <85% sleep efficiency during the second and third laboratory night; no medical insomnia or serious psychiatric disorders) first received 6 frontalis EMG sessions to learn how to sit comfortably in an easy chair for at least half an hour and can relax at least to the degree that EMG artefacts on the EEG channel become rare. Once adequately relaxed, patients started with either Theta or SMR training sessions. All of them received 26 sessions of Theta or SMR training within 13 weeks. According to evaluations by home sleep logs both treatmentgroups could benefit from IEC, whereas objective evaluations at the sleep laboratory revealed that tense and anxious insomniacs benefited only from theta but not from SMR training, while those who were relaxed but still could not sleep benefited only from SMR- but not from theta training. Therefore Hauri et al. (1982) could show that appropriate IEC has a longlasting effect on insomnia, although patients have to be carefully selected, as the same type of IEC did not appear effective for all insomniacs. A further approach of IEC patterns during wakefulness reaching translation into sleep EEG was presented by Amzica, Neckelmann and Steriade (1997). Cats were trained to generate fast (20-50Hz) oscillation bursts within the motor cortex (area 4) as well as the visual cortex (area 17). The training of each animal consisted of seven sessions of motor cortex conditioning, three sessions of extinction and seven sessions of visual motor cortex conditioning. Extinction sessions were used to abolish the local increase in generation of fast oscillation bursts and to reset the thalamocortical synchrony of fast oscillations to control values. During the training sessions every 10sec a light flash was delivered into the visual field of the cat (conditioned stimulus) – at least 200 stimuli per session. If there was a qualifying burst (conditioned response) produced within the next 2sec, the animal was rewarded by a jet of water 100ms later. The experimental paradigm was successful in


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conditioning an increase in generation of fast oscillation bursts within both locations. Furthermore, the increased burst-generation was associated with an enhanced synchrony of fast oscillations at different levels of the thalamocortical network. Most interestingly for the present investigation, the increased thalamocortical synchrony acquired during the conditioning sessions was also expressed during subsequent quiet waking, NREM sleep and REM sleep, indicating that the facilitation of the desired oscillation bursts through instrumental conditioning during wakefulness selectively enhances similar patterns during subsequent sleep (for details see Amzica et al., 1997). Additionally, more recent research focused on healthy individuals providing evidence that subjects who are able to gain control over different EEG parameters might even succeed in increasing performance levels in various tasks (for review see Gruzelier, Egner, & Vernon, 2006; Vernon, 2005). Those studies have pointed out that distinct IEC-protocols can be successfully used to improve attentional processing (Egner & Gruzelier, 2001, 2003; Egner, Strawson, & Gruzelier, 2002), increase accuracy in working memory tasks (Vernon et al., 2003) or improve performance in mental rotation (Hanslmayr, Sauseng, Doppelmayr, Schabus, & Klimesch, 2005). Taken together there is a growing body of evidence suggesting that it is feasible to learn to regulate specific brain oscillations. Thereby it becomes possible to directly counteract the maladaptive brain activity which is associated with various disorders such as epilepsy, ADHD or sleep disorders. Unfortunately, much of the previous research concerning IEC has suffered from a lack of standardized measures of target symptoms, neglected the assessment of EEG changes and control groups or was conducted with insufficient sample sizes. Additional, well-controlled investigations are thus recommended before IEC can be considered a reliable non-pharmacological treatment for several disorders such as epilepsy, ADHD or even insomnia. To provide an insight into the vast amount of studies concerning the issue ―Instrumental EEG conditioning‖ an overview of the current IEC literature is presented in Table 4. Table 4. Overview of current IEC literature. Reference

Subjects

Feedback protocol

Berner et al. (2006)

11 healthy subjects

Birbaumer (1999)

2 ―locked-in‖ patients

↑ 11.6-16Hz (sigma); Cz; sleep spindle activity + overnight memory performance change; neurofeedback-training (NFT) vs. pseudoneurofeedback-training (PFT); visual NFT negative/positive slow cortical potentials (SCP); Cz; brain-interface; spelling device; imagery strategy

Number and duration of sessions 1 4 x 10 consecutive min

288 / 327 6-12 per day 5-10 min

Results

↑ sigma power during subsequent sleep-stage 2-4 (NREM)

both patients were better producing positive SCP; subjects were able to communicate by that kind of spelling device


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Table 4. Overview of current IEC literature. (Continued) Reference

Subjects

Feedback protocol

Beauregard & Lévesque (2006)

20 children (8-12 years) diagnosed with attention deficit hyperactivity disorder (ADHD)

Egner & Gruzelier (2001)

22 healthy subjects

Egner et al. (2002)

18 healthy subjects

Egner & Gruzelier (2003)

25 healthy subjects

Fuchs et al. (2003)

34 children (8-12 years) diagnosed with ADHD

experimental group (EXP): ↑ beta (15-18Hz) and ↑ sensorimotor rhythm (SMR; 12-15Hz), ↓ theta (4-7Hz); control group (CON): no NFT; digit span, integrated visual and auditory continuous performance test (IVA), Conner’s parent rating scale-revised (CPRS-R); experiment 1: counting stroop task, experiment 2: go/no-go task during functional magnetic resonance imaging (fMRI; pre and post training) ↑ beta 1 (15-18Hz) and ↑ SMR (12-15Hz), without concurrent rises of theta (4-7Hz) or high beta (22-30Hz); attention task; C3/C4; audio-visual NFT; oddball task; test of variables of attention (T.O.V.A.) ↑ theta/alpha ratio; ↑ theta (5-8Hz), ↓ alpha (8-11Hz); NFT vs. PFT; Pz; audio-visual NFT ↑ beta1 (15-18Hz) or SMR (12-15Hz); Cz; PFT; T.O.V.A.; auditory oddball paradigm; audio-visual NFT NFT-group (22) vs. pharmacotherapy-group (12); reward bands: SMR (12-15Hz) / beta (1518Hz); inhibition bands: theta (4-7Hz) / beta2 (2230Hz); C4 / C3; audiovisual NFT; T.O.V.A.; attention endurance test (d2); Conner’s behavior rating scale (CBRS) for teachers and parents

Number and duration of sessions 40 (3 per week) 13,5 weeks 60 min

Results

EXP: ↑ scores on digit span and IVA; ↓ CPRS-R scores; ↑ scores on accuracy (stroop-task, go/nogo task); fMRI-data indicate that NFT has the capacity to functionally normalize brain systems mediating selective attention and response inhibition in ADHD children

10 (2 per week) 30 min

↑ task performance and ↑ P300 after NFT; correlation between NFT learning rates and measure changes

5 (2-3 a week) 15 min

subjects receiving NFT could significantly increase theta/alpha ratio

10 (once a week) 15 min

↑ SMR activity is associated with ↑ attention whereas ↑ beta activity with ↑ arousal

36 (3 a week) 30-60 min

NFT as well as pharmacotherapy leads to comparable results: improvements in all subscales of T.O.V.A.; ↑ speed + accuracy (d2); ↓ ratings in CBRS

Non-Pharmacological Alternatives for the Treatment of Insomnia Gevensleben et 102 children al. (2009) (8-12 years) diagnosed with ADHD

Gosepath et al. (2001)

40 subjects suffering tinnitus; 15 controls

Hanslmayr et al. (2005)

18 healthy subjects

Hardt & Kamiya (1977)

16 male subjects

Hinterberger et al. (2004)

54 healthy subjects

Hoedlmoser et al. (2008)

27 healthy subjects

Kaiser & Othmer (2000)

1089 subjects with attentional complaints

Kotchoubey et al. (1999)

27 subjects suffering focal epilepsy

EXP: combined training: SCP and theta/beta; CON: computerised attention skills training; behavioral rating scales (parents, teachers) ↑ alpha, ↓ beta; P4, electromyography (EMG); audio-visual NFT; tinnitus questionnaire

36 (2-3 a week) 3-4 double-sessions / week (á 2 x 50min)

↑ upper alpha, ↓ theta frequency (individually adjusted frequency bands); F3, Fz, F4, P3, Pz, P4; mental rotation task; visual NFT anxiety-therapy; ↑↓ alpha (8-13Hz) ; Oz, O1, C3; audio NFT; eyes closed; Minnesota multiphasic personality inventory (MMPI); mood scales; high vs. low anxiety group ↑↓ SCP; Cz; 3 NFTmodalities: (i) visual, (ii) auditory and (iii) combined; thought translation device (TTD); ―locked-in syndrome‖

1 2 x 4 x 5 consecutive min

↑ SMR (12-15Hz) or randomized IEC protocol (randomized 3Hz frequency bins between 720Hz (except 12-15Hz) was used as relevant conditioning parameter ↑ SMR (12-18Hz) or beta (15-18Hz), ↓ theta (47Hz) and beta2 (2230Hz); C3/C4; audiovisual NFT; T.O.V.A. SCP; Cz; visual NFT; transfer trials; seizure rate

10 8 x 3 min

15 (2-3 a week) 5 x 5min 6 months follow up

only experimental group: ↑ parent and teacher ratings

significant reduction of the score in the tinnitus questionnaire; 24 subjects could ↑ alpha, 16 subjects ↓ beta; controls: no changes in EEG activity subjects that could ↑ upper alpha activity could improve cognitive performance

7 32 min

↑ alpha reduces state anxiety, ↓ alpha increased state anxiety in high anxiety group; low anxiety group was superior at ↑↓ alpha

3 500 trials per session 250 ↑ SCP, 250 SCP↓

Auditory as well as combined visual-auditory feedback is feasible to self-regulate SCPs; combined NFT showed the smallest learning effect only EXP (SMRconditioning): ↑ declarative learning, ↑ spindle number, ↓sleep onset latency

20 – 40 30 min

35 (2 a day) 140 trials per session 20 sessions – 8 weeks break – 15 sessions

85

↑ attentiveness, impulse control and response variability; subjects performing 40 sessions showed better results than those performing 20 patients who produced larger negative SCP during the first 20 sessions showed no decrease in seizure frequency


86


Subjects

Feedback protocol

Number and duration of sessions

Results

Lantz & Sterman (1988)

24 subjects suffering epilepsy

18 (3 a week) 30 min

reduced seizures; ↑ memory performance

Leins et al. 2007


↑ SMR (11-15Hz), ↓ delta (0-5Hz) and beta (20-25Hz); C1, C5; audio-visual NFT; Dodrill’s Neuropsychological Battery for Epilepsy 1st group: SCP, Cz; 2nd group: ↓ theta (48Hz), ↑ beta (12-20Hz), FC3, FC4; parental + teachers ratings, IQ (full scale, verbal, performance); test of attention

30 60 min (4 x 38 trials) 6 months follow up

Lubar, Swartwood, Swartwood, & Timmermann (1995) Lubar, Swartwood, Swartwood, & O'Donnell (1995)

19 subjects (8-19 years) diagnosed with ADHD

↓ theta (4-8Hz), ↑ beta (16-20Hz); CPz, FCz; audio-visual NFT; T.O.V.A.


both groups: intentional regulation of cortical activity; ↑ attention and IQ; parents and teachers reported ↑ behavior ratings and ↑ cognitive performance; effects remain stable six month after treatment successful NFT (N=12) resulted in ↑ T.O.V.A.performance


↑ beta (16-20Hz), ↓ theta (4-8Hz); CPz, FCz; audio-visual NFT; T.O.V.A., continuous performance task, behavior rating scale

30 – 45

Moore et al. (2000)

35 male subjects suffering substance abuse

3 conditions: (i) ↑ alpha (8-12Hz), (ii) ↑ theta (4-8Hz), ↓ alpha and (iii) EMG (25-32Hz); O2; theta/alpha ratio, theta/alpha crossover; audio NFT; eyes closed; imagery content (imagery occurring during feedback measured by questionnaire)

~20 40 min

success in NFT can be monitored by changes in the overall EEG; NFT-responders (N=12) showed stronger improvement on T.O.V.A. than NFT-non-responders (N=7) all 3 conditions were associated with similar amounts of average theta/alpha ratio and percentage of theta/alpha crossover; self-reported production of imagery is not related to any EEG/EMG correlate

Non-Pharmacological Alternatives for the Treatment of Insomnia Pfurtscheller, Müller et al. (2003)

1 tetraplegic patient

Rosenfeld et al. (1996)

5 subjects suffering depression

Sterman et al. (1970)

8 cats

Sterman & Lantz (2001)

20 epileptics unilateral temporal lobe lesion

Strehl, Leins et al. (2006)

5 subjects suffering Epilepsy

Strehl, Trevorrow et al. (2006)


↑ beta (16-18 Hz); two electrode pairs located over the right hand foot representation areas (2.5cm anterior and posterior to position C3/C4 or Cz, respectively); functional electrical stimulation (FES); imagination of foot movement; brain-computer interface (BCI) for hand grasp restoration; ↑ alpha (8-13Hz); F3Cz, F4-Cz; auditory NFT; alpha asymmetry training; eyes closed; mood scale prior and after each session ↑ SMR (12-14Hz) vs. low voltage fast activity (LVF); lateral pericruciate and posterior cortical sites; food reward; sleep recordings ↑ SMR (11-15Hz), ↓ delta (0-5Hz) and beta (20-25Hz); C1, C5; audio-visual NFT; Dodrill‘s Neuropsychological Battery for Epilepsy EEG & fMRI; negative/positive SCP; Cz; visual NFT; hemodynamic changes (blood oxygen leveldependent [BOLD] response) during producing positive SCP ↑↓ SCP; Cz; audio-visual NFT; parent ratings; IQ and attention; behavior ratings for teachers and parents

87

62 2-4 sessions a day 60 min ~5 months

by producing beta bursts and using BCI a FES device could be controlled; the patient was able to grasp a cylinder with the paralyzed hand

8 - 19 30 min

significant correlation between alpha asymmetry score and affect change score

14 - 28 daily 2 - 4 weeks 1 month follow up

↑ spindle activity and epochs of undisturbed sleep


successful NFT leads to improvement on memory tasks specific to the hemisphere contralateral to the lesion

35 á 145 trials 6 months follow up;

2 successful ―regulators‖; during positive SCP BOLD response indicated deactivation around the recording electrode Cz, frontal lobe and thalamus

30 (3 phases á 10 sessions) 6 months follow up

children learned to self regulate negative SCP; significant improvement in behavior, attention and IQ; all changes proved to be stable at the follow up


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Subjects

Feedback protocol

Number and duration of sessions

Results

Vernon et al. (2003)

30 healthy Subjects

↑ theta (4-7Hz) while ↓ delta (0-4Hz) and alpha (8-12Hz) or ↑ SMR (12-15Hz) while ↓ theta and beta (1822Hz); Cz; audio-visual NFT; continuous performance task (attention, CPT); conceptual span task (working memory, CST)

8 (2 a week) 5 x 3 min

SMR-NFT increased SMRactivity and CPT- and CSTperformance; theta-NFT failed to exhibit any changes

Abbreviations: ↑ = increase; ↓ = decrease; min = minutes; Hz = hertz; NREM = non rapid eye movement sleep; NFT = neurofeedback-training; PFT = pseudo-neurofeedback-training; SCP = slow cortical potentials; EXP = experimental group; SMR = sensorimotor rhythm; CON = control group; IVA = integrated visual and auditory continuous performance test; CPRS-R = Conner‘s parent rating scale – revised; fMRI = functional magnetic resonance imaging; ADHD = attentiondeficit hyperactivity disorder; T.O.V.A. = test of variables of attention; CBRS = Conner‘s behavior rating scale; EMG = electromyography; EEG = electroencephalography; MMPI = Minnesota multiphasic personality inventory; TTD = thought translation device; FES = functional electrical stimulation; BCI = brain computer interface; LVF = low voltage fast activity; BOLD = blood oxygen level dependent; IQ = intelligence quotient; CPT = continuous performance task; CST = conceptual span task.

5.5.1 Instrumental SMR Conditioning (ISC) and its Impact on Sleep Quality and Declarative Learning Recently we applied the earlier described IEC method to investigate the effect of instrumental 12-15Hz (SMR) conditioning (experimental group) as compared to randomized IEC (control group) on sleep as well as declarative memory performance (Berner, Schabus, Wienerroither, & Klimesch, 2006; Hoedlmoser et al., 2008). In a pilot study done in our laboratory (Berner et al., 2006) we investigated whether (i) ISC can have direct influence on sleep spindles produced during the night and whether (ii) a subtle change in this activity could even have an impact on successful memory encoding or overnight memory consolidation. These questions were hypothesized according to earlier findings where we indicated a significant positive correlation between overnight change in the number of recalled words in a declarative word-pair association task and spindle activity change from a control to experimental night (Schabus et al., 2004). Although sleep spindle activity remained unchanged after ISC in this first study, we found enhanced ―spindle frequency‖ band power during sleep, indicating that ISC effects become most easily evident in the actual trained frequency bands rather than in associated phasic spindle ―events‖. The caveat of this pilot study, however, was the amount of ISC-sessions: the ISC-protocol consisted only of four 10min long blocks, thus, was not comparable to the much more intense ISC-protocols used in previous studies.


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Inspired by this preliminary pilot study we continued our investigations by a more extensive approach. Twenty-seven healthy subjects (13 male, 14 female; mean age = 23.63 years, SD=2.69) were randomly assigned (parallel group design) to either (i) a SMRconditioning protocol (experimental group; N=16) or to (ii) a randomized IEC protocol (control group; N=11). As depicted in Figure 2 all of them attended the laboratory on 13 occasions.

Figure 2. Study design. Subjects had to attend the laboratory 13 times. The first visit – 3 days prior to pretreatment – served as entrance examination. Pretreatment included a declarative memory task (encoding [ENCpre], retrieval before nap [RET1pre], retrieval after nap [RET2pre]) as well as a 90min nap (NAPpre) and was followed by 10 IEC sessions on 10 consecutive days (except weekends). Posttreatment (same procedure like pretreatment: ENCpost, RET1post, NAPpost and RET2post) - one day after the last conditioning session - completed the study protocol. Figure reprinted with permission from Hoedlmoser et al. (2008).

First subjects had to pass an entrance examination consisting of several parts: clinical evaluation of sleep quality [Pittsburgh Sleep Quality Index (PSQI); Buysse, Reynolds, Monks, Berman, & Kupfer, 1988]; anxiety (self-rated anxiety scale; Zung, 1971); depression (self-rated depression scale; Zung, 1965); memory („Wechsler Memory Scale – revised―; Härting, Markowitsch, Neufeld, Calabrese, & Deisinger, 2000) and intelligence (Advanced Progressive Matrices; Raven, Raven, & Court, 1998). Throughout the study participants had to complete a sleep diary every day in the evening and in the morning (Self-rating scale for Sleep and Awakening quality; Saletu, Wessely, Grünberger, & Schultes, 1987) to control their sleep-wake-cycle and to prevent sleep deprivation prior to laboratory examination. During the nap-session before (NAPpre) and after (NAPpost) ISC subjects performed a declarative word-pair association task (Plihal & Born, 1997). Subjects had to learn a first list of 80 word-pairs during NAPpre, and a second one during NAPpost. Polygraphic sleep recordings using Synamps EEG amplifiers (NeuroScan Inc.) started at 2:00 pm and ended at 3:30 pm. Fifteen gold-plated silver electrodes were attached according to the international 10/20 system. In addition, four electrooculogram (EOG) channels, one submental EMG channel, one electrocardiogram channel (ECG) and one respiratory channel (chest wall movements) were recorded. Between pre- and post-treatment the subjects were trained to enhance their band amplitude within specific frequency bins during 10 IEC sessions on 10 consecutive days (except weekends) using visual online feedback. Each session was conducted in a standardized procedure and lasted for about 1 hour (including electrode adjustment). Immediately before and after instrumental conditioning subjects were instructed to relax during a 2min eyes-closed resting condition followed by a 2min eyes open resting

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condition. EEG was recorded from C3 with reference on the right earlobe and ground electrode placed on the left earlobe. For offline artefact rejection a bipolar vertical EOG channel was recorded. The ongoing EEG at site C3 was band-pass filtered to continuously extract amplitude values within the frequency of interest. Band amplitude of interest was calculated online and used as relevant conditioning parameter. The instrumental conditioning design was performed as depicted in Figure 3. One trial consisted of a 3sec baseline followed by a continuous feedback interval lasting until the EEG signal exceeded the predefined reward threshold measured during the baseline for more than 250ms. Any time the subject was able to produce the requested EEG rhythm, the compass needle moved to the left. The aim was to move the needle as far to the left as possible reaching the previously fixed threshold represented by a green dot. In case of exceeding the amplitude threshold for at least 250ms, subjects got an audiovisual reward (appearance of a sun for 2sec accompanied by a 200ms lasting sound of 800Hz).

Figure 3. Schematic representation of one block within an IEC session. A 3sec lasting ―Baseline― before visual feedback onset was used to calculate the mean amplitude within the frequency of interest which served as reference during ―Feedback interval‖. An audiovisual ―Feedback quote‖ was triggered by an EEG signal containing at least 250ms of the frequency of interest at an amplitude exceeding a certain reward threshold measured during the 3sec baseline. Figure reprinted with permission from Hoedlmoser et al. (2008).

There were no specific instructions for the subjects as everybody was encouraged to find his or her own appropriate strategies like physiological relaxation combined with positive mental activity. To prevent rewards elicited by movements, eye, or muscle artefacts, trials with amplitudes exceeding 200µV were abandoned by starting a new trial. Experimental and control group only differed concerning frequency adjustments. Subjects of the experimental group had to enhance the amplitude within their 12-15Hz frequency range throughout all sessions, whereas for the control group the band amplitude of randomized, each session varying 3Hz frequency bins between 7 and 20Hz (except 12-15Hz) were used as conditioning parameter. Subjects were not aware about their treatment until the study was over.


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Figure 4. Main effects of ISC compared to randomized IEC on sleep and learning. 2-way ANOVAs depicting differences between experimental ( ) and control (⁫) group. a Significant increase of relative SMR amplitude after ISC (experimental group) vs. randomized IEC (control group). b Significant reduction of sleep onset latency during NAPpost compared to NAPpre. c Significant increase of sleep spindle number from NAPpre to NAPpost. d Significant enhancement of retrieval score computed at immediate cued recall (RET1) after ISC (experimental group) compared to randomized IEC (control group). Note that only 1215Hz conditioning (experimental group) could increase relative SMR amplitude, sleep spindle number and retrieval score as well as decrease sleep onset latency. Error bars indicate standard errors of mean. Reprinted with permission from Hoedlmoser et al. (2008).

As depicted in Figure 4a significant SMR amplitude changes from early to late conditioning sessions confirmed the success of our ISC paradigm. Most interestingly, these EEG changes transferred into sleep (Figure 4b-c) and even improved immediate memory retrieval after learning (Figure 4d). There were no effects on memory consolidation (i.e., ―overnap‖ change in memory performance after ISC) indicating a more unspecific effect of ISC. Heightened attention or relaxation levels after ISC are supposed to cause the improvement in word-pair recall. Our results therefore demonstrate to our best knowledge for the first time successful ISC in a healthy human population (cf. Figure 4a) leading to enhancement of sleep spindles (cf. Figure 4c) and thereby indicating that specific neural mechanism trained during wakefulness can be translated into sleep. There was no change in the duration of stage 2 sleep and therefore it can be ruled out that the spindle increase is

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caused by an increase of stage 2 sleep. Furthermore, sleep onset latency (cf. Figure 4b) was significantly shortened after ISC compared to a randomized IEC paradigm. Therefore our results additionally support Hauri‘s approach (1981, 1982) to use ISC as an alternative treatment for primary insomnia. Note that here we used a much more rigorous control group than usually adopted. Subjects of the control group underwent exactly the same study protocol with only the type of IEC being altered.

6. Prospects: ISC as Treatment for Primary Insomnia? Given our recent findings (Hoedlmoser et al., 2008) we further aimed at changing sleep quality in humans suffering from primary insomnia by using ISC. In a preliminary study we recruited 12 subjects (11 women) aged between 19 and 48 (M =29.33; SD = 10.56) with clinical symptoms of primary insomnia. Individuals suffering from primary insomnia had to meet the following inclusion criteria: a) difficulty initiating [i.e., sleep-onset latency (SOL), >30min] and/or maintaining (i.e., time awake after sleep onset >30min) sleep and b) insomnia or its perceived consequences caused marked distress or significant impairment of occupational or social functioning. Several questionnaires [PSQI, Buysse et al., 1989; Becks Depression Inventory (BDI–II), Beck et al., 1996; Becks Anxiety Inventory (BAI), Margraf & Ehlers, 2007)] as well as a semi structured clinical interview for sleep disorders (―Strukturiertes Interview für Schlafstörungen nach DSM-III-R‖ (SIS–D), Schramm et al., 1993) were used to evaluate subjects compatibility (primary insomnia without comorbidities). A counterbalanced within subjects design was used. Subjects had to attend the sleep laboratory 19 times over the course of 3 to 6 weeks (4 nights, 10 x ISC, 5 x randomized IEC; cf. Figure 5). Participants were instructed to arrive at the sleep laboratory at 7:30 pm each night. Polysomnographic recordings (PSG) started between 11:00 and midnight and were terminated after eight hours time in bed (TIB). The first PSG night served as screening and adaptation night. During experimental nights (1 x pre-treatment, 2 x posttreatment) a standard PSG montage with 21 gold plated silver electrodes was applied. Concerning ISC we used the same method like in our previous study (Hoedlmoser, 2008) however, this time a within subjects design was implemented. Subjects were randomly assigned to either a protocol starting with ISC followed by randomized IEC or to a protocol starting with randomized IEC followed by ISC. Therefore every subject received both treatments – ISC and randomized IEC (cf. Figure 5). Preliminary results confirmed the increase of 12-15Hz activity over the course of the ten ISC training sessions (p=0.027) but not over the course of the randomized IEC training sessions. Interestingly, the increased SMR activity was associated with the enhancement of subjective sleep quality measured by the PSQI (p=0.001). Furthermore sleep onset latency was tendentially reduced after ISC (p=0.056) but not after randomized IEC. However, there were no significant changes concerning sleep spindle activity like we could show in our previous study (Hoedlmoser et al., 2008).


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Figure 5. Study design. Subjects suffering from primary insomnia take part in a first adaptation/screening night (PSG1) followed by an experimental pre-treatment night (PSG 2). Pre-treatment night was either followed by 10 ISC sessions or by 5 randomized IEC sessions. Note that the order of treatments (ISC or randomized IEC) was counterbalanced. Post-treatment nights (PSG3, PSG4) were each conducted one day after the last conditioning session of ISC or randomized IEC, respectively.

Therefore our current preliminary data indicate that people suffering from primary insomnia experience subjective benefits from ISC before objectively verifiable. Further research is highly needed in order to reveal whether more intense ISC – or other forms of biofeedback or neurofeedback are able to consistently improve also objective sleep parameters such as wake after sleep onset or total sleep time. Taken together our recent work confirms that instrumental conditioning of SMR has positive impact on sleep quality as well as on declarative learning in healthy participants (Hoedlmoser et al., 2008). Whether a similar instrumental conditioning protocol is also effective in the treatment of sleep disorders such as primary insomnia has yet to be revealed by well-controlled empirical studies.

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Chapter IV

A Novel Disease Condition Presenting with Insomnia and Hypersomnia Asynchronization Jun Kohyama* Tokyo Bay Urayasu/Ichikawa Medical Center, 3-4-32 Toudaijima, Urayasu 279-0001, Japan

Abstract More than half of the preschoolers/students in Japan have recently complained of daytime sleepiness, while approximately one quarter of junior and senior high school students reportedly suffer from insomnia. These children might suffer from behavioralinduced insufficient sleep syndrome due to inadequate sleep hygiene, and conventional therapeutic approaches often fail. The present study addressed whether asynchronization, a novel clinical notion, could be responsible for the pathophysiology of these sleep disturbances and could provide a better understanding for successful interventions. This clinical concept was designed with special reference to the basic concept of singularity. The essence of asynchronization comprises disturbances in various aspects (e.g., cycle, amplitude, phase, and interrelationship) of biological rhythms that normally exhibit circadian oscillation. These disturbances presumably involve decreased activity of melatonergic and serotonergic systems. The major triggers for asynchronization are hypothesized to be a combination of light exposure during the night, which decreases melatonin secretion, as well as lack of light exposure in the morning, which decreases activity in the serotonergic system. Prevention of asynchronization must include acquisition of morning light and avoidance of nocturnal light. Possible potential therapeutic approaches for asynchronization involve conventional and alternative therapies. We should know more about the property of the biological clock.

*

Tel +81 47 351 3101 Fax +81 47 352 6237, [email protected]

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Keywords: desynchronization; melatonin; serotonin; sleep; circadian rhythm; singularity

1. Introduction Circadian rhythms are generated in the suprachiasmatic nucleus (SCN). SCN development takes place throughout the course of gestation, remains immature for some time after birth, and is suggested to be vulnerable to maternal influences [1]. Studies have shown that the earlier mothers fell into nocturnal sleep during late pregnancy, the longer the babies slept during the night at one month of age [2]. The same report described that onset time for the longest nocturnal sleep of mothers during late pregnancy was similar to the babies at one month of age, suggesting that synchronization of sleep rhythm begins during late pregnancy. Because circadian rhythm disturbances in the young can impact SCN function during the lifespan, therapeutic strategies are much needed. Nevertheless, very little is understood regarding pathophysiology of circadian rhythm disruption, which makes it difficult to determine the appropriate clinical approach for these patients. This review article introduces the recent phenomenon of a nocturnal lifestyle among youth in Japan, and the association between nocturnal lifestyle and behavior. In addition, the presumed involvements of neurological systems such as the biological clock, melatonergic system and serotonergic system in youth that prefer a nocturnal lifestyle are reviewed. Finally, a new clinical entity – asynchronization [3, 4] - has been proposed, in an attempt to elucidate the pathophysiology of circadian disruptions and to provide novel, clinical therapeutic approaches. This clinical concept has been termed with special reference to the basic concept of singularity. Circadian singularity behavior was discovered in 1970, according to observation that specific, dim, blue-light, pulse stimulus, with a unique stimulus time and duration, resulted in disturbed circadian rhythm in Drosophila [5].

2. Insomnia and Hypersomnia Among Japan Youth 2.1. Recent Statistics of Bedtime and Sleep Duration The percentage of 1-year-old children who go to bed later than 22:00 has increased from 25.7% in 1980 to 54.4% in 2000. Similar statistics have also been reported for the rate of 3year-old children who go to bed later than 22:00: 21.7% in 1980 [6], 43.8% in 1999 [7], 49.8% in 1999-2000 [8], 52.0% in 2000 [6], and 51.1% in 2004 [9]. The rate of fourth-grade students at elementary schools in Tokyo going to bed later than 0:00 has also increased from 0% in 1979 to 2% in 2002 [10]. The mean bedtime in 2004 for elementary school students in the fifth and sixth grade was 22:03, junior high school students was 23:18, and senior high school students was 0:06 [11]. An additional study from 2005 reported the mean bedtime for students in the fifth grade was 22:10, students in the second grade of junior high school was 23:26, and students in the second grade of senior high school

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had a mean bedtime of 23:50 [12]. Tagaya et al. reported an average bedtime of 0:03 from senior high school students in 2000 [13]. In 3-year-old children, the bedtime delay has resulted in a reduction of total daily sleep [8]. Indeed, in accordance with a recent development in later bedtimes, sleep duration of Japanese children has also reduced. Shimada et al [14] examined studies of sleep duration of infants, and concluded that sleep duration in the early 1990s decreased from 12.9 hours in 1985 [15] to 10.9 hours. The nocturnal sleep duration of children aged 3-6 years in 2000 (10.10 hours for children attending kindergarten, 9.35 hours for children attending nursery school, and 9.95 hours for children attending neither kindergarten nor nursery school) was reported to be 9-15 minutes less than in 1995 [16]. Among 21273 children aged 0-36 months from 12 different countries (United States, United Kingdom, Australia, New Zealand, Canada, Hong Kong, Korea, Taiwan, Thailand, Indonesia, Japan, China), Japanese children exhibited the shortest sleep duration (nap + nocturnal sleep duration) of 11.6 hours, while those in New Zealand revealed the longest duration of 13.3 hours [17]. Between 1965 and 2000, the sleep duration of elementary school, as well as junior and senior high school students, in Japan decreased on average by 1.1-1.6 minutes per year [18]. More specifically, mean nocturnal sleep duration in 2004 was 8.77 hours for elementary school students in fifth and sixth grade, 7.42 hours for junior high school students, and 6.55 hours for senior high school students [11]. Similarly, in 2005, mean nocturnal sleep duration was 8.40 hours for fifth-grade elementary school students, 7.23 hours for second-grade junior high school students, and 6.51 hours for second-grade senior high school students [12]. Tagaya et al. reported average sleep duration of senior high school students in 2000 to be 6.30 hours [13].

2.2. Complaints of Young People with Nocturnal Lifestyle In 1979, 8.1% of children attending day nursery schools in Japan were reported to frequently yawn in the morning, and 10.5% were easily tired. By 2000, these numbers had increased remarkably to 53.2% and 76.6%, respectively [19]. Accordingly, approximately 80% of kindergarten and nursery school teachers reported that many children were sleepdeprived [20]. In 2004 in Tokyo, 50% of fifth- and sixth-grade elementary school boys, 60% of fifthand sixth-grade elementary school girls, 70% of junior high school boys, and 80% of junior high school girls reportedly complained of sleepiness during the third and fourth lesson periods (from approximately 10:00 to 12:00) [21]. In contrast to the early morning (around 4:00) and afternoon (around 14:00) periods, late morning is the period when humans generally tend to be most alert and active [22]. In addition, 47.3%, 60.8%, and 68.3% of fifth-grade elementary school students, secondgrade junior high school students, and second-grade senior high school students reportedly experienced sleep deficiency, respectively [12]. The reasons given for sleep deficiency indicated by these students are shown in Table 1. A nationwide study to ascertain the prevalence of insomnia, the symptoms, and associated factors among students in junior and senior high schools in Japan revealed a

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prevalence of difficulty in initiating sleep (14.8%), difficulty maintaining sleep (11.3%), and early morning awakening (5.5%) [23]. The prevalence of insomnia, defined as the presence of one or more of these three symptoms, was 23.5%. Table 1. Causes of sleep deficiency [12].

2

Elementary school students Difficulties falling asleep (43.8%) TV and video (39.3%)

3

Homework (26.3%)

1

Junior high school students TV and video (44.5%) Homework (32.2%) Difficulties falling asleep (31.1%)

Senior high school students Cellular phone use (42.4%) TV and video (38.8%) Difficulties falling asleep (27.1%)

The number in parentheses indicates the percentage of students who listed the issue among students who felt they suffered from sleep insufficiency.

Taking these facts together, young people in Japan are likely to suffer from both daytime sleepiness and nocturnal insomnia. In Japan, it was reported that sleep insufficiency was the main cause of daytime sleepiness in junior high school students, and that inappropriate sleep habits, such as low physical activity level and television viewing, were the potential responsible factors [24]. Exercise is important for good sleep hygiene [25], and an association between the duration of television viewing and irregularity of sleep habits in young children has been described [26]. Television viewing during childhood and adolescence has been associated with increased weight, poor fitness, smoking, and increased cholesterol in adulthood [27]. Watching television, along with playing videogames for an extended period of time, were significantly associated with prolonged sleep onset latency, as well as poor sleep hygiene and an insufficient amount of sleep [28]. Lack of sleep increases body weight [29]. Overweight individuals tend to be less physically active, and reduced physical activity, in turn, exacerbates weight gain. Reduced physical activity and excessive media exposure are likely to be factors that increase inadequate sleep hygiene, which can result in insomnia leading to sleep deficiency and daytime sleepiness. In addition, the lack of discipline in the home and in public education system, as well as shopping centers that are open 24 hours per day and mobile phone, might contribute to poor sleep hygiene. Data obtained from 17,465 university students, aged 17 to 30 years, that were taking non-health-related courses at 27 different universities in 24 countries, revealed that both male and female students in Japan exhibited the shortest sleep duration and the highest rate of self-rated unhealthiness [30]. In addition, according to the study performed by Walt Disney Studio Home Entertainment in 2008, sleep duration of individuals aged 18-64 years was shortest in Japan, from the 17 countries evaluated [31]. I wonder that most adults, including parents in Japan, do not view sleep as a valuable behavior and, therefore, neglect sleep, which might lead to increased prevalence of inadequate sleep hygiene among the younger generation. The major complaints of elementary school and junior high school students in 2001 in Tokyo [10] are listed in Table 2. Most of these complaints were consistent with symptoms described as associated features of behaviorally induced deficient sleep syndrome (irritability, concentration and attention deficits, reduced vigilance, distractibility, reduced motivation,


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anergia, dysphoria, fatigue, restlessness, lack of coordination, and malaise) in the International Classification of Sleep Disorders-2 (ICSD-2) [32]. Can these complaints, however, be explained by sleep insufficiency? Table 2. Major complaints of students (>20%) [10]. Elementary school students Persistent need to yawn (62%), desire to sleep (58%), desire to lie down (47%), Eyestrain (33%), difficulties to sit straight (29%), memorizing difficulties (28%), irritated (27%), Neck stiffness (26%), low activity (25%), difficulties to concentrate (25%), Hypersensitive (24%), thirsty (21%), make many mistakes (20%) Junior high school students Desire to sleep (boys/girls; 73.8%/80.8%), persistent need to yawn 43.6%/69.1%), Desire to lie down (43.2%/47.2%), eyestrain (40.7%/44.7%), Memorizing difficulties (35.2%/33.6%), neck stiffness (29.3%/35.1%), Lumbago (26.5%/23.2%), low activity (21.3%/28.0%), Hypersensitive (20.0%/27.0%), difficulties to concentrate (21.0%/23.8%), Irritated (20.5%/24.2%),

As mentioned previously, bedtime delay in youngsters reduces total daily sleep duration [8], and approximately 80% of kindergarten and nursery school teachers reported that many children are sleep-deprived [20]. In fact, sleep deprivation has been demonstrated to exert a negative effect on daytime functions [33-35], general well being [36], metabolic and endocrine function [37, 38], and body weight [29]. However, the required sleep duration of an individual person is very difficult to determine, because the need for sleep is variable and depends on several factors [39]. Adults normally sleep for varied lengths of times, and such habits are considered to develop at a young age [32]. Of course, these differences should not mean that one should not take care of their sleep duration. If individuals are alert and active during late morning, then they are more likely to have healthier sleep duration, sleep quality, and life rhythms.

3. Nocturnal Lifestyles and Behaviors Not only a shortage of sleep duration, but also delayed bedtimes and wake-up times are known to produce physical, mental, and/or emotional problems.

3.1. Adults and Older Children Later bedtimes and wake-up times are significantly associated with sub-clinical manictype symptoms among working adults [40], and evening-type medical school students are reported to experience reduced sleep efficiency compared with morning-type students [41]. To determine if an individual is a morning-type or evening-type person, a self-assessment questionnaire was used. According to an original report [42], morning-type people went to bed and arose significantly earlier than evening-type people. Evening-type young adolescents

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in Taiwan exhibited a greater association with mood and anxiety symptoms [43]. Among 6631 adolescents aged 14.1-18.6 years, evening-types were found to exhibit more attention problems, perform more poorly in school, experience more injuries, and were emotionally upset more often than the other chronotype individuals [44]. Japanese junior high school students, with an evening preference, were reported to be more likely to exhibit poorer sleepwake parameters and lifestyle habits than those with a morning preference [45], and there was a greater association between evening-type individuals and impulsivity in students [46]. Compared with morning-type students, evening-type 12- to 13-year old students were reported to be more likely to exhibit behavioral/emotional problems, suicidal behavior and ideation, and habitual substance use [47]. Evening-type children aged 8-13 years have been shown to exhibit a greater tendency towards antisocial behavior, rule-breaking, attention problems, conduct disorder symptoms in boys, and aggression towards others in girls [48]. According to a nationwide survey, students in Japan with regular bedtimes and waking times showed better school performance than those with irregular sleeping times [49]. And conversely, an irregular lifestyle is known to be associated with delayed bedtimes and waking times. Of the college students surveyed, those with poor sleep quality exhibited less regularity in social rhythms relative to those with good sleep quality, and later rising times and bedtimes were reported to be associated with worse sleep quality [50]. Moreover, in adult populations, evening-type people are reported to demonstrate a more irregular daily lifestyle than morning-type people [51]. These reports all suggest an association between delayed waking times, bedtimes and irregular lifestyle with problematic behaviors of older children, adolescents, and adults.

3.2. Studies on Preschoolers Although few studies have described an association between sleep habits and behavior in preschoolers, problematic behaviors among children aged 4 to 6 years have been associated with late and irregular waking times and bedtimes, but not with sleep duration [52]. Suzuki et al. [53] compared the relationship between a 2-week sleep diary and the ability to copy a triangular figure on the first attempt in 222 children aged 5 and 6 years. The children who successfully copied the triangle had significantly earlier mean morning wake-up times, as well as significantly longer mean total sleep duration, compared with children who failed to copy the triangle. Compared with children with regular sleep-wakefulness rhythms, children with irregular sleep-wakefulness rhythms exhibited a 5.9-times greater risk of inability to copy the triangle. A semi-structured interview with 16 teachers identified 48 troublesome episodes in 42 children. The rate of children with irregular sleep-wakefulness rhythms among the children with the troublesome episodes (19/42) was significantly greater than children without troublesome episodes (15/180). These results suggested that children with irregular sleep-wakefulness rhythms exhibit more behavioral problems, as well as problems with integration of cognitive and motor activity. In a separate study, 204 children, aged 12-40 months (mean 22.6 months), were assessed for daily average physical activity counts per minute (PA) [54]. Results showed that increased age, male gender, and early wake-up times exhibited significant positive


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correlations with PA. Among children with a mean age of 7.3 years, higher mean daytime activity counts were reported to be associated with a decrease in sleep latency [55].

4. Nocturnal Lifestyle and Neurological Systems The above-mentioned studies on preschoolers, along with previously cited papers on older children, adolescents, and adults, report problematic behaviors that are associated with delayed wake-up times, delayed bedtimes, and an irregular lifestyle. Although delayed bedtimes also resulted in sleep loss [8], problematic behaviors were found to be more likely associated with delayed wake-up times, delayed bedtimes, and an irregular lifestyle, regardless of sleep duration [52]. In the following section, the presumed neuronal mechanisms associated with these results will be addressed.

4.1. Biological Clock Circadian signals are relayed from the SCN to the hypothalamic dorsomedial nucleus via the subparaventricular zone. The dorsomedial nucleus of the hypothalamus combines inputs from the SCN with inputs from other areas, allowing for flexible control, and sends signals to structures that regulate various circadian rhythms, such as feeding, locomotion, sleep-wake alternation, corticosterone secretion [56], and the autonomic nervous system [57]. Typically, the endogenous period of the circadian clock is longer than 24 hours, and it is through exposure to sunlight in the morning people become accustomed to the 24-hour cycle [58]. Conversely, light exposure at night delays the circadian clock phase [58], or disrupts its function [59-61]. Non-photic cues, such as eating times [62] and activity [63], also serve to synchronize the circadian system to a 24-hour day. In the absence of time cues, daily rhythms become altered, developing their own rhythm. After spending life under such conditions for a considerable period of time, the staging of various biological rhythms changes, such as sleep– wakefulness and temperature [64]. Under such conditions, reciprocal phase interactions within circadian rhythms are disturbed. In general, most people spontaneously awake in the morning when the body temperature begins to rise from its lowest level and, conversely, fall asleep at night when the body temperature begins to decline from its highest level. However, once this reciprocal interaction is impaired, the phase relationship between body temperature and sleep-wake circadian rhythms is disrupted [64], known as circadian desynchronization [65, 66]. This condition might produce various physical and mood disturbances (disturbed nighttime sleep, impaired daytime alertness and performance, disorientation, gastrointestinal problems, loss of appetite, inappropriate timing of defecation, excessive need to urinate during the night). Similar complaints and mood alterations have been observed in patients with jet lag [67], seasonal affective disorder [68], and in astronauts [69]. Endogenous phasing of the circadian biological clock in morning-type individuals varies from evening-type individuals [70], who experience a temperature rise later in the morning and later waking times [71]. Moreover, individuals who are alert in the morning experience an earlier circadian rhythm temperature peak than do individuals who are alert in the evening

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[72]. These reports suggested that evening-type individuals suffer from circadian desynchronization [65, 66]. Those with delayed waking times and bedtimes, and an irregular lifestyle (an evening preference) are hypothesized to suffer from circadian desynchronization. Arendt et al. [67] showed that jet lag recovery rate, which is attributed in large part to temporary circadian desynchronization, varies with individuals, as well as with the direction of time zone change. The susceptibility for developing symptoms, presumably due to desynchronization, is likely to vary in different individuals. In this regard, the following reports suggest that desynchronization susceptibility is affected by biological background. Nilssen et al. [73] compared the prevalence of sleep disorders in two ethnically different populations living in the same extreme arctic climate. More than 50% of the Norwegian population in these studies [73, 74] resided in the northern region of Norway, whereas the Russian subjects were primarily recruited from the southern part of Russia and the Ukraine. The study determined that Russians exhibited a greater prevalence of sleep disorders than Norwegians. A one-year prevalence of self-reported depression was also compared in the two populations [74], with similar results. The authors [73, 74] postulated that insufficient acclimatization after migration to the north resulted in these effects. Susceptibility to these symptoms was presumably due to desynchronization, which was likely affected in part by unknown biological background factors, including acclimatization. However, acclimatization cannot be altered within one generation.

4.2. Melatonergic System Melatonin not only regulates the circadian phase [75], but also acts as a hypnotic, is an effective free-radical scavenger and antioxidant, and directly induces gonadotropin-inhibitory hormone expression [76]. Interestingly, bright light during nighttime decreases melatonin secretion [77]. The existence of immunoreactivity against melatonin was demonstrated in the bacterium Rhodospirillum rubrum, one of the oldest species of living organisms, at possibly 2-3.5 billion years [78]. Bacterial melatonin might provide on-site protection of bacterial DNA against free-radical attack. Melatonin is also known to exert antioxidant effects in the brain [79], and sleep is hypothesized to function as an antioxidant or scavenging process in the brain [80]. Melatonin promotes and synchronizes sleep by acting on SCN-expressing melatonin MT1 and MT2 receptors, respectively. Synthesized melatonin receptor agonists exhibiting increased duration of action are expected to provide significant clinical value for treating insomnia patients [81]. The onset of melatonin secretion begins 14-16 hours after waking, usually around dusk [82]. Exposure to bright, midday light has been shown to increase melatonin secretion during the night, without a circadian phase shift [83]. Although the results are preliminary, in a study of 3-year-old children, early sleepers tended to exhibit higher levels of urinary 6-sulfatoxymelatonin (6SM) (6SM/creatinine ratio), the primary melatonin metabolite, compared with late sleepers [84]. Decreased melatonin levels in aged zebrafish have been shown to correlate with altered circadian rhythms [85]. Danel et al. observed an inversion in melatonin circadian rhythm


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secretion in alcoholics, not only during intake, but also during short- and long-term withdrawal. They concluded that circadian disorganization of melatonin secretion could be responsible for desynchronization in some alcoholic patients [86]. Because melatonin regulates the circadian phase [75], altered melatonin secretion could disturb circadian oscillation, producing various biological alterations. Nevertheless, in the rat, altered melatonin rhythm had no effect on circadian rhythms of locomotor activity and body temperature [87].

4.3. Serotonergic System Exposure to morning sunlight has been demonstrated to activate the serotonergic system [88] and, conversely, a nocturnal lifestyle is unlikely to activate the serotonergic system. Moreover, depression correlates with decreased norepinephrine, serotonin, or both [89]. In addition, selective serotonin reuptake inhibitors, which increase the availability of serotonin at the synaptic cleft, have been widely used to treat depression. Emotional instability, typical in individuals with nocturnal lifestyles, might be associated with insufficient serotonergic activity. The serotonergic system is activated through rhythmic movements, such as gait, chewing, and respiration [90]. Adequate physical activity could, therefore, be important for the activation of serotonin. Exercise-derived benefits for brain function have been demonstrated at the molecular level [91], and physical activity has been reported to decrease the risk of Alzheimer‘s disease [92–95]. Physical activity, which activates serotonergic activity, is one of the key factors in promoting brain function in animals and humans. The concept of low serotonin syndrome, which comprises aggressiveness, impulsivity, and suicidal behavior has been proposed [96]. In adult, male, vervet monkeys, decreased serotonergic activity was reported to be a disadvantage, and enhanced activity an advantage, for attaining high social dominance status [97]. Disturbance in the lateral orbito-prefrontal circuit induces aggressive behavior and loss of sociability [98], and the serotonergic system has been shown to activate this circuit [99]. Serotonin levels, which are increased through exercise, have been shown to enhance learning ability [92]. Serotonergic activity is profoundly affected by the sleep-wakefulness cycle, exhibiting highest activity while waking, and lowest activity during rapid eye movement sleep [100]. Taking these facts together, it has been postulated that irregular sleep-wakefulness rhythm disturbs emotional control and sociability, due to decreased serotonergic activation in the lateral orbito-prefrontal circuit. It is likely that circadian desynchronization results in unsatisfactory physical, mental and/or emotional conditions, presumably leading to decreased physical activity. If physical activity becomes too low, then the serotonergic system will not be activated. This is further confounded by a lack of morning light. The following negative cycles (solid filled lines in Figure 1) can be postulated in those with delayed wake-up times, delayed bedtimes, and an irregular lifestyle.

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Figure 1. Schematic drawing of the development of asynchronization modified from Figure 1 in reference 4.

4.4. Reported Disease Conditions Associated with Circadian Disruption Miike et al. [101] described altered circadian rhythms in childhood chronic fatigue syndrome, and reported that these patients suffered from an atypical, but continuous, jet lag condition. A British cohort study over more than 30 years [102] revealed that sedentary behavior during childhood increased the risk of chronic fatigue syndrome/myalgic encephalomyelitis, for which depression is a major symptom. Selective serotonin reuptake inhibitors have been reported to be effective in treating chronic fatigue syndrome patients [103]. It has been assumed that decreased serotonergic activity is involved in the occurrence of this syndrome. Melatonin has also been shown to be effective for chronic fatigue syndrome patients with delayed circadian rhythm [104]. One third of children with chronic fatigue syndrome exhibited abnormal cardiovascular regulation during postural changes (orthostatic dysregulation), which is characterized by instantaneous orthostatic hypotension, postural, or neural-mediated syncope [105]. Orthostatic dysregulation is a well-established clinical concept among pediatricians in Japan. The characteristic clinical burnout symptoms, first described in 1974 [106], comprise excessive and persistent fatigue, emotional distress, and cognitive dysfunction. These symptoms are common among disorders such as depression, chronic fatigue syndrome, and vital exhaustion [107]. Burnout is positively associated with poor sleep quality, a sensation of not feeling refreshed upon awakening, and sleepiness and/or fatigue during daytime [108]. Burned-out subjects are reported to exhibit a higher frequency of arousal during sleep [107]. A study of University Hospital nurses revealed that daylight exposure for at least 3 hours per day resulted in reduced stress and greater job satisfaction, both of which were favorable


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factors for reducing burnout [109]. Because bright, midday light increases melatonin secretion during the night in elderly individuals [83], the melatonergic system, as well as the serotonergic system [110], might be involved in the pathogenesis of burnout. Appels et al. introduced the terminology of vital exhaustion, which is conceptually akin to burnout [111]. In a prospective study of a large sample of healthy men, vital exhaustion was shown to comprise three factors - fatigue, depressive affect, and irritability - and the risk of subsequent myocardial infarction was attributed to fatigue from vital exhaustion [112]. Vital exhaustion is also associated with sleep disturbances. Polysomnographic recordings indicated that deep sleep stages were significantly reduced in exhausted subjects, compared with control subjects, suggesting that normal restoration processes, which occur while sleeping, are impaired in exhausted subjects [113]. In addition, exhausted subjects presented with a greater number of sleep complaints, shorter sleep duration, frequent napping, and poorer sleep quality [111, 114-116]. Fibromyalgia is characterized by widespread pain and muscle tenderness lasting at least three months, as determined by palpation [32]. Patients with fibromyalgia commonly complain of light and non-refreshing sleep, fatigue, cognitive difficulties, and psychological distress, including symptoms of depression and anxiety. Interestingly, a serotonin and norepinephrine-reuptake inhibitor has been reported to be successful in these patients [117], as well as melatonin for treating the pain associated with fibromyalgia [118]. Decreased circadian rhythm amplitude has also been reported in a more common condition - depression [119]. Moreover, decreased amplitude in circadian core body temperature changes was reported in delinquent student patients diagnosed with a desynchronized condition [120]. External and internal desynchronizations were two of the three major components of jet lag [121]. Another major component was sleep deprivation [121]. External desynchronization refers to the conflict between the internal clock and external time cues. As an individual is exposed to new, external, time cues, the internal clock adjusts to the new time zone, which may take several days. Internal desynchronization, a loss of phase coupling between phenomena revealing circadian oscillation, takes place during readjustment of internal clocks, and each system adjusts itself differently. Internal desynchronization can also be induced by acute manipulation resulting in phase alteration [122], which is the case in jet lag. As a result of internal and external desynchronization, sleep loss occurs, which decreases the quality and quantity of various activities [29, 33-38]. This ultimately results in decreased serotonergic activity. For the transmeridian traveler, both physical cues such as daylight and darkness, and social cues, such as mealtimes and noise, encourage realignment of the circadian system. In contrast, for the shift worker, physical cues are resolutely opposed to nocturnal alignment, as are most social cues stemming from a day-oriented society. Therefore, circadian realignment of shift workers takes longer than realignment from jet lag [123]. In addition, a forced, extraordinary schedule can also induce desynchronization [124]. As previously mentioned, alcoholics have been reported to display an inversion of melatonin circadian rhythm secretion, which could be responsible for their desynchronization [86]. As described in this review, chronic fatigue syndrome, orthostatic dysregulation, burnout, vital exhaustion, fibromyalgia, depression, jet lag, and shift work are likely to be a result of desynchronization and decreased serotonergic, as well as decreased melatonergic activity.

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Although each of these disease conditions possesses its own specific origin, major symptoms, and course, there might be a similar pathophysiology between these disease conditions and the condition that many Japanese preschoolers/students are currently suffering from.

5. Asynchronization More than half of the preschoolers/students in Japan complained of daytime sleepiness, while about one quarter of junior high school students in Japan suffer from insomnia. Moreover, as shown in Table 2, frequent complaints of students in Japan were compatible with associated features of behavioral-induced sleep-deficient syndrome [32], most likely due to inadequate sleep hygiene. If this were the case, these symptoms should be ameliorated following adequate sleep (by exclusion of dotted lines in Figure 1). However, such therapeutic approaches often fail. The students cannot fall asleep, despite sleep loss, and this is partly due to inadequate sleep hygiene consistent with excessive media exposure and lowlevel physical activity. Indeed, delayed wake-up times and bedtimes could be symptoms of a delayed sleep phase form of circadian rhythm sleep disorder. Although this article does not discuss this disorder in detail, it should be noted that there is confusion between this disorder and the biological- and lifestyle-related sleep phase delays that are especially common during adolescence [125]. It is possible that certain factors other than simple sleep loss and inadequate sleep hygiene are involved in many of the young people in Japan that exhibit delayed wake-up times, delayed bedtimes, and an irregular lifestyle. It has been assumed that decreased activity in the melatonergic and serotonergic systems, as well as desynchronization, are candidates for explaining pathophysiology.

5.1. Presumable Pathophysiology In 1976, Aschoff and Wever described [126] that activity rhythm (wakefulness and sleep) and other rhythmic variables (e.g., temperature) often have similar circadian periods of approximately 25 hours. However, on occasions, the activity period may become substantially longer (e.g., 33 hours), while other rhythms continue with a period of about 25 hours. Such a state is termed internal desynchronization. Thus circadian desynchronization is used to indicate a loss of phase coupling between certain phenomena, which lead to circadian oscillation. It should be noted that this term arose from basic studies, and was not originally a clinical-related term. Individuals with delayed wake-up times, delayed bedtimes, and an irregular lifestyle may also exhibit a loss of phase coupling between phenomena, circadian oscillation, and decreased amplitudes of other phenomena, although no concrete evidence has obtained to date. Desynchronization alone is not adequate to describe the clinical conditions that many young people in Japan are suffering from. In addition, many of these individuals likely display reduced serotonergic and/or melatonergic activity. I wonder a novel, clinical entity is required to improve understanding of the pathophysiology of these disturbances [3, 4].


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In 1970, Winfree [5] reported that a specific, dim, blue-light, pulse stimulus, with a unique stimulus time and duration, resulted in unusual broadening of the daily eclosion peaks of the fruitfly, Drosophila pseudoobscura, even to the extreme of obscuring circadian rhythm. This phenomenon was termed ―circadian singularity behavior‖, and has been described in a range of organisms, such as algae, plants, and mammals [127-132]. In humans, Jewett et al. [129] reported circadian rhythms of rectal temperature and plasma cortisol were abolished by a single, long duration, bright-light pulse administered during one or two successive circadian cycles. Huang et al. [133] demonstrated that temperature increases and light pulses can trigger singularity behavior in Neurospora circadian clock gene frequency. In addition, Ukai et al. [59] reported that a critical light pulse (3-hour light pulses delivered at a specific circadian time (CT) ~17 (near subjective midnight (=CT18))) drives cellular clocks to singularity behavior in mammals. Interestingly, this phenomenon is transient [133], although removal of the stimulus is needed. Table 3. Asynchronization. Essence Presumable causes

Symptoms

Therapeutic approaches

Prognosis

Disturbance of various aspects (e.g., cycle, amplitude, phase, and interrelationship) of biological rhythms that indicate circadian oscillation. Light exposure during the night. Lack of light exposure in the morning. Decreased physical activities. Disturbance of the biological clock and/or the serotonergic system. Disturbances related to the Autonomic Nervous System sleepiness, insomnia, disturbance of hormonal excretion, gastrointestinal problems, sympathetic nervous system predominance Somatic Disturbances tiredness, fatigue, neck and/or back stiffness, headache, persistent yawn, desire for sleep, wish to lie down, inactivity, lumbago Disturbances related to Higher Brain Function disorientation, loss of sociality, loss of will or motivation, impaired alertness and performance, difficulties to remember, difficulties to concentrate Neurological Disturbances attention deficit, aggression, impulsiveness, hyperactivity, irritated, hypersensitive Psychiatric Disturbances Symptoms observed in depressive disorders, personality disorders, and anxiety disorders Morning light, an avoidance of nocturnal light exposure, conventional approaches - light therapy, medications (hypnotics, antidepressants, melatonin, vitamin B12), physical activation, chronotherapy and alternative ones - Kampo, pulse therapy, direct contact, control of the autonomic nervous system, respiration (qigong, tanden breathing), chewing, crawling Early phase: Disturbances are functional and can be relatively easily resolved, e.g., through establishment of a regular sleep-wake cycle Chronic phase: Without adequate intervention, disturbances can gradually worsen, involving loss of serotonergic activity, which is difficult to resolve.

Taken together with this basic entity - singularity -, I designed a novel clinical concept asynchronizatiopn-. Asynchronization is the result of disturbed aspects (e.g., cycle, amplitude, phase, and interrelationship) of biological rhythms that normally exhibit circadian oscillation, which presumably involves decreased serotonergic and/or melatonergic activity.

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The major trigger of asynchronization is hypothesized to be a combination of light exposure during nighttime, which reduces melatonin secretion, and a lack of morning light exposure, which decreases serotonergic activity. Thus asynchronization symptoms (Table 3) include disturbances of the autonomic nervous system (sleepiness, insomnia, disturbed hormonal excretion, gastrointestinal problems, sympathetic nervous system predominance, etc.), as well as higher brain functions (disorientation, loss of sociability, loss of will or motivation, impaired alertness and performance, etc.). Neurological (attention deficits, aggression, impulsiveness, hyperactivity, etc.), psychiatric (depressive disorders, personality disorders, anxiety disorders, etc.) and somatic (tiredness, fatigue, neck and/or back stiffness, headache, etc.) disturbances are also putative symptoms of asynchronization. Complaints introduced in this article (Table 2) could be symptoms of asynchronization. To detect the disturbance of biological rhythms, actigraphic recordings [134], as well as diurnal measurements of body temperature, corticosteroids, and melatonin are useful. Takimoto et al. monitored human clock genes in whole blood cells to evaluate internal synchronization [135]. The early phase of asynchronization is hypothesized to be functional and can be relatively easily resolved by establishing a regular sleep-wakefulness cycle. However, without adequate intervention, disturbances can gradually worsen, resulting in decreased serotonergic and/or melatonergic activity, which can be difficult to resolve. In Figure 1, red lines, especially the broad ones, are hypothesized to be involved in asynchronization. A portion of patients with chronic fatigue syndrome, orthostatic dysregulation, burnout, vital exhaustion, fibromyalgia, and depression are thought to suffer from asynchronization.

5.2. Potential Therapeutic Approaches 5.2.1. Basic Principles For synchronization of the biological clock to a 24-hour cycle, exposure to morning light and avoidance of nocturnal light are essential. Therefore, lack of these two behaviors will result in asynchronization. Moreover, light-induced adrenal gene expression and corticosterone release have been demonstrated [136]. Under normal conditions, steroid secretion is greatest in the morning. In addition to light and social factors [124], food [137] is known to affect the circadian clock. The dorsomedial hypothalamic nucleus was determined to be a putative foodentrainable circadian pacemaker in mice, and oscillation of this pacemaker was found to persist for at least 2 days, even when mice received no food during the expected feeding period following establishment of food-entrained behavioral rhythms [62]. Regular mealtimes, as well as participation in social activities, are likely to prevent asynchronization. A daytime nap is known to result in favorable performance [138]. However, eveningtype adolescents were reported to nap more frequently during school days than other chronotypes [44], although improved school performance after an afternoon 15-minute-nap was reported in a Japanese high school [139]. Further studies are needed to determine whether napping affects asynchronization.


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Nevertheless, to prevent asynchronization, the social promotion of favorable sleep hygiene is important [140, 141]. 5.2.2. Conventional Approaches

5.2.2.1. Light therapy

Light therapy has been shown to effectively treat patients with depression [142, 143] and seasonal affective disorder [144]. It has been recommended that patients with seasonal affective disorder initially receive morning light shortly upon awakening [68]. In patients with winter depression (seasonal affective disorder), one week of bright, morning light (2500 lux) treatment produced significantly greater remission rates (53%) than evening (38%) or midday (32%) treatment [145]. A clinical trial [68] that administered 5 weeks of bright, morning light therapy (10000 lux, 60 minutes) to chronic (≥ 2 years) major depression outpatients resulted in a remission rate of 50%, while the control group showed only minor improvements. Light therapy also reduced depression scores in patients with fibromyalgia [146]. The effects of light therapy on chronic fatigue syndrome have, however, been controversial [147, 148]. As described previously, exposure to at least 3 hours daylight per day was suggested to produce favorable effects on burnout patients [109], and light therapy was used to treat patients with shift work and jet lag disorders [149]. However, in animals and humans, short nights attenuate both evening light-induced circadian phase delays and morning light-induced circadian phase advances [150, 151]. In addition, circadian clocks advance phases by inducing earlier waking time and bedtime, while circadian clocks delay phases by pushing waking and bedtime later [152, 153]. Although these light effects should be clues for treating patients with early phase asynchronization, attenuation of light-induced circadian phase delays during short nights results in decreased light therapy effects on individuals suffering from jet lag and night workers engaged in a nocturnal life with a long nocturnal photoperiod (= short nights) [151].

5.2.2.2. Medications 5.2.2.2.1. Hypnotics

There is insufficient evidence to assess the safety and efficacy of hypnotic medication for delayed sleep phase disorder [154]. Data encompassing the safety and efficacy of hypnotics with other types of circadian rhythm sleep disorders are scant [154]. In addition, the effects of hypnotics on shift work disorder patients are inconsistent [149]. However, the use of hypnotics for jet lag-induced insomnia is a rational treatment and is consistent with standard recommendations for treating short-term insomnia. The efficacy of benzodiazepines on patients with fibromyalgia, together with non-steroidal anti-inflammatory drugs, has been inferior to amitriptyline [155]. In addition, ultra-short- or medium-acting hypnotics have been used in children with chronic fatigue syndrome [148], and are widely used to treat insomnia in depression patients [156]. It is likely that appropriate use of hypnotics should be taken into consideration for the management of asynchronization.

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5.2.2.2.2. Antidepressants The efficacy of antidepressants has been reported in depression, as well as chronic fatigue syndrome [103] and fibromyalgia [117, 155]. These agents could also be promising for treating depressive tendencies in asynchronization patients. However, because asynchronization are likely to be involving serotonin depletion, the use of selective serotonin reuptake inhibitors or serotonin and norepinephrine-reuptake inhibitors as the first agent of choice for treating asynchronization needs further studies.

5.2.2.2.3. Melatonin and its Agonists

The effects of melatonin in patients with delayed sleep phase disorder and free-running disorder have been established [154]. Afternoon or evening melatonin administration would be expected to shift rhythms earlier, thereby correcting pathological phase delay. Appropriately timed melatonin administration has been shown to entrain totally blind individuals with free-running disorder. Melatonin or melatonin agonists might benefit daytime sleep in night workers through their hypnotic, as well as phase-shifting, effects [149]. Melatonin, administered at the appropriate time, can reduce symptoms of jet lag and improve sleep following travel across multiple time zones [149]. Melatonin is also effective treatment for some patients with chronic fatigue syndrome [104], as well as pain associated with fibromyalgia [118]. Interestingly, agomelatine, a compound with melatonin receptor agonist properties, has been reported to exert an antidepressant effect superior to selective serotonin reuptake inhibitors and selective serotonin and noradrenaline reuptake inhibitors [157]. However, because melatonin is not regulated by the U.S. FDA, there are a variety of preparations, and its usefulness has been limited [158]. In a 4-year-old boy diagnosed with Smith-Magenis syndrome, Carpizo et al. reported treatment with a beta (1)-adrenergic antagonist in the morning (to suppress diurnal melatonin secretion) and melatonin in the evening (to generate nocturnal melatonin peak), which resulted in improved sleep quality, as evaluated by polysomnographic methods [159]. This approach could be beneficial for asynchronization patients that exhibit altered diurnal melatonin secretion.

5.2.2.2.4. Vitamin B12

Vitamin B12 has been shown to enhance light pulse-induced phase shifts and thus augment entrainability of the circadian clock to light in rats [160]. In fact, high-dose vitamin B12 (3 g/day) proved to be effective in childhood chronic fatigue syndrome patients with free-running disorder [148]. An association between low vitamin B12 status and depression in elderly individuals has been suggested [161]. Because vitamin B12 deficiency causes decreased remethylation of homocysteine and is, therefore, most likely contributing to increased homocysteine levels, Regland et al. [162] measured homocysteine and vitamin B12 levels in cerebrospinal fluid of patients that fulfilled criteria for both fibromyalgia and chronic fatigue syndrome. They measured increased homocysteine concentrations, as well as a correlation between vitamin B12 levels and clinical variables. In other words, decreased vitamin B12 levels resulted in more severe clinical conditions. However, a recent review suggested that vitamin B12 was not an effective treatment for delayed sleep phase disorder


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[154]. Also, vitamin B12 was not recommended for treating jet lag or shift work disorders [149].

5.2.2.3. Physical activity

Physical activity is associated with an antidepressant effect in clinical depression [163]. Exercise leads to improved physical and mental health in fibromyalgia patients [164] and was shown to re-time circadian rhythm in individuals suffering from jet lag or shift work [165]. In patients with chronic fatigue syndrome, graded exercise therapy was shown to be valuable in randomized controlled trials [166]. Exercise induces these effects not only through the serotonergic systems, which is activated by rhythmic movements, such as gait, chewing, and respiration [90], but also through other molecules, such as brain-derived neurotrophic factor [91]. Physical activity or exercise could be potentially used to relieve asynchronization. Each morning in Japan, we have a 10-minute radio program of gymnastic exercises with piano accompaniment. This set of exercises is very familiar to almost all people in Japan, especially those older than twenty years of age. The efficacy of these exercises should be re-evaluated for physical and mental health.

5.2.2.4. Chronotherapy

To resynchronize the circadian clock with the desired 24-hour cycle, chronotherapy has been used in patients with circadian rhythm sleep disorder. This approach assumes that the circadian clock cycle of the majority of people is longer than 24 hours. In a case of delayed sleep phase, a successive delay of sleep onset by 3 hours each day, over a 5-6-day period, is required to achieve desired sleep onset [167]. This shift should be rigidly adhered to establish a set sleep-wake schedule and proper sleep hygiene practice. However, the potential confounding effects of light exposure at inappropriate circadian times might limit the effectiveness and practicality of this approach [168]. 5.2.3. Alternative Approaches The following are potential approaches to manage asynchronization, although the diagnostic standards and methodology, in terms of applicability, remain to be determined.

5.2.3.1. Kampo

Kampo medicine is a traditional Japanese herbal medicine that originated from traditional Chinese medicine. Examples for prescription are listed in Table 4 [169-171]. In addition to these prescriptions, Kanbaku-taisou-to (72) (the value in parentheses is the standardized number for prescription in Japan) and Yoku-kan-san (54) is the author‘s preference for patients with early-phase asynchronization and presumed elevated sympathetic nerve activity. I also use Dai-saiko-to (8) to treat insomnia due to hypertension or tinnitus. In patients with depression [172] and fibromyalgia [173], Kampo or traditional Chinese medicine have been commonly used.

Table 4. Presumable Kampo prescriptions for asynchronization.

fatigue syndrome

chronic fatigue syndrome

child patients with school refusal

Rokumi-gan (88), Hochu-ekki-to (41), and ShoSaiko-to (9) [169] Ninjin-yoei-to (108) [169] [170]

weakness in the lower extremities

systemic hypofunction and/or coldness

glow ing (or heat sensation in the palm or foot)

Hachimiziou-gan (7) [171]

Sinbu-to (30) or Ougiken-chu-to (98) and Ninzin-to (32) [171]

Rokumigan (87) [171]

Rokumigun (87) [171]

apathy,

Seishoekki-to (136) [171]

Number in the parenthesis is the standardized number for prescription in Japan.

aggressiveness or impulsiveness,

Saiko-karyukotuborei-to (12) [171]

depressive tendency

Kamishouyousan (24) [171]

anemia

GI disturbance

fatigue after acute infection

Zyuzentaiho-to (48) and/or Ninjin-yoeito (108) [171] Zyuzentaiho-to (48) and/or Ninjin-yoeito (108) [171]

or insomnia Kihi-to (65) or fatigue Hochu-ekkito (41) [171] or insomnia Kihi-to (65) Hochu-ekkito (41) [171]

Saiko-keishi-to (10) [171]


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5.2.3.2. Rhythmic Movements

As described in the former section, exercise could produce favorable effects on depression [163], fibromyalgia [164] jet lag, shift work [165], and chronic fatigue syndrome [166], presumably not only through the activation of serotonergic system [90] but also by the induction of other molecules [91]. Among rhythmic movements which activate serotonergic system [90], gait must be a part of exercise. In this section, rhythmic movements other than gait –respiration and chewing- will be introduced. Qigong is an ancient, oriental, mindful exercise [174], also described as a mind-body, integrative exercise or traditional Chinese medicine intervention that is used to prevent and cure ailments, as well as to improve health and energy levels [175]. Qigong (or ch'i kung) refers to a wide variety of traditional ―cultivation‖ practices that involve movement and/or regulated breathing [176]. Qigong has recently been designated as an alternative therapy to help meet the increasing demand of non-pharmacologic modalities for achieving bio-psychosocial health in patients suffering from anxiety [174] or pain [177]. Although the metaanalyses to date have been based on low-quality studies and small numbers of hypertensive participants, Qigong and Zen meditation have been shown to significantly reduce blood pressure [178]. Tanden breathing involves slow breathing (range of 0.05-0.15 Hz) into the lower abdomen, and was found to affect cardiac variability, which is controlled by the autonomic nervous system [179]. Although rhythmic respiration has been reported to activate serotonergic activity [90], Arita and Takahashi [180] preliminarily determined that tanden respiration also elevates serotonergic activity. Chewing has also been reported to activate the serotonergic system [90, 181]. This behavior could be used to manage asynchronization by deliberately activating serotonergic activity. Locomotion is a sort of rhythmic movements. Failed locomotion (crawling) during infancy (lack of interlimb coordination between upper and lower extremities) has been reported to be due to hypofunctioning serotonergic and/or noradrenergic neurons [182]. This results in postural atonia by disfacilitating postural augmentation pathways and/or disinhibiting the postural suppression pathway and preventing locomotion [183]. Forcedcrawl training has been described as relieving symptoms resulting from low serotonergic activity [184].

5.2.3.3. Direct Contact

An older generation Japanese pediatrician [185] was quoted to say, ―Holding a baby in the arms (―dakko‖ in Japanese) is the most effective tranquilizer for a baby.‖ Although therapeutic touch is now receiving attention as a method to manage anxiety disorders, including depression [186], dakko is a typical and classic daily behavior that involves direct contact between caretakers and youngsters. With the rapid spread of various types of media, including mobile phones, one concern is that direct contact between people is rapidly diminishing. In fact, concurrent television exposure is reported to correlate with fewer social skills [187]. In addition, hugging and intimate, face-to-face conversations are expected to be promising in the effort to manage and/or prevent asynchronization.

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5.2.3.4. Control of the Autonomic Nervous System To provide adequate cues for the circadian clock, morning activation of the sympathetic nervous system and evening stimulation of the parasympathetic system might be helpful to manage asynchronization. In Japan, some pediatricians recommend scrubbing the skin with a dry towel or cold water in the morning to train the autonomic nervous system in patients with orthostatic dysregulation [188]. However, this approach has not been covered in the recently published guideline [189].

5.2.3.5. Pulse Light In addition to the removal of stimuli that induce singularity effects, adequate stimuli (light pulse at CT 9-15 (transition from subjective day to night) [59]) could also reverse singularity. Further studies are needed to identify adequate stimuli for reversing circadian singularity behavior in asynchronization.

6. Conclusion Many young people in Japan suffer from daytime sleepiness and nocturnal insomnia, and are persistently tired and inactive. This review focused on the association between nocturnal lifestyle and biological clock disorders, as well as the melatonergic and serotonergic systems. However, involvement of dopamine [190] and opioid peptides [101] are also possible. A novel clinical concept – asynchronization - has been proposed, and a similar basic concept singularity - was also introduced. In this review, studies that recommended morning-type behavior to reduce behavioral/emotional problems were introduced [28, 47, 52]. Ayurveda, an ancient system of health care that is native to the Indian subcontinent, suggests that, in addition to good conduct, thought, diet, interpersonal dealings, physical activity, early rising, and early bedtimes are good for a healthy life [191]. Ekken Haibara wrote in his essay, Youzyoukun (1713), that one should awake early in the morning and avoid late bedtime to live a healthy life [192]. Byoukesuchi (Hirano, 1832), a book describing medical practices for the home, stated that one should go to bed early at night and awake before dawn for a healthy life [193]. Thus both traditional wisdoms and recent researches recommend morning-type behavior, and this article reviewed the possible background mechanisms for the favorable effects on physical and mental health. Senior high school students in Korea are reported to go to bed (0:54 on school nights) [194] later than those in Japan (0:06 [11] or 23:50 [12]). Although Chinese senior high school students in Hong Kong went to bed earlier (23:24) than those in Japan, it was concluded that they did not receive sufficient sleep [195]. Many young people not only in Japan but also in the other countries might be potential patients with asynchronization. In addition, some NEET (Not in Employment, Education, or Training) [196] individuals might also suffer from asynchronization. Now we are living in the society with 24-hour activity. I am afraid that this type of society might produce unfavorable effects on the SCN. A quarter of the world‘s population is subjected to a 1 hour time change twice a year (daylight saving time; DST) [197]. DST is


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now known to disturb normal seasonality seen in sleep timing assessed by mid-sleep times [197]. In addition, at the beginning of DST (=spring), the rates of traffic accidents [198] and the attacks of myocardial infarction [199] are reported to increase. I wonder we should be more careful on the property of the biological clock. I hope a novel concept of asynchronization to contribute to noticing the significance of the SCN, and to helping patients suffering from circadian disruptions.

Acknowledgment This study was supported by a grant from the Ministry of Health, Labour, and Welfare of Japan (19231001).

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Chapter V

Aggression in Older Adult Populations Sarah E. Parsons1, Luis F. Ramirez1,2, Philipp Dines1,2 Scott Magnuson3 and Martha Sajatovic1,2 University Hospitals Case Medical Center1 Case Western Reserve University School of Medicine2 Cleveland State University3, USA

Abstract In 2005, a report from the United Nations Populations Division noted that the number of individuals aged 60 years and older is expected to nearly triple, increasing from 672 million in 2005 to almost 1.9 billion by 2050. Currently the elderly population in developed countries has surpassed the number of individuals under the age of 14 years, and by the year 2050 it is anticipated that there will be two elderly persons for every child. Population aging is thus anticipated to precipitate a situation in the United States where health care needs for older-adult populations may exceed care access and availability. This may be particularly pressing in the case of mental health conditions accompanied by behavior that put individuals at physical risk. It has been reported that 27% of all workplace violence occurs in nursing homes. Aggressive behavior by older individuals with mental disorders incurs substantial humanitarian and financial burden on patients, families and society at large. This review will address aggression in elderly populations with general medical conditions that include delirium, toxic states and drug-drug interactions as well as in populations with dementing illness, mood and anxiety disorders and psychotic disorders. A pragmatic approach optimizing safety and quality of life for individuals, families and caregivers is stressed. Lastly, recommendations for future research in late-life aggressive behavior are provided.

Keywords: Elderly, aggression, delirium, dementia

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I. Introduction and Background Aggressive behavior amongst the elderly population is a significant problem in the community and in institutions. The relative paucity of information on the subject and the projected aging trends globally, particularly in developed countries such as the United States, are indicative that there is increasing need for additional research. In 2005, a report from the United Nations Populations Division noted that the number of individuals world-wide aged 60 years and older is expected to nearly triple, increasing from 672 million in 2005 to almost 1.9 billion by 2050 [1]. Currently the elderly population in developed countries has surpassed the number of individuals under the age of 14 years, and by the year 2050 it is anticipated that there will be two elderly persons for every child [1]. According to the U.S. Census Bureau, the percentages of people aged 60 and over are projected to increase from 16.8% of the U.S. population in 2005 to 25.1% in 2030 [3]. Prevalence of aggressive behavior in elderly persons differs drastically amongst studies. In institutional settings, Zimmer reported aggressive behavior occurring in 8.3% of patients [4], whereas Winger reported 91% [5]. Prevalence rates for community settings differ from 1% [6] to 47% [7]. This wide range of prevalence can be attributed to researchers‘ diverse definitions of aggressive behaviors as well as sampling methods and sample composition. The definitions of aggressive behavior amongst studies have included tantrum-like behaviors, physical aggression, self-injurious behavior, property destruction, and verbal abusiveness. The divergence of prevalence reports can also be attributed to the use of differing methods, including standardized scales to evaluate aggressive behaviors. Common standardized measures of aggression include, but are not limited to, the Cohen-Mansfield Agitation Inventory (CMAI) [8], the Rating Scale for Aggressive Behavior in the Elderly (RAGE) [9], and the Ryden Aggression Scale [7]. Additionally, researchers derive their data from varying sources including incident reports [10], caregiver report [11], patient interview [12], or review of the medical record [13]. Aggressive behavior and agitation are a non-specific group of behaviors that can occur in the context of many different clinical conditions. Phenomenologically there are several behavioral syndromes which may overlap with aggression or agitation, including restlessness, hyperactivity, fidgetiness and akathisia as well as vegetative symptoms such as changes in sleep and sleep cycles. The functional nueroanatomy and the neurochemical basis of agitation have not been clearly elucidated. A model proposed by Sachdev and Kruk [14] posits agitation as a disturbance in multiple brain circuits involving the limbic system, the striatum, the globus pallidus, and disinhibition in neurons of the thalamocortical tracts and brain stem. Because of the involvement of multiple and differing parts of the brain, various neurotransmitters may be at least partially responsible for some of the behaviors observed in agitated states. For example, in the case of agitated depression there is an increase in serotonergic responsivity with a decrease in GABA [15]. In mania and acute psychosis there is an increase in dopamine, in dementia there is a decrease in GABA, in panic disorder and GAD there is an increase in norepinephrine and a decrease in GABA with a decrease in dopamine and an increase in norepinephrine in the case of akathisia [15].

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The impact of aggressive behaviors can be very detrimental to the elderly aggressor, as well as caregivers. Studies have indicated that as much as 20% of caregivers for people with dementia report physical violence as a serious problem [16]. These behaviors may result in physical danger to those in close proximity to the aggressor, to the caregiver, or to the aggressor themselves. In addition, those who commit these behaviors often elicit reactions from others that exacerbate the behavior. According to Patel and Hope, aggressive behaviors cause the greatest impact on the elderly and their caregivers [17]. It has been found that caregivers who have been physically abused by their care receivers are more likely to act abusively in return [18]. In addition, aggressive behavior is one of the most frequent causes for institutionalization among the elderly and increases the requirement for drug therapy and hospitalization [19]. The health care professional facing a clinical situation in which aggressive behavior is present is confronted with two tasks: assess the clinical situation and treat the individual/manage the environment. The detail involved in the evaluation is determined by the circumstances surrounding the patient and the urgency demanded by the characteristics of the symptoms. Many times the professional facing these issues has to act quickly without all the information available in order to guarantee the safety of the patient or the people surrounding the patient. The first step is to determine if the patient is suffering a delirium. In general terms delirium can be defined as a transient, potentially catastrophic or life threatening syndrome caused by severe and acute physiological changes in the brain. Delirium is commonly seen in medical conditions or toxic states due to medications or drug interactions. Elderly individuals with chronic impairment in cognition and behavior caused by neurological damage or degeneration may have dementia. Both delirious and demented patients may exhibit a variety of psychiatric and/or neurological signs and symptoms with clear manifestations of irritability, agitation, aggression, fear, anger, suspiciousness, cognitive impairment, sleep-wake cycle disruption and extra sensibility to stimuli. Elderly individuals who exhibit aggression and behavior symptoms may also suffer from mood, anxiety or psychotic disorders as will be discussed in this chapter. Appropriate assessment and treatment of these psychiatric conditions will reduce /resolve aggressive behavior and is generally associated with improvement in symptoms and functional status. Therapeutic approaches aimed to optimize safety and enhance quality of life are needed to address and decrease aggressive behaviors irrespective of underlying cause. It is important for caretakers to uphold the dignity of the care receivers to the maximum level possible and respect their rights of privacy. In summary, population aging is anticipated to precipitate a situation in the United States where health care needs for older-adult populations may exceed care access and availability. This may be particularly pressing in the case of mental health conditions accompanied by behavior that puts individuals at physical risk. Aggressive behavior by older individuals with mental disorders incurs substantial humanitarian and financial burden on patients, families and society at large.

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This review will address aggression in elderly populations with general medical conditions that include delirium, toxic states and drug-drug interactions as well as dementing illness, mood and anxiety disorders and psychotic disorders. A pragmatic approach with optimizing safety and quality of life for individuals, families and caregivers is stressed. Lastly, recommendations for future research in late-life aggressive behavior are provided.

II. Aggression in Elderly Patients with Medical Conditions Elderly patients are more likely than younger patients to have a number of health problems [20]. These medical conditions often lead to an increased number of prescriptions, increased hospitalizations, and an increased number of prescribing medical specialists. The ageing brain has less ―cerebral reserve‖ and is more sensitive to minor and major alterations in physiology. Elderly patients are likely to react differently to a vast array of medical conditions, from minor infections to major surgery, compared to their younger counterparts. The result of multiple medical conditions, medications, and an alteration in physiology is often delirium; aggressive behavior can be a manifestation of this delirium. Understanding delirium and its management is essential to a positive outcome for an aggressive elderly patient with medical conditions.

A. Delirium and Toxic States Delirium is an acute disturbance in consciousness and cognition that is causally linked to physiologic changes and is especially common in older populations. In adults, as age increases, vulnerability for delirium increases as well, with the highest incidence in those aged 60 years and older [21]. Additional factors that increase the risk for delirium are cognitive disorders, recent surgery, specific medical conditions, and certain medications. Delirium is typically transient and reversible, thus the etiology needs to be thoroughly investigated as quickly as possible once a diagnosis is reached. The rate of delirium in the general population is difficult to assess; most studies on prevalence of delirium focus on specific hospital referrals or specialized hospitalized populations. Across these studies, delirium is evident in 5-44% of patients aged 65 years and older on medical/surgical wards or in long term care facilities [22-25]. Specialized populations with higher rates of delirium include those patients with recent coronary artery bypass grafting (CABG), recent hip replacement, advanced cancer, or on mechanical ventilation in the intensive care unit [26-28]. Delirium is important to identify and treat, as it is associated with mortality in 25% of patients [29] and also contributes to longer hospitalizations and increased cost of hospitalization [30, 31]. Delirium is characterized by impairment of consciousness and cognition, developing over a short period of time, and explained by a change in physiologic condition. The disturbance in consciousness can be a decrease in ability to focus and/or difficulty sustaining or shifting attention. The disturbance in cognition can manifest as disorientation, perceptual


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changes, alteration in memory function, or changes in language ability. This cognitive impairment must not be better explained by preexisting, established, or evolving dementia. These changes in consciousness and cognition must have developed over a short period of time (hours to days) and tend to fluctuate over the course of a day. A prodrome is frequently described in the hours to days leading up to florid delirium, characterized by restlessness, irritability, sleep disturbance, and distractibility; a review of the patient record/caregiver report may reveal subtle symptoms building over the course of a few days. A diagnosis of delirium is reached if the changes in consciousness and cognition are noted in response to a physiological change, such as medical condition, administered medication, or illegal substance use or withdrawal. When diagnosing delirium, an etiology needs to be identified (e.g. delirium due to hepatic encephalopathy). Delirium due to multiple etiologies can be diagnosed if several factors seem to be contributing; if no clear etiology is evident, a diagnosis of delirium not otherwise specified is warranted [32]. Delirium can be described as hypoactive or hyperactive, based on psychomotor behavior, and is frequently under recognized and under diagnosed [33]. Delirious patients with relative alertness, though continued clouding of consciousness (hyperactive delirium) are more likely to experience hallucinations, delusions, and illusions, as well as to exhibit agitation [34]. Hypoactive delirium is frequently misdiagnosed as depression, whereas hyperactive delirium is frequently misdiagnosed as new onset psychosis or behavioral problems. Delirium is a reversible cause of mental status changes, thus needs to be explored when evaluating aggression in an elderly patient with medical conditions. When delirium is superimposed on preexisting dementia, patients demonstrate more aggressivity, agitation, delusions, anxiety, and hallucinations as compared to their non-demented counterparts [35]. Although dementia can present with behavioral problems, any abrupt onset of change in aggression or agitation could be delirium and warrants investigation. Diagnosing delirium involves recognizing clinical features, as well as a thorough mental status exam and complete physical and neurological exams. The potential contributing medical factors need to be explored through laboratory tests and brain imaging. Electroencephalogram (EEG) typically shows diffuse slowing, though this is a nonspecific finding and most useful when a previous EEG is available (or repeating EEG after delirium resolves). A mental status exam needs to include attention and concentration tasks, evaluation of short and long term memory, visuoconstructual ability, abstraction, and language tasks including writing and naming. Once delirium has been diagnosed, prompt identification and prioritization of potential contributing etiologies is essential; etiology can be singular (less than 50% of cases) or multifactorial, averaging 2-6 contributing factors per patient [22]. Etiologic categories of delirium include: autoimmune, cardiac, cerebrovascular, drug intoxication, drug withdrawal, hypoxic, infection, metabolic disturbance, neoplastic disease, and traumatic [36]. Medications, especially opiates, benzodiazepines, and drugs with anticholinergic properties, can precipitate delirium. Table 1 illustrates medications commonly associated with delirium.


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Table 1. Medications Commonly Associated with Delirium. Analgesics Antibiotics

opiates (esp. meperidine), salicylates acyclovir, ganciclovir, aminoglycosides, amphotericin B, cephalosporins, interferon, isoniazid, metronidazole, rifampin, sulfonamides, vancomycin

Anticholinergics

antihistamines, antispasmodics, atropine, benztropine, phenothiazines, tricyclic antidepressants

Anticonvulsants

Phenobarbital, phenytoin, valproic acid

Anti-inflammatories

corticosteroids, NSAIDs

Antineoplastic Drugs

asparaginase, 5-fluorouracil, methotrexate, procarbazine, tamoxifen, vinblastine, vincristine

Antiparkinsonian Drugs

amantadine, bromocriptine, levodopa

Cardiac Drugs

beta-blockers, captopril, clonidine, digitalis, lidocaine, methyldopa, procainamide, quinidine, tocainide

Sedative-hypnotics

barbiturates, benzodiazepines

Sympathomimetics

amphetamines, cocaine, ephedrine, phenylephrine, theophylline

Others

baclofen, disulfiram, ergotamines, lithium, propylthiouracil

Compiled from: 1.) American Psychiatric Association. Practice guideline for the treatment of patients with delirium. American Journal of Psychiatry, 1999 156 (supplement), 1-20. 2.) Marcantonio, ER; Juarez, G; Goldman, L. The relationship of postoperative delirium with psychoactive medications. JAMA, 1994 272, 1518-1522. 3.) Trzepacz, PT; Meagher, DJ. The American Psychiatric Publishing Textbook of Psychosomatic Medicine (J.L. Levenson, Ed.). Washington DC: American Psychiatric Publishing Inc; 2005.

Management of Delirium The first step in managing delirium is to treat the underlying medical cause of the symptoms. Depending on the cause and medical condition of the patient, resolution of delirium could take some time; clinical duration is usually 4 days to two months, with an average of 10-12 days [37]. Psychopharmacologic treatment of symptoms may be required as delirium resolves; aggression and agitation of delirious patients are some of the first symptoms requiring treatment due to the need for safety on a medical/surgical unit or in a long term care facility. Antipsychotic medications have been shown to be effective in treating several aspects of delirium, including aggression and agitation. Haloperidol is the most frequently used, as it is a potent antipsychotic with very little anticholinergic or hypotensive side effects; it is also available in intravenous form, allowing for easier administration. Other antipsychotic medications have been shown to be effective in the treatment of delirium: chlorpromazine, droperidol, olanzapine, risperidone, and quetiapine [38]. Short-acting benzodiazepines, preferably lorazepam may be helpful if delirium is related to alcohol withdrawal; longer acting benzodiazepines should be avoided, as they do not seem to improve delirium and can paradoxically worsen aggression and agitation [39]. Other nonpharmacologic treatment can be employed, including redirection and minimizing disruptions to the environment [40]. If the delirious patient is aggressive or agitated, providing a room


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near the nursing station and a sitter may be necessary; restraints may be used if all other attempts to keep the patient and others safe have failed. The severity of the delirium typically correlates with the length of time for the symptoms to resolve; thus, early identification and treatment of the underlying cause should aid in quicker resolution of the delirium and less need for treatment of symptoms.

B. Drug-Drug Interactions One of the most common contributing factors to delirium is drug-drug interactions with associated adverse medication effects. Older patients frequently have multiple medical problems and multiple providers; they are often taking many medications and all providers may not have access to an accurate medication record. Drug-drug interactions are preventable causes of adverse drug events, increased morbidity and mortality, and higher health costs [41, 42]. Studies on the prevalence of drug-drug interactions are scarce, listing the prevalence as 1 to 66% across all age groups [43, 44]. One study focused on drug-drug interactions among the elderly and reported that the average number of prescribed medications per patient was 7.0; each patient had an average of 0.83 drug-drug interactions, with 10% of those listed as major drug-drug interactions [45]. Kohler and colleagues [46] found that the prevalence of drug-drug interactions in the elderly increases as the number of prescriptions increases. Elderly patients often present to the Emergency Department or to their primary care providers when experiencing a drug-drug interaction [47]. The clinical presentation of medication adverse effect and drug-drug interactions are identical to delirium as described above. If a timeline can be established, relating a change in medication (discontinuation, addition, extra dose, etc.) with mental status changes; the observed delirium can be directly related to a medication effect. Management of delirium caused by a suspected drug-drug interaction should consist of careful examination of recent medication administration and discontinuation, including communication with patient‘s providers, caregivers, and pharmacists if possible. Withdrawing or tapering the offending agent or combination is the first step in management of this cause of delirium. Involving the patient‘s entire medical team is recommended, as even slight adjustments in offending medications could cause other health problems. As with any delirious state, medication or environmental interventions may be employed to manage the patient on a medical/surgical floor or in a long term care facility. As the population ages and more drugs are brought to market, the incidence of drug effects and drug-drug interactions may increase. It is important for providers to coordinate care and for patients to have accurate medication information when presenting to providers in emergent or routine settings. The emergence of electronic prescriptions and medical record may help to decrease the incidence; however knowledge of drug-drug interactions is of key importance, especially in treating the older population. Avoidance of drug-drug interactions is one way to effectively prevent delirium in elderly patients. Aggression in the elderly population is a frequent occurrence on medical and surgical inpatient units, as well as in long term care facilities. In any patient with a sudden onset of mental status changes, including increased aggressive behavior, delirium should be considered high on the list of differential diagnoses. Management of delirium needs to consist

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of investigation of underlying cause and treatment of symptoms, often including aggression. Physicians and nursing staff working with an aggressive elderly patient need to work as a team to recognize delirium, determine the cause, and support the patient as symptoms resolve. Drug-drug interactions are easily preventable causes of delirium; physicians need to be aware of dangers of medications in the elderly and of drug-drug interactions in this population. Delirium is one of the few reversible causes of mental status change and has dire consequences if overlooked.

III. Aggression in Elderly Patients with Dementia Dementia is a brain disorder which manifests with clinical deficits in two or more areas of cognition which are of enough magnitude to significantly affect basic and necessary activities of daily living. Impairments typically present with memory loss and difficulties with executive function, judgment, insight, abstract thinking, visualspatial ability or language dysfunction which occurs in the context of a decline from a previous higher level of functioning [48]. The prevalence of cognitive impairment in large, community-based studies is 2.9% in the age group of 65 to 74, 6.8% in the range from 75 to 84 and 15.8% from age 85 and older [49]. Another study reported the prevalence of Alzheimer‘s dementia in the community aged 65 and older to be 10.3%, and in addition, the prevalence appears to increase by age group, with 3% in the age group 65 to 74, 18.7% in the age group 75 to 84 and 47.2% in the age group 85 and older [49, 50]. Thus, it might be anticipated that as the general population ages, the population of those with dementia will continue to grow. Approximately, 67% of dementias are of the Alzheimer‘s type followed by Vascular dementia which constitutes 15% to 25% of dementia syndromes. Lewy Body dementia comprises about 10% of dementia cases [48]. There are many less common degenerative brain disorders which manifest as dementia which include the parkinsonian dementias, as well as frontal dementias with prefrontal executive dysfunction as an earlier feature. Very rapidly progressing frontal dementias include Pick‘s Disease and Creutzfeldt-Jacob Disease [51]. It has been reported that 60% of individuals with dementia living in the community have manifested behavioral or psychiatric disturbances [52, 53]. In the nursing home population, 80% of elderly with dementia exhibit psychiatric or behavioral findings [54, 55]. Lifetime risk of psychiatric symptom or behavioral disturbances in the elderly with dementia is reported to reach 100% [53]. Agitation and aggression are relatively common in demented populations, particularly in the content of psychotic symptoms. Zimmer [4] reported that physical and verbal agitation was seen in 86% of demented elderly and was largely associated with bathing and toileting care, which can result in frequent injury to care giver staff [56]. In general, the prevalence of agitation in dementia is reported to range from 20% to 80% [57-59]. Physical aggression among community- living individuals with dementia occurs in the order of 11% to 46% [58]. Physical aggression can be manifested in association with mood disturbances, cognitive compromise, psychosis or combinations of these phenomena [60]. In Alzheimer‘s disease, major depression has a prevalence rate of 24% contrasted to 7% in


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similar populations without dementia [61]. Psychosis presents with delusions or hallucinations in Alzheimer‘s disease [62]. It has been reported that the prevalence of delusions in Alzheimer‘s disease ranges from 9% to 63% with a median of 36% [58]. Hallucinations in Alzheimer‘s disease are reported to occur at rates of 4% to 41% with a median of 18% [58, 63]. Progressive dementia generally leads to more severe behavioral disturbance, aggression and progressively worsening clinical outcomes. It is known that psychotic features and agitation are associated with decreased quality of life in the elderly [64, 65], and rapidly deteriorating cognitive functioning is associated with more severe psychosis [66-68]. Overall, it has been reported that behavioral disturbances in dementia decrease survival [58, 69]. In addition to profoundly destructive effects on the individual, psychosis and agitation with dementia cause substantial caregiver distress [70-74]. Caregiver burden and behavioral disturbances increase the likelihood of nursing home placement [75]. Additionally, behavioral disturbances in dementia are associated with increased healthcare costs [76].

Management of Behavioral Symptoms of Dementia Both behavioral and neuropsychopharmacological approaches have been applied to manage behavioral disturbances in dementia in elderly individuals. The Omnibus Budget Reconciliation Act (OBRA) of 1987 mandates behavioral management prior to the use of physical or chemical restraints [77]. Behavioral approaches to aggression in institutional care include differential reinforcement of alternative behaviors [77-79]. Limitations in these approaches among individuals with severe memory and cognitive deficits have prompted other approaches including non-contingent reinforcement to treat behavioral disturbances in elderly using a time- based method of reinforcement [77]. This technique has the advantage of higher reinforcement, ease of implementation and rapid response [77]. Other therapies that may hold promise include cognitive stimulation therapy, music therapy and educational approaches [58]. Studies [80, 81] have demonstrated reduced antipsychotic use and reduced behavioral disturbances [82] with educational approaches [58]. Nevertheless, the evidence for the overall effectiveness of psychosocial approaches has, in general, been equivocal [58, 83, 84]. Although behavioral approaches should be a starting point in the management of aggression in the elderly with dementia, pharmacological interventions are indicated when the response to behavioral disturbances is limited. Medication management, sometimes viewed as a ―chemical restraint‖, is the most common approach to aggression and agitation in nursing homes [85]. A more recent report notes that 40% to 50% of residents of nursing homes are treated with psychotropic medications affecting resident ambulation [86]. Even so, the inappropriate excessive use of antipsychotics, sedative hypnotics and anxiolytic to sedate patients has decreased since the implementation of the Nursing Home Reform Act contained in OBRA 87 [87]. Four principal classes of agents used in the management of behavioral disturbances in the elderly with dementia include the cognitive enhancers, antidepressants, anticonvulsants, and the antipsychotics.

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The use of pharmacological interventions, particularly the antipsychotics, are widely used [58]. In general, antipsychotics—particularly aripiprazole, olanzapine, quetiapine, risperidone and haloperidol, have been found in the literature to have modest effectiveness compared to placebo [58]. At the same time the literature currently indicates a higher incidence of mortality, 1% to 2% over 8 to 12 weeks, associated with treatment with atypical antipsychotics as a class [58]. The risks for cardiovascular adverse events and death after 8 to 12 weeks of antipsychotic treatment are unclear [58]. As a result this has lead to an FDA warning for atypical antipsychotics and an increased risk of stroke and adverse cardiovascular events. There have been a paucity of studies looking at comparing the typical and atypical antipsychotics which showed comparable efficacy in most studies and greater efficacy of the atypical antipsychotics in only one study [58]. However, in one study typical antipsychotics have also been reported to have a higher risk of death compared to atypical antipsychotics [58, 88]. The atypical antipsychotics, in addition, were found to be less likely to cause involuntary movement disturbances including dyskinesias and dystonias in individuals with dementia compared to typical antipsychotics [58]. Particularly, high potency typical antipsychotics are most likely to be associated with involuntary movement disturbances in the elderly [58]. The cognitive enhancers include the cholinesterase inhibitors (galantamine, rivastigmine, donepezil) and the NMDA-acting drug memantine. Efficacy of these agents in the treatment of behavioral disturbances in the elderly with dementia appear to be modest, at best, with their overall effectiveness unresolved [58, 89, 90]. Serotonin antidepressants including trazodone and the selective serotonin reuptake inhibitors may diminish aggression and agitation in a subset of elderly individuals with dementia [91-96]. The anticonvulsants have had a spectrum of reports demonstrating limited to no benefit in a subset of elderly with dementia and agitation/aggression [96-99]. With regard to the use of benzodiazepines in elderly populations with dementia, the results have been equivocal relative to therapeutic efficacy and tolerablity [58]. Of concern are reports linking benzodiazepine use and falls in the elderly [100, 101]. Overall, none of the classes of psychotropic agents nor psychosocial approaches have clearly established superior effectiveness in treating agitation and aggression in dementia [58]. All of the currently available psychotropic agents have been employed to treat other illnesses, and then their application has been extrapolated to address symptom complexes of dementia. Currently there are no specifically targeted agents for the aggressive and agitated features of dementia [58]. At the same time, the available psychotropic agents carry newly recognized risks that need to be weighed against unclear benefit. Current clinical practice requires balancing these putative unestablished benefits with known risks in the context of a thoughtful, transparent consenting process with family and patient.

IV. Aggression in Elderly Patients with Mood, Anxiety and Primary Psychotic Disorders Depression, mania, anxiety and primary psychotic illness (such as schizophrenia) at times are associated with agitation, and there is a generally positive relationship between the


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severity of depression and the level of agitation. As a possible explanation for this overlap, a model of based upon brain neurotransmitters, specifically serotonergic sensitivity, has been proposed [15]. The serotonergic sensitivity model has two types,1) a serotonin- sensitive model with manic symptoms and impulsive aggression and, 2.) a serotonin- resistant model with different agitated behaviors [15]. Stahl [102] has proposed the serotonin (5HT1) a receptor as one of the ―links‖ between these effects on emotion and behavior. Additional possible links involve other neurotransmitters such as GABA and noradrenergic transmission. These mechanisms may explain why serotonergic antidepressants drugs (SSRIs such as fluoxetine) and other serotonergic compounds (azapirones) may reduce levels of aggression/agitation. Older patients with depression, mania, severe anxiety or psychosis may have symptoms of agitation with differing components. This can be aggressive physical behavior such as fighting, grabbing, destroying things, or aggressive verbal behavior such as cursing and screaming. Non-aggressive physical behaviors include pacing, and non-aggressive verbal behavior includes constant or repetitive questioning. These symptoms are generally more frequent and prominent when individuals have cognitive impairment [60] due to inability to analyze the environment or feelings experienced during stress.

Geriatric Mood, Anxiety and Primary Psychotic Disorder: Prevalence and Symptoms Depression Geriatric depression is a growing problem which is under-recognized and under-treated. It has been estimated that the prevalence of major depression in the general population is 12% with depressive symptoms affecting as much as 15% of older persons [103]. Major depression is one of the leading causes of disability in adults, and in the elderly may have an additive effect to medical illnesses creating an increase in morbidity, mortality and placement in nursing homes. Late- life depression is a heterogeneous syndrome that may occur in the context of cognitive impairment, structural brain abnormalities, and other psychiatric and medical comorbidities which are frequently associated with poor treatment responses. Medical comorbidities are very common among older adults with depression and are risk factors for the development or worsening of depression, with depression itself being a risk factor for medical illnesses. Depression plus physical problems leads to increased morbidity, high levels of disability with frequent hospitalizations and nursing home placement and an increase in mortality. Currently there is substantial literature documenting the complex relationship between depression, cardiovascular and cerebrovascular disease, with evidence that depression is associated with a greater number of re-hospitalization days after angioplasty or myocardial infarction [104, 105]. Also 20-30% of patients develop depression after stroke with left- sided stroke more likely to be associated with earlyonset depression [106]. The diagnosis of depression relies heavily on somatic such as changes in sleep, weight, appetite, levels of energy and psychomotor activities. These symptoms can be caused by medical (non-psychiatric) comorbidities making them ―exclusionary‖ criteria for the

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diagnosis. In these cases it is important to pay attention to the ―psychological‖ symptoms such as sadness, unhappiness, inability to enjoy things (anhedonia), isolation, irritability, anger and delusions/hallucinations. A challenge in the evaluation of geriatric patients with mood disorders is the patient who appears to be suffering a depressive syndrome but denies that s/he is depressed, creating a ―clinical‖ diagnosis of ―masked‖ depression. Aggressive behavior is most generally seen in individuals with the more severe types of depression, but as noted previously are amplified when dementia or cognitive impairment is present. Bipolar Disorders Elderly patients with bipolar disorders represent 5-19% of the patients presenting for acute treatment within geriatric psychiatric services [107]. These patients represent a mixed and complex set of patients with frequent comorbidities, poor outcomes and in many cases, high morbidity and mortality rates. It has been generally accepted that the type and range of manic symptoms in the elderly are similar to the general population but with a tendency to be of lesser severity and intensity. Co-existing symptoms of depression and mania are fairly common in bipolar elders with increasing symptoms of irritability or aggression corresponding to increased illness severity. Some patients have ―mixed‖ presentations with manic symptoms and perceptual abnormalities such as delusions and hallucinations. Some patients will show ―dis-inhibition‖ symptoms such as pathological laughing with lesions of the right side of the brain and pathological crying with lesions on the left side. Secondary manias (mania associated with medical or neurological disease) are associated with other behavioral or physical symptoms indicating head injuries, alcoholism, tumors, endocrine disorders, AIDS, silent cerebral infarctions, medications and multiple sclerosis. Anxiety Disorders The prevalence rates for anxiety disorders in older adults range from 3.5% to 10.2% suggesting a higher prevalence than late-life depression with increased incidence among those who are home-bound, living in a nursing home or those with other comorbidities. The prevalence of anxiety symptoms may be as high as 20% [108]. Generalized anxiety disorder (GAD) is highly prevalent in the elderly, with a reported rate of 7.3% . Panic disorders have a prevalence rate of 0.1-1%. Phobias range from 3.1% to 12%. Older patients with anxiety disorders report similar symptoms as do younger patients, but with the confounding situation of comorbid medical conditions. Patients suffering anxiety disorders may have a series of ―physical‖ symptoms which in many cases are the symptoms causing the patient to seek medical help. Somatic symptoms such as tachycardia, chest tightness, vertigo, tremors, sweating, dizziness, paresthesias are common in medical and anxiety problems. Aggression is uncommon with anxiety disorders unless overall illness severity is relatively high. Schizophrenia Most individuals with schizophrenia first develop the illness in young adulthood, although it is known that some individuals experience a later-onset form (sometimes called ―paraphrenia‖) after age 45 or beyond. Thus older adults with schizophrenia comprise individuals with illness of varying duration and time of onset. In the large scale


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Epidemiological Catchment Area (ECA) survey of psychopathology in the United States general population, the reported 1 year prevalence rates for schizophrenia were 0.6% for people aged between 45 and 64 and 0.2% for those over 65 years [109]. A review done by Harris and Jeste [110] reported that 23.5% of patients with schizophrenia had an onset after the age of 40 with 3% after the age of 60. In several studies reported between 1955 and 1993 it was found that the frequency of late-onset schizophrenia among patients in psychiatric facilities had a range from 3 to 10% [111, 112]. The older person who develops psychotic symptoms represents a diagnostic and management dilemma for the clinician. The aging process is a risk factor for the development of psychosis, and if the patient presents cognitive deficits it is difficult to determine if the psychotic symptoms are part of a dementia process or a primary psychotic disorder such as schizophrenia. Patients with late-onset schizophrenia show a generalized pattern of cognitive deficits that are similar to the patterns of young patients with schizophrenia, but different from cognitive deficits in patients with dementia of the Alzheimer type, with the schizophrenia patents generally preserving their learning capacity. Delusions are the most common presenting symptom of late-onset schizophrenia. Persecutory delusions are most frequent but other delusions are not uncommon. Howard et al [113] reported delusions of reference in 76% of elderly patients, noting that auditory hallucinations are common while formal thought disorders and negative symptoms are uncommon. Arango et al [114] reported that schizophrenic patients posing the greatest risk for violent behavior appear to be those who show suspiciousness and hostility, have more severe hallucinations, show less insight into their delusions, experience greater thought disorder and have poorer control of their aggressive impulses.

Treatment of Elderly Populations with Mood, Anxiety and Primary Psychotic Disorders If a patient suffers an affective disorder it has to be determined if the agitation is caused by a unipolar depression or a bipolar disorder. This differentiation is easy to make in some situations but it becomes more difficult when the diagnosis under consideration is a psychotic depression or an agitated depression. A psychotic depression is defined as the occurrence of delusions or hallucinations in the setting of a major depressive disorder and may occur in as much as 15% of all depressed patients. Patients with agitated depression have increased psychomotor activity and may exhibit pacing, hand wringing, nail biting, hair pulling, incessant smoking, and incessant talking. A similar situation can happen with patients suffering an exacerbation of symptoms of a schizophrenic disorder. The first step in dealing with these patients is to ensure the safety of the individual and those around them. Patients in these conditions should be approached in a non-threatening matter, if necessary with a show of force provided by trained personnel. The cautious use of sedation with intramuscular (IM) medication and seclusion and/or physical restraints may be necessary to guarantee the safest setting in which to administer evaluation and treatment. In cases of severe agitation the use of antipsychotic medication continues to be the first line of treatment despite the ―black box‖ warning in the manufacturer‘s package insert added

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to all antipsychotic (conventional and atypical) specifying the ―Iincreased risk of mortality in elderly patients treated for dementia-related psychosis‖ [115]. A meta-analysis done by Schneider [116] (in elderly with dementia) compared seven studies done between 1966 and 1989 resulting in improvement of 41% for placebo and 59% for active medication. Other studies done after 1990 confirmed these observations, but showed moderate to significant extrapyramidal symptom (EPS) side effects with haloperidol when the dose is 2-3 mg a day. For this reason, most clinicians recommend that elderly patients who require typical antipsychotic drugs receive doses approximately equal to 25-50% of the regular adult dosage. Compared to older, conventional agents, the atypical antipsychotic drugs offer different side effects profiles including less EPS but potentially more orthostatic hypotension, cardiac arrhythmias and/or autonomic dysfunction. Metabolic derangement and propensity for diabetes can occur with longer term use of atypical antipsychotic medications. Among the atypicals the ones which have been most studied are risperidone and olanzapine [58] Risperidone has been shown to reduce psychosis and agitation with relatively few side effects at doses below 2 mg a day [117, 118]. Olanzapine has been shown to be effective in reducing agitation and psychosis with relatively low side effects with doses between 2 and 15 mg per day. Both risperidone and olanzapine can be given orally, utilizing rapid dissolving tablets that may be helpful in the elderly who are unable to swallow pills. In patients that require IM medication the alternatives for treatment are haloperidol, olanzapine, ziprazidone and aripiprazole. The recommended doses for geriatric patients, consistent with most elderly vs. younger populations, are 25-50% of the regular adult dosage. Once the acute clinical state has been treated and resolved, the urgent treatment of the basic psychopathological state needs to be addressed. It is important to decide if the patient is suffering a bipolar disorder or a unipolar depression. This distinction is critical because if the patient is suffering a bipolar disorder the treatments of choice are ―mood stabilizers‖ such as lithium carbonate or valproic acid, but if the patient is suffering a unipolar depression or an anxiety disorder the treatment of choice will generally be antidepressant medications. While the treatment of depression in older patients often requires the use of medication treatment, effectiveness is increased if medication is combined with psychotherapy. According to meta-analysis done by Wilson and Mottram [119] the SSRIs and TCAs have comparable efficacy and tolerability. A similar statement can be made about the efficacy and tolerability of SNRIs. Selegiline, a selective MAO B inhibitor has been studied in older populations with Schneider and Sobin showing improvement in behavior, cognition and mood [120]. The main concern with these medications in the elderly is the potential for interactions with other medications and diet. The availability of a transdermal antidepressant patch may be useful in some patients with difficulties taking medications. Psychotic depression occur in approximately 20-45% of hospitalized depressed elderly patients. Despite its relative frequency, that there is a lack of empirical data in the treatment of patients with depression accompanied by psychotic symptoms. The Expert Consensus Guidelines suggest the combination of an antidepressant and antipsychotic medication or electro convulsive therapy (ECT) as treatments for geriatric psychotic depression [121]. ECT has been found to be particularly effective in moderate to severe depression and depression


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with melancholic features, and in the case of psychotic depression, catatonia or treatment refractory conditions. Bipolar Disorders The literature about the pharmacological treatment of older patients suffering a bipolar disorder is limited. Nemeroff [122] showed in patients 21 to 71 years old that a combination of paroxetine and lithium was more efficacious than lithium alone. Robillard [123] reported that lamotrigine was useful in addition to lithium or divalproex, and also useful in the maintenance of geriatric patients with bipolar disorder. Other alternatives are the use of the combination fluoxetine/olanzapine, the antipsychotic quetiapine or ECT in patients with manic episodes. In terms of the dosing of lithium, some clinicians suggest the utilization of the same lithium blood levels utilized in mixed aged adults, but there are reports of toxic reactions with this strategy motivating others to utilize lower blood levels (between 0.5 and 0.8 mEq/L). It is important to keep in mind drug-drug interaction and comorbid conditions in bipolar elders. Sajatovic and colleagues [124] have reported that older adults with bipolar disorder discharged from a geropsychiatric unit had a mean 3.7 medical illnesses --- a ready setting for drug to drug interactions. There is good evidence that the use of divalproex in the treatment of mania and mixed episodes is efficacious and well tolerated but the studies involving older patients are limited [125]. While medications such as aripiprazole, olanzapine and quetiapine have been approved by the FDA for the treatment of manic episodes in mixed-age populations, there is little data regarding the efficacy of antipsychotic medication in the treatment of geriatric bipolar disorders. Schizophrenia When psychotic patients present with agitation due to an exacerbation of symptoms the treatment of choice must be directed to the management of the agitation in a safe and rapid way. The first step is to ensure that the patient and the people around are safe from physical danger. Patients in these conditions should be approached in a non-threatening matter with a show of force provided by trained personal. Sedation with intra-muscular (IM medication) and seclusion and/or physical restraints under careful supervision may be necessary to guarantee a proper treatment and evaluation. Antipsychotic medications are the most effective symptomatic treatment for both earlyonset and late-onset schizophrenic disorders. Because of age- related bodily changes that may affect the pharmacokinetics and pharmacodynamics of these medications in the elderly it is important to follow the principle of ―start low and go slow‖ when using them. The decision of which antipsychotic to use is very much predicated on the side effect profile of the particular medication in question. Significant improvement of psychotic symptoms has been reported with the typical antipsychotics haloperidol, trifluoperazine and thioridazine [126]. Typical antipsychotics have a wide variety of side effects related to their high affinity for the dopamine receptors. They also have anticholinergic and adrenergic side effects. For example, thioridazine produces the longest prolongation of the QT interval making this medication generally unsuitable for use in the elderly population. Atypical antipsychotics have become the standard of care for their effectiveness with positive and negative symptoms and their relative lack of dopamine- related side effects (parkinsonian syndrome, akathisia, dystonias and tardive dyskinesia) but they are not free of

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side effects. Besides causing sedation and hypotension they may also produce prolongation of the QT interval as well as weight gain and serious metabolic side effects including causing or worsening diabetes [126]. Other medications commonly utilized in these cases are the short- acting benzodiazepines with lorazepam being the most utilized. Once the episode of agitation is controlled most patients are placed on regular, oral antipsychotic medication. Patients with adherence problems must be considerd to be candidates for long acting medications such as haloperidol decanoate and long-acting, injectable risperidone. Howard and Levy [127] reported good outcomes, good adherence, and a reduced amount of medication with long acting- neuroleptics in older patients with psychosis. Anxiety Disorders Naturalistic studies looking at patients treated in primary care clinics for anxiety disorders point toward the use of anxiolytic or antidepressant medications in older patients but there is a lack of systematized studies. Despite side effects and problems with cognition and falls, benzodiazepines remain the mainstay of pharmacological therapy for acute management of anxiety and panic disorders and as an initial adjunct to therapy with SSRIs or SNRIs. These medications are beneficial because they have a rapid onset and little effect on the cardiovascular system. On the other hand the long term use has potential problems such as excessive daytime drowsiness, cognitive impairment, and confusion, increase risk for falls, respiratory problems and dependence potential with withdrawal syndromes. Because of the withdrawal syndromes it is recommended that older patients taking benzodiazepines for 4-6 weeks be tapered off them for at least 2-4 weeks. For the older patient the recommended benzodiazepines are the ones with short half-life such as lorazepam, oxazepam and temazepam as they are inactivated by direct conjugation in the liver which is a mechanism minimally affected by normal aging. Several studies have shown the efficacy of antidepressants in the treatment of anxiety disorders in the elderly. Sheik [128] found that imipramine and alprazolam were better than placebo in the treatment of anxiety. In another study the same authors showed that sertraline had a significant effect in the symptoms of anxiety. In one of the few prospective, randomized trails, Lenze and colleagues, demonstrated that citalopram was better than placebo in the treatment of generalized anxiety (GAD) (65% -vs- 27%) [129]. In a secondary analysis evaluating individuals age 60 and older, from several multicenter studies, Katz and colleagues [130] found a significant positive effect by venlafaxine in the treatment of symptoms of GAD. Azapirone and buspirone, as reported by Rickels and colleagues [131] have efficacy comparable to diazepam in patients with generalized anxiety disorder. Boehm and colleagues [132] reported that buspirone is well tolerated by geriatric patients and is effective for the remediation of chronic anxiety. Despite the results of some of these clinical studies the experience in ―real world‖ clinical settings has not been satisfactory, creating the impression of inconsistence therapeutic results. Finally, other drugs utilized for the management of anxiety are antihistaminics such as hydroxyzine, beta blockers and antipsychotics but there are no good placebo controlled studies or the presence of side effects has precluded their use in the older patients.


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Non-Pharmacological Interventions Elderly individuals suffering depressive, anxiety or bipolar disorders may benefit from psychotherapeutic interventions. A wide variety of therapies have been utilized with these patients but there is a scarcity of systematic, prospective studies. At present there is evidence showing that cognitive behavioral therapy and interpersonal therapy are probably the first line of non pharmacological intervention, and it is generally accepted that the utilization of psychotherapy plus medication is better that one of the two modalities alone. This has been studied for cognitive behavioral therapies [133]. Interpersonal therapy (IPT) has been studied and shown that is as effective as nortriptyline in older adults with fewer drop-outs [134]. Other therapies utilized but less studied are: Reminiscence Therapy, Brief Dynamic Therapy, Problem-Solving Therapy, Group therapy and Couple and Family therapy [135].

V. Future Outlook and Needed Research Unfortunately, as is evident from the preceding text, treatment research on late-life aggressive behavior has lagged behind the pace of the growing population. Without appropriate management, aggressive behavior in the elderly has profound personal and societal consequence. For example, the older individual with dementia might be placed in a nursing home because his elderly spouse is unable to manage transient aggressive behavior. There is a critical need for greater understanding of biological and psychological underpinnings and precipitants of late-life aggression. Additionally expansion of evidence – based assessment protocols as well as treatments are essential. Treatments should ideally minimize both adverse effects on the individual as well as reduce burden to caregivers and families. Three main types of interventions to manage aggression in older adult populations are currently being utilized. They are behavioral interventions, educational interventions and pharmacological interventions. All of these avenues both separately and in combination should be explored in order to refine and improve outcomes.

VI: Final Commentary Aggressive behavior in elderly populations is common and can be associated with acute medical conditions, toxic states, neurodegenerative conditions and acute or chronic psychiatric disorders. It is clear that population trends predict growing numbers of older adults and it is anticipated that there will be a great need for effective treatment approaches that minimize aggressive behavior and the effects of aggression in elders with a variety of medical, neurological and psychiatric disorders. Current treatments appear to have efficacy in clinical trial settings, but have limited effectiveness in real-world, clinical settings. Public awareness of this growing problem, and large-scale exploration of treatment methods and technologies are essential in order to meet future healthcare needs of this population.

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Chapter VI

The Impact of Cultural Changes on the Relationship between Senior Sleep Disturbance and Body Mass Index among Older Adults in Two Asian Societies 唐秉輝 Bingh Tang1 and Lyn Tiu2 1

New York College of Traditional Chinese Medicine, Mineola, Long Island, NY USA 2 Danville, California USA

Abstract Population aging has materialized as an innovative demographic inclination with imperative insinuation for government programs, public health and education, and family restructuring. Among such changes, insomnia, snoring and sleep apnea, in conjunction with sleep hygiene have been usually ignored. Changes in sleep are part of the ageing process. Nocturnal total sleep time can become more fragmented with age, with an increase in awaking early in the morning and nighttime awakenings. Body mass Index (BMI) and body weight have important health and educational implications across the lifespan. Most recent attention has been focused on the issue of obesity, an epidemic that occurs in most parts of the world. Yet the older Filipinos have prevalence of underweight, approximately thirty per cent of the population, while that of overweight close to ten percent. By comparison, in Taiwan, the prevalence of underweight is less than ten percent, while approximately thirty percent of Taiwanese elderly are overweight. The main purpose of this article is to signify the economic and cultural impacts on healthy weight and BMI maintenance in potentially decreasing the prevalence of sleep disturbance and improving quality of the elderly life in two Asian societies.

Bingh Tang and Lyn Tiu

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With advancing age, age-related changes have been described for sleep–wakefulness and additional behavioral cycles. Trends in the relationship between elderly sleep disturbance and BMI in the observed two societies merit our serious attention. Further study is necessary to investigate whether the differences between two societies are caused the limitation of hospital-based study or by differences in ethnicity.

Keywords: Asian, Body weight, Body Mass Index, Sleep Disturbance, Older adults

Selected Abbreviations ad Acronyms Apnea-Hyperpnoea-Index (AHI), Body Mass Index (BMI) Coronary heart disease (CHD) National Cholesterol Education Program (NCEP) National Heart Lung and Blood Institute's (NHLBI's) guidelines for body weight Spearman's rank correlation coefficient (rs)

Introduction Sleep Disturbance in the elderly population is not uncommon. One of the most common complaints of sleep disturbance is insomnia.. Whether it is a solitary disorder or merely a symptom is still unclear. In the Philippines, it is noted that, for exa,ple, insomnia has its prevalence in non-governmental community dwelling elderly individuals in a dwelling facility in Quezon City was 43%, and they were mostly females (Kamble 1979): Philippines poverty assessment). The prevalence of chronic insomniac (>4 weeks) in that facility was enormous female predominance, which was accredited to the much larger proportion of females in the dwelling association, about 92% of 2,200 members. Table 1. The relationship of BMI in the elderly people in the Philippines and Taiwan Country Age (y) The year of survey Prevalence Underweight, BMI< 14.8 Overweight, BMI > = 30

The Philippines 69.3 (7.2) 1996

Taiwan 69.9 (7.2) 1999

29.9 % 12.2%

6.4% 29.3%

As per Jenkins et al (Jenkins et al 2007), the data from two nationally-representative surveys of older adults (aged 60 and older) in the Philippines (1996) and Taiwan (1999) to assess the prevalence of underweight and overweight and examine associations between body weight and demographic, socioeconomic, and health characteristics in these populations. The reverse is observed in Taiwan (6.4 and 29.3%, respectively).

The Impact of Cultural Changes on the Relationship …

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Table 2. Comparison of Different Sleep Studies between two Societies in three hospitals Setting

Number of participants Age range (yr) Gender F/M Mean age Exclusion criteria

Health insurance coverage Height cm Weight kg [[190.5, 46.31 BMI kg/m2 Neck circumference cm

AHI events/hr <5

St. Luke's Medical Center, The Medical City Quezon City, Philippines Hospital A tertiary hospital in Metro Manila, The Philippines 223 126 18 – 65 1/3.76 1/1.07 47.40 (13.06) 60.30 (13.70) COPD, heart failure, asthma, other respiratory disease, and taking respiratory medications 169.5 (7.61) 86.39 (21.00) 29.10 (7.61) 44.45 (13.92)

160.83 (15.4) 59.26 (13.70) 23.59

37.80 (24.73)

AHI events/hr >5 AHI > 5, snorers vs. AHI > 5, nonsnorers Prevalence of snoring Total No. of snorers Total No. of non-snorers Total sleep time for entire subjects n=mean+SD the median TST of insomniacs n = For those above median vs. those below median Mean+_SD Polysomnography

66.67% 53.17% of 126 46.83% of 126

Changhua Christian Hospital Medical Center, Taiwan 124 65 - 88.5 1/1.17 71.69 (4.4) COPD, heart failure, and age < 65 years National health insurance of Taiwan 159.76 65.5 25.68 (4.54) 36.7, among which for females is 34.79+_2.85, whereas for males is 37.89+_3.16 AHI 2.3+_1.64, i.e. 95% C I (26.22 - 34.99) n=21 (21/124 = 16.94%) AHI 30.62+_22.20, i.e. 95% C I (1.59 - 3.00) n=103 (103/124 = 83.06%) 53.17 % of 126 46.83% of 126 Taichung area 110 14 402.06+-35.01 min n=124 402.06+-35.01 min n=60 345.25 min 398.05 +_31.37 min Vs. 248.8 +_72.75 min Yes

Noticeably, during the decade from 1979 to 1989, most of East and South-East Asian countries have undergone a period of swift, communal, financial and demographic modifications. Population aging has materialized as an innovative demographic inclination with imperative insinuation for government programs, public health and education, and family restructuring. Changes that are usually ignored include sleep disturbance, sleep apnea, associated with sleep hygiene. Changes in sleep are part of the aging process. Nocturnal total

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sleep time can become more fragmented with age, with an increase in awaking early in the morning and nighttime awakenings (Bliwise, 1999). Since nocturnal total sleep time is affected, daytime sleep may be prolonged. Sleep hygiene, beyond nocturnal and day time cycles may be warped. Daytime sleepiness and frequent sleep apnea and increases in nighttime awakenings, along with decreases in both slow-wave sleep and REM sleep have been reported. (Prinz, Peskind et al. 1982; Prinz PN, Vitaliano PP et al, 1982; Vitiello and Borson 2001) According to Sawit et al (2006), Filipino physicians seldom inquire about snoring during their clinical encounter with patients. Both doctors and patients consider snoring to be a normal sleeping characteristic, without health implications. Thus, a closer study on snoring is warranted. (Sawit et al, 2006) Snoring is a common phenomenon seen in approximately 20% of the adult population and in about 60% of men over 40 years of age. One of the objects of this article is to explore the role of snoring on the above health issues. One of the other aims of this article was to examine the prevalence of abnormal body weight among elderly Filipino and Taiwanese adults and investigate the factors that are correlated with body weight in these populations with emphases on sleep disturbance vs. good sleep quality.

A Strong Contrast of the Elderly Populations Exists Between Two Societies The socioeconomic status and age distribution of the subjects in these two societies may explain the different distribution of BMI of the two societies. (Table 1) These cross-cultural distinctions are consistent with the greater economic development in Taiwan than in the Philippines (Tables 2 to 5). One of the aims is to compare the implications related with healthy weight and BMI the prevalence of sleep disturbance and improving quality of the elderly life. Body mass Index and body weight have important health implications across the lifespan. Recent attention has focused on the issue of obesity that is prevalent in most parts of the world. Older Filipinos are more likely to be underweight. Approximately 30% of the population, while overweight Filipinos is close to 10%. In Taiwan, less than 10% of the population is underweight and approximately 30% are heavier than normal. (Table 1) The aforementioned situation contrasts starkly with each other between these two societies. This article evaluates the trend in the Association of the Elderly Sleep Disturbance and Body Mass Index in the Philippines and Taiwan two Asian societies.

The Necessity of a Cross-Cultural Evaluation Few studies deal with cross-cultural evaluation regarding the Elderly Sleep Disturbance and the Body Mass Index. There is little emphasis on society and patient interaction as well as cultural factors. Few works are devoted to the sleep quality and sleep hygiene in the


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elderly population, and its research. This article includes a qualitative approach to the understanding of sleep disturbance in two Asian societies.

Materials and Methods Data The Taiwanese data in the present article have been described in detail somewhere else mainly for total nocturnal sleep time (TST) and sleep study 2. From 1 January 2002 to 31 January 2003 the Sleep Medicine Laboratory, Changhua Christian Hospital Medical Center, Taiwan, admitted no subjects with heart failure and chronic obstructive lung disease, as there was no physician at night in the Sleep Laboratory. The 124 participants aged from 65 to 88.5 years were studied. No pair of participants was related. No participant had more than one PSG. Among the 124 individuals, there were 117 subjects with available BMI data. Written informed consents including personal and clinical data in the research database of all participants. The research protocol was approved by the Review Board of the Medical Center, and conformed to the Declaration of Helsinki. Apnea/hypopnea Index (AHI) is defined as the number of apneic episodes (obstructive, central, and mixed) plus hypopnea per hour of sleep as determined by all-night PSG. AHI is synonymous with respiratory disturbance index. AHI was measured for all the subjects. All AHI values were classified as first, second and third degrees of sleep-apnea severity. The gold standard for diagnosis of sleep disturbance is in-laboratory nocturnal PSG. Participants were required to have in-laboratory nocturnal PSG at sleep medicine laboratory. PSG was used not only to measure AHI, but also to evaluate sleep efficiency and snoring. Obstructive sleep apnea/ hypopnea (OSAP) was defined as AHI >= 15 per hour. A computerized PSG system (Alice 4 Sleep Diagnostic System, Respironics) was used in this study. As previously mentioned, no second PSG study was conducted after the single-night PSG. Mean, standard deviation, student t-test and correlation were measured with SPSS version 10. A two tailed p value of < 0.05 was accepted as statistically significant. The mean age of male subjects was 71.6 +_4.47 years, while that of females was 72.3 5.47 years. All 124 subjects had chief complaints of sleeping disturbance. The ratio of female to male subjects was 1: 1.7 (the total number of subjects was 124) (Tang, 2007).

Control Subjects A second data set consisting of 1,014 (aged 65 and over) control subjects came from 15,798 subjects who had participated in the Nutrition and Health Survey in Taiwan (NSC 93WFD2000205), between 1993 and 1996. The data of age and blood pressure of those 1,014 subjects were cited and analyzed. Among them, merely 665 subjects had complete data consisting of their age, blood pressure, weight, height, and BMI, while 95.79% (15,133/15,798) of the control subjects lacked one or more of the above listed information.


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In this article, the author compares data from national surveys.

The Taiwanese Census Data Taiwan has been excluded from the United Nations and its related organizations since 1971. Taiwan has not been privy to the health related work of the World Health Organization (WHO). There is no Taiwanese census data available from WHO file. The Taiwanese National Health and Nutritional Survey for the period from 1999 to 2000 were not published until 2005. One of the Taiwanese sleep medicine studies covering the period from 2002 to 2003 was published by Tang (2007). The control data used for Tang‘s study (2007) was from a national survey, which was not published in Taiwan until 1999. Another report entitled 'Elderly Nutrition and Health Survey in Taiwan (1999–2000): research design, methodology and content' was not published until 2005.

The Filipinos Census Data The WHO report for 2006, showing the 2004 estimates, for the Philippines is presented in http://www.who.int/tb/publications/global_report/2006/pdf/full_report_correctedversion (accessed 1 September 2009). The updated estimates for 2005 in the Philippines 2007 WHO report can be located at the following site (accessed 1 September 2009): http://www.who.int/tb/publications/global_report/2007/download_centre/en/index.html

Clinical Research Materials used in this Article for Comparison A related literature review follows. It is nested within case series studies of sleep disturbance of two different societies. Tang's case-serious study (2007) was used as the framework for discussion. Tang's (2007) study mainly is on total sleep time and PSG findings. Tang's (2007) study is compared with data of other studies in Taiwan and the Philippines. The relationship among snoring, total sleep time, apnea-hypopnea index (AHI), body mass index (BMI), sleep efficiency, etc are evaluated and compared in this article (Tables 1-6). To understand the relative impact of each set of independent variables (such as demographic, socioeconomic, and health characteristics, along with sleep variables) on the risk of being overweight or underweight (versus normal weight), examples were derived from related studies of both societies. The comparison was then made.

The Classification of Obstructive Sleep Apnea Syndrome The OSAHS was classified according to the criteria of severity of sleep apnea. The degrees in severity of sleep apnea were defined, bases on the protocol of American Academy


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of Sleep Medicine Task Force (1999). These include: 1] zero (0) degree, apnea/hypopnea index (AHI) < 5, 2] first degree, 5 <= AHI < 15, second degree, and 3] 15 <= AHI < 30, and third degree, AHI > 30. It is worthwhile to evaluate the difference between 1999 and 2007 two different American Academy of Sleep Medicine (AASM) criteria. The difference between AASM's 1999 and 2007 criteria in AHI follows. For example, the recommended hypopnea definition of 2007 has to meet the following criteria: 1) 2) 3) 4)

The nasal pressure signal excursions drop by not less then 30% of pre-event baseline. The duration of this drop occurs for a period lasting 10 seconds. There is a not less than 4% desaturation for pre-event baseline. At least 90% of the event's duration must meet the amplitude reduction of criteria for hypopnea.

The aforementioned definition of AASM's 2007 criteria is somehow different from that of 1999's criteria. It would cause some hypopnea cases to be deleted in the classification, if one is using the criteria based on 2007's instead on 1999 's criteria. Such a consideration in the aforementioned difference is applicable to all the clinical classification (Tang, 2009a).

Criteria Commonly used in Applying Apnea-Hypopnea-Index (AHI) For the indication for clinical treatment or not, the criteria include: 1] AHI < 5, SDB can probably be ruled out , 2] 10< AHI < 15 gray zone, 3] AHI = 15 warranted treatment, and 4] 30
Results Sleeping Apnea in a Taiwanese Sleep Study Sleeping apnea was found 81.3 % with age of 65 years and over suffering from sleep disturbance found in a Taiwanese study (Tang, 2007) according to the result of PSG. Tang (2007) reported that 15.32% of his subjects had an AHI<5; 14 out of 19 were obese and each had an AHI>30. Obesity is defined by the U S National Institute of Health. There were 45 overweight patients (39.52%), only 7 had an AHI<5. Sixteen out of 38 subjects subject w2ere overweight and each had an AHI not less than 30. (Tang, 2007)

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Obstructive Sleep Apnea (OSA) Notwithstanding the fact that obstructive sleep apnea (OSA) may be common in Asian and Southern Pacific patients as compared with what has been reported for Western patients, there is hardly any information of large study. No prior publication relating height measurement with AHI exists. Apnea (elevated AHI) and snoring are associated with obesity and increased neck size has been widely reported in the literature, as well as has the relationship of AHI to hypertension (Paw et al, 1996; Fletcher et al, 1995, Hader et al, 1998; Hoffstein et al, 19 91; Wilcox et al, 1003, Shahar et al 2003; Johnson et al, 1984).

AHI: Decile and the Quartile Distributions 1]. Decile Distributions In this study, using Tang‘s 2007 clinical data, study, a decile, instead of quartile, distribution of height was found with a significant negative correlation with AHI. There was no such a relationship found between the latter (AHI) and weight. In the tenth decile (D10), the range of height was from 169 to 174 cm, and that of AHI was from 0.3 to 106 per hour. In D10, the Spearman rank correlation test revealed that between height and AHI, there was a significant negative correlation coefficient rs – 0.74, with two tailed p value = 0.0058, which was significant. 2]. Quartile Distribution It has, as well, shown that a quartile distribution by the height with the Spearman correlation coefficient being - 0.34, albeit the two tailed p (0.01) was marginal insignificant. (p = 0.06). Another novel finding reported here is that AHI relates with weight only but not with height.

A Novel Finding Of AHI: A Quantile-Quantile Plots (Q-Q Plots) The quantile-quantie plots (q-q plots) of AHI suggest deviations from normality, supported with kurtosis and skewness that are greater/less than a -2 to +2 range when their standard deviations are considered, imply that the assumption of normality is not met; notwithstanding, none of the diagnostics of kurtosis and skewness on multiple linear regressions of AHI being significant or worrisome. (Figs. 1-4) Among the four figures, the Fig.1 shows regressional residual versus filted diagnostic values. The Fig. 2 shows a relationship between theoretical quantiles and standardized residuals in a Q Q curve. The Fig.3 shows a relationship between the standardized residuals and regressional filted values. The Fig.4 shows relationship between the standardized residuals and leverage.


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Figure 1. (upper left) There is a slight increase in variability with increasing fitted values in the Fig. 1 as compared with Fig. 3, but it is not problematic Figure 2. (upper right) Harrell-Davis plot not only gives empirical probability intervals, it does not depend on normality of the distribution of interest. Figure 3. (lower left) There is a slight decrease in variability with decreasing fitted values in the fig. 3 as compared with Fig. 1, but it is not problematic either. Figure 4. (lower right) Judging from the Residual Diagnostics (right bottom) we can fairly assume that outliers do not distort the parameters (even though the residuals have extreme values).

AHI and BMI BMI was calculated as weight (kilograms) divided by height squared (meters squared). It has relevance to OSA (upper limit of normal BMI in Far-East Asian is 23.5 kg/m2 from current WHO data.) For the correlation between AHI and BMI, after checking with Spearman's rank correlation coefficient (rs), using the same data as that of one of Taiwanese studies (Tang, 2007, 2008, 2008a, 2009, and 2009a), the rs revealed 0.295. This rs is close to 0.330, that is, the rs between AHI and neck circumstance. As another novel application, the relationship between AHI and Neck Circumference can be used to approximate with that between AHI and BMI. It is noted that in Taiwan, distributions of body composition are usually generated for children, adolescent, and middle-aged groups, but not for the older people.

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The Taiwanese study (Tang, 2007) revealed that the AHI mode was 9.4 per hour; its count for 40 subjects. The highest number of AHI was 106 per hour in that study. There was an insignificant effect on frequency of snoring by grouping factor of AHI. Spearman's rank correlation coefficient (rs) test revealed a mildly positive correlation between AHI and snoring (rs was 0.26). Characteristics of BMI in subjects with sleep disturbance follow. Females had mean height, weight and cervical circumference less than the counterparts of the males. The female subjects had mean BMI of 26.550 kgs/m2, and male 25.19. The mean BMI of total 124 subjects was 25.574 +_4.521 kgs/m2, while that of control was 23.768 +_3.662 Kgs/ m2, the difference was significant (the p value < 0.0009). The Pearson's correlation coefficient between height and BMI was significantly different between males (- 0.227) and females (0.0854). In these data, the female subjects were about one year older than the male in the average. However, the female subjects had average (mean) height, weight and cervical circumference, which were respectively less than the counter parts of the males. The 95% confidential interval for mean BMI was 24.746 - 26.402. The minimum BMI was 15.20, and maximum was 39.15. AHI was correlated with BMI, snoring, body height and weight, and cervical circumference respectively. There was a highly significant correlation between BMI and snoring. The subjects whose BMIs were more than 25 had more frequent snoring than those whose BMIs were less than 25 in the studied population. BMI of patients was higher than control subjects. There were significant positive correlation between AHI and BMI; Spearman's rank correlation test revealed that the relationship between snoring and BMI was highly significant.

The Effect of BMI Grouping on the Frequency of Snoring in a Taiwanese Study BMIs were classified as following 3 groups: (BMI_group 1, BMI >30), (BMI_group 2, BMI between 25 and 30), and (BMI_group 3, BMI <25). Mann-Whitney test reveals as follows. The two groups of BMI were selected for comparison. Group differences were insignificant between group 1 and group 2 (BMI_group = 1, BMI >30, and BMI_group = 2, BMI between 25 and 30), (Grouping factor BMI: MannWhitney test, degree of freedom (d.f.) = 1, P = 0.432). Group difference was significant between group 1 and group 3, also significant between group 2 and group 3. Grouping factor BMI: Mann-Whitney test, d.f. = 1, p < 0.001, p = 0.001, respectively significant. (Tang, 2007) The groups of subjects with their BMI >30, and a BMI between 25 and 30 snored more frequent than those in the group with a BMI <25.


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Discussion Asian OSA Prevalence There is little information of the prevalence and severity of OSA in Asian snorers although OSA may not be uncommon in Asian patients. There is no information on snoring and OSA in Asian population either. Nevertheless, there is a single report on Singapore population, which is predominantly Chinese (Puvanendran et al , 1999).The authors contend that the sleep apnea syndrome is more common than the 2-4% prevalence frequently quoted (Young et al., 1993). The authors studied the snorers in an adult population in Singapore and then went ahead to evaluate how many snorers suffer from pathological apnea as well as sleep apnea syndrome. Their examinees age ranged from 30-60 years. There were 106 consecutive habitual loud snorers of a similar age group in the same population studied with PSG in their sleep laboratory. In that laboratory, an AHI greater than 5 was regarded as pathological. The authors have found that 24.09% were loud habitual snorers. Among the latter, 87.5% of loud habitual snorers had significant OSA on PSG and 72% of these apneics complained of excessive daytime sleepiness (EDS). Assuming the clinical observation that all apneics snored, and by extrapolating these figures, the authors conjecture that sleep apnea syndrome affects about 15% of the population. EDS in their cases were validated with clinical hypersomnia. Hypersomnolence was significantly related to the poor delta wave sleep. OSA occurred mainly in stage 1 and 2 non-rapid eye movement (NREM) sleep instead of in REM sleep. Frequently, the arousals prevented sleep from going beyond stage 1 and 2. With such a higher-than-expected prevalence of sleep apnea syndrome in Singaporean population aged 30-60 years is likely because of the evidence that the people in that population, aged 30 to 60 years, suffer more hypersomnolence, which is associated with the repression of delta wave sleep by apnea occurring taking place mostly in stage 1 and 2 NREM sleep. (Puvanendran et al, 1999) Conversely, the reported prevalence of OSA reveals as follows. The 19% of 1,775 subjects with a mean age 71 years, SD 10.5, range 40-100 had OSAH (obstructive sleep apnea-hypoxia) (Gottlieb DJ, 2004). In the Philippine and Taiwan, there is a lack of the above studies. Sleep-disordered breathing (SDB) is defined as having AHI score of 5 or higher, it was 9 percent for women and 24 percent for men. Male sex and obesity were strongly associated with the presence of sleep-disordered breathing, according to a US study (Young et al, 1993). In the U.S., a high percentage of over-65 years subjects have AHI>5; this is the population norm. All elders do not need to be treated if their AHIs are greater than 5. An AHI >=5 has conventionally been a cutoff for the presence of SDB. A higher cut-off of AHI >15 has been used, especially for the elderly, in most of sleep studies. An AHI >20 might be better to distinguish those requiring treatment. There are not enough prospective studies to indicate any treatment responses at different levels of AHI. It is unclear that AHI is a risk factor for those aged over 65 years. A report in English by Ancoli-Israel et al presented that (AncoliIsrael, 1996) it was largely central apnea, NOT obstructive apnea. Hence, central apnea predicts mortality above age 65 years; others also published similar data (Lavie et al, 2005; Tang, 2007). Nevertheless, to the interest of researchers, Asian‘s small upper airway merits

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attention. With respect to the risk factors for SDB, for example, a report from Singapore indicated that the risk factors associated with habitual snoring and SDB were largely similar to those reported in other populations (Puvanendran, 1999). However, differential risks may underscore the importance of ethnicity in determining the burden of SDB. It is mandatory for health care development and research on SDB in Asia and the answer will come with hard work towards endorsement of alertness of this circumstance in both lay professional communities (Lam et al, 2007). Snoring is an independent and significant risk factor for a vascular disease especially for stroke and myocardial infarction. It is not uncommon that patients in Sleep Studies are not aware of their own snoring, which was consistent with the original indication of sleepproblem referrals to one of the Taiwanese studied population that patients were not referred solely for sleep apnea, or for snoring alone. For all practical purpose, they were referred rather for mixed sleep problems in most of Sleep Medicine Laboratories. Many patients are not aware of their own heavy snoring and nocturnal arousals. Any excessive and inappropriate assumption that subjects who did not give an account of snoring and sleepiness were lacking OSA is almost definitely erroneous. We should always be ready to lend a hand by questioning the bedroom partner of a potential patient with chronic sleepiness and fatigue, or other type of sleep disturbances. Table 3. Comparison of descriptive Data (Basic Parameters) between two societies' studies Setting Age, yr Gender (F/M) Height, cm Weight, kg BMI, kg/m2 Neck size, cm Obstructive sleep apnea AHI

The Philippine N=78 46.4 +_ 15.35 35/43 (45/55) 163.9+_ 9.42 156.8+_ 50.60 25.9 +_6.36 15.5 +_ 2.13 None <5, 0.98 +_ 1.40

N=223 47.8 +_ 12.11 28/195 (13/87) 169.5 +_ 7.61 190.5 +_ 46.31 30.2+_7.72 17.5 +_5.48 Yes >=5 50.8+_ 31.47

p value NS NS 0.002* 0.002* 0.001* 0.004* NS 0.000

Taiwan N=21 700.66+-3.89 14/7 155.95+-6.73 58.58+-7.40 24.01+-2.89 34.56+-2.82 None <5, 2.04+-1.42

N=103 72.1+-4.98 32/71 160.54+-7.68 67.01+-12.17 26.03+-4.69 37.20+-3.30 Yes <=5 30.38+-22.16

p value NS NS 0.15 0.003* 0.069 0.001* NS <0.001*

It is noted that all AHI values have been dichotomized at its level of 5. Such a situation, in which BMI as a result has become marginally not significant upon independent sample t test (p= 0.069) in the Taiwanese (Tang, 2007) study, whereas that of the Filipino Conde-Corpuz's study has been significant (p=0.001) as tabulated as above. (The rest of discussion as per vide supra: the full text). In this Table, following the pattern the data were recorded in the Philippine Conde-Corpuz's study, it is noted that the t test instead of Mann Whitney test was used. (The rest of discussion as per vide supra: the full text, and vide infra: the Table 6) In this Table, it is as well noted that in that Taiwanese study, the difference of the BMI, is merely 2.02, whereas that in the Filipino study is 4.3, two folds of that of Taiwanese study. (The rest of discussion as per vide supra: the full text)

For another example, in one of the U S studies reveals that Tractrenberg et al's finding is as follows. Their 2006 and 2005 articles are based on a large sample recruited from the community, and not from a sample with sleep disturbances. Their data may be useful as an external (independent) reference for the samples cited in this study. Hence, comparing studies


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referred in this article, Tractenberg et al had the analysis based on the intake interviews of 399 healthy non-demented elderly whose data were achieved as of September 2002. (Tractenberg, 2003 and 2006) (Table 5) In their studies, those participants who were nondemented elderly people had the frequency rating of heavily snoring from 0.7 +_ 1.1 to 0.9 +_ 1.2. Noticeably, on the frequency measure of heavy snoring, its rating was defined as following: 0, for rating for no snoring in previous month, that is, never; 1, less than once per month; 2, at least once per month, 3, at least once per week; and 4 nearly everyday per day/night. Table 4. Comparison of Summary of Characteristics in Those with OSA in studies between Two Societies Demographic Condes-Corpuz Philippines N=223 Data OSA

Age yr Height cm Weight kg BMI kg/m2 Neck size cm AHI

AHI >5 to 20 N=54

AHI >20 to 30 N=22

AHI > 30 N= 146

46.4 +_ 15.33 169.4 +_ 7.82 179.3+_45.11 29.18+_5.70 17.3 +_ 5.30 in 11.6 +_ 3.97

49.5 +_ 14.01 46.6 +_ 11.28 168.7 +_ 9.71 169.7+_ 7.19 188.0 +_ 40.21 195.2 +_ 47.18 30.6 +_ 7.85 30.5 +_8.36 16.2 +_ 1.98 17.8 +_ 5.90 23.6 +_ 2.62 69.4+_21.72

Tang Taiwan N=124 Sleep disturbance AHI < 5 AHI AHI Zero Degree of 5<= to 15 15<= to 30 Severity First Degree Second of Sleep Apnea of Severity of Degree of N=21 Sleep Apnea Severity of N=32 Sleep Apnea N=27

Table 5. Table of Comparison for Prevalence of Snoring and Insomnia Metro Manila Local dwelling Philippines elderly individuals Quezon City, Philippines Snoring: 66.67% Frequency

Insomnia Total sleep time (hours) The number of subjects Age (years) Location Authors

43% (mostly females)

Metro Manila The Philippines Sawit et al

Taichung area Taiwan

Tractenberg et al

Self-reported 47.8% 0.7+_1.1 to 0.9+_1.2 * F (n=646) 37.2% M (n=606) 57.1% Healthy non-demented elderly 18.3% Alzheimer's disease patients 27.6% 6.53+_1.55 160 >60 Taichung area Taiwan Liu and Liu

Oregon State The US Tractenberg et al

The literature estimates the prevalence of snoring from 25 to 83%, with that of insomnia from 10 to 69%.

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Snoring As a comparison, it is interesting to notice that in the U S, a) on Tractenberg et al's reports (2003, 2006), the criteria of the frequency of snoring is defined as: 0 for never; 1 for less than once per month; 2 for at least once per month; 3 at least once per week; and 4 nearly everyday per day/night. b) those reports encounter the issue of the level of awareness of the sleep disturbance problems in the reporters at nights. Conversely, the literature estimates the prevalence of habitual snoring in general population ranges from 3.6% to 35.7%. (Rice et al, 1986; Koskenvuo et al; Young et al, 1993) In one of the studies in Taiwan (Tang, 2007), it investigated the subjects of a sleepmedicine-laboratory based cohorts, who lived in the dwelling communities of Changhua area, Mid-Taiwan, which is adjacent to Taichung area. The snoring prevalence in Taichung area, Taiwan is 47.8 % for males, whereas 37.2 % for females with age ranging from 10 to older than 60 years, all together 1,252 people who were successfully interviewed, whereas 606 were males and 646 were females, according to a report by Liu and Liu (2004) on the prevalence of snoring in a regional area of Mid-Taiwan. Snoring as a risk factor for stroke has been reported in the Philippines as well. Sawit (2006) has extensively reported with its relevance to sleep apnea. Snoring is a not only an independent risk factor for acute vascular disease, but also a factor for stroke and myocardial infarction. In addition, habitual snorers are more at risk for acute vascular disease compared to occasional snorers. Taiwan is short of such studies except one by Liu & Liu (2004). They merely reported the prevalence of snoring in a regional area of Mid-Taiwan. Further studies to inquire on the relationship of sleep apnea with snoring in Taiwan should be done.

BMI and Environment BMI has been affected by urbanicity and obesigenic nature of environment. For example, I-lan County, located at the northwestern region of Taiwan, is a rural area with high labor work (e. g. farming). There, body weight tends to be lower. Urbanites tend to have higher BMIs than their rural counterparts. As rural area became more urbanized in I-lan County, the relationship between urbanicity and obesigenic nature of environment merits further consideration. In Taiwan and the Philippine societies, modernization of certain rural areas leads to an increase in their body weight. This aspect of modernization has exerted a strong influence on the debates on the role of agriculture as a prerequisite for developing countries. Ishikawa (1967), Johnston ( 1969), Kelley and Williamson ( 1971), and Hayami (1974) to contribute to this debate.


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The Comparison of BMI among Three Sleep Studies between Two Societies Three studies between two societies are contrasted. BMI was marginally not significant upon independent sample t test (p= 0.069) in the Taiwanese (Tang, 2007) study, whereas that of the Filipinos Conde-Corpuz's study was significant (p=0.001) as tabulated in Table 2. In Table 2, the t test instead of the Mann Whitney test was used in the Filipino CondeCorpuz's study. The updated census data for Taiwanese BMI (2000) was 18.5-24 (applied to all ages), issued by the Health Department of Taiwan ( http://www.doh.gov.tw/ ). An earlier (19931996) survey conducted by the same department concluded that BMI for subjects with 19-44 years old > 26.4 would be classified as obese. The census data of BMI in the period from 2001 to 2003 was 20-24.9 ( http://www.doh.gov.tw/ ). With respect to the comparison of BMI (and other basic parameters) between non-snores and snorers in two different societies, by examining Table 1 of this article, it is, as well, noted that in the Taiwanese study (Tang, 2007), the difference of BMI between non-snores and snorers is 2.02; that in the Filipino study in Table 1 is 4.3, twice that of Taiwanese study (Table 2). All AHI values in Table 3 have been dichotomized at a level of 5. BMI was a result has become marginally not significant upon independent sample t test (p= 0.069) in the Taiwanese study, whereas that of the Filipino Conde-Corpuz's study (Conde-Corpuz) was significant (p=0.001) (Table 3).

The Significance of Marginally Not Significant (P Value = 0.069, Instead Of 0.05) in Measurement (Table 3) With regard to the fact that AHI values in Table 3 have been dichotomized at a level of 5 and BMI was a result has become marginally not significant upon independent sample t test (p= 0.069) in the Taiwanese study, it merits evaluation as follows. The p value suggests a "very small amount of evidence in support of the null hypothesis". It does not suggest that the difference (the alternative hypothesis) is true, because p-values are strictly related to the null, and not the alternative, hypotheses. Thus, a p value = 0.069 is "marginally not significant" is the most appropriate; one should not attribute any characteristic apart from marginality to the p-value.

The Importance of Gender Factor The prevalence of OSA in patients up to the age of 60 is two times higher in men than in women (Franco, 2004). The gender data on BMI in one of the Taiwanese study (Tang, 2007) is consistent with the literature.

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The Importance of Who was Doing Measurement of Height and Weight In Denmark and the U S, a self-reported measurement of height and weight is strongly i practiced. The height and weight data are predictors of health outcomes (Stunkard & Albaum, 1981; Troy et al., 1995). Most studies involving BMI are in conjunction with data of height and weight. The key issue is whether they are self-reported or not. In a Taiwanese studies (Tang, 2007), a clinical research was carried out on individuals aged from 65 to 88.5 years; PSG technologists measured 117 individuals‘ height and weight before PSG testing. BMI was then calculated. There was no chance for self-reported bias. Anthropometric indicators of height measures may underestimate BMI because people of short people may over report their height, and heavy individuals may under report their weight (Black, Taylor, & Coster); this aforementioned can happen in any society regardless of cultures.

The Significance of Asian BMI Researchers modified WHO expert committee‘s suggestion and used the criterion of > = 27 instead of >= 30 for Asian BMI. The upper limit of normal BMI in Far-East Asian is 23.5 kg/m2 from new WHO data. Obesity in Asia, as in Singapore nationwide, is defined as BMI >23. Asian nutritionists are inclined to apply a limit of BMI > 23kg/m2 for obesity due to lower stature and body weight in Asians. Asian BMI allows for a smaller skeleton (physical) frame, of most Asians. For every height, weight is set lower to compensate for the smaller frame. The current WHO data the upper limit of the normal Asian BMI is 23.5 kg/m2; this been as well applied in Singapore nationwide. Singapore nationwide protocol reveals that the scales that have been compiled using a nationwide survey data in Singapore. If one is not an Asian or an Asian descendent, Asian BMI will not be applicable. For example, census data of BMI from 2001 to 2003 in one of Taiwanese studies (Tang & Chen, 2003) is 20-24.9 kg/m2 . Obstructive sleep apnea (OSA) may not be uncommon in Asian and Southern Pacific patients (Tan W. C., 2004) compared to what has been reported for Western patients (Duran J et al, 2001; Redline, S. et al, 2004). Several studies comparing OSA between Caucasians and Asians have shown that Asian subjects have a greater severity of illness, as indicated by high AHI, when contrasted with Caucasian patients matched with age, gender, and BMI (Fletcher, 1995; Pawer et al, 1996). Asians generally have a higher percentage of body fat than Caucasians. Hence, making cross-ethnic comparison of body structures by using absolute BMI values may be misleading. Obesity is associated with an increased risk of OSA. (Young, Peppard, Gottlieb, 2002; Fletcher, 1995; Pawer et al, 1996; Hoffstein et al, 1991). Therefore, OSA‘s association with BMI in Asia should be evaluated with Asian BMI criteria.


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Underweight The risk of being underweight (instead of normal weight) increases with age in the Philippines and Taiwan. In one Taiwanese Sleep Study (Tang 2007), 3.22% of the studied cohort was underweight. Another Taiwanese cohort of 778 cases was recruited in the multinational Global Lower Extremity Amputation (LEA) Study. Risk factors included age, sex, smoking, BMI, hypertension, systolic (SBP), diastolic blood pressure (DBP), and LEA level. Mortality was ascertained from the National Death Registry. With a follow-up period of up to 6.5 (median: 4.0) years and 1239.17 patient-years, 214 patients died. The underlying cause of death was recorded as diabetes mellitus; 57.9% died. After adjustment for age and sex twp variables, then smoking, SBP and underweight are predictive for mortality. (Tseng, 2007)

Underweight and Overweight A sleep-laboratory-based Taiwanese study, using Asian BMI criteria, for those subjects who were underweight: with the BMI of 18.5 included 0.85% of the population. For those with the BMI< 18.5, it was three times greater, 2.56 % (Tang, 2007). Tang stressed the importance of Asian BMI, the upper limit of normal BMI in Far-East Asian is 23.5 kg/m2. (Table 6) Table 6. The data of a national survey in Taiwan that was conducted in 1999 * Variables Age (years) Height (cm) Weight (kg) BMI (kg/m2)

Male (n = 1,243)

Female (n = 1,189)

72.7 (72.1–73.2) 162.9 (162.6–163.3) 61.4 (60.7–62.1) 23.2 (23.0–23.5)

73.0 (72.5–73.4) 149.9 (149.3–150.5)* 53.9 (53.0–54.8)* 24.0 (23.7–24.4)*

* Elderly Nutrition and Health Survey in Taiwan (1999–2000): research design, methodology and content' was not published until 2005.

Among other studies that adapt Asian BMI criteria, in Taiwan, there is a study for checkup population in 2001 used mean BMI in Asian criteria compared with socioeconomic status (SE) for the elderly aged 65 years and over. (Chien, K.L., 2004) Due to changes in socioeconomic status and dieting habit, there are other publications that employ Asian BMI criteria. There were reports on dietary changes from 1978 to 2003 in the Philippines. The relationship between BMI and Sleep Apnea has been identified. Trends of dietary changes from 1978 to 2003 in the Philippines might affect the composition of BMI, and thus secondarily influence sleep apnea. The expanding Filipino economy from 1998 to the 2003 reduced the consumption of starchy roots and tubers from 37 g/day in 1978 to 19 g/day in 2003. (Jenkins at el, 2007). Conventional and cultural food consumption is primarily from yams and tubers is diminishing. A double burden of malnutrition and high food costs

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was illustrated in case studies carried out in six developing countries (FAO Corporate Document Repository of the Philippines). Such a trend might affect the composition of BMI, and thus consequently affect sleep apnea. In Taiwan, there is the higher proportion of underweight people among the elderly (70+) than among the near elderly (53-69 y). In Taiwan, an analysis reveals that with a sample size for the elderly cohort (70+ years) and near elderly cohort (53-69 years) 1855 subjects, and near elderly cohort (53-69 years) 2014 subjects , the number of was 211 for the elderly and 65 for the near elderly respectively. When expressed as a percentage, the values are 1.13% for the former, and 0.32% for the latter (SA and Larsen, 2007). Based on clinical studies, body weight peaks in the 50s and remains stable or decreases after the mid- or late 60s. The weight data for Taiwanese elderly data seem to fit this pattern. Underweight is more prevalent in the Philippines (29.9%) than in Taiwan (6.4%). By comparison, overweight is more prevalent in Taiwan (29.3%) than in the Philippines (12.2%) (Jenkins et al 2007) This difference can be attributed to the level of economic development and their impact on nutrition transition of the two societies. Different sets of factors are related with the two extremes of body weight. The risk of being underweight instead of normal weight increases with age in both countries. Old adults aged from 70 to 80 years have had less exposure to the nutrition transition towards the Western diet than those aged from 50 to 70 years. A cohort effect might explain why 50 to 69 year Taiwanese adults have a greater risk than the older old Taiwanese adults, aged from 70 to 80 years of being overweight instead of normal weight. The absence of this pattern in the Philippines may be due to its lower economic development relative to what in Taiwan. Men are generally less likely than women to be either underweight or overweight. In the Philippines, almost 30% of older adults are underweight. (Table 1) A study of under-nutrition in Taiwan follows. A simple questionnaire adopted from the Mini Nutritional Assessment (Sa & Larsen, 2007) was recently employed as a preliminary screening method for Taiwanese elderly individuals who were at increased risk of nutritional inadequacy. The proportion of Taiwanese elderly who were regarded at the high risk of under-nutrition increased with age, ranging from 0.88% for 53 to 60 year-old subjects, 1.86% for those subjects aged 60 to 70 years, 3.6% for those from 70 to 80-year-olds, and 5.3% for those subjects aged older than 80-year-old (Tsai, A). Not surprisingly, different sets of factors are related with the two extremes of body weight. There are both similarities and differences in predictors across settings. The risk of being underweight instead of normal weight increases with age in both settings, because of a cohort effect; the older old adults have had later and lesser exposure to the nutrition transition towards the Western diet than have the younger old adults. A cohort effect might also explain why younger-old (50 to 69 year old) Taiwanese adults have a greater risk than the older old (70 years and over) Taiwanese adults of being overweight instead of normal weight. The absence of such a pattern in the Philippines may be due only to its lower level of economic development relative to Taiwan. (Table 1) Several studies comparing OSA in Caucasians and Asians have shown that Asian subjects have a greater severity of illness, as indicated by higher AHI, contrasted with Caucasian patients matched with age, gender, and BMI. Asians generally have a higher percentage body fat than Caucasians of the same matched items. Hence, making cross-ethnic


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comparison of body habitués using absolute BMI values may be misleading as previously mentioned. Culture and eating habit have to be taken into account. For example, the people in Gujarat state of India are mostly merchants, instead of farmers; they are fond of food made from sweets. Generally, the prevalence of being overweight will become much greater in urban areas and among the rich. The relationship between obesity and socio-economic status (SES) has been altered as countries develop. Likewise, that between obesity and urbanicity will change as countries grow. Urbanites are inclined to have higher BMI than their rural counterparts. Other studies have found differences by age and gender. Therefore, BMI has been affected accordingly, which in turn influences sleep apnea. The drawback of one of the Taiwanese studies (Liu & Liu, 2004) is the lack of BMI data. Both Taiwanese and the Filipino other studies cover weight, height and BMI data. Nevertheless, there are still some issues that bear further studies. There are clues to determine and to find the subgroups that are most vulnerable to abnormal weight, which is affecting BMI, but not height. Adequate attention should be paid to the localities where economic development that benefits only the urban elite, such as in Brazil (Jenkins et al, 2007). Visceral fat accumulation of obese and overweight patients should be considered. The secondary increase of the negative intrathoracic pressure by respiratory efforts may play a role in the pathophysiology of SDB. The standard PSG used in most of sleep studies does not include the measurement of esophageal pressure (Pes), which represents the intrathoracic pressure. Hence, the upper airway resistance syndrome is often overlooked because the severity of OSA has already been evaluated by the AHI. Obesity, BMI and socioeconomic status (SES) are important issues. Huang et al (2005) report on obesity in the elderly and its relationship with cardiovascular risk factors in Taiwan. Conversely, there is a study that assesses the association between socioeconomic status (SES) and overweight and obesity among near elderly (aged 53-69) and elderly (age 70+) people, using a longitudinal survey data in Taiwan. In mainland China, status and current income were positively related with BMI among near elderly and elderly men. SES was not associated with BMI in elderly women, while education was inversely related with BMI among near elderly women. The shifting of paradigm in the relationship between SES and overweight/obesity between near elderly and elderly women suggests a budding social inequality in overweight and obesity in Taiwan. The signs indicate that prototypes of social gradients in obesity are acclimatizing to socioeconomic and cultural background (Sa and Larsen , 2007). There is some complementary provision that the desirable body image may also become more westernized. A propensity in the cultural insight of body weight is currently affected on the younger generation by fashion-models. This prevails in societies that where the younger generation wants to be more fashionable, while among the older generation wants to be 'slimmer'. The above tendency is found in the Philippine, Taiwan, in other Asian countries like India. The traditional culture of Taiwanese and the Philippines tend to recognize a more appealing physical body structure. Such structure contrasts to the existing Western physical standard to be socially acceptable, presentable and desirable. Working through examples can help highlight the issues involved and demonstrate how to conduct a possible solution. More extensive comparisons may assist in recognizing the


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subset groups that are most susceptible to abnormal body weight, and consequently, lead to hypertension and then to sleep apnea. It would be practical and educational to account for the role of public health and sleep hygiene together with National Cholesterol Education Program (NCEP). Conceivably, nutrition programs that keep a tight rein on hypertension and excessive weight will prevent sleep apnea for all the steps of the social-class ladder and the rich and poor in both societies. Obviously, both developed and underdeveloped countries conceivably need more sleep studies (See Tables 1-5). Patterns of being underweight and overweight, which affect sleep apnea, should be studied in more details in both societies.

Cigarette Smoking In the Philippines, the population is predominantly young. Cigarette smoking is a problem. In the Philippines, cigarettes can be bought one at a time, which makes them easily accessible to adolescents and children. Increasing fat intake, diabetes, high cholesterol levels, and CHD are now increasing health problems in the adult population. The population is spread over many islands, and there are diverse ethnic groups. Thus collecting epidemiological data is difficult. One of the unusual strengths in gathering data is that the Philippines are well supplied with dietitians. Filipino experts are committed to continuing health education. In Taiwan, the elderly people are increasing in number. Unfortunately, the problem of sleep disturbance in the elderly has not been sufficiently studied. However, there is a repot on 6,406 adult subjects (41.4% women) from January to December 2001 from the healthscreening program in a tertiary hospital. C reactive protein (CRP) was found positively related to smoking status (Chien K. L. et al, 2003) High CRP levels were strongly associated with metabolic syndrome. CRP significantly associated with smoking and metabolic syndrome. Inflammation, smoking and atherosclerotic risks were interrelated among healthy young and elderly Taiwanese. (Chien KL et al, 2003) For elderly adults, CRP's relationship with sleep disturbance needs further evaluation in the two societies. It is unclear which metabolic syndrome risk factor components could predict CRP levels and possible interaction with smoking. Elderly smoking at nights may be related to insomnia; this should to be evaluated. Sleep apnea syndrome is an important risk factor for atherosclerosis, cardiovascular morbidity, and cigarette smoking. Smoking interacts with sleep apnea to increase cardiovascular risk (Lavie et al, 2007).

Latent Clinical Factors for the Elderly People The elderly, a factor that is worthy of discussion in relation to the height distribution is the latent clinical factor. It is the rate people, mostly the elderly, have height loss due to ageing. The elderly people have hormonal changes, which are related to loss of bone density. Latent Clinical Factors are clinically unobservable. In the current work of this author‘s observation of the height loss, there is a lack of knowledge about their rate of height loss. On


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the parlance of the latent variable modeling, there might be a true nature, as whether a fast or slow shrinker of height in the elderly people - and this is what really causes subjects to fall into one or the other statistical distribution that one can possibly observe. The latent variable should explain the observable variability. In addition, the latent variable should have a theoretically sound basis. There are many equivalent models of the correlations among observed variables. Hence, a latent variable (or more than one) requires some serious hypothesizing to link the possible relationship of height to sleep disturbance in the elderly people.

Health Insurance Coverage and its Effect on Sleep Education and Sleep Studies For Taiwanese, the National Health Insurance plan in Taiwan provided and provides the expense of PSG, with 1/10 of its co-payments to be paid by a patient per test. Therefore, the subjects were not particularly richer than the average, for any full payment of the expensive PSG. Prior to March 1995, 12.7 million people, about 60 percent of the Taiwanese population were eligible to benefit from thirteen public health insurance plans. More than 8.5 million were uninsured. Many were children and half were over sixty-five. After six years of planning, the Taiwan government launched the National Health Insurance (NHI) program on March 1, 1995. In 2008, 99% of the Taiwanese population are insured. By comparison, National health insurance is not available in the Philippines. There are other issues: urban-learned Western eating habits, patterns of life style, nightlife and entertaining activities into rural parts, versus those in rural areas that either directly or indirectly affect sleep patterns.

The Poor Elderly Get Less Sleep The elderly people living in poverty get less sleep than those in higher SES group. This is an important societal problem, regardless of the various cultural backgrounds. Examples of the influence of poverty on the elderly people can be found, even in advanced countries like U S A. There is recent evidence that the obesity burden tends to shift towards the poor as countries develop (Monteiro, 2004). Obesity has an adverse effect on sleep apnea, and is more prevalent in males than females. Furthermore, many health disparities even are linked to inequalities in education and income (Drewnowski, 2004). Over 47 million Americans uninsured and even more underinsured. Approximately, 18 million Americans suffer from obstructive sleep apnea (OSA). Unfortunately 10-20% of these people are aware of that they have OSA and are being treated. An increasing number of an aging population and obeseity will lead to an increase in OSA. Elderly people who are living in poverty get less sleep than those in higher SES group; this will exacerbate a bad situation ( McCamy Taylor, 2007). In the Mindanao region of the Philippines, women cried out 'we boil bananas for our children when food is not available.‘ In

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some cases, when the Department of Agriculture distributes corn seeds, we cook these seeds instead of planting them. Ironically, they borrow money to acquire these seeds. The cycle of poverty continues, as they are unable to pay for these loans. Moreover, some indigenous people feel that they are 'gradually losing control over their ancestral lands. In some areas, non-indigenous people get titles to indigenous people's lands in connivance with unscrupulous government representatives.' In the Philippines, approximately 16 to 27% of the population would remain poor in 2010. As a result, the Philippine will have to move rapidly if poverty is to be reduced perceptibly.

Poverty and Obesity There are interrelations between socioeconomic factors and obesity when taste, heavy dietary energy, and food prices are employed as superseding factors. Increasingly Americans are becoming overweight and obese while consuming more added sugars and fats and spend a lower portion of their throwaway earnings on food (Drewnowski, 2004). A similar trend occurs in the Philippines and Taiwan. Biofuel production drives up the food price, and damages the environment and speeds up global warming. Food should not be so expensive that many elderly, disabled and homeless people will be unable to feed themselves and their children. The increase food prices can raise people‘s anxiety and adversely affects their sleep quality (Braun and Pachauri, 2006).

National Health Insurance As previously mentioned, by 2005, nearly 99 percent of the Taiwanese population was covered by National Health Insurance (NHI). Despite public satisfaction rates of over 70 percent, an increasing number of elderly people has given rise to changing patterns of health problems. As the proportion of elderly people increased, chronic cardiovascular diseases have replaced infectious diseases as the major health problem among adults. In Taiwan, the Ministry of the Interior is planning to alter its immigration policy by adding a program aimed at attracting foreign white-collar professionals. According to ministry statistics, the Taiwanese birth rate in 2002 was 11.02 percent, compared to 49.97 percent in 1951. The number of children in the average family was 1.34 in 2001, down from 7.04 in 1951. The Ministry of Interior of Taiwan deals with an increasing number of elderly people, developing ways to raise the birth rate and altering the immigration policy. With such an increasing number of elderly people, the problem of sleep disturbance has not been addressed. Like many developing countries, the Philippines are experiencing both rapid urbanization and an ageing population. In the Philippines, with such an increasing number of elderly people, the problem of their sleep disturbance has not been suitably attended.


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Limitations of Cross-Cultural Sleep Studies There is no definite information of the prevalence and severity of obstructive Sleep Apnea in Asian snorers, including Taiwan and the Philippines. Conversely, the relationship between the AHI scores and the immediate consequences in the asymptomatic and/or undiagnosed general elderly population needs more study (Tang 2005, Tang 2006a, Tang 2006b). It is important to have both subjects and controls in the same age group in a sleep study. Due to the lack of WHO reports on Taiwan, together with the delay of publishing a national survey in Taiwan, some sleep studies had no choice but to analyze two different samples (participants) from two different time periods. For example, in a study, the subjects were from 2002 to 2003, while controls were from 1993 to 1996 (Tang, 2007). The limitations of studies such above include the selection of study subjects might be challenged. Such as the above is also potentially subject to sources of bias and variation, and the generalization of the results may be limited. Therefore, the findings in such studies might underestimate the prevalence of sleep-disordered breathing (SDB) in the entire population in a certain country. Hence the relationship between the AHI scores and the immediate consequences in the asymptomatic and/or undiagnosed general elderly population needs more study. The comparison data from a national survey (1993-1996, Taiwan) was used in one of the studies of Taiwanese. Participants in that survey were not taking the nocturnal PSG. The survey reported on the population a few years earlier than the beginning of the sleep study in Taiwan (Tang, 2007), but survey was not published until 1999 for public reference in Taiwan, which was merely two years before the beginning of the sleep study (Tang, 2007). The height and weight measurements should have been obtained from the census data to have validity in any comparison. Unfortunately, comparative year to year comparative data do not exist. The report of 'Elderly Nutrition and Health Survey in Taiwan (1999 to 2000): research design, methodology and content' was not published until 2005, three years and eleven months after the conclusion of a Taiwanese sleep study (Tang, 2007). Most of the sleep studies discussed in this article are cross-sectioned. Most of such variables studied are restricted by the application of a dichotomous measure of urbanicity. Modifications do happen in sleep disturbance and apnea, along with metabolism and dieting habit during the life span; such modifications may decrease the odds of being overweight for those who survive to the age of 70 years and over. Given the cross-sectional nature of most of the studies referred here, elderly participants who live long enough to join the studies naturally were the survivors. On the tapis of such a cross-sectional nature of studies cited in this article, it is difficult to justify that changing metabolism, dieting and nutrition habits across the life span may mitigate the effects of being obese or overweight for those who survive to the older age. Hence, there is a need for the proper longitudinal survey for the future work in this area. Associations between obesity and urbanicity will alter as countries develop, as has the relationship between socio-economic status (SES) and obesity. Current studies are restricted not only to cross-sectional studies as outlined in the aforementioned section, but also in the use of a dichotomous gauge of urbanicity. The measurement of the latter needs improvement. The application of a dichotomous description of urbanicity, while convenient and frequently

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helpful, can as well be challenging (Champion 2004, McDade 2001, Vlahov 2002, and Yach 1990).

Conclusion The study of sleep disturbance in the elderly is a new area of scientific research. This is a research field that has largely been neglected for this age group. Probable reasons for this are numerous. One of the most likely factors may be due to a combination of the lack of documented data, together with the complexity of human sleep itself. This field is an undiscovered entity, especially in sleep research on the age groups mentioned in this article. All patients are vulnerable, especially those who are elderly. Thus, the difficulty is due to the problem faced in obtaining volunteers as well as the philosophical and theological undertones people associate with ''the sleep when they are at the end stage of their life‖. Moreover, there is as well the misconception of sleep study on 'those who haven't many years left anyhow' in general. Additionally, there is difficulty in recognizing cross-cultural differences among the elderly people's sleep disturbance. Hence, as aforementioned, the objective of this article was to provide a broader understanding of the complicated relationship of various aspects of sleep apnea in the age group studied. Results from this article may provide direction for fruitful areas of future research. National differences in epidemiology of sleep apnea may be helpful for better understanding of triggers and pathogenesis of this condition. Thus this article can be used to help establish proper concepts, to improve the wellbeing of the elderly people with sleep disturbance in countries regardless of developing status of the nation. Further study is necessary to investigate whether the differences between two societies are caused the limitation of hospital-based study or by differences in ethnicity. Finally, society helps keep a person 'up to the times', and enables her/him to refurnish her/his ‗mental shop with the latest wares‘, see the 1904 statement by William Osler (18491919) (Osler, 1904).

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Chapter VII

A Novel Model Using Generalized Regression Neural Network (GRNN) for Estimating Sleep Apnea Index in the Elderly Suffering from Sleep Disturbance 唐秉輝 Bingh Tang 1 and Weizhong Yan2 1

New York College of Traditional Chinese Medicine, Mineola, Long Island, NY, USA 2 GE Global Research Center, Niskayuna, NY, USA

Abstract Objective: The main objective of this paper is to present a novel model for classifying senior patients into different apnea/hypopnea index (AHI) categories based on their clinical variables. Methods and materials: The proposed model is a generalized regression neural network (GRNN). Three important variables were first selected from the original 30 clinical variables. The GRNN was trained using 75 patients that were randomly selected from the 117 patients. The remaining 42 patients were used for testing GRNN model. The design parameter of the network, i.e., the spread of the radial basis function, was empirically optimized. To alleviate the model complexity, the original AHI values were dichotomized into two different groups, i.e., AHI>13 and AHI<=13. The use of GRNN for this application appear fairly novel, notwithstanding that there is a host of literature on predicting obstructive sleep apnea (OSA) syndrome from demographic or other easy means to assess clinical variables. Results: The proposed model has sensitivity and specificity of 95.7% and 50.0%, respectively, for the training cases, while 88.0% and 52.9%, respectively, for the testing cases.


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Conclusions: The proposed neural network model has outperformed existing classification approaches in terms of classification accuracy and generalization, thus it can be potentially used in clinical applications, which would lead to a reduction of the necessity of in-laboratory nocturnal sleep studies.

Keywords: AHI, sleep apnea, elderly, GRNN, ROC

Abbreviations AHI AUC BMI ROC ANN GRNN NC NN OSA

= apnea/hypopnea index = area under curve = body mass index = receiver operator characteristics = artificial neural network = generalized regression neural network = neck circumference = neural network = obstructive sleep apnea

Introduction Sleep disordered breathing (SRBD) is present in 4% of men and 2% of women above 40 years of age. However, less than 3% of patients with SRBD syndrome are diagnosed due to lack of awareness of the disease among health care practitioners and patients. Polysomnography (PSG) has been used as a golden standard for diagnosing SRBD, however, this test is available only in selected centers. [1-5] Studies on using neural network techniques for prediction of OSA are fairly sparse until recent years. In 2005, Fontenla et al [6] presented a novel approach for sleep apnea classification. Their goal was to classify each apnea in one of three basic types: obstructive, central and mixed. [6] More recently, Liu et al in 2007 [7, 8] developed an innovative signal classification method capable of differentiating subjects with sleep disorders which cause excessive daytime sleepiness (EDS) from normal control subjects who do not have a sleep disorder. The aim of their study was to develop an artificial neural network to predict sleep disordered breathing in the elderly.

Clinical Subjects and Materials The data were collected during the period from 1 January 2002 to 31 January 2003 at the Sleep Medicine Center, Changhua Christian Medical Centre, Taiwan. While patients‘ confidentiality was maintained, accessing to patients‘ records was approved by the ethics committee of Changhua Christian Medical Centre. Among the subjects who underwent

A Novel Model using Generalized Regression Neural Network (GRNN)…

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nocturnal polysomnography (PSG), no patients with heart failure and chronic obstructive lung disease were admitted. . Also the data belonged to subjects who were younger than 65 years were excluded. As a result, the clinical data included a total of 124 elderly aged from 65 to 88.5 years. Out of the 124 subjects, a total of 117 subjects had both weight and height, from which body mass index (BMI) was calculated. Apnea/hypopnea index (AHI), defined as the number of events of apnea/hypoxia per hour of sleep, was measured from PSG, which documented the objective sleep criteria. Although PSG has been the golden standard for the diagnosis of obstructive sleep apnea syndrome (OSAS), it is highly invasive, timeconsuming, and expensive. The ratio of females/males in this data is 1: 1.7. The mean age of male subjects is 71.6 ± 4.47 years, while that of females is 72.3 ± 5.47 years. All subjects have chief complaints of sleeping disturbance. The reasons for selecting this elderly age group are as follow. First, this field is a rather understudied entity, especially in sleep research on such an age group mentioned in this article. Indeed, all patients are vulnerable, but it is so much as those who are elderly. Thus, the difficulty of sleep study is due to the problems faced in obtaining volunteers as well as the possible philosophical and theological under-tones that people in general associate with ‗the sleep when they are at the end stage of their life'. Moreover, there is as well the misconception of sleep study on 'those who haven't many years left anyhow' in general. Next, there are more than half of community-living people aged 65 year and over experience sleep disturbances. Third, sleep onset is often reported to be more difficult and nighttime awakenings more prevalent in the elderly. The datum source of clinical subjects includes the corresponding author's own study of 124 elderly aged from 65 to 88.5 years. Predominantly, the data of the total sleep time (TST), except that related to body height and its distribution, have been reported elsewhere [9].

Nocturnal in-Laboratory Polysomnography Nocturnal polysomnography (PSG) (Alice 4 Sleep Diagnostic System, Respironics, Carlsbad, Calif., USA) was done from about 9:30 pm to 6:30am next morning in the sleep laboratory. The following parameters were measured and recorded by the PSG: (i) chest and abdominal wall motion by uncalibrated respiratory inductance plethysmography; (ii) heart rate by ECG; (iii) inspired and end-tidal carbon dioxide pressure (PETCO2), sampled at the nose or mouth at a rate of 60 mL/min by mass spectrometry (model 1100 Medical Gas Analyzer, Perkin Elmer; Pomona, CA) or by capnography (model 1000 Capnograph, Nellcor, Hayward, Calif. USA); (iv) combined oral nasal air flow, sampled with a three-pronged thermistor placed at the upper lip; (v) arterial oxygen saturation by pulse oximetry (model N 200, Nellcor, Hayward, Calif., USA); (vi) oximeter pulse wave form; (vii) electro-oculogram; (viii) EEG in overnight PSG; (ix) chin electromyogram; (x) actigraphy (placed on the hand); and (xi) microphone placed over the neck to monitor snoring. The transducers and lead wires permitted normal positional changes during sleep. Bedtime and awakening time were at each subject‘s discretion; the PSG was terminated after the final wakening.

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Clinical Classification of Obstructive Sleep Apnea Syndrome Apnea was defined as a decrease in airflow of ≥ 90% for a minimum of 10 seconds. Hypopnea was defined as ≥ 30% decrease in airflow and desaturations required a ≥ 3% decrease in oxygen saturation for a minimum of 10 seconds. The apnea hypopnea index (AHI) was calculated as the sum of apneas and hypopneas divided by nocturnal hours of sleep. Based on the protocol of American Academy of Sleep Medicine Task Force (1999) [11].The degree in severity of sleep apnea is defined in Table 1. Table 1. Degrees of Severity of Sleep Apnea (elevated AHI) Sleep variables with Apnea (changes of AHI) Apnea (AHI<5) Apnea (AHI 5~15) Apnea (AHI 15~30) Apnea (AHI>30)

The Degree Zero degree first degree, second degree, third degree,

In terms of the staging of sleep, it follows Rechtschaffen et al‘s criteria (1963) [12].

Methods Generalized regression neural network (GRNN) is a special type of neural networks. GRNN is a universal approximator that can approximate a continuous function to an arbitrary accuracy, given a sufficient number of neurons [14]. Comparing to conventional multilayer perceptron networks, GRNN has several advantages, including 1) it can accurately approximate functions from sparse and noisy data; 2) it can converge to the conditional mean surface with increasing the number of data samples; 3) it only has one design parameter (i.e., spread factor); and 4) it is easy to train. It is these unique advantages associated with GRNNs that make us to choose GRNN as our model for predicting OSA syndrome. In this study, the single design parameter, i.e., spread factor, of GRNN is obtained via empirically optimization. The input variables to the GRNN model are also empirically determined based on classification performance. The three variables used for our final model are BMI, neck circumference (NC), and nocturnal total sleep time (TST). It is worth pointing out that TST values used in our model are dichotomized into two levels, <=6 hours and > 6 hours, before input to the model. It is also interesting to note that including age as inputs to our model does not improve our model performance. To alleviate the model complexity, the original AHI values (the dependent variable of our model) were also dichotomized into two different groups, i.e., AHI>13 and AHI<=13. That is, our GRNN model is designed to perform 2-class classification.


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Results The 117 cases are randomly split into two disjoint subsets: 75 cases for training, whereas 42 cases for testing (validation). To evaluate the goodness of the GRNN model, following performance metrics are used in this study: 1) Accuracy; 2) Sensitivity/specificity; 3) PPV/NPV; Kappa statistics; and 4) AUC of ROC.

GRNN Performance Figure 1 shows the ROC curves of the GRNN model for both the training and testing sets, respectively. For the training set, the area under curve (AUC) of the ROC is 0.8405 with 95% confidence interval from 0.8304 to 0.8506. For the testing set, the AUC calculated for this ROC is 0.751 with 95% confidence intervals between 0.728, and 0.77.

Figure 1. ROC curve for the training set

Given the fact that the desired requirements for sensitivity and specificity are unknown, we choose the decision threshold for GRNN model to be 0.4, which gives the sensitivity and specificity of 95.7% and 50%, respectively, for training set. The confusion matrices corresponding to the decision threshold of 0.4 are given in Table 2, from which other performance measures are derived. Those performance measures are summarized in Table 3.


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Table 2. Confusion matrix of the training and testing sets (a)

(b)

Predicted AHI< =13

Truth

AHI< =13 AHI> 13

14

Predicted AHI >13

AHI<= 13

14

Truth 2

45

AHI<= 13 AHI>1 3

AHI >13

9

8

3

22

Table 3. Summary of performance metrics of GRNN model Performance metrics Accuracy Sensitivity Specificity Positive predictive value Negative predictive value Kappa (95% CI) AUC (95% CI)

Training set 0.787 0.957 0.500 0.763 0.875 0.501 [0.302, 0.700] 0.8405 [0.830, 0.851]

Testing set 0.738 0.880 0.529 0.733 0.750 0.430 [0.154, 0.705] 0.751 [0.728, 0.774]

By looking at the Table 3, it can help to identify subjects with moderate to severe degree OSAHS (the second and third degrees) who need PSG badly, but were misclassified as AHI <=13 by the model, with a rate of 12%. Among the total five (two in the training set whereas three in the testing set) being misclassified as AHI <=13, there were merely one with AHI >25, whereas the other >40. The rest of three were all had AHI < 18 per hour.

From Table 2 one can observe the followings. Using this model, for the 47 subjects whose AHI measured from the nocturnal sleep study with in-laboratory PSG is greater than 13, 45 were correctly classified, whereas 2 was misclassified as AHI being less than or equal 13. Out of 42 testing subjects, there are 25 subjects whose AHI is greater than 13. For those 25 subjects, our model correctly classifies 22 of them while misclassifies 3, which gives the sensitivity of 88.0%. Similarly, for the 17 subjects whose AHI is less than or equal to 13, our model correctly classifies 9 and misclassifies 8, which yields the specificity 52.9%. Characteristics of the two misclassified subjects are listed in Table 4, from which one can see that both subjects are women and their AHIs are 17.6 and 16.2, respectively. Characteristics of the three subjects whose AHI is greater than 13 but misclassified as AHI being less than 13 are also listed in Table 4 . Prof. zz Tang: We need some text here for each of tables/figures we refer to. It looks strange to me if we leave nothing here while each table/figure has a long legend.


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Table 4. Misclassified cases Sex Age For training set F 64.85 F 72.96 For testing set F 72.53 F 69.88 M 66.72

High

weight

BMI

NC

Latency

TST

Snore

RDI/T

150 150

48.2 54.3

21.42 24.13

34 35

12 8

351 247.5

534 0

17.6 16.2

164 159 145.5

57.5 53.1 54

21.38 21.00 25.51

34.5 35 34

6.5 22.5 38.5

315 295 227.5

674 752 1399

40.4 14.2 25.5

The un-weighed likelihood ratios for the training set are 1.914 and 0.086 for conventional positive and negative, respectively. The un-weighed likelihood ratios for the testing set are 1.868 and 0.227 for conventional positive and negative, respectively. Table 5 a. Comparison among different models – training set Performance metrics Accuracy Sensitivity Specificity Positive predictive value Negative predictive value Kappa (95% CI) AUC (95% CI)

Linear regression 0.667 0.809 0.429 0.704 0.571 0.250 [0.026, 0.474] 0.628 [0.613, 0.642]

Logistic regression 0.667 0.809 0.429 0.704 0.571 0.250 [0.026, 0.474] 0.636 [0.622, 0.651]

GRNN 0.787 0.957 0.500 0.763 0.875 0.501 [0.302, 0.700] 0.841 [0.830, 0.851]

Table 5 b. Comparison among different models – testing set Performance metrics Accuracy Sensitivity Specificity Positive predictive value Negative predictive value Kappa (95% CI) AUC (95% CI)

Linear regression 0.667 0.800 0.471 0.690 0.615 0.028 [-0.011,0.574] 0.617 [0.590,0.643]

Logistic regression 0.690 0.800 0.529 0.714 0.643 0.339 [0.05, 0.628] 0.614 [0.588, 0.641]

GRNN 0.738 0.880 0.529 0.733 0.750 0.430 [0.154, 0.705] 0.751 [0.728, 0.774]

Comparison with the Results of other Regression Models To demonstrate performance superiority of GRNN model proposed in this study, two other models, that is, linear regression and logistic regression, are developed for the same data and the results are compared and shown in Tables 5a and 5b for the training and testing


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sets, respectively. From Tables 5, one can see clearly that GRNN model performs significantly better than both linear and logistic regression models do.

Comparison with Results of other Studies To better appreciate our model performance, results from our model are further compared with those from other studies (See Table 6). While all three other studies show relatively lower sensitivity (ranging from 74% to 85%), ours has higher sensitivity (88% and 95.7% for testing and training respectively). It is worth noting that since no requirement for sensitivity and specificity is given, the comparison among different studies is difficult. Table 6. The comparison among various studies FEIN et al Method

#

Sensitivity 74% Specificity 93% AHI predicted >=10 Probability NA cutoff-point

Kapuniai Crocker et al et al Logistic # regression 78"% 85% 67% 61% >10 >15

This study This study (Training group) n=75 (Testing group) n=42

NA

>= 0.15

GRNN

GRNN

95.7% 50.0% >13

88.0% 52.9% >13

>=0.40

>=0.40

# According to the original respective authors, their methods were based on derivation from ascribing a point value to a number of clinical characteristics that have been indicative for OSAS.

Comments on Sensitivity and Specificity It is well understood that designing a diagnostic system to achieve both high sensitivity and specificity is almost impossible in real-world applications. Thus striking a best trade-off between the two is the most practical solution. Obviously choosing such trade-off between sensitivity and specificity is problem-dependent. That is, there are no such thing as good numbers for sensitivity and specificity. For instance, for diagnosing clinically significant ankle fractures, the Ottawa Ankle Rule had a specificity of only 50% but a sensitivity of 100%. Henceforth, not all patients will meet the decision rule criteria, but in their case of those who do, the necessity for an ankle radiograph can be disregarded. The Ottawa Ankle Rule has a diagnostic gray zone of about 70%, but in the field testing, it is estimated that the rule has reduced the necessity for ankle radiography by 30% (Siellet al) [20]. For another example, due to the severe morbidity associated with Obesity Hypoventilation Syndrome (OHS), some researchers selected a highly sensitive threshold of serum bicarbonate level. A threshold of 27mEq/l had a sensitivity of 92% and a specificity of 50%. Merely 3% of patients with a serum bicarbonate level <27 mEq/l had hypercapnia compared to 50% with a serum bicarbonate ≥27 mEq/l. In their conclusion, OHS is common


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in severe OSA. A normal serum bicarbonate level excludes hypercapnia and an elevated serum bicarbonate level should prompt clinicians to measure arterial blood gases. [21, 22] There are several other instances in the literature of sleep medicine. For example, an Italian version of the Epworth sleepiness scale (ESS) is an easy-to-use form useful for preliminary screening of daytime sleepiness level in specialist settings. Noticeably, the (ESS) cut-off scores associated with the best sensitivity and specificity were set to be 12 and 17. For the 5-min multiple sleep latency test (MSLT) cut-off, sensitivities were 87% and 47% for cutoff scores of 12 and 17 respectively, andspecificities of 39% and 74%. For the 8-min MSLT cut-off, sensitivities were 84% and 49%, and specificities of 50% and 88%. [22] In this paper our model achieves the sensitivity of 95.7% and specificity of 50.0 % for the training set, while 88.0%, and 52.9%, respectively, for the testing set. Specificity of equal or greater than 50% while sensitivity is higher than 85% indicates that our model developed in this paper is reasonable. Our sensitivity and specificity results are based on the decision threshold of 0.40, which can be tuned if costs associated with false positive and false negative errors are known.

Discussion It is true that the widely recognized definition of sleep apnea has the round numbers of AHI cutoff = 5, 10, and 15. Conversely, our data did indicate that using AHI of 13 as cutoff is better than using 15. A brief review of the following mechanisms may help to understand the issues that we shall advance latter on.

The Reason Why We Selected AHI Cut Off of 13 Events per Hours is as Follows While the accepted AHI cut offs for defining OSA severity is somewhat arbitrary, as suggested by the current authors and others, using an AHI cut off of 13 instead of 15 events per hour seems ‗unusual‘. Nevertheless, this was used merely based on our previous clinical experience. Furthermore, our selection of the criterion is clinically and not statistically. What is the actual clinical meaning of the two events represented by a cutoff of 13 (more precisely, 13.21) and not 15 is as follows. Clinically, we do observe a better sleep efficiency (%) for those patients whose AHI were < 13.21 but not for those whose AHI > 13.21 (p=0.05). On the contrary, when we use AHI cutoff of 15, there is no difference between AHI <15 and > 15 these two groups. It can thus be stated that the employing of AHI cutoff of 13 is based on clinical finding of sleep efficiency (%) The employing of AHI cutoff 13 is not based on this GRNN modeling here. OSA was defined by a polysomnographical AHI cut-off that has been considered by investigators to be clinically important. The cutoff of 13 for AHI does fall into the current definition of sleep apnea. Although the value was derived from the ROC, its clinical significance was particularly for symptomatic elderly patients. In our model, with AHI = 13

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is obvious for the reason as follows. The cutoff value of 13 for AHI falls into the upper range of mild sleep apnea. In addition, there are the clinical significances of any particular cut off points between AHI 10 and 20 9. In fact, AHI=15 has never been the absolute and sole point of cut-off. It all dependents on the nature of disease, and other clinical factors involved along with the setup of the device used in the measurement. For example, the cut-off value of estimated AHI set at 17, instead of 15, was optimal for the differentiation between patients with or without sleep related breathing disorder using the Lifescreen Apnea software from Holter ECG as an accurate, specific and sensitive method for the detection and classification of obstructive and mixed SRBD 19. According to their estimated AHI, 50 (68%) patients were correctly diagnosed. The ROC analysis showed high accuracy of SRBD detection using Est. AHI: AUC – 0.91 with sensitivity – 91.2%, specificity – 87.5%, PPV – 88.6%, and NPV – 88.9%.

Cost Effectiveness Assessment of our Model As shown in the section of RESULTS, with the decision threshold of 0.40, our GRNN model achieves the sensitivity of 95.7% and specificity of 50.0 % for the training set, as well as 88.0%, and 52.9% respectively. If a PSG sleep study were performed only in subjects for whom the model predicted an AHI > 13, the number of PSG required for the 42 subjects in our testing set would have been decreased from 25 to 22, a 12% (3/22) reduction in the number of PSG taken. To assess true cost effectiveness of our model, a cost-benefit analysis on the numbers of false positive an false negative case is needed, which can take into account the impact of quality of life on the subject (patient) and the family, and the financial impact on the community. in our model, the specificity attained of >=50% when sensitivity is high (>=88.0%), it is definitely indicative that the methodology used in our model is geared up for prime time. It is important to note that our study conducted in this paper here is not a CPAP treatment study,even though it is indeed on diagnostic PSG. We intend to develop into a CPAP treatment study in future, with our aim in cost–effective purpose and are looking forward in seeing a potential savings. With this model, we can determine if a subject with complaints of poor sleep and with an AHI<13 requires a CPAP treatment, which leads to an earlier therapic action without the need of a diagnostic PSG. .

Limitations of Study Some clinical variables, such as TST, used in this model for estimating AHI, may require some device to measure the sleep time as accurate if possible. There is an exception to the aforesaid. For example, sleep latency, which has been removed as an independant (input) variable after the initial trial in this model, may not be accurately measured by actigraphy, not to mention by subjective reports. By comparison, data of the total sleep time except sleep


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latrency is some what easier to be measured than sleep latency per se. Devices such as simple monitors using web-camera with a home personal computer (PC) can serve the purpose. They are not expensive. Hence such measurements for TST are cost-eefective. As compared to the portable home monitoring for OSA, the disadvantages follow. Generally, the set-up to be used at the examinees‘ homes using portable recording with an ambulatory monitoring system recording nasal/oral airflow (thermistor) without electroencephalogram (EEG) or nasal airway pressure or pleural pressure measurements. By contrast, it is most important to note that in this context, the recording system that are described here for the ambulatory monitoring system indeed lacks to detect upper airway resistance. On the other hand, the moderate specificity depicted in our model may suggest that when we use this model, the chance of co-applying other expensive extra tests is not indicated. Although the economics of these additional screening, web-camera and P C, may not be disregarded, the expense of setting up a web-camera with the P C is really minimal, since often home P C is preexisting. Using TST as a variable in this model is meaningful for the reason as follows. First of all, TST has been one of the ‗good‘ (friendly) variables selected by the algorism used in this model. Nevertheless, one might still argue that it might be ‗meaningless to use a PSG variable such a TST to predict OSA‘. At first glance, such a statement sounds ‗plausible‘. However, it is neither logical nor acceptable. Unlike other sleep medicine variables, TST is one of the few that can be measured easily and precisely with web-camera and a home P C at home instead of the Sleep Medicine Laboratory. Second, whoever believes that PSG and actigraphy, other than PSG, are the only two precise ways in obtaining a record of an individual‘s TST may be misleading. Third, TST, unlike sleep latency, can be used as an easily obtaintable clinical datum.

Conclusions Generalization of this GRNN model over other populations in general medicine is possible. It all depends on the various combinations of influence among age, gender, weight, and BMI. They may attribute a significant explanatory power for the AHI, above and beyond what has been explained by the samples in the current study.

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[19] Siell I, Greenberg G, McKnight R, Nair R., McDowell R, et al Decision rules for the use of radiography in acute ankle injuries: refinement and prospective validation. JAMA 1993;269:1127–1132. [20] Tsai W, John E., Remmers J, Brant R, Flemons W, et al Decision Rule for Diagnostic Testing in Obstructive Sleep Apnea. American Journal of Respiratory and Critical Care Medicine, 2003, 167: 1427-1432 [21] Mokhlesi B, Tulaimat A, Faibussowitsch I, Wang Y and Evans A. Obesity hypoventilation syndrome: prevalence and predictors in patients with obstructive sleep apnea. Sleep and Breathing 2007, 11 (2) [22] Vignatelli L, Plazzi G, Barbato A, Ferini-Strambi A, Manni R, et al and on behalf of GINSEN. Italian version of the Epworth sleepiness scale: external validity. Neurological Science, 23; Neurological Science, 2003, 23;6: 295-300 [23] Collop N, Anderson W, Boehlecke B, Claman D, Goldberg R, et al American Academy of Sleep Medicine Clinical guidelines for the use of unattended portable monitors in the diagnosis of OSA in adult patients. Portable Monitoring Task Force of the American Academy of Sleep Medicine. J Clin Sleep Med. 2007 Dec 15;3(7):737-747. [24] Ancoli-Israel S, Kripke D, Klauber M. Morbidity, mortality and sleep-disordered breathing in community dwelling elderly. Chest 1996; 109: 890–5. [25] Lavie P, Lavie L, Herer P. All-cause mortality in males with sleep apnea syndrome: declining mortality rates with age. Eur. Respir. J. 2005; 25: 514–20. [26] Kohavi and Provost F. Glossary of Terms- Special Issue on Applications of Machine Learning and the Knowledge Discovery Process. Machine Learning, 1998;30:271-4 [27] Berger V: Improving the information content of categorical clinical trial endpoints. Control Clinical Trials 23:502-514, 2002 [28] Ohayon M: The effects of breathing-related sleep disorders on mood disturbances in the general population. J Clin Psychiatry 2003, 64:1195-1200 [29] Schröder M and O'Hara R. Depression and Obstructive Sleep Apnea (OSA) Annals of General Psychiatry 2005, 4:13 - 19 [30] Collop NA, Anderson WM, Boehlecke B, Claman D, Goldberg R, et al Portable Monitoring Task Force of the American Academy of Sleep Medicine. 2007



Chapter VIII

Hormones and Insomnia Axel Steiger and Mayumi Kimura Max Planck Institute of Psychiatry, Munich, Germany

Abstract Human sleep is characterised by an electrophysiological component, which is recorded by the sleep EEG, and by distinct patterns of the secretion of various hormones. A bidirectional interaction exists between these two components of sleep. During disturbed sleep, changes of sleep EEG and of hormone secretion occur. For example during an episode of depression and during normal ageing, slow wave sleep and growth hormone (GH) secretion decrease whereas wakefulness increases and the activity of the hypothalamo-pituitary-adrenocortical (HPA) system is changed. During depression and during primary insomnia, elevated HPA activity is mirrored by increased cortisol levels. There is much evidence from preclinical and clinical studies that various neuropeptides and steroids participate in sleep regulation, and that changes in their activity contribute to disturbed sleep. The reciprocal interaction of the peptides growth hormone-releasing hormone (GHRH) and corticotropin-releasing hormone (CRH) plays a keyrole in sleep regulation. In young normal male subjects, GHRH promotes slow wave sleep and GH secretion, whereas CRH exerts opposite effects. Changes in the GHRH/CRH ratio in favour of CRH are thought to result in disturbed sleep, particularly in insomnia-related depression (CRH overactivity) and in normal ageing (reduced GHRH activity). Treatment with a CRH-1 receptor antagonist was shown to improve sleep in patients with depression. The menopause is a major turnpoint of sleep quality in women. In postmenopausal women the levels of circulating estrogens and progesterone are low. Replacement therapy with these steroids improved sleep in postmenopausal women.

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Axel Steiger and Mayumi Kimura

Introduction Sleep is a time of considerable activity in various endocrine systems. A bidirectional interaction exists between the sleep electroencephalogram (EEG) and neuroendocrine activity during sleep. Changes of the sleep structure result in changes of hormone secretion and vice versa. Certain hormones, particularly neuropeptides and neurosteroids were identified as common regulators of sleep EEG and peripheral hormone secretion. There is now much evidence that changes in their activity contribute to impaired sleep including insomnia. In young normal subjects during the first half of the night, the major amounts of slow wave sleep (SWS) and the growth hormone (GH) surge occur, whereas the levels of corticotropin (ACTH) and cortisol reach the nadir. In contrast during the second half of the night, rapid eye movement (REM) sleep, ACTH and cortisol preponderate whereas GH release is low (Weitzman, 1976). This pattern of sleep-endocrine activity suggests that (i) a reciprocal interaction exists between the hypothalamo-pituitary-somatotrophic (HPS) and the hypothalamo-pituitary-adrenocortical (HPA) systems and (ii) there exist common factors regulating sleep EEG and the nocturnal hormone secretion as well. It appears likely that the key hormones of the HPS and HPA systems, GH-releasing hormone (GHRH) and corticotropin-releasing hormone (CRH) are such factors and that their reciprocal interaction plays a major role in the physiological regulation of sleep. Finally changes in the balance between GHRH and CRH appear to contribute to impaired sleep. This chapter aims to summarize the state of the art in the field of endocrine mechanisms of insomnia and the related basic research.

Sleep-Endocrine Changes in Patients with Insomnia In an early study Adam et al. (1986) compared poor and good sleepers, selected on the basis of their stated opinion about the sleep. According to sleep EEG the poor sleepers woke up more often and achieved half an hour less sleep. They tended to have higher urinary cortisol and adrenalin excretion. In a preliminary study Vgontzas et al. (1998) found an association between chronic insomnia and the activity of the stress system. The participants of the study were 15 younger adult patients with insomnia, less than 50 years old. Each patient was recorded in the sleep laboratory for three consecutive nights. The 24-hour levels of urinary free cortisol were positively correlated to the total wake time. Furthermore the 24hour urinary levels of the catecholamine metabolites dihydroxyphenylglycol (DHPG) and dihydroxyphenylacetic acid (DOPAC) showed a positive correlation with the percentage of sleep stage 1 and intermittent wakefulness. Also norepinephrine tended to correlate positively with these sleep-EEG variables. Urinary GH excretion was detectable in only three of the subjects. The authors concluded that in chronic insomnia the activity of both limbs of the

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stress system, the HPA and the sympathetic system as well relate positively to the degree of objective disturbance. The same authors (Vgontzas et al., 2001a) investigated the sleep EEG of young patients with insomnia and normal controls during four consecutive nights. During the fourth day plasma measures of the HPA hormones ACTH and cortisol were performed. During baseline nights sleep latency and wakefulness were more extended or longer respectively in the patients than in the controls. The 24 hours ACTH and cortisol levels were significantly elevated in the patients. Within 24 hours the greatest elevations of these hormones were observed in the evening and in the first half of the night. Insomniac patients with high degree of objective disturbance secreted a higher amount of cortisol compared to those with a low degree of sleep disturbance. Pulsatile analysis showed a significantly higher number of peaks per 24 hours in the patients than in the control subjects, whereas no difference in the temporal pattern of ACTH or cortisol secretion were found by cosinor analysis. The authors concluded that insomnia is associated with an overall increase of ACTH and cortisol secretion, which, however, retains a normal circadian pattern. They suggested that these findings are consistent with a disorder of CNS hyperarousal rather than one of sleep loss. In a group of seven male patients with a severe chronic primary insomnia, evening and nocturnal cortisol levels were significantly increased compared to matched controls. Evening cortisol correlated with the number of nocturnal awakenings in patients and controls. Furthermore the patients showed significant correlations between several sleep-EEG parameters and the cortisol secretion during the first four hours of the night (Rodenbeck et al., 2002). In contrast, in another study nocturnal cortisol levels of patients with insomnia did not differ from those of normal controls, whereas the nocturnal melatonin production was significantly diminished in the patients (Riemann et al., 2002). After awakening salivary cortisol decreased in patients with primary insomnia (Backhaus et al., 2004). The authors suggest that its decrease may be related to nocturnal cortisol activation after an increased number of nocturnal awakenings. Insomnia is a frequent symptom in patients with depression. Accordingly their sleep EEG shows characteristical changes consisting of (Armitage, 2007, Benca et al., 1997, review: Reynolds & Kupfer, 1987): (i) impaired sleep continuity (prolonged sleep latency, increased number of intermittent awakenings, early morning awakenings), (ii) changes of nonREM sleep (decreases of SWS, slow wave activity [SWA] and sleep stage 2, a shift of SWS and SWA from the first to the second sleep cycle in younger patients), (iii) REM sleep desinhibition: a shortened REM latency or sleep onset REM periods (SOREMPs), REM latency (0-20 min), prolonged first REM period, enhanced REM density (measure of the frequency of rapid eye movements) particularly during the first REM period. A robust finding in depressed patients is elevated levels of the hormones of the hypothalamo-pituitary-adrenocortical (HPA) system cortisol and corticotropin (ACTH) throughout the night (Antonijevic et al., 2000c, Steiger et al., 1989, Steiger, 2007) or throughout 24 hours (Linkowski et al., 1987), respectively, in comparison to normal control

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subjects. Nocturnal GH secretion is blunted in most studies in depressed patients (Jarrett et al., 1990, Steiger et al., 1989, Voderholzer et al., 1993). These finding suggest a crucial relationship between shallow sleep, HPA overactivity and low GH levels in patients with depression. In a longitudinal study sleep EEG and hormone secretion were compared in acute depression and recovery (Steiger et al., 1989). During acute depression characteristical sleepEEG changes were found. These persisted after recovery and the time spent in sleep stage 4 even decreased. Also GH levels were low at both examinations. In contrast cortisol levels decreased after recovery. This finding is in line with various observations showing that HPA overactivity is a state marker of depression. Obviously cortisol normalizes independently from sleep. Therefore hypercortisolism in depressed patients is unlikely to be a consequence of shallow sleep. The persistence of most sleep-EEG (Kupfer et al., 1993) and GH changes (Jarrett et al., 1990) in remitted patients has been confirmed over a period of three years. It appears likely that the metabolic aberrances during acute depression result in a biological scar which is mirrored by the persistence of sleep-EEG and GH changes after recovery. This hypothesis is further supported by a study in male patients who survived severe brain injury (Frieboes et al., 1999). Several months after the injury, cortisol levels of these patients were in the range of normal controls. In contrast, the time spent in sleep stage 2 was reduced and GH levels were blunted. Whereas cortisol concentrations were normal at the time of examination in this study, it appears likely that either HPA overactivity due to stress under the intensive care situation after brain injury or treatment with glucocorticoids in some patients contribute to the changes of sleep EEG and of GH levels. Interestingly there are similarities in sleep-endocrine changes during depression and during normal ageing. As early as during the third decade of the lifetime, a continuous decline of SWS, SWA and GH starts. In male subjects near to the onset of the fifth decade, the GH pause occurs. From then nearly no GH release occurs. In females the menopause and the GH pause are related. Whereas in male subjects sleep quality declines continuously throughout the life span, in females the menopause is the major turnpoint in sleep quality (Ehlers & Kupfer, 1997). There are controversial reports on the influence of age on HPA hormones. Elevated and unchanged cortisol levels as well have been reported in elderly subjects. Age-dependent increases of mean cortisol levels and of cortisol nadir and, selectively in women, of the acrophase were found in the study which includes the largest sample of normal human adult subjects over a lifetime. The pattern of cortisol secretion was preserved in the elderly, whereas the amplitude was dampened and the morning rise appeared advanced (Van Cauter et al., 1996). From clinical practice, it is well known that changes of sleep-wake behaviour are frequent symptoms of disorders of the thyroid gland. Hyperthyroidism is linked with insomnia whereas fatigue occurs frequently in patients with hypothyroidism. Astonishingly only a few data on sleep EEG in these diseases are available. Reduced SWS was reported in patients with hypothyroidism in comparison to normal controls. After therapy these changes turned to normal (Kales et al., 1967). In clinical practice sedating antidepressants are often used for treating insomnia. The effects of the tricyclic doxepin on nocturnal sleep and plasma cortisol levels were tested in 10


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patients with chronic insomnia between 1700 and 0800 h. Single infusions of placebo and 25 mg doxepin were given according to a double-blind randomized crossover design. Afterwards all patients received 70 mg doxepin orally for three weeks in an open study. Both doxepin administration forms improved sleep EEG and reduced mean cortisol levels. The duration of the quiescent period of the cortisol rhythm was significantly prolonged after both doxepin administrations compared to placebo. The authors suggest that the sleep-improving effects of doxepin are mediated at least partly by a normalization of the HPA system (Rodenbeck et al., 2003). Similar effects were observed after sleep-improving antidepressants in patients with depression. In a four week double blind clinical trial, the effects of the tricyclic antidepressants trimipramine and imipramine on the sleep EEG and on nocturnal secretion of HPA hormones were compared in 20 male inpatients with major depression, whereas both treatments produced rapid significant clinical improvement of depression the two drugs had markedly different influences on sleep-endocrine activity. Trimipramine enhanced REM sleep and SWS, whereas imipramine suppressed REM sleep and showed no effect on SWS. Total sleep time and the sleep-efficiency index increased after trimipramine, but not after imipramine. The nocturnal cortisol secretion decreased with trimipramine but remained unchanged with imipramine. Imipramine, but not trimipramine induced a decrease in GH secretion during the first half of the night (Sonntag et al., 1996). Already at the second day of treatment of depressed patients with the noradrenergic and specific serotoninergic antidepressant mirtazapine, sleep continuity was improved. This effect persisted after four weeks, when SWS, low-delta, theta and alpha activity decreased. Furthermore cortisol and ghrelin levels were reduced, whereas leptin and melatonin levels increased. ACTH and prolactin remained unchanged. This study shows a parallel improvement of sleep and a blunting of cortisol levels in patients with depression (Schmid et al., 2006).

Hypothalamo-Pituitary-Adrenocortical (HPA) System The HPA system mediates the reaction to acute physical and psychological stress and is essential for the individuals' survival. The cascade of HPA activity starts with the release of CRH from the parvocellular neurones of the paraventricular nucleus of the hypothalamus. This results in the secretion of ACTH from the anterior pituitary gland and finally in the secretion of cortisol (in humans) or corticosterone (in rats) from the adrenocortex. Nonpharmacological manipulations which help to study the interaction between sleep EEG and hormones include sleep deprivation and nocturnal awakenings. The pioneering work of Weitzman (1976) led to the still valid conclusion that the pattern of cortisol secretion is widely dependent on a circadian rhythm, whereas manipulation of the sleep-wake pattern causes subtle changes of HPA secretion. In a first investigation of this group, control subjects underwent a repetitive three hour sleep-wake cycle for 10 consecutive days. Each of the cycles consisted of two hours of wakefulness and one hour sleep. Cortisol was consistently low during the intervals with sleep and during the wake periods in each cycle, independently of circadian time (Weitzman, 1976). In a four days protocol, a baseline investigation was followed by sleep deprivation. On day 3, the proband was allowed to sleep at a time 12 hours

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later than usual. On day 4, he slept again at his usual sleeping time. During the first four hours after sleep onset, cortisol was low even when sleep took place during the time when the subject was usually awake (Weitzman et al., 1983). There exist very few reports on HPA activity at several intervals during and after partial and total sleep deprivation. During the night of sleep deprivation, enhanced and unchanged cortisol levels as well were reported (Steiger, 2002). In the recovery night following one night of sleep deprivation, cortisol was unchanged in young and elderly normal subjects compared to the baseline condition (Spiegel et al., 1999). In the evening of the day after partial or total sleep deprivation, cortisol was enhanced (Leproult et al., 1997). Similarly the evening level of cortisol was higher when sleep in normal young men was restricted to four hours per night for six days (Spiegel et al., 1999). In the recovery night after four nights with restricted sleep, cortisol levels were blunted during the second half of the night (Follenius et al., 1992). A delayed sleep onset in controls was followed by a later occurrence of the cortisol rise (Fehm et al., 1993). Patients with depression were studied during three consecutive nights before, during and after sleep deprivation. Saliva samples of cortisol were collected during daytime before and after the sleep deprivation night. During the night of sleep deprivation, cortisol levels were significantly higher than at baseline. Daytime cortisol levels during the first half of the day were higher than at baseline in the patients who responded to sleep deprivation but not in the nonresponders. During recovery sleep, cortisol secretion returned to baseline values. The authors concluded that the data demonstrate a significantly stimulatory effect of one night of sleep deprivation on the HPA system in depressed patients (Voderholzer et al., 2004). In animal studies the effect of sleep deprivation appears to be not only a consequence of sleep loss but also partly a consequence of the procedure that is used for sleep deprivation, which is the arousal resulting from being kept awake (Rechtschaffen et al., 1999). For example, mice that were kept awake by minimal stimulation and sounds have low glucocorticoid levels, whereas animals that kept awake by letting them engage in social activities with other mice have distinctly elevated corticosterone levels (Meerlo & Turek, 2001). In rats 27 hours of sleep deprivation led to increases of CRH levels in the striatum, limbic areas and pituitary, whereas hypothalamic CRH was reduced. Significant decreases in CRH binding were found in the striatum and pituitary (Fadda & Fratta, 1997). An in vivo microdialysis study in rats showed a marked rise in corticosterone levels in the brain during sleep deprivation (Penalva et al., 2003). In all these data suggest that changes of HPA secretion, particularly elevated HPA levels are a frequent consequence of restricted or disrupted sleep. In the rat CRH gene transcription levels increase during the dark period, when the animals are active, and decrease in the morning and throughout the light period (Watts et al., 2004). In the Lewis rats, the release of CRH is diminished due to hypothalamic gene defect. These rats spend less time awake and more time in SWS than intact strains (Opp, 1997). Vice versa spontaneous wakefulness was reduced in rats by a CRH antisense oligodeoxynucleotide (Chang & Opp, 2004). These data suggest that CRH exerts a physiological role in the maintenance of wakefulness and that it impairs sleep. In homozygous mice overexpressing CRH in the central nervous system, wakefulness and REM sleep are elevated, whereas nonREM sleep is slightly reduced in comparison to the wildtype and control mice (Kimura et al., 2009).


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Intracerebroventricular (icv) administration of CRH decreases SWS in rats (Ehlers et al., 1986) and rabbits (Obál et al., 1989), and both nonREM and REM sleep in mice (Romanowski et al, 2006; Sanford et al., 2008). SWS is reduced even after 92 hours of sleep deprivation in rats. Furthermore sleep latency and REM sleep increase (Marrosu et al., 1990). When CRH was injected in a pulsatile fashion each hour between 2200 and 0100 hours to young normal men, SWS, REM sleep and GH decreased and cortisol increased (Holsboer et al., 1988). In young normal women in an analogue study protocol, CRH prompted an increase of wakefulness in the second half of the night and a decrease of sleep stage 3 (Schüssler et al., 2008a). The role of age in the sleep-impairing effect of CRH is illustrated by a study comparing young versus middle-aged men. A dosage of CRH which was not effective in young men increased wakefulness and decreased SWS in middle-aged men (Vgontzas et al., 2001b). Treatment of depressed patients with the CRH-1 receptor antagonist R121919 counteracted the characteristical sleep-EEG changes. The time spent in SWS increased compared to baseline after one week and after four weeks of treatment. The number of awakenings and REM density showed a trend towards a decrease during the same time period. Separate evaluation of these changes for two panels receiving different dosages showed no significant effect at lower doses, whereas in the higher doses after the antagonist REM density decreased and SWS increased significantly between baseline and the end of the trial (Held et al., 2004). These results suggest that (i) CRH participates in the pathophysiology of sleep-EEG changes during depression and (ii) CRH-1 receptor antagonism is capable to treat impaired sleep in depressed patients. The neuropeptide vasopressin is a major cofactor with ACTH in the activation of the stress reaction. In rats wakefulness increases after icv vasopressin (Arnauld et al., 1989). Chronic intranasal vasopressin administration however improved sleep in normal elderly subjects (Perras et al., 1999b). The synthetic ACTH (4-9) analogue ebiratide shares several behavioural effects of ACTH whereas it does not affect peripheral hormone secretion. Accordingly GH and cortisol levels were not influenced by repetitive iv administration of the substance whereas sleep latency increased, and during the first third of the night wakefulness increased and SWS decreased (Steiger et al., 1991). Continuous nocturnal (2300 to 0700 h) infusion (Born et al., 1991) and pulsatile iv administration of cortisol (hourly from 1700 to 0700 h) increased SWS (Friess et al., 1994) and SWA (Friess et al., 2004) and decreased REM sleep in young normal control subjects. In the latter study GH levels increased after cortisol. Similarly increases of SWS, SWA and GH and decreases of REM sleep were found in analogue protocols with iv administration of cortisol in elderly men (Bohlhalter et al., 1997) and in patients with depression (Schmid et al., 2008). Since CRH (Holsboer et al., 1988) and cortisol exert opposite effects on SWS (Born et al., 1991, Friess et al., 1994) and GH (Bohlhalter et al., 1997, Friess et al., 1994), it is unlikely that these effects are mediated by increased cortisol levels. In contrast, these changes appear to be the consequence of negative feedback inhibition of endogenous CRH.

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The mixed glucocorticoid receptor and progesterone receptor antagonist mifepristone disrupted sleep distinctly in a single case study (Wiedemann et al., 1992). The effects of acute and chronic glucocorticoid administration on sleep appear to differ. Subchronic treatment of female patients suffering from multiple sclerosis with the glucocorticoid receptor agonist methylprednisolone resulted in shortened REM latency, increased REM density and a shift of the major portion of SWS from the first to the second sleep cycle. These changes resemble the sleep-EEG disturbances in depression (Antonijevic & Steiger, 2003).

Hypothalamo-Pituitary-Somatotrophic (HPS) System GH stimulates protein anabolism and tissue growth. Its synthesis and secretion are stimulated by GHRH and ghrelin and are inhibited by somatostatin. All components of the HPS system participate in sleep regulation. GHRH is an important endogenous sleep-promoting factor. In mice the GH receptor gene is found in the region of chromosome 13 which is linked to SWA (Franken et al., 2001). The expression of hypothalamic GHRH mRNA depends on a circadian rhythm. Its peak is found in rats at the onset of the light period. At this time sleep propensity reaches its maximum in these night active animals (Bredow et al., 1996). Hypothalamic GHRH levels are low in the morning, increase in the afternoon and decrease at night (Gardi et al., 1999). Calcium levels in GABAergic neurons cultured from rat fetal hypothalamus increase when they are perfused with GHRH (De et al., 2002). It appears that many hypothalamic GHRH responsive neurons are GABAergic. After icv administration of GHRH, SWS increases in rats and rabbits (Ehlers et al., 1986, Obál et al., 1988). This effect is also found after GHRH injection into the medial preoptic area of rats (Zhang et al., 1999) and after its iv administration to rats (Obál et al., 1996). Also in young normal male subjects repetitive hourly iv injections of GHRH between 2200 and 0100 h prompt increases of SWS and GH and blunting of cortisol levels (Steiger et al., 1992). The sleep-promoting effect of GHRH in male subjects was confirmed after iv (Kerkhofs et al., 1993, Marshall et al., 1999) and intranasal (Perras et al., 1999a) administration of GHRH. The effects of GHRH on human sleep were investigated in three conditions with change of the GHRH/CRH ratio in favour of CRH in (i) the early morning hours in young normal male subjects, (ii) in healthy elderly men and women and (iii) in patients with depression. These studies showed the following results: (i) After repetitive iv GHRH from 0400 to 0700 h no major changes of sleep EEG were found (Schier et al., 1997). (ii) The sleep-promoting effect of iv GHRH was much weaker in elderly women and men (Guldner et al., 1997) than in young male subjects (Steiger et al., 1992).


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(iii) A sexual dimorphism in the effects of iv GHRH on sleep EEG and HPA hormones was found in drugfree patients with depression of both sexes of a wide age range and in matched normal controls. Cortisol and ACTH concentrations were blunted in male patients and controls whereas in female patients and controls were elevated. Similarly wakefulness decreases and nonREM sleep increases in male patients and controls, whereas opposite sleep-impairing effects occur in women. These data point to a reciprocal antagonism of GHRH and CRH in male subjects, whereas the synergism is suggested in female subjects (Antonijevic et al., 2000b, 2000c). In the rat after GHRH receptor antagonists (Obál et al., 1991) and antibodies to GHRH (Obál et al., 1992), nonREM sleep decreases. In the so- called supermice, the giant transgenic mice, GH is enhanced. In these mice nonREM sleep and REM sleep are elevated compared to normal mice (Hajdu et al., 2002). Dwarf rats showed deficits in the central GHRHergic transmission and reduced hypothalamic GHRH. In these animals the amount of nonREM sleep is reduced compared to control animals (Obál et al., 2001). Also in dwarf homozygous (lit/lit) mice possessing non-functional GHRH receptors, nonREM sleep and REM sleep are reduced (Obál & Krueger, 2004). These data show that the amount of nonREM sleep is high, when the amount of GHRH is high and vice versa GH deficiency and decreases in nonREM sleep are associated. In spontaneous dwarf rats, GH deficiency is found due to mutation in the GH gene. In these animals plasma GH levels were almost undetectable. The expression of hypothalamic GHRH mRNA was increased, whereas GHRH receptor and somatostatin mRNAs were decreased. During the light period REM sleep was reduced, and nonREM sleep was enhanced compared to control rats. EEG delta and theta power decreased during nonREM sleep. After icv administration of GHRH, nonREM sleep increased in spontaneous dwarf rats and controls as well (Peterfi et al., 2006). Unilateral administration of low doses of GHRH to the surface of the rat somatosensory cortex ipsilaterally decreased SWA, whereas higher dosages enhanced SWA. This effects of GHRH on EEG power occurred during nonREM sleep but not during REM sleep. Further the cortical forms of GHRH and its receptor were identical to those found in the hypothalamus and the pituitary, respectively. Cortical GHRH receptor mRNA protein levels did not vary across the light/dark cycle, whereas cortical GHRH mRNA increased with sleep deprivation. These data suggest that cortical GHRH and its receptor play a role in the regulation of localized SWA which is state dependent, as well as their hypothalamic role in nonREM-sleep regulation (Szentirmai et al., 2007c). Sleep deprivation is the most potent stimulus for sleep homeostasis (Borbély et al., 1981). It is thought that GHRH mediates this stimulatory effect. Sleep promotion after sleep deprivation is inhibited by GHRH antibodies (Obál et al., 1992) and microinjections of a GHRH antagonist into the preoptic area of the rat (Zhang et al., 1999). Sleep deprivation causes a depletion of hypothalamic GHRH and decreased hypothalamic GHRH contents (Gardi et al., 1999). Furthermore hypothalamic GHRH mRNA increases and hypothalamic somatostatin decreases after sleep deprivation in rats (Toppila et al., 1997, Zhang et al., 1998). In humans during the recovery night following sleep deprivation, the nonREM sleep

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promoting effect of sleep deprivation was augmented by repetitive iv GHRH injections. Interestingly this effect was shared by CRH injections (Schüssler et al., 2006b). NonREM sleep is decreased by negative feedback inhibition of GHRH after administration of GH in humans (Mendelson et al., 1980) and animals (Obál & Krueger, 2004) or higher icv dosages of insulin-like growth factor-1 (IGS-1) (Obál et al., 1999). Since GH antagonism impairs sleep (Obál et al., 1997) also, GH appears to promote sleep. However chronic GH substitution in patients with acquired GH deficiency did not result in sleep-EEG changes (Schneider et al., 2005). Systemic and icv administration of the somatostatin analogue octreotide reduced nonREM sleep and GH in rats (Beranek et al., 1999). Similarly in young normal male control subjects, intermittent wakefulness increases and SWS decreases after subcutaneous octreotide administration (Ziegenbein et al., 2004). Octreotide is long acting, and its potency is superior to exogenous somatostatin. This explains why sleep EEG remained unchanged after somatostatin administration in young subjects (Kupfer et al., 1992, Steiger et al., 1992). However the same dose of somatostatin which is ineffective in young men impairs sleep in normal elderly women and men (Frieboes et al., 1997). This difference is probably due to a decline of endogenous GHRH during ageing. In rats and cats, somatostatin inhibits GABAergic transmission in the sensory thalamus via presynaptic receptors (Leresche et al., 2000). This mechanism may contribute to the decrease of nonREM sleep after somatostatin. Taken together these data suggest a reciprocal interaction of GHRH on somatostatin in sleep regulation similarly to their role in the regulation of GH secretion. Similar to GHRH repetitive iv, ghrelin administration increases SWS, SWA and GH in young normal male controls (Weikel et al., 2003). In contrast to the decrease of cortisol after GHRH in young men (Steiger et al., 1992), ACTH and cortisol levels are elevated after ghrelin (Weikel et al., 2003). During the recovery night after sleep deprivation, ghrelin secretion in normal subjects increased earlier than during the baseline night (Schüssler et al., 2006a). This observation supports the hypothesis that ghrelin is a sleep-promoting substance. Similar to findings after GHRH, a sexual dimorphism was found as sleep remained unchanged after ghrelin in young normal women (Kluge et al., 2007a). Another similarity to GHRH is the lack of sleep-EEG changes after ghrelin administration during the early morning hours (Kluge et al., 2007b). In contrast to GHRH, ghrelin binds to the growth hormone secretagogue GHS receptor. Also synthetic GHSs modulate sleep. After iv administration of GHRP-6 sleep stage 2 increases (Frieboes et al., 1995), and after oral administration of MK-677 for one week a distinct sleep-promoting effect was found in young men whereas there are only weak effects in elderly controls (Copinschi et al., 1997). After iv hexarelin SWS and SWA decreased probably due to a change of the GHRH/CRH ratio in favour of CRH (Frieboes et al., 2004). Similar to the sleep-promoting effect of ghrelin in young normal men, nonREM sleep increases after systemic ghrelin in mice (Obál et al., 2003). An intact GHRH receptor is a prerequisite for this effect. In animals with nonfunctional GHRH receptors, sleep remains unchanged. A sleep-promoting effect of GHRH is furthermore supported by the observation that wakefulness increases and nonREM sleep decreases in ghrelin knockout mice in comparison to the wildtype (Szentirmai et al., 2007b). However after icv (Szentirmai et al., 2006) and intrahypothalamic (Szentirmai et al., 2007a) administration of ghrelin in rats wakefulness increased during the first two hours after


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injection. The increase of wakefulness during this interval may be related to increased feeding.

Gonadal Hormones The menstrual cycle, pregnancy and the menopause reflect distinct changes in endocrine activity in women having some impact on sleep regulation. Only a few studies address this issue so far. Most previous studies of sleep regulation were performed in men or in male animals. One of the reasons why females are not included in these studies is the variability of sleep patterns influenced by hormonal changes due to the ovulational cycle (Kimura, 2005). One consistent finding is a higher rate of insomnia found in women. According to a metaanalysis including more than a million subjects, women are at 41 % greater risk for developing insomnia than are men. Zhang and Wing (2006) reported that a greater risk of insomnia in women increases with age. In the elderly the risk almost doubles to a 73 % greater risk for insomnia in older women than in older men. It was discussed that this higher prevalence of insomnia in women probably does not emerge until puberty, suggesting a possible contribution of endocrine changes (Johnson et al., 2006). After administration of gonadal hormones to adult animals only weak sleep-EEG changes were found (review: Manber & Armitage, 1999). After administration of chronic dosages of estradiol in transsexual men undergoing crossgender therapy, sleep stage 1 increased (Künzel et al., 2000). After the menopause sleep-endocrine changes associated with depression are accentuated. This is demonstrated by a comparison of sleep-endocrine data in pre- and postmenopausal female patients with depression and in matched normal controls. Cortisol levels are enhanced in the postmenopausal patients, whereas they are reduced in the postmenopausal controls. SWS decreases and REM density increases in post-, but not in premenopausal female patients. An inverse correlation exists between the decline in SWS and in sleep continuity and follicle-stimulating hormone (FSH) secretion in the patients. It appears likely that the menopause contributes to these sleep-EEG changes (Antonijevic et al., 2003). Estrogen replacement therapy via skin patch improves sleep as wakefulness decreases and REM sleep increases during the first two sleep cycles. The normal decrease of SWS and SWA from the first to the second nonREM period is restored (Antonijevic et al., 2000d). Similarly, estrogen supplement in old female rats is also capable of restoring imbalanced sleep patterns (Kimura & Inoué, 2003). Oral progesterone replacement for two weeks increases REM sleep and decreases intermittent waketime in postmenopausal women (Schüssler et al., 2008b).

Other Peptides After pulsatile iv thyrotropin-releasing hormone (TRH) sleep efficiency decreases (Hemmeter et al., 1998).

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The peptide galanin is widely located in the mammalian brain. A cluster of GABAergic and galaninergic neurons was found in the ventrolateral preoptic area, which participates in nonREM sleep promotion (Saper et al., 2001). This fits with the observation that after repetitive iv galanin SWS increases in normal control subjects. Furthermore the duration of REM sleep periods is prolonged (Murck et al., 1997). In animal models of anxiety, opposite effects of CRH and neuropeptide Y (NPY) were found (review: Steiger & Holsboer, 1997). After icv administration of NPY to rats, EEG spectral activity changes similarly to the effect of benzodiazepines (Ehlers et al., 1997a). The increase of REM latency after CRH is antagonized independently by NPY in rats (Ehlers et al., 1997b). In young normal men after repetitive iv NPY, sleep latency and the duration of the first REM period decreases, whereas stage 2 sleep and sleep period time increases. Furthermore cortisol and ACTH is blunted (Antonijevic et al., 2000a). In patients with depression of both gender with a wide age range and in matched controls, sleep latency is reduced and prolactin levels increases after NPY, whereas HPA hormones and other sleepEEG variables remain unchanged (Held et al., 2006). It is thought that NPY participates in sleep regulation, particularly as a signal of sleep onset acting as an antagonist of CRH via the GABAA receptor.

Conclusions Between sleep EEG and hormone secretion exists a bidirectional interaction. Some peptides and steroids participate in sleep regulation. Figure 1 depicts a model of peptidergic sleep regulation. It is thought that at least in male subjects a reciprocal interaction of GHRH and CRH plays a keyrole in sleep regulation. In male subjects GHRH promotes nonREM sleep, in younger subjects GHRH enhances particularly SWS and reduces cortisol secretion. In both gender GH was stimulated by GHRH. In contrast, CRH maintains wakefulness and enhances HPA hormones. In addition, CRH promotes REM sleep. Changes in the CRH:GHRH ratio in favour of CRH contribute to the similar sleep-endocrine changes during an acute episode of depression and during normal ageing. On the other hand, GHRH participates in the promotion of sleep after sleep deprivation. In women however GHRH exerts CRH-like sleep-impairing effects. Similar to the reciprocal role in GH secretion, GHRH and somatostatin influence sleep EEG in an opposite fashion, at least in male subjects. Somatostatin is beside of CRH another sleep-impairing peptide. In addition to GHRH, in males galanin and ghrelin promote nonREM sleep. In women however sleep remains unchanged after ghrelin. Ghrelin may act as an interface between the HPA and HPS systems. Galanin was found in clusters colocalized with GABA in the ventrolateral preoptic nucleus. Many GHRH-responsive neurons in the hypothalamus are GABAergic. Galanin, ghrelin and GHRH may either act synergistically, or all these peptides may promote nonREM sleep as part of a cascade. GABAergic neurons appear to mediate the effects of these peptides. The GABAA receptor appears to mediate also the effects of NPY, which acts as a major signal for sleep onset. Interestingly in most studies in patients with insomnia, cortisol levels are enhanced like in depressed patients. Since the risk to develop a depressive episode is highly elevated in patients with untreated insomnia, the question arises whether there are


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similarities in the pathophysiology and in the genetics, at least of certain, yet not determined subtypes of insomnia and depression. In both disorders elevated HPA hormones appear to be related to impaired sleep. The improvement of sleep after CRH-1 receptor antagonism in depressed patients leads to the question, whether also patients with primary insomnia may benefit from this therapy.

Figure 1. Model of peptidergic sleep-endocrine regulation. CRH, corticotropin-releasing hormone; GHRH, growth hormone-releasing hormone; NPY, neuropeptide Y; SRIF, somatostatin. Characteristic hypnograms and patterns of cortisol and GH secretion are shown in a young and in an elderly normal subject and in a depressed patient. It is thought that GHRH is released during the first half of the night, whereas CRH preponderates during the second half of the night. GHRH stimulates GH and SWS around sleep onset, whereas CRH is related to cortisol release and REMS in the morning hours. NPY is a signal for sleep onset. Besides of GHRH, galanin and ghrelin promote sleep, whereas somatostatin impairs sleep. During depression (CRH overactivity) and during normal ageing, similar changes of sleep-endocrine activity are found. Changes in the GHRH/CRH balance in favour of CRH appear to play a key role in these aberrances. Nervenarzt (1995), 66: 15-27, Schlafendokrinologie, Axel Steiger, Fig. 2, Copyright Springer-Verlag 1995, used with permission.

Beside of peptides steroids participate in sleep regulation. There appears to be a synergism of CRH and cortisol in the pathophysiology of sleep-EEG changes in patients with depression. The elevated risk for insomnia in menopausal women and the beneficial effects of

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estrogen and progesterone replacement therapy suggests a role of these hormones in impaired sleep in menopausal women. The therapeutic outcome after CRH-receptor antagonism in depressed patients and after estrogen and progesterone replacement in menopausal women and the observation that intranasal vasopressin impairs sleep in elderly subjects are promising hints for new therapies of insomnia in the future related to endocrinology. GHRH or GH secretagogues may help to counteract age-related changes of sleep. However it may be too late to start such treatment too late during the lifespan. A threshold age should be found when such an intervention should start.

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Chapter IX

Insomnia Among Suicidal Adolescents and Young Adults: A Modifiable Risk Factor of Suicidal Behaviour and A Warning Sign of Suicide? Latha Nrugham1 and Vandana Varma Prakash2 1

National Centre for Suicide Research and Prevention, University of Oslo, Norway. 2 Fortis International Hospital, NOIDA - Delhi, India.

Abstract This chapter examines existing research literature on sleep difficulties, primarily insomnia and the various dimensions of suicidality among adolescents and young adults as compared to adults. Studies have been grouped into epidemiological studies, clinical studies and reviews. Findings on gender have been given special importance. The literature overview has been complemented by case vignettes from a major corporate hospital in New Delhi (India). The chapter concludes by stating that a relationship appears to exist between insomnia and suicidality, especially with completed suicide, regardless of age. However, far too little is known about the relationship for clinicians to be able to use it as research evidence, as almost all the findings on suicidal behaviour came from cross-sectional studies, whether epidemiological or clinical. Therefore, the conclusion calls for research studies with a prospective design.

1. Introduction Sleep difficulties, specified by inability to sleep or sleeping all the time, is one of the consensus warning signs for suicide indicating the need for contact with a mental health

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professional as developed by a group of experts of the American Association of Suicidology working together to reach a consensus on warning signs for suicide 1 (Rudd et al, 2006). However, sleep difficulties are not among the risk factors listed in the American Psychiatric Association‘s practice guidelines for the assessment and treatment of patients with suicidal behaviours (http://www.psychiatryonline.com/pracGuide/pracGuideTopic_14.aspx). Face-toface diagnostic interviews that took place within a week after hospital admission, with patients after a suicide attempt, revealed that 89% of these patients reported some kind of sleep disturbance and that nightmares were associated with a 5-fold increase in risk for high suicidality (Sjostrom, Wærn & Hetta, 2007). This relationship continued to remain significant even after adjustment for psychiatric diagnosis and psychiatric symptom intensity. In this chapter, after an orientation of the current status of knowledge about sleep disturbances among adolescents as compared to adults, we will briefly summarize findings from research reports published in scientific journals about insomnia (as defined by the authors) among adolescents as related to suicidality. Only studies available in English on the PuBMed (a free internet portal of medical research reports) were used. The entire spectrum of suicidal phenomena from deliberate acts of self-harm (DSH) without suicidal intent, recurrent thoughts of death, suicidal ideation, plans to attempt suicide, attempted suicide and completed suicide will be taken up for examination, with relationship to sleep disorders, particularly insomnia. Due to the inherent difficulties in separating these suicidal phenomena from each other (Silverman, Berman, Sanddal, O‘Carroll, Joiner, 2007a; 2007b), the term attempted suicide/suicidality used henceforth includes all suicidal phenomena except completed suicide. Findings specifically related to DSH or recurrent thoughts of death or suicidal ideation will be mentioned whenever available in the reports. As the female gender is more often associated with sleep disturbances such as insomnia (Buysse et al, 2008) and insomnia/hypersomnia (Liu et al, 2007) and also with all aspects of suicidal phenomena apart from completed suicides except in China (Bridge, Goldstein, Taylor, 2006) than the male, this aspect will be focussed upon as and when findings are available. Apart from being a symptom of depressive disorders, insomnia is also closely related to anxiety disorders, specifically post-traumatic stress disorders (PTSD) and therefore, the chapter will review available literature on this relationship. Differences and similarities between adult and adolescent populations, clinical and non-clinical populations, crosssectional and longitudinal studies and conclusions common to different reviews will be explored and presented. Unless specified otherwise, studies are on adult samples from the USA and from the general population. In addition to this review of published research findings, we will examine whether the management of sleep disturbances among suicidal persons can help us understand the mechanisms of relationships between sleep disturbances and suicidal phenomena, using interspersed case vignettes from a major corporate hospital in the New Delhi (India), before reaching our conclusions. This hospital has an outpatient and 1

Warning signs were described as being subjective, proximal, clinically identified/derived, poorly defined constructs, individually applied, implying imminent risk, likely to be useful only within a constellation and demanding specific intervention; and thus differentiated from risk factors which were described as being objective, distal, well-defined constructs, empirically derived, population dependent, implying long-term risk, could be individually explored and applied and, with limited implication for intervention by the former group (Rudd et al, 2006).

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an inpatient department in which walk-in patients as well as cross-referrals from other departments like neurology, medicine, etc. are assessed. The departments of Psychiatry and Clinical Psychology work collaterally and patients have the freedom to select their doctor/therapist. The Child and Adolescent Clinic is run with the help of a psychiatrist and a clinical psychologist, under the aegis of these two mental health departments. The mental health professionals of this hospital are on the panel of many schools, corporate houses and non-governmental organisations that have insurance contracts with the hospital. Patients can be either referred by their respective organisations or be self-referred.

2. Insomnia and Suicidality Among Adults and Adolescents 2.1. Epidemiological Studies 2.1.1. Insomnia and Impact on Health Among Ordinary Adults and Adolescents In a study exploring the under-recognition and under-treatment of insomnia, it was found that among the nearly 25% of persons who reported insomnia, 42% reported almost daily sleep problems, with 88% reporting difficulty sleeping for more than a year and that among the nearly 25% with insomnia, multiple symptoms such as difficulty falling asleep, staying asleep and poor sleep quality were reported (Leger and Poursain, 2005). Although insomnia is the most common sleep complaint in the general population, a review of epidemiologic studies showed that the reported prevalence of insomnia in the general population could range from 2% to 48% depending on the definition of insomnia used (Buysse, Ancoli-Israel, Edinger, Lichstein & Morin, 2006; Ohayon, 2002). The matter of definition of insomnia has been taken up and examined to test a range of frequency and severity criteria sets that could discriminate primary insomnia sufferers from normal sleepers (Lineberger, Carney, Edinger & Means, 2006). The authors reported that their data could not reveal a single combination of severity and frequency criteria which maximised sensitivity and specificity and that optimal frequency cut-off decreased as the severity criterion increased. They found that an average sleep-onset latency or middle-of-the-night wake time (that is, time awake between sleep onset and final morning awakening) cut-off of 20 minutes or longer over 2 weeks of sleep-log monitoring appeared to best maximise sensitivity (94.4%) and specificity (79.6%) for insomnia classification. They noted simultaneously that their findings were different from previously proposed ones. It is relevant to remember here that the diagnostic criteria for insomnia requires a negative daytime consequence associated with the sleep disturbance, as defined in the DSMIV (Diagnostic and Statistical Manual of Mental Disorders, American Psychiatric Association, 1994). It has also been documented that, when compared to depression, insomnia has en equally important and independent role in contributing to use of disability pensions among Norwegian adults (Overland et al, 2008). This finding is an indicator of the

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impact insomnia has on society in economic terms and the loss of value added by work life across the range of adult life. A longitudinal cohort study using a representative stratified population sample (n = 591) distinguished four duration-based subtypes of insomnia in young adults (mean age = 19 years) with 6 interview assessments spanning 20 years: 1-month insomnia associated with significant distress, 2- to 3-week insomnia, recurrent brief insomnia and occasional brief insomnia (Buysse et al, 2008). The findings revealed that the annual prevalence of 1-month insomnia increased gradually over time, with a cumulative prevalence rate of 20% and a greater than 2-fold risk among women. They observed that in 40% of those examined, insomnia developed into more chronic forms over time. They also examined the comorbidity of insomnia with depression. They found that insomnia was highly stable over time, with or without comorbid depression. Further, they found that insomnia lasting 2 weeks or longer predicted major depressive episodes, in the immediately following interview: Odds Ratio (95%Confidence Intervals) [OR (95%CI)] = 1.9(1.3–2.6) and in any subsequent interview OR (95%CI) = 1.6(1.1–2.1). They also found that a current episode of major depression significantly predicted a +2-week insomnia in any subsequent interview, OR(95%CI) = 1.5(1.1–2.1), revealing that the relationship is bi-directional. They further reported that while ‗pure‘ insomnia and ‗pure‘ depression were not longitudinally related to each other, insomnia comorbid with depression was longitudinally related to both. Another prospective study with a nationally based population sample (n = 4494, 12 to 18 years at baseline) found that insomnia symptoms during adolescence were a significant risk factor for a diagnosis of depression in young adulthood OR = 2.3, even after controlling for gender and depression (Roane and Taylor, 2008). Sleep/wake timings change in young humans during the second decade of life (Crowley, Acebo & Carskadon, 2007; Taylor, Jenni, Acebo & Carskadon, 2005; Fredriksen, Rhodes, Reddy & Way, 2004; Carskadon & Acebo, 2002). Despite this shift being so welldocumented and report of adolescents sleeping substantially less than earlier developmental stages (Dahl and Lewin, 2002), there is a surprising lack of empirical data examining effects of sleep deprivation and insufficient sleep among adolescents, especially about adolescent and youth suicidal behaviour (Liu, 2004; Liu and Buysse, 2006). Among adolescents, the prevalence of insomnia has been estimated to be 25% while 46% of these insomniac adolescents continued to report insomnia after a year, indicating that it is both common and chronic among adolescents (Roberts, Roberts & Duong, 2008). It has been observed that insomnia is a common treatable disorder of insufficient or poor quality sleep, with adverse daytime consequences and presents as trouble falling asleep (long-sleep latency), trouble staying asleep (excessive or prolonged awakenings), or feeling non-restored from sleep (Schenck, Mahowald & Sack, 2003). A nationally representative longitudinal study examined the association between sleep, adolescent growth and developmental stage in a large sample of adolescents between 12 to 16 years of age (Knutson, 2005). Sleep variables in this investigation included sleep duration, frequent insomnia (once/week or more), frequently waking tired (once/week or more), and insufficient sleep. The results of this study revealed a significant increase in sleep problems with increasing pubertal development score among females, but not among males indicating a


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gender difference in the association between sleep problems and pubertal development. The negative association between sleep duration and pubertal development score, however, was significant in both, males and females of this study. A later investigation by the same author and a colleague (Knutson and Lauderdale, 2008) revealed that adolescents spent less than the recommended 9 hours in bed on school days. The authors did not find any evidence to indicate that this was a recent change in bed and wake times. Although the authors found that many factors influence bed time, school start time was the strongest determinant of wake time on school days and concluded that increased computer use and earlier school days might be contributing to insufficient sleep in adolescents. The prevalence rate of sleep disturbances among adolescents has been estimated to be between 9.4% and 33% in epidemiological studies (Roane and Taylor, 2008; Roberts, Roberts & Chan, 2008; Ivanenko, Crabtree & Gozal, 2005; Liu, 2004; Vignau et al, 1997). One year incidence (new cases in the last 12 months) was 13.9% for one or more symptoms, 5.5% for one or more symptoms plus daytime fatigue or sleepiness, and 5.3% for insomnia caseness with rates of chronicity at 45.8% for one or more symptoms, 34.7% for daytime fatigue or sleepiness, and 22.8% for insomnia caseness while no effects of age, gender, or family income were seen in predicting incidence or chronicity of insomnia among adolescents (Roberts et al, 2008). This study, along with an earlier one on insomnia among adolescents from managed care enrolment rosters (Roberts, Roberts & Chen, 2002), demonstrated that such sleep disturbances had a severe negative impact on the health and functioning of these adolescents, with the burden of insomnia being comparable to the burden of other psychiatric disorders such as mood, anxiety, disruptive, and substance use disorders. 2.1.2. Insomnia Among Suicidal Adults and Adolescents Multivariate models of analyses of a nationally representative survey using diagnostic interviews revealed that the presence of any sleep problem was significantly related to every measure of suicidality (Wojnar et al, 2008). The risk for suicidal ideation was [OR(95%CI) = 2.1(1.6-2.8)], for planning [OR (95%CI) = 2.6(1.4-4.9)], and for suicide attempt [OR(95%CI) = 2.5(1.2-5.2)]. In this study, suicidal ideation was associated with early morning awakening [OR (95%CI) = 2.0(1.4-2.9)] and insomnia [OR(95%CI) = 1.4(1.3-1.6)] respectively. Suicide planning was also associated with early morning awakening [OR(95%CI) = 2.1(1.1-3.7)] and insomnia [OR(95%CI) = 1.4(1.1-1.8)] while suicide attempt was associated similarly with early morning awakening [OR(95%CI) = 2.7(1.4-5.3)] and insomnia [OR(95%CI) = 1.6(1.22.1)] while difficulty initiating sleep was a significant predictor of suicidal ideation [OR (95%CI) = 1.9(1.4-2.4)] and planning [OR(95%CI) = 2.2(1.3-4.0)] and difficulty maintaining sleep during the night was a significant predictor of suicidal ideation [OR(95%CI) = 2.0 (1.52.7)] and suicide attempts [OR(95%CI) = 3.0(1.4-6.4)].

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Case Vignette 1 V is a 14 year old girl, studying in Class VIII of a public school, belonging to an upper socioeconomic status family. She was brought by her parents and elder sister with complaints of disturbed sleep, lowered academic grades, occasional crying spells and school avoidance. Her sister reported that V had, on several occasions, expressed death wishes to her. A day before V was brought to the Child and Adolescent Clinic, the sister had found a strip of ten diazepam tablets in her school bag. This was the precipitating factor for the parents to bring V to the attention of a psychologist. During the routine Mental Status Examination (MSE, which also probes for suicidal ideation) of V, mild mood disturbance, early insomnia, occasional crying spells and death wish were revealed as present. V revealed that she had planned to kill herself that day as she did not want to live anymore. On further probing V revealed that she had a crush on a boy and was so distracted that her school grades had fallen. V was scared that her parents would get to know about it and would beat her when they saw her report card. This fear was related to an incident that had taken place a couple of years ago with V’s elder sister. V’s elder sister, who is ten years older to V, had come to the Out Patient Department (OPD) with moderate depression. The precipitating factor for depression had been that she had developed friendly relations with a boy and had bunked college to see a movie. When her parents came to know about it she was brutally beaten up by her father and locked in her room for several days. She was deprived of food for two days. Parents were counselled not to use punitive methods to deal with developmental issues. Both the parents responded well and worked towards building a healthy and trusting relationship with the elder daughter. She was successfully treated with a combination of tricyclic antidepressants and cognitive behaviour therapy. Follow-up after 3months and 6-months showed that home environment had become congenial and happy and she maintained gains. The index patient, V, feared that she too would be meted the same treatment as her elder sister. However, reassurance was given to her and with her consent the parents were included in the next six therapeutic sessions. Again, Family Therapy was specifically used to increase trust between the parents and the children. The patient was taught sleep hygiene methods. Supportive psychotherapy was used to help her utilize her recreation time in games. Suggestion and persuasion were used for reorienting her to academics again. Cognitive Behaviour Therapy helped in reducing her depression. She was symptom free after 17 weekly sessions and readjusted to her school and academics. Subsequently she developed close ties with her mother and learnt to confide in her. Discussion In this case, we see that careful and detailed examination by experienced clinicians can result in information useful for management, especially when the family members are co-operative. Although suicidal intent was present, lethality of the plan was low. As the repertoire of coping skills is limited in adolescence, the usual dilemmas of growing up appeared to be overwhelming to the adolescent. This experience of being overwhelmed might have increased in the absence of parental support and presence of fear of harsh response from parents. Fear of parental punishment led to sleep disturbance and mood disturbance in this case. Once the fear reduced, both sleep and mood, improved. The co-operation and active participation of the family members was extremely useful in the entire case managemnet.


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In a study using data from an earlier phase of the same project, short sleep (1 to 5 hours of sleep per 24 hours) was found to be significantly associated with an increased likelihood of suicidal ideation [OR(95%CI) = 2.5(1.6-3.9)] and suicide attempt [OR(95%CI) = 3.0(1.46.4)] irrespective of the influences of comorbid mental disorders (Goodwin and Marusic, 2008). They had also found significant bivariate relationships between attempted suicide and short sleep [OR(95%CI) = 3.5(1.01-12.2)] among those with suicidal ideation in the past twelve months which disappeared into statistical non-significance when adjusted for depression, anti-social personality disorder, alcohol dependence, substance dependence, bipolar disorders and panic attacks. Yet, this bivariate relationship between short sleep and attempted suicide among those with suicidal ideation in the past year continued to remain significant when adjusted for socio-demographic characteristics such as age, gender, race, marital status, education and income. The significant and positive relationship of sleep disturbances, primarily nightmares and sleep difficulties, to suicidal ideation and attempts was documented in early studies of suicidal phenomena among US and French adolescents (Tishler, McKenry & Morgan, 1981; Choquet and Menke, 1990; Choquet, Kovess & Poutignat, 1993) which was later elaborated in a study of French high school students (Vignau et al, 1997). In this later study, a total of 763 students were randomly chosen among 15 secondary schools of a main administrative division of land in France for assessment of prevalence and correlates of sleep problems among adolescents (Vignau et al, 1997). Difficulty in waking up and nightmares were excluded from this study. Poor sleepers were defined as those who answered ‗often‘ or ‗always‘ to one of the three questions about: (a) having trouble falling asleep, (b) the occurrence of early awakenings, or (c) their need for more sleep, or reported (d) bad sleep quality or (e) sleeping pill intake. They found that as much as 40.8% of these high school students reported at least one of the five sleep disturbances and a higher prevalence among girls on all four sleep parameters. The only poor sleep item in which boys were more frequent than girls was ‗sleeping pill intake‘ although this item was not statistically associated to a significant level with any specific gender. The authors reported that poor sleepers had suicidal ideas (p = 0.001) and attempts (p = 0.001) significantly more often, irrespective of gender. The significant and positive association between insomnia and suicidal ideation among adolescents was attenuated [OR (95%CI) = 3.4(2.7-4.2)] even though it continued to remain significant when controlled for age, gender and socio-economic status (Roberts, Roberts & Chen, 2001). Among rural Chinese school adolescents participating in a questionnaire survey (n = 1362, mean age = 14.6, 60% males), however, the significant association of insomnia with suicidal ideation disappeared when controlled for depression (Liu, 2004). Yet, the association of insomnia with attempted suicide [OR (95%CI) = 2.8(1.07-7.8)] remained significant even after controlling for age, gender, father occupation and depressive symptoms as did the relationship between nightmares and suicidal ideation [OR (95%CI) = 1.6(1.2-2.3)] in this study.

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2.2. Clinical Studies 2.2.1. Insomnia Among Adults: Attempted Suicide and Related Suicidal Phenomena Suicidal ideation and insomnia/hypersomnia were significantly associated with a diagnosis of depression while insomnia/hypersomnia and depressed mood were found to be the most frequently elicited symptoms in family practice assessments (Ani et al, 2008). Brazilian adult outpatients [n = 70, mean age = 40.0 (standard deviation, SD = 12.5) years] with diagnoses of major depressive disorder (mean duration in months = 6.14, SD = 1.90) with insomnia had significantly higher scores on the following components: active suicide ideation, specific plans for suicide and previous suicide attempts (Chellappa & Araújo, 2007). The results of multivariate analysis in this study showed that only insomnia had a significant association with suicidal ideation. Sjostrom and colleagues (2007) have reported that difficulties in initiating sleep was the most common sleep disturbance (69%) reported by persons with suicidal attempts followed by nightmares (66%) and early morning awakening (58%) among the 89% of participants who reported some kind of sleep disturbance. This finding was supported by findings from Wojnar and colleagues (2008, described above) for suicidal ideation and planning but not for suicide attempts as mentioned above. Sjostrom and colleagues (2007) have also reported that in the multivariate model, nightmares were the only sleep variables associated with high scores of suicidality, even after adjustment for Axis I disorders, post-traumatic stress disorder and symptom intensity: OR (95% CI) = 3.7(1.5–9.0). In a study of outpatients (n = 176), the initially significant relationship between insomnia and suicidal ideation disappeared with only nightmares remaining significant among women (p = .04) when controlled for depressive symptoms (Bernert, Joiner, Cukrowicz, Schmidt & Krakow, 2005). Global insomnia was reported by 46% and partial insomnia by 92% of 100 patients consecutively admitted to a psychiatric unit after a severe suicide attempt (Hall, Platt & Hall, 1999). However, this study did not report any multivariate analyses and had patients from managed care only. Agargun, Kara & Solmaz (1997a) used the Schedule for Affective Disorders and Schizophrenia (SADS) to examine the association between sleep disturbances and suicidal behaviour in 113 Turkish patients with major depression. They found that hypersomnia and insomnia were associated with suicidal behaviour (p<0.001, for both) in patients with major depression. The same authors (1997b) had also reported a statistical significant association between poor subjective quality of sleep and suicidal behaviour in patients with major depressive disorder. Agargun and a different set of colleagues recently reported that patients with suicide attempts with melancholic features of unipolar depression had a higher frequency of nightmares, middle and terminal insomnia than melancholic non-attempters, leading the authors to conclude that melancholia may be associated with increased risk of suicide attempts due to repetitive and frightening dreams (Agargun et al, 2007).


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2.2.2. Insomnia Among Adolescents: Attempted Suicide and Related Suicidal Phenomena Early biological studies have indicated that suicidality in depressed adolescents is associated with increased sleep dysregulation around sleep onset (Dahl et al, 1990; Dahl et al, 1992). However, early clinical studies were unable to distinguish between children and adolescents [mean age = 10.3(3.8)] who attempted suicide from those with suicidal ideation on the basis of clinical symptoms alone, as both groups had similarly high levels of symptoms of depression (87% and 94%, respectively), anxiety (77% and 73%, respectively), sleep disorders (63% and 64%, respectively) and irritability (50% and 54% respectively) (Kosky, Silburn & Zubrick, 1990). A study which set out to examine the clinical symptoms and comorbid psychiatric disorders of depressed children and adolescents, from either in/outpatient services of a psychiatric clinic, with and without clinically significant suicidal ideation found that depressed suicidal youth presented with a more severe episode (p<0.001) and a poorer functional status (p = 0.019), were more hopeless (p<0.001), and presented more frequently with insomnia (p = 0.011) (Barbe et al, 2005). These findings led the authors to conclude that compared with the non-suicidal depressed youth, depressed suicidal youth presented with more severe depressions and had increased rates of hopelessness and insomnia and that the findings were similar when depressed suicide attempters were compared with depressed nonattempters. Depressed suicide attempters in this study reported more hopelessness (75% [N = 6/8] vs. 33% [N = 42/127]; Fisher exact test, p = 0.025) and presented with more insomnia (anytime) (88% [N = 7/8] vs. 52% [N = 66/127]; Fisher exact test, p = 0.07) than depressed non-attempters. The only longitudinal study is a more recent Norwegian study on a high school subset selected for high depression scores during adolescence and which therefore resembles the outpatient population most (Nrugham, Larsson & Sund, 2008). The subset of adolescents [n = 345, 72.5% females, mean age = 14.9(0.6)] years was formed by 225 school students who reported high depression scores and 120 school students who reported low/moderate depression scores) were matched at random on age and gender and interviewed for psychiatric diagnoses. This subset was followed-up into young adulthood [n = 242, 77% females, mean age = 20.0(0.5)] investigating the relationships between attempted suicide and depressive symptoms as assessed by the same semi-structured psychiatric interview [KiddieSchedule for Affective Disorders and Schizophrenia (K-SADS)] used during the last assessment.This study revealed that initial insomnia: OR (95% CI) = 4.7(2.6–8.5), OR (95% CI) = 3.4(1.6–7.2); circadian reversal: OR (95% CI) = 5.4(2.4–12.1), OR (95% CI) = 5.5(2.5–12.2) and non-restorative sleep: OR (95% CI) = 4.5(2.5–8.1), OR (95% CI) = 4.3(2– 9.1) were significant bivariate associates of attempted suicide, regardless of age (by 15 years or between 15-20 years of age) or time (by 15 years or the later 5-year follow-up period). However, only initial insomnia: OR (95% CI) = 3.3(1.5–7) and hypersomnia: OR (95% CI) = 4.1(1.5–10.8) were predictors of attempted suicide across adolescence into young adulthood. Middle insomnia: OR (95% CI) = 6.0 (1.3–27.8) was an associate of attempted suicide between 15 to 20 years of age, also in the multivariate analyses while initial insomnia for this age group changed direction: OR (95% CI) = 0.04 (0.0–0.4) and became a protective factor, when controlled for other depressive symptoms. When this multivariate model was adjusted

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for a diagnosis of major depression, both, major depression and middle insomnia were absent in the significant model obtained. However, this multivariate model retained initial insomnia with the reversed direction continuing. Case Vignette 2 N, a 23 year old woman, training to be a painter, came to the psychiatric Outpatient Department (OPD) in September, with complaints of sleep disturbance, primarily early insomnia. The MSE revealed that she had low mood, anhedonia with sleep and appetite disturbances since the last 4 months. She complained of a recurrent dream of falling into nothingness and would wake up screaming. Several times in a week, she could not sleep the entire night, in fear of this nightmare. The precipitating factor for the current depressive episode seemed to be an inability to cope with the curriculum of a prestigious Art School in which she had enrolled in June. She returned to her hometown after a month of joining the Art School. A sense of failure and guilt feelings about letting her parents down persisted within her. She was prescribed a selective serotonin reuptake inhibitor (SSRI) drug, Sertraline, and simultaneously started on Cognitive Behaviour Therapy, twice a week. Her father and paternal grandmother had a history of bipolar disorder. She came regularly for psychotherapy and improved significantly. Her guilt, related to the sense of failure and letting her parents down, diminished remarkably. Her biological functions like sleep and appetite improved. As her mood became better she started painting again. She had worked as a Disc Jockey on part-time basis. This job required her to be witty and humorous. She started hosting the shows again although she reported that the fun was still missing. After three months of intensive psychotherapy she dropped out of the therapy without notice. Her mother called to inform that she was progressing satisfactorily. After three weeks, N came to the OPD to inform that she was helping a friend of hers who was becoming suicidal and this strain had again led to sleep disturbance and the dreams were reoccurring. The MSE did not elicit any psychopathology apart from sleep disturbance and nightmares. She was encouraged to practice sleep hygiene methods and to resume psychotherapeutic sessions. Her mother was asked to help her monitor her medication to regulate her sleep cycle again. Nonetheless, a week later she was dead by suicide. Her parents could not come up with any explanation for this act of hers. In fact, a day previous to her suicide she had expressed her satisfaction and happiness in successfully helping her friend overcome suicidal thoughts. Discussion In this case, a strong relationship between poor quality of sleep, nightmares and suicide was revealed. Therapeutic sessions substantiated the above finding as she had expressed her anguish mostly regarding her poor sleep patterns and a sense of failure. As therapy progressed, her distress was more strongly associated with disturbed sleep and nightmares than a sense of failure. Although depressive symptoms appeared to have remitted and the subjective distress of low mood was apparently absent, recurrence of depression cannot be ruled out.

The reversal of direction could be due to confounding variables. As hypersomnia was excluded from the predictor multivariate analyses due to multi-collinearity with hopelessness, which itself is a well-known predictor of later suicidal behaviour, only speculations are possible on this relationship as reported in this study. It appears that initial insomnia is an


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important bivariate associate and predictor of attempted suicide, regardless of age and time while the role of other sleep disturbances varied with age and time. As the onset timing of each symptom was not analysed in this study, it is not possible to comment on the impact of the timing of onset and duration of these sleep disturbances as related to attempted suicide, although some sort of an influence, which may or may not be prodromal or residual or both in nature, seems to be indicated by the change of direction of initial insomnia for older adolescents and young adults. As this study was primarily not about sleep disturbances or insomnia, its ability to draw related conclusions are limited despite it raising interesting questions. It therefore does not answer the call for longitudinal studies that examine the occurrence of future suicidal behaviour in those with and without sleep disturbances at baseline by the authors of the latest review on the topic, viz., Liu and Buysse (2006, described later). In an early study of depressive symptoms and suicidal behaviour among 64 consecutively hospitalized adolescents, insomnia was identified as being bivariately significantly related to suicidal tendencies (p<0.001) and multivariately to seriousness of intent (p<0.03) (Robbins and Alessi, 1985). All items were assessed by the SADS semi-structured clinical interview. However, this study also reported negatively significant relationships between initial insomnia and suicidal tendencies (p<0.001), somewhat similar to Nrugham and colleagues (2008). Although insignificant, negative relationships were also found between initial, middle and terminal insomnia and all the four aspects of suicidality probed for in the study: suicidal tendencies, number of gestures, seriousness of intent and medical lethality. All these four aspects were significantly and positively correlated to each other and all assessments were made after the suicidal behaviour. Multi-collinearity was not controlled for and therefore, the results must been regarded with due consideration for this absence. 2.2.3. Insomnia Among Suicidal Adolescents: Post Traumatic Stress Disorder (PTSD) A study designed to describe and evaluate the clinical pattern of 14 youths (aged 10 to 18 years) with presenting suicidality, found a common pattern characterized by: (a) suicidality, (b) insomnia, (c) bodily reactions such as stiffness and pain, and (d) deranged mood regulation with involuntary intrusions of negative emotive states and images (Hogberg and Hallstrom, 2008). This condition, the authors cite, has been described earlier in a similar way in a post-rape study by Darves-Bornoz in 1997. The authors called this condition a suicidal trauma reaction. Choquet, Darves-Bornoz, Ledoux, Manfredi & Hassler (1997) have also reported that rape victims among a nationally representative sample of high school students [n = 8140, 48.7% males, 51.3% females, mean age = 16.2 (2.02) years] were associated with attempted suicide (males) and current sleep difficulties (both genders) along with a host of behaviour problems.

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Case Vignette 3 K is a 14 year old girl, studying in Class IX, coming from an upper middle-class family. Both parents had been married before to different persons. K’s stepfather had a son from his previous marriage and one girl child was born from his marriage with K’s mother. However, soon after this second marriage, disputes arose between the parents regarding styles of parenting. The stepfather was a conservative and domineering man whereas the mother was more liberal with the children. As K also had primary dyslexia, her mother had been encouraging her to participate in sports and extra-curricular activities, which the step-father opposed. All three children witnessed repeated physical abuse of the mother who supported their interests and ambitions. The mother had lodged a police complaint against the father a month before she came to the Child and Adolescent Guidance Clinic. Consequently, the father was evicted out of the family’s house by police. He took away his son and repeatedly demanded that the younger daughter, K’s younger sister be given to him. When the mother refused to hand over the younger daughter to him he would create a scene outside the house. K was very embarrassed by these daily occurrences. One day the father threatened bodily harm to K if the mother persisted in her refusal to hand over the younger daughter to him. K developed fever after hearing this and was taken to a general physician. She was treated for fever that improved in 3 days time. However, K developed sleep difficulties, intermittent awakening and hypervigilance. Her sleep patterns did not improve and she would wake up screaming several times in the night after experiencing nightmares of being harmed by her stepfather. She talked a few times about killing herself, to her mother, which prompted the anxious mother to bring K to the clinic. K and her mother refused to meet the psychiatrist for medication. She was then seen twice a week for psychotherapeutic sessions. Deep muscular relaxation technique and sleep hygiene methods were taught to her. Cognitive Behaviour Therapy, catharsis and Behaviour Therapy techniques were used to alleviate her fear and stress. Both parents were called in for marital therapy even though both of them had individually decided not to live together. Mutual agreement was reached where the father was allowed to meet the younger daughter. He profusely apologised to K and promised never to harm her. Gradually, after 15 sessions of psychotherapy, K’s mental health improved. Her sleep patterns became normal and her suicidal ideation disappeared. Discussion In this case, a fairly strong relationship was indicated between traumatic stress, sleep disturbance and suicidal ideation. The traumatic stress led to sleep disturbance and consequent suicidal ideation although a suicide attempt was not known to be made. The improvement in symptoms occurred as soon as the ongoing traumatic stress decreased leading to improvement in sleep patterns.

2.2.4. Insomnia Among Adults and Adolescents: Suicide In order to investigate whether certain DSM-IV depressive symptoms were more prevalent among individuals who die in the context of a major depressive episode and those who do not, whether this increased prevalence was associated with proximal or distal suicide risk, and whether depressive symptoms cluster to indicate suicide risk, 156 suicides who died in the context of a major depressive episode were compared with 81 major depressive controls (McGirr et al, 2007). They found that independent of concomitant axis I and II


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psychopathology, depressive symptoms among the suicides were more likely to include insomnia [OR(95%CI) = 2.3(1.2-4.6)] and recurrent thoughts of death or suicidal ideation [OR (95%CI) = 12.5(4.8-32.4)], among other depressive symptoms. They also found that the concomitant presence of weight or appetite gain and hypersomnia was associated with decreased suicide risk [OR(95%CI) = 0.29(0.06-1.2)]. The authors of this study concluded that inter-episode symptom concordance seemed to suggest insomnia as an immediate indicator of suicide risk, while other depressive symptoms were not. Case Vignette 4 S, male, aged 15 years, studying in Class IX in a public school and the only child of an upper socio-economic status family was brought to the Child Guidance Clinic. Presenting complaints were disturbed sleep, disruptive and quarrelsome behaviour in school for more than 6 months. His parents revealed that S’s school had been repeatedly complaining about his disruptive behaviour in class and his bullying behaviour with classmates and younger children in the school bus. As he was the only child of his parents, most of his demands had been promptly fulfilled since childhood. From infancy and throughout his childhood, his sleeping time had ranged between 5-6 hours. He would sleep intermittently and wake up several times during the night. At the age of 6 years he was diagnosed to be suffering from borderline attention-deficit hyperactivity. However, he was never put on psychopharmacological therapy. As he grew older his hyperactivity decreased but attention span remained short. Academically, he was at the average level in his class, obtaining between 50-60% marks. He was brought to the OPD for his continuing behavioural disturbance. The routine mental status examination did not reveal any gross pathology except poor adjustment. Cognitive functions were grossly normal and attention span was adequate. He was advised to come the following day for detailed psychological evaluation and a psychiatric consultation for sleep disturbance. Probes for a family history of any psychiatric disorder did not reveal positive findings. However, the same evening, his father developed angina pain and was admitted to a hospital. Consequently, the patient was not brought to the Clinic. The patient behaved responsibly during this period and was a support to his mother. During this period his sleep was disturbed and he appeared to be restless. These symptoms were taken as a natural anxiety for his father’s health. On the 12th day after the father’s admission, the patient went to meet him in the hospital. On the way back he was happy that his father would be discharged after 2 days. He planned a surprise holiday for his father and appeared in good spirits, chatting with his mother and paternal grandfather. Soon after lunch, he suddenly locked his mother in her room. He found a rope, called out to his mother that he was ending his life and hung himself. No significant event/symptom could be elicited from the parents prior to the suicide except sleep disturbance and restlessness. Discussion In this case, hidden depression cannot be ruled out, keeping in mind the history of poor adjustment. Young boys are known to exhibit aggressive behaviour when distressed or depressed, even in dysthymic condition. Sleep disturbances are a part of the clinical profile of depression.

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Global insomnia was found to be one of the six clinical features significantly associated with those who completed suicide (p = 0.011) within one year (n = 13) among 954 psychiatric patients with major affective disorders also assessed by SADS (Fawcett et al, 1990). Half of the patients were 36 years old or younger and the mean age was 38.1 years. The authors called clinical symptoms that may be responsive to early clinical intervention as ‗modifiable risk factors‘ and one year as short-term risk period amenable to therapeutic intervention that can substantially reduce acute suicidal risk. Nearly 20 years later, sleep difficulties preceding death in a sample of 140 adolescent suicide completers as compared with a matched sample of 131community control adolescents were thoroughly investigated using a psychology autopsy protocol and semi-structured psychiatric interview in the only study of its kind among adolescents (Goldstein, Bridge & Brent, 2008). Their findings indicated that when compared with controls, suicide completers had higher rates of overall sleep disturbance, insomnia and hypersomnia than controls, within the last week and the current affective episode, even after adjustment for the differential rate of affective disorder between the two groups. When severity of depressive symptoms was accounted for, overall sleep disturbance (last week and present episode) and insomnia (last week) distinguished completers from controls. This paper concluded that the findings supported a significant and temporal relationship between sleep problems and completed suicide among adolescents, just as Fawcett and colleagues (1990) had done among adults.

2.3. Reviews: Adults and Adolescents Reviewers examining the importance of sleep regulation and behaviour in pathways to adolescent health found that while substantial evidence for bi-directional effects between sleep and behavioral/emotional regulation existed, there is mounting evidence that sleep deprivation has its greatest negative effects on the control of behaviour, emotion, and attention, a regulatory interface that is critical in the development of social and academic competence, and psychiatric disorders (Dahl and Lewin, 2002). The reviewers pointed out that clinicians experienced with these problems have pointed out that in many cases, it is difficult to differentiate decreased motivation, school refusal/anxiety, delayed circadian phase, attention difficulties, and depressive symptomatology indicating the clear need for the careful assessment of sleep patterns and behavioural symptoms for prevention, accurate diagnosis, and/or treatment planning. After examining the scientific literature (predominantly biological) on the relationship of sleep with suicide, two reviewers called for further studies to investigate the possible role of sleep disturbance in suicidal behaviour (Singareddy and Balon, 2001). They summarized that although sleep-related complaints and EEG (electroencephalographic) changes have been seen widely across the spectrum of psychiatric disorders, sleep complaints such as insomnia, hypersomnia, nightmares and sleep panic attacks are common in suicidal patients. The authors added that the subjective quality of sleep as measured by self-rated questionnaires also appeared to be more disturbed in depressed patients who were also suicidal. They hypothesized that one mechanism responsible for the possible association between suicide and sleep could be the role of serotonin (5HT) and that the intervening factor between


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serotonin and suicide could be the dysfunctional control of aggression. They supported their hypothesis with the observations that serotonergic function had been found to be low in patients who attempted and/or completed suicide, particularly those who used violent methods and that serotonin has been documented to play an important role in the onset and maintenance of slow wave sleep and REM (rapid eye movement) sleep which has been documented to be increased in suicidal patients with depression, schizoaffective disorder and schizophrenia while 5HT2 receptor antagonists have been reported to improve slow wave sleep and that agents that enhance serotonergic transmission decrease suicidal behaviour. A recent review concluded that sleep loss or disturbances were likely to signal an increased risk of future suicidal action in adolescents and that the link between insomnia and suicidal behaviour appeared to be mediated by depression (Liu and Buysse, 2006). The conclusion of these reviewers gains additional relevance in the light of sleep disturbances being argued to be a core symptom of depression with emphasis on the early restoration of sleep in the management of major depression among adults (Kennedy, 2008). However, polysomnographic and neuro-endocrine studies in children and adolescents have not found consistent changes in sleep architecture paralleling adult major depression (Ivanenko, Crabtree & Gozal, 2005). Here it is pertinent to note that Conroy and colleagues (2006) have documented that perception of poor sleep is associated with significant distress and consequences even in the absence of objective polysomnography findings. This distress would need to be clinically addressed, regardless of mechanical/laboratory evidence, more so, among children and adolescents. A review on pharmacologic treatment approaches for children and adolescents with posttraumatic stress disorder stated, as a part of its conclusions that even the reduction in one disabling symptom, such as insomnia or hyperarousal, may have a positive ripple effect on a child's overall functioning (Donnelly, 2003).

3. Conclusion It is heartening to note that concerted efforts are being made to define insomnia and that research interest is being shown on this topic. Such efforts will go a long way in providing the spurt required in insomnia research, which is required in order to reject/accept hypotheses regarding the association of insomnia with different aspects of suicidality. We see that published research on the relationship between sleep disturbances and deliberate self-harm is absent, while publications of findings from research projects studying the relationship between sleep disturbances and completed suicide are rare, both in the adult and adolescent literature. The relationship between sleep disturbances and PTSD has been explored equally sparsely as with suicide while the bulk of existing literature is on the relationship between sleep disturbances and either suicidal ideation or attempted suicide or both these aspects of suicidal phenomena. This available literature is essentially crosssectional and many of the research projects or the studies were not designed specifically for the purpose of examining these relationships, with the findings on sleep coming as a byproduct of research on some other issue, usually depression. Biological aspects of this relationship have hardly been researched and this gap needs to be filled.

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Although it is noted that insomnia and other sleep disturbances are common, chronic and expensive to society when untreated, neither insomnia nor sleep disturbances have received the attention they deserve from researchers. Clinicians, on the other hand, have been vigilant to the distresses in their patients and use their skills to include sleep management as a core part of the case management, even in the absence of support from research studies. Among adolescents, the vulnerability added by the presence of insomnia/other sleep disturbances is increased due to the increased task mastery expected from them and the incomplete coping repertoire available to them. This vulnerability appears to be enhanced among females. It was also seen from the review of research findings that although there are some gender specific findings, there is not enough replication to draw conclusions or to validate generalizations. In both epidemiological and clinical studies, it was seen that the relationship between insomnia and all aspects suicidality remained statistically significant even in multivariate models of adult samples, while the same was true in the adolescent samples only for suicidal attempts and was inconsistent for suicidal ideation. The role of initial insomnia as an associate and as a predictor of suicide attempts from adolescence to early adulthood has been documented only in a single longitudinal study with a sample that is in-between the general population and clinical sample and needs to be replicated among both samples. On the other hand, the negative relationships between types of insomnia, including initial insomnia and aspects of suicidality, documented in clinical studies among adolescents must also be thoroughly investigated for confounding factors so that the true relationship can emerge. In doing so, not only will the nature and direction of the relationship be revealed but also the mechanism of its functioning. It was also seen that the statistical relationship between insomnia/sleep disorders were impervious to age, race and other sociodemographic variables but remained sensitive to psychiatric/psychosomatic variables. Insomnia and other sleep disturbances must be addressed by the clinician during case management, regardless of whether these disturbances are prodromal, residual or core signs of the presenting suicidal phenomena. This cannot happen unless research steps in with evidence so urgently required by clinicians, who cannot be blamed for ignoring the importance of insomnia as a prodromal/core/residual sign of suicidal phenomena in the absence of research evidence. For clinicians, suicidality is a multi-faceted phenomenon of which insomnia is just one facet.. The close temporal relationship between insomnia and suicidality seen in studies with PTSD and completed suicide samples, among adolescents and adults, needs to be examined urgently, so that research can aid the clinician in case management with scientific evidence. Despite the findings of all the available studies concurring on the direction and nature of this relationship, the number of studies found are too few to draw a clear conclusion. However, the findings of these available studies cannot be ignored, either by clinicians or by researchers. Although clinical significance is noted and managed by clinicians on their own, the establishment of statistical significance of this relationship will make case management more secure and safe, for the patient and the clinician. The case studies presented here were able to inform us about several important aspects of clinical work; viz, the importance of normalising sleep patterns and the clinical benefits of doing so; the difficulty of clinical distillation of sleep disturbances from other behaviour disturbances; the role of stress-reduction, sleep hygiene, medication and psychotherapy in the clinical management of suicidal ideation and how sleep disturbances, specially insomnia


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might be enough reasons to keep the clinical relationship alive and active, with careful monitoring of sleep patterns by the clinician and family members. The case studies reveal exactly how important it is to ask the patient or elicit from the patient the most disturbing aspect of personal distress so that the management plan can address it first and be vigilant for its re-occurrence. The clinician‘s observations also inform us about the sequence of the symptoms: sleep disturbances may be a trait seen to develop from infancy itself or a state responding to negative environmental stimuli/stress. However, the clinician‘s documentation of observations also raise the issue of exploring the relationship between continuity into adulthood of sleep disturbance traits established in early life and later suicidality. In other words, do children/adolescents who have insomnia continuing into adulthood also become suicidal later on? Is insomnia a predictor or an associate or both, of suicidality? Or is it a warning sign? This question begs a longitudinal research study design, whether epidemiological or clinical. A relationship between insomnia and suicidality appears to be present as revealed in research findings and clinical case vignettes. The relationship is seen most clearly with suicide, as all the studies found the same temporal relationship between insomnia and suicide: immediate, ranging from last week to last 12 months, regardless of age. However, far too little or next to nothing is known about the nature of the relationship and the mechanisms of how this relationship works. Isolating a single symptom has its own shortcoming in a clinical setting where the reliability and adequacy of clinical history, the sequence of events, duration of each symptom and temporal relationship between occurrences of symptoms, are all important determinants. Far too often, underlying pathology gets known retrospectively, particularly as symptoms of depression may not be manifested early or may be hidden/masked. If markers of suicidal behaviour are isolated by researchers with a clinical background, clinicians can be better equipped to deal with suicidal patients. We repeat the call for longitudinal studies examining the relationship between insomnia and suicidality among adolescents made by Liu and Buysse (2006), supporting this call with the specificity of prospective designs, more questions and hypotheses. We also reiterate the statement made by Donnelly (2003) that it is possible that reduction of clinical distress of such a disabling symptom as insomnia may have a ripple effect on the overall functioning of the individual, especially during adolescence and more so among suicidal adolescents.

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Chapter X

Melatonin and Nocturia Kimio Sugaya*, Saori Nishijima, Katsumi Kadekawa and Minoru Miyazato From the Division of Urology, Department of Organ-oriented Medicine, Faculty of Medicine, University of the Ryukyus, Okinawa, Japan.

Abstract Nocturnal frequency of urination (nocturia) is common in the elderly, and it is one of the most troublesome urologic symptoms. Urinary frequency interferes with daily activities, while nocturia may also result in sleep disturbance that can cause daytime fatigue as well as worsening the quality of life (QOL). Multiple factors may contribute to the occurrence of nocturia, including pathological conditions such as cardiovascular disease, diabetes mellitus, lower urinary tract obstruction, anxiety disorders or primary sleep disorders, and various other behavioral and environmental factors. Recently published guidelines have attributed the occurrence of nocturia to nocturnal polyuria and/or diminished nocturnal bladder capacity. However, since these factors may express the states of nocturia rather than the causes, it remains difficult to develop effective treatments for nocturia if the underlying etiology is not determined. Accordingly, in order to investigate which factors are strongly related to occurrence of nocturia, we performed a suite of examinations in elderly persons who had nocturia without any other diseases (elderly nocturia group) and two (young adult and elderly) control groups. As the results, sleep disturbance (a decrease of the nighttime plasma melatonin level), hypertension (an increase of nighttime plasma catecholamine levels), and excessive fluid intake (an increase of total urine volume) were major factors contributing to nocturia in the elderly. On the other hand, some elderly persons do not consider nocturnal urination to be bothersome even if they have a number of episodes. So, as a next step, the factors related *

Correspondence: Kimio Sugaya, MD,PhD, Division of Urology, Department of Organ-oriented Medicine, Faculty of Medicine, University of the Ryukyus, 207 Uehara, Nishihara, Okinawa, 903－0215, Japan, Phone : +81-98895-1186, Fax +81-98-895-1429, E-mail [email protected]

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Kimio Sugaya, Saori Nishijima, Katsumi Kadekawa et al. to nocturnal urination that was not considered bothersome by comparing biochemistry tests were investigated between subjects who felt nocturnal urination ( twice per night) as bothersome and those who did not. As the results, the plasma melatonin level was lower in the bothersome group than in the non-bothersome group. Therefore, nocturnal urination might be not considered bothersome when subjects maintain sufficient levels of melatonin. As the third step, the effects of melatonin and the hypnotic, rilmazafone, on nocturia were compared in the elderly patients. After 4 weeks‘ treatment, the number of nocturnal urinations was decreased and the QOL score was improved in both groups. Melatonin and rilmazafone were equally effective for nocturia in the elderly, and the plasma melatonin level was increased in the melatonin-treated group. Therefore, the decrease of the plasma melatonin level may be one of the most important causes of nocturia, and sleep disturbance should be considered when choosing a therapy for nocturia.

What is Nocturia? Nocturnal frequency of urination (nocturia) is common in the elderly, and it is one of the most troublesome urologic symptoms [1,2]. Urinary frequency interferes with daily activities, while nocturia may also result in sleep disturbance that can cause daytime fatigue as well as worsening the quality of life [1-3]. Moreover, persons with nocturia have an increased risk of falls [4], and their survival rate is lower than normal [3,5]. It can be suggested that survival is decreased by factors associated with nocturia. Nocturia is the complaint that the individual has to wake at night one or more times to void [6]. The percentage of individuals with nocturia of two or more times increased constantly with age: less than 30 years, 3.1% of women and 3.4% of men; 30 to 59 years, 7.2% of women and 5.7% of men; and 60 years old or older, 26.7% of women and 32.4% of men in Austria [7]. Age-adjusted extrapolation to the general population (older than 20 years) currently living in Austria yielded that 10.8% of men and 11.8% of women have nocturia of two or more times. Overall, 66.9% of women and 62.2% of men reported a negative impact of nocturia on their quality of life (QOL). The correlation was close between the degree of nocturia with the QOL impairment in both sexes. Therefore, nocturia is almost equally present in both sexes, and the incidence and severity increase constantly from early adolescence to senescence. Approximately 10% of the general population (older than 20 years) have nocturia of two or more times, which impairs the QOL in two thirds. Many individuals with nocturia, particularly elderly men, have other lower urinary tract symptoms such as urinary frequency, weak stream, and urgency due to benign prostatic obstruction (BPO) [8,9]. In women, these symptoms are often considered to result from aging or childbirth [10,11]. However, multiple factors may contribute to the occurrence of nocturia, including pathological conditions such as cardiovascular disease, diabetes mellitus, lower urinary tract obstruction, anxiety disorders or primary sleep disorders, and various other behavioral and environmental factors [12-15]. Recently published guidelines have attributed the occurrence of nocturia to nocturnal polyuria and/or diminished nocturnal bladder capacity [10,16,17]. This classification has been widely accepted. However, since nocturnal polyuria and/or diminished nocturnal bladder capacity may express the states of nocturia rather than

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the causes, it remains difficult to develop effective treatments for nocturia if the underlying etiology is not determined. Among the medical treatments for nocturia, it has been reported that administration of anticholinergics [18], arginine vasopressin (antidiuretic hormone) [19,20], or hypnotics before sleeping [21,22] can be useful. In patients with BPO, administration of adrenergic alpha-1 receptor antagonists improves voiding disorders and also reduces urinary frequency (including nocturia) [23,24]. Therefore, there is a possibility that dysfunction of the cholinergic and adrenergic nervous systems, an abnormal water balance, and/or sleep disorders may also contribute to nocturia. However, there have been few previous investigations of biochemical parameters in patients with nocturia, apart from studies on natriuretic peptides [25,26] or antidiuretic hormone [27].

The Causes of Nocturia in the Elderly In order to clarify which factors are strongly related to occurrence of nocturia, we investigated the following 3 groups: 1) a young adult control group composed of healthy persons without nocturia (no urination from the time of sleeping until the next morning), 2) an elderly control group composed of healthy persons with a low mean frequency of nocturnal urination < once per night over recent several month, and 3) an elderly nocturia group composed of healthy persons who had a high mean frequency of nocturnal urination more than twice per night over recent several month without any other micturition disorders [28]. All the subjects underwent medical examinations at hospitals, their workplaces, or community medical centers once or twice every year. They had a good performance status and motor function. None of the subjects was receiving any medical treatment, and had any medical problems. One hundred and eighty volunteers who fulfilled the above criteria and agreed to participate in this study were enrolled. The young control group had 60 members (30 men and 30 women aged 20-45 years; mean age ± standard deviation: 32 8 years), the elderly control group had 60 members (30 men and 30 women aged 65-80 years; 70 4 years), and the elderly nocturia group had 60 members (30 men and 30 women aged 65-80 years; 72 5 years). There was no significant difference of mean age between the elderly control group and the elderly nocturia group. In all subjects from the 3 groups, blood samples were taken at 1-3 p.m. (daytime) and at 1-2 a.m. (at least 2 hours after going to bed at home or in the institutions: nighttime). Blood collection was performed after the subject had maintained a recumbent position for at least 30 minutes. Each blood sample was immediately placed in crushed ice, and analysis of 9 parameters (plasma adrenaline, noradrenaline, dopamine, serotonin, melatonin, orexin A, human atrial natriuretic peptide (HANP), brain natriuretic peptide (BNP), and arginine vasopressin) was performed. The osmotic pressure of plasma obtained during the daytime and nighttime was also measured, as well as that of urine voided between 1-3 p.m. and in the early morning. In the elderly control group and the elderly nocturia group, the blood pressure was measured at 1-3 p.m. Urinary frequency-volume charts were also recorded for 1-3 days to check the frequency of urination, the single voided urine volume, the total urine volume

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(daytime, nighttime, and 24-hour), and the nocturnal urine volume ratio (total urine volume excreted at night, including early morning urine, relative to the 24-hour urine volume). In subjects who have agreed to undergo body composition analysis in the early morning, at noon, and before sleeping, the body weight, the body mass index (BMI), the body water volume (intracellular water, extracellular water, and total body water), the ratio of total body water volume to body weight, and the ratio of extracellular water volume to total body water volume (edema ratio) were measured using a body composition analyzer (InBody2, MP Japan Co., Ltd. Tokyo)[29]. Daytime pg/mL 800

Noradrenaline

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pg/mL 60

40 20 0

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pg/mL 200

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10

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Figure 1. The daytime plasma nomoamine levels in young control, elderly control, and elderly nocturia groups.

20

0

pg/mL 40

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pg/mL 200

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Figure 2. The nighttime plasma nomoamine levels in young control, elderly control, and elderly nocturia groups.


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Daytime p<0.01

pg/ml 60

p<0.01 p<0.01

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p<0.01

40

p<0.01

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0 HANP

BNP

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Figure 3. The daytime plasma HANP, BNP and arginine vasopressin levels in the young control, elderly control, and elderly nocturia groups.

Nighttime pg/ml 60

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p<0.01 p<0.01 p<0.01

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40

20

0 HANP

BNP

Arginine vasopressin

Figure 4. The nighttime plasma HANP, BNP and arginine vasopressin levels in the young control, elderly control, and elderly nocturia groups. Nighttime pg/ml 80

p<0.01 p<0.01 p<0.01

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60

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0

0 Melatonin

Orexin-A

Figure 5. The nighttime plasma melatonin and orexin-A levels in the young control, elderly control, and elderly nocturia groups.

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In the biochemistry test of 3 groups, the daytime and nighttime plasma noradrenaline levels, as well as daytime HANP and BNP levels, were significantly higher, while the nighttime plasma melatonin level was significantly lower in both the elderly control group and the nocturia group than the young control group (Figs.1-5). Comparing the elderly control group with the elderly nocturia group, the nighttime plasma noradrenaline level, the daytime and nighttime dopamine levels, and the daytime and nighttime HANP and BNP levels were significantly higher, while the nighttime plasma melatonin level and the daytime and nighttime arginine vasopressin levels were significantly lower in the elderly nocturia group than the elderly control group. The daytime and nighttime plasma osmotic pressures were significantly higher in the elderly control group than the young control group or the elderly nocturia group. Urinary osmotic pressure during the daytime and the early morning was significantly lower in both the elderly control group and the nocturia group than the young control group, and both values were also lower in the nocturia group than the elderly control group. Among 9 biochemical parameters and the plasma and urinary osmotic pressures in all 180 subjects, there were significant correlations between the daytime and nighttime levels of adrenaline (r = 0.455, P < 0.001), noradrenaline (r = 0.705, P < 0.001), dopamine (r = 0.687, P < 0.001), serotonin (r = 0.946, P < 0.001), melatonin (r = 0.285, P < 0.001), HANP (r = 0.721, P < 0.001), and BNP (r = 0.975, P < 0.001). As the common gender difference of each group, the daytime and nighttime plasma adrenaline levels and plasma arginine vasopressin levels were significantly (each P < 0.05) higher in men than women. While, the daytime and nighttime plasma BNP levels were significantly (each P < 0.05) higher in women than men of the young and elderly control groups. The trends of the biochemical parameters among the men from the 3 groups were almost the same as among the women. About osmotic pressure in plasma and urine, same tendencies were also observed.

Daytime mmHg 180

Elderly control Elderly nocturia

150

p < 0.01

120

p < 0.05

90 60 30 0 Systolic pressure

Diastolic pressure

Mean pressure

Figure 6. The daytime blood pressure in the elderly control and elderly nocturia groups.


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Daytime blood pressure was measured in 31 subjects (19 men and 12 women) from the elderly control group and 44 subjects (29 men and 15 women) from the elderly nocturia group. None of the subjects had been diagnosed as having hypertension, but the systolic blood pressure and mean blood pressure were significantly higher (P = 0.002 and P = 0.012, respectively) in the elderly nocturia group (systolic blood pressure: 138.5 ± 13.7 mmHg, mean blood pressure: 98.2 ± 10.4 mmHg) than the elderly control group (systolic blood pressure: 126.0 ± 17.5 mmHg, mean blood pressure: 90.9 ± 12.9 mmHg) (Fig. 6). There was no significant difference of diastolic blood pressure between the elderly control group (73.3 ± 11.6 mmHg) and the elderly nocturia group (77.8 ± 10.6 mmHg). Twenty-seven subjects (19 men and 8 women) from the elderly control group and 29 subjects (21 men and 8 women) from the elderly nocturia group completed a frequencyvolume chart for a period of at least 24 hours. Based on these charts, 10 subjects had a single nocturnal urination in the elderly control group. Urinary frequencies at daytime and nighttime were significantly higher in the elderly nocturia group than the elderly control group. Mean single voided urine volume at nighttime (including early morning urine) was significantly larger in the elderly control group than the elderly nocturia group. The nighttime total urine volume and 24-hour total urine volume were significantly larger in the elderly nocturia group than the elderly control group. In the elderly nocturia group, 17 subjects (59%: 9 men and 8 women) had a nocturnal urine volume ratio > 33%, 6 subjects (21%: 4 men and 2 women) had a large 24-hour urine volume (> 2500 ml), and 4 of these 6 subjects (2 men and 2 women) also had a nocturnal urine volume ratio > 33%. The mean nocturnal urine volume ratio was significantly larger in the elderly nocturia group than the elderly control group. Since there were 17 subjects with a high nocturnal urine volume ratio > 33% (indicating nocturnal polyuria)[10,26,30] in the elderly nocturia group, we performed a further analysis based on the nocturnal urine volume ratio. When data from the 17 subjects (9 men and 8 women) with nocturnal polyuria and 12 subjects (all men) from the elderly nocturia group who had a normal nocturnal urine volume ratio (indicating no nocturnal polyuria) were compared, only plasma arginine vasopressin levels at daytime and nighttime were significantly lower (P = 0.018 and P = 0.007, respectively) in the subjects with nocturnal polyuria (1.8 ± 1.3 pg/ml and 1.5 ± 1.3 pg/ml, respectively) than the subjects without polyuria (4.3 ± 3.1 pg/ml and 3.8 ± 2.3 pg/ml, respectively). The daytime and nighttime plasma arginine vasopressin levels were also significantly lower (P = 0.005 and P < 0.001, respectively) in the subjects with nocturnal polyuria from the elderly nocturia group than those (3.3 ± 3.1 pg/ml and 3.4 ± 2.6 pg/ml, respectively) in the elderly control group (19 men and 8 women), but there was no significant difference between the subjects without nocturnal polyuria from the elderly nocturia group and those from the elderly control group. Body composition analysis was performed in the early morning, at noon, and before sleeping in 29 subjects (14 men and 15 women) from the young control group, 16 subjects (8 men and 8 women) from the elderly control group, and 20 subjects (8 men and 12 women) from the elderly nocturia group. There were significant differences of body weight, as well as intracellular, extracellular, and total body water among the 3 groups. However, there was no significant difference of the early morning BMI among the young control group (22.96 ± 3.56 kg/m2), the elderly control group (22.11 ± 3.71 kg/m2), and the elderly nocturia group (21.32 ± 3.59 kg/m2), as well as no significant difference of the ratio of total body water amount to


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body weight between the elderly control group and the elderly nocturia group. The ratio of extracellular water amount to total body water amount (edema ratio) measured at each time was significantly higher in both the elderly control group and the nocturia group than the young control group, and its ratio before sleeping was also significantly higher in the elderly nocturia group than the elderly control group (Fig. 7). In each 3 group, the edema ratio increased gradually throughout the day. In the young control group and the elderly control group, the edema ratios at noon or before sleeping were significantly higher (noon: P < 0.001 and P = 0.029, respectively; before sleeping: P < 0.001 and P = 0.029, respectively) than that in the early morning. In the elderly nocturia group, the edema ratio before sleeping was also significantly higher (P = 0.041) than that in the early morning. We also analyzed the water content of various regions of the body (the right and left upper extremities, the trunk, and the right and left lower extremities), but no region showed a significant increase of the edema ratio before sleeping compared with that in the early morning.

0.38 0.37

early morning noon before sleeping

0.36 0.35 0.34 0.33 0.32 0.31 0.3 young control

elderly control

elderly nocturia

Figure 7. The edema ratio of extracellular water amount to total body water amount in the young control, eldery control, and elderly nocturia groups.

In previous studies of nocturia, Carter et al. found that persons with nocturnal polyuria had diuresis and natriuresis, as well as a significant increase of HANP overnight, when compared with a control group [26]. It has also been reported that the nocturnal voided volume is correlated with the urinary arginine vasopressin/urinary creatinine level in urine samples obtained at 12 a.m. and 6 a.m. [27]. However, there have been few other reports about biochemical parameters or hormones in persons with nocturia, and body composition analysis had not been performed before. In the present study, we found that elderly persons had a characteristic increase of the plasma noradrenaline level during both the daytime and nighttime, an increase of HANP and BNP levels during the daytime, and a higher edema ratio in the early morning, noon, and before sleeping when compared with the young controls. Plasma noradrenaline and natriuretic peptide levels are increased in patients with congestive


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heart failure [31], and a significant increase of natriuretic peptide also occurs in patients with edema due to myocardial disease in an attempt to maintain arterial pressure by expansion of the blood volume [32]. Therefore, these results suggested that our elderly subjects were storing more water than our young subjects. The low urinary osmotic pressure during the daytime and early morning in both the elderly control group and the nocturia group also supported excessive water storage. On the other hand, the plasma melatonin level at nighttime was significantly lower in the elderly control group and the nocturia group than in the young control group. Since melatonin acts as a regulator of nocturnal sleep in humans [33], our elderly subjects may have suffered from sleep disturbance compared with the young persons. Comparison of the elderly control group with the elderly nocturia group revealed that the plasma noradrenalin level at night, the dopamine, HANP, and BNP levels during daytime and nighttime, and the edema ratio before sleeping were higher in the elderly nocturia group than the elderly control group. Additionally, the elderly nocturia group had lower plasma and urine osmotic pressure during daytime and nighttime, as well as lower plasma arginine vasopressin, and also had higher systolic and mean blood pressures during the daytime. These results suggest that our elderly subjects with nocturia suffered from excessive water retention compared with our elderly controls. The plasma melatonin level was also significantly lower at night in the elderly nocturia group than the elderly control group, implying that our elderly subjects with nocturia had more severe sleep disturbance than the elderly controls. Other characteristics of the elderly nocturia group were an increased daytime and nighttime frequency of urination, as well as an increase of the nocturnal urine volume, 24-hour urine volume, and the mean nocturnal urine volume ratio. Therefore, our elderly persons with nocturia seemed to have chronic excessive fluid intake, more severe sleep disturbance, and a tendency for hypertension compared with our elderly persons without nocturia.

The Causes of Nocturnal Polyuria Recently, it has been reported that the occurrence of nocturia can be attributed to nocturnal polyuria and/or diminished nocturnal bladder capacity [10,16]. Regarding nocturnal polyuria, it has been reported that the prevalence of nocturia in persons with hypertension is 68% for both men and women [25], and that the mean blood pressure is higher in men with nocturnal polyuria than in controls [34,35]. Therefore, hypertension may be one factor contributing to nocturnal polyuria. Hypertension caused by an increased noradrenaline and dopamine during the daytime would increase renal arterial resistance, decrease renal blood flow, and lead to insufficient daytime urine production [25,34] (Fig. 8). In the present study, the daytime plasma noradrenaline and dopamine levels, as well as the blood pressure, were significantly higher in the elderly nocturia group than the elderly control group, although there was no significant difference of daytime urine volume between these groups. Therefore, the daytime urine production may not be adequate in the elderly nocturia group with high catecholamine levels even though they have an excessive fluid intake. However, plasma noradrenaline and dopamine levels were lower at night than during the daytime in the elderly nocturia group. When catecholamines decrease at night, renal arterial


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resistance would also decrease and renal blood flow would increase, allowing urine production to increase in order to excrete water stored during the daytime. The decrease of arginine vasopressin in the elderly nocturia group might also be the result of excessive fluid intake and water retention based on an increase of circulating catecholamines and hypertension. In this study, we performed body composition analysis to explore the basis of nocturia from a new perspective. The body composition analyzer that we employed could rapidly provide detailed body composition data (weight, water volume, edema ratio, body mass index, fat mass, etc.) without the inconvenience of more invasive traditional methods [29,3638].

Increase of plasma catecholamine levels (Hypertension) Daytim e・ Kidney Increase of NA & DP

Nighttim e・ Kidney Decrease of NA & DP

Increase of renal Decrease of renal arterial resistance arterial resistance Decrease of renal blood flow Decrease of urine production

Bladder

Urethra・ Prostate

Increase of NA & DP

Increase of NA & DP

Activation of alpha-1 receptor

Activation of alpha-1 receptor of urothelium

Activation of alpha-1 receptor of smooth muscle cells

Increase of renal Decrease of glycinergic Increase of urine flow blood flow and GABAergic Increase of ATP resistance release neuronal activities Easy appearance Easy appearance of urge of urge

Increase of Extracellular water Increase of HANP & BNP

Spinal cord Increase of NA & DP

Obstructive bladder Increase of connection of smooth muscle cells

Nocturnal polyuria

Diminished bladder capacity

Nocturia Figure 8. Relationship between hypertension and nocturia.

Clinically, this machine is used to measure the dry weight of hemodialysis patients or to control the fluid balance in patients with end-stage renal failure [36,38]. In the present study, body composition analysis revealed that the edema ratio showed a gradual increase from morning to evening in all 3 groups. In the elderly nocturia group, the edema ratio before sleeping was higher than in the young and elderly control groups. This suggests that water accumulated in the extracellular compartment of the elderly nocturia group due to a decrease of renal blood flow and/or inadequate muscle pump function during the daytime. Water that has accumulated in the extracellular compartment during the daytime may enter the intravascular compartment at night and increase the circulating blood volume, thus bringing about a rise of HANP and BNP to increase urine production. It has been reported that daytime diuretic therapy is useful to prevent nocturia because it increases both frequency and urine volume during the day and decreases nocturnal frequency [39], and patients with nocturia who respond to diuretic therapy (azosemide) have high HANP levels [40].


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Therefore, a high fluid intake is another factor contributing to nocturnal polyuria, and excess water stored in the extracellular compartment may need to be voided before sleeping to prevent nocturia. The sleep apnea syndrome also induces nocturnal polyuria [41]. Venous return increases rapidly when inspiration occurs after apnea, and increased venous return releases HANP and BNP from the heart. This phenomenon may induce nocturnal polyuria (Fig. 9).

Sleep disturbance Sleep apnea syndrome

Decrease of melatonin

Increase of venous return during inspiration

Shallower sleep

Increase of HANP & BNP

Decrease of waking threshold

Nocturnal polyuria

Diminished bladder capacity

Nocturia Figure 9. relationship between sleep disturbance and nocturia.

The Causes of Diminished Nocturnal Bladder Capacity Sleep disturbance are a major factor related to nocturia in elderly persons [10,17,22]. Melatonin is one of the strongest natural antioxidants, and is produced by the pineal gland; it also has a close relation to the timing of sleep in humans [42-45]. In the present study, nighttime plasma melatonin level was found to be significantly lower in both elderly groups than the young control group, and the melatonin level of the elderly nocturia group was lower than that of the elderly control group. In young persons, the single voided urine volume in the morning is 1.5- to 2-fold larger than the mean single voided urine volume during the daytime [46]. In the present study, however, the single voided urine volume of elderly persons showed no significant difference between daytime and nighttime. Therefore, it is possible that a higher melatonin level increases the waking threshold in young persons, while a decrease of plasma melatonin leads to sleep disturbance and a lower waking threshold in older persons (Fig. 9). Elderly people with sleep disturbance may wake up to urinate at least once during the night because of both diminished nocturnal bladder capacity and shallower sleep. Indeed, administration of melatonin safely improves nocturia in patients with bladder outlet obstruction [47], while treatment with melatonin (3 mg per day) for up to 6 months improved

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the sleep quality and decreased the sleep onset latency in patients with insomnia [48]. In addition to melatonin, hypnotics are reported to be useful for treating nocturia [21,22,49]. Fujikawa et al. have reported that minor tranquilizers are especially effective for controlling nocturia in patients with low HANP levels [40]. Therefore, sleep disturbance may be one of the factors that diminish nocturnal bladder capacity, and treatment of sleep problems may be important to improve nocturia. It is also possible that an increase of plasma catecholamine levels is not only related to nocturnal polyuria but also to diminished nocturnal bladder capacity. Intrathecal injection of an alpha-1 adrenergic receptor antagonist inhibits isovolumetric bladder contraction without affecting the amplitude of bladder contraction in rats [50]. This suggests that an increase of plasma catecholamine levels may influence the ascending limb of the micturition reflex in the spinal cord and induce the urge to urinate at lower bladder volumes. This phenomenon may be similar to the feeling of urgency associated with stress. Indeed, administration of an alpha1 adrenergic receptor antagonist before sleeping to patients with morning hypertension has been shown to decrease nocturnal urinary frequency [51]. Moreover, administration of an alpha-1D adrenergic receptor antagonist inhibits the ATP release from the bladder urothelium [52,53]. The ATP activates afferent terminals of the bladder, and induces the urge to urinate. The catecholamines also activate the smooth muscles in the prostate and the proximal urethra, and induce the bladder outlet obstruction. The obstructive bladder also affects the spinal cord [54,55], bladder urothelium, and bladder smooth muscle structure [56], and induces easy appearance of the urge to urinate [57] (Fig. 8). Therefore, the increase of plasma catecholamine levels diminish bladder capacity.

Why Nocturia is Troublesome? Nocturia is the complaint that the individual has to wake at night one or more times to void [6]. However, some elderly persons do not consider nocturnal urination to be bothersome even if they have a number of episodes, while other persons feel bothered even if they wake up once per night. Accordingly, a therapy to target the perception of nocturnal urination as non-bothersome seems worthwhile to pursue, even though the actual decrease in the number of urinations may be small. Therefore, we investigated the factors related to nocturnal urination that was not considered bothersome by comparing various parameters between subjects who felt nocturnal urination as bothersome and those who did not [58]. The subjects were selected from among our outpatients. Patients who met the following criteria were enrolled: 1) their lower urinary tract symptoms --except for nocturnal urination-were controlled by medication (adrenergic alpha-1 receptor antagonists, anti-muscarinic agents, and/or herbal medicines) over a period of 2 months; 2) they had urination once per night; 3) they did not have neurological or psychological abnormalities, hepatic dysfunction, renal dysfunction, diabetes mellitus, or cardiovascular disease; and 4) they were not taking either tranquilizers, hypnotics, or melatonin. Patients with bacterial cystitis, bacterial prostatitis, urinary tract cancer, hematuria, or proteinuria were excluded. A total of 94 persons (50 males and 44 females aged 26-93 years) consented to this study and were enrolled. All 50 male patients had benign prostatic enlargement with or without an overactive


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bladder, while the 44 female patients had urethral syndrome and/or overactive bladder. Their residual urine volume was <20 mL on abdominal ultrasonography. We examined the average number of daytime urinations over one month, the average number of nocturnal urinations during the sleeping period, the International Prostatic Symptom Score questionnaire (IPSS) [59], the QOL score (happy: 0, satisfied: 1, almost satisfied: 2, not satisfied/not dissatisfied: 3, slightly dissatisfied: 4, dissatisfied: 5, unhappy: 6), and the perception of nocturnal urination (not bothersome, slightly bothersome, bothersome, or very bothersome). Subjects who stated that it was not or slightly bothersome were assigned to the non-bothersome group. When subjects stated that it was bothersome or very bothersome, they were assigned to the bothersome group. These groups were also stratified into subgroups by the frequency of nocturnal urination. Blood samples were taken from all subjects at 10-12 a.m. Then the complete blood count (white blood cells: WBC, red blood cells: RBC, hemoglobin: Hb, hematocrit: Ht, platelets: Plt) was measured, and biochemistry tests (serum total protein: TP, albumin: ALB, aspartate aminotransferase: AST, alanine aminotransferase: ALT, lactate dehydrogenase: LDH, cholinesterase: ChE, gamma-glutamyl transpeptidase: -GT, total bilirubin: T-Bil, blood urea nitrogen: BUN, creatinine, melatonin, and plasma arginine-vasopressin: AV, adrenalin, noradrenalin, dopamine, serotonin, human atrial natriuretic peptide: HANP, brain natriuretic peptide: BNP) were performed. The blood viscosity and the plasma osmotic pressure were also measured. These data were compared between the two groups and the subgroups. Among the 94 subjects with urination once per night, 60 subjects (32 males and 28 females aged 56 16 years) were in the non-bothersome group, and 34 subjects (18 males and 16 females aged 57 17 years) were in the bothersome group. However, the rate of subjects in the non-bothersome group gradually decreased with an increase in frequency of nocturnal urination, and the number of subjects in the bothersome group became larger than that in the non-bothersome group when the subjects were limited to those with urination 4 times per night. Daytime 20

non-troublesome troublesome

15

10 p<0.05

5

0 Melatonin

Arginine Vasopressin

HANP

Figure 10. The daytime melatonin, arginine vasopressin and HANP levels in patients with non-troublesome or troublesome noctururnal urination once per night.


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Among the 94 subjects with urination once per night, the serum melatonin level of the bothersome group was significantly lower (p=0.047) than that of the non-bothersome group (Fig. 10). The urinary frequency at nighttime, the total score of the IPSS, and the QOL score of the bothersome group were significantly higher (p=0.004, p=0.049 and p<0.001, respectively) than those of the non-bothersome group. There were no significant differences in other parameters between the two groups. Among the 50 subjects with urination twice per night, the serum melatonin level of the bothersome group (15 males and 9 females aged 65 13 years) was significantly lower (p=0.023) than that of the non-bothersome group (15 males and 11 females aged 62 16 years) (Fig.11). The QOL score of the bothersome group was significantly higher (p<0.001) than that of the non-bothersome group. There were no significant differences in other parameters between these two subgroups. Daytime 25

non-troublesome troublesome

20 15 10 p<0.05

5 0 Melatonin

Arginine Vasopressin

HANP

Figure 11. The daytime melatonin, arginine vasopressin and HANP levels in patients with non-troublesome or troublesome noctururnal urination twice per night.

In this study, biochemical parameters were compared between subjects with nonbothersome nocturnal urination and those with bothersome nocturnal urination. The serum melatonin level was lower in subjects with bothersome nocturnal urination regardless of the frequency of urination ( once per night and twice per night). In subjects with bothersome nocturnal urination once per night, the urinary frequency at nighttime, the total score of the IPSS, and the QOL score were higher compared with those in subjects with non-bothersome nocturnal urination once per night. However, among subjects with nocturnal urination twice per night, only the QOL score was significantly higher in the subjects with bothersome nocturnal urination. The parameters of the IPSS did not differ between the subjects with and without bothersome nocturnal urination because their lower urinary tract symptoms were controlled by medication, suggesting that the main cause of the increased scores of the IPSS and the QOL in subjects with bothersome nocturnal urination was nocturia itself. The melatonin level is significantly higher at night, with a significant correlation between daytime and nighttime melatonin levels [28]. Therefore, the difference in daytime melatonin levels between the two groups in the present study is thought to reflect a difference in the


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nighttime melatonin level. The decrease in the serum melatonin level in subjects with bothersome nocturnal urination suggests that they may have a sleep disturbance, which is one of the main causes of nocturia, rather than the decrease in the melatonin being produced by a lack of sleep due to nocturia. Administration of melatonin was found to improve nocturia in patients with bladder outlet obstruction [47]. Administration of melatonin (3 mg/day) for up to 6 months was reported to improve sleep quality and decrease the sleep onset latency in patients with insomnia [48]. In addition to melatonin, hypnotics are reported to be useful for treating nocturia [21,40]. Fujikawa et al. found that minor tranquilizers are especially effective for controlling nocturia in patients with low HANP levels [40]. Therefore, treatment of sleep problems is important for improving nocturia. Besides medication, walking for 30 minutes or more in the evening also decreases the number of nocturnal urinations and induces better sleep [60]. The main factor related to the influence of walking on nocturia is that sleep becomes deeper, which may increase the arousal threshold bladder volume. Therefore, any therapy for sleep disturbance may also become a therapy for nocturia. Nocturnal urinary frequency, a common symptom in the elderly, is one of the most bothersome urologic symptoms [1]. However, we found that the number of subjects in the non-bothersome group was larger than in the bothersome group. Among the subjects with nocturnal urination 4 times per night, however, the number in the bothersome group was larger than that in the non-bothersome group. Therefore, simply decreasing the number of nocturnal episodes of urination is not an effective therapy for nocturia. From the present findings, nocturnal urination being perceived as non-bothersome was thought to be related to maintaining a higher level of melatonin (a sleep inducer) and obtaining sufficient sleep. Therefore, any therapy for improving sleep will also be able to improve nocturia, even if the number of nocturnal urinations does not decrease significantly.

Can Melatonin Improve Nocturia? The serum melatonin level was found to be very low in patients with nocturia compared with those patients without nocturia [28]. Moreover, the level was lower in patients with bothersome nocturia compared with patients without this condition [58]. It has also been reported that melatonin is effective for nocturia in patients with benign prostatic enlargement [47]. Melatonin is an antioxidant and sleep inducer in humans [42] and is available as a supplement in many countries. We therefore compared the effects of melatonin and the hypnotic, rilmazafone, on nocturia in elderly patients. We also measurerd serum melatonin level before and after treatment. The subjects were selected from our outpatients. Patients who met the following criteria were enrolled: (i) their lower urinary tract symptoms (except for nocturia) were already being controlled by medication (adrenergic α-1 receptor antagonists, antimuscarinic agents and/or herbal medicines) for a period of at least 2 months;(ii) they had nocturia that was bothersome and urinated at least twice during their sleeping period; (iii) they did not have a high fluid intake for health reasons and they were being careful to avoid excessive intake because it could cause nocturia [61]; (iv) they did not have neurological or psychological abnormalities,

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hepatic dysfunction, renal dysfunction, diabetes mellitus, or cardiovascular disease; (v) they were not taking tranquilizers, hypnotics or melatonin; and (vi) they were not performing regular physical exercise (walking has been shown to decrease nocturnal frequency) [60]. Patients with bacterial cystitis, bacterial prostatitis or urinary tract cancer were excluded. The residual urine volume of each patient was < 20 ml on abdominal ultrasonography. The patients were randomly divided into two groups; one group received melatonin (2 mg/day) and the other group received rilmazafone hydrochloride (2 mg/day) for 4 weeks. Patients in both groups took their medication just before going to bed. This study was unblinded, hence patients knew which medicine they were using. We examined the mean number of daytime and nocturnal (during the sleeping period) urinations over 4 weeks, the QOL score using the International Prostatic Symptom Score (happy, 0; satisfied, 1; almost satisfied, 2; not satisfied/not dissatisfied, 3; slightly dissatisfied, 4; dissatisfied, 5; and unhappy, 6) [59], and the perception of nocturnal urination (not bothersome, slightly bothersome, bothersome, or very bothersome) before and after 4 weeks of treatment. Subjects who reported that nocturnal urination was not bothersome or only slightly bothersome were assigned to the ‗non-bothersome‘ category, while subjects who stated that it was bothersome or very bothersome were assigned to the ‗bothersome‘ category. We also examined the side effects of these agents and whether the subjects would like to continue treatment with melatonin or rilmazafone. Blood samples were taken from all subjects at 10:00 – 12:00 h at baseline and again after 4 weeks of melatonin or rilmazafone therapy for measurement. Serum melatonin, plasma HANP and brain natriuretic peptide (BNP) levels were measured by radioimmuno assay, and those levels were compared before and after treatment. This study was performed after obtaining approval from the Ethics Committee of the Faculty of Medicine, University of the Ryukyus, Japan, and all patients entered provided informed consent to participate. A total of 42 patients (25 men and 17 women, aged 65 – 79 years) were enrolled in this study. All 25 male patients had benign prostatic enlargement with or without an overactive bladder, while 10 female patients had urethral syndrome and/or an overactive bladder. The remaining seven female patients only had nocturia. A total of 20 patients (13 men and seven women, aged 73 7 years old) were randomly assigned to the melatonin group; and 22 patients (12 men and 10 women, aged 71 8 years old) were randomly assigned to the rilmazafone group. All male patients were being treated with α-1 receptor antagonists (tamsulosin or naftopidil) and an anticholinergic agent (propiverine hydrochloride). All female patients were receiving an anticholinergic agent (propiverine hydrochloride). Five female patients from each group had taken herbal medicines for at least 8 weeks before the start of this study. These medications were continued during the present study. There were no significant differences in age, QOL score, serum melatonin level, and plasma HANP and BNP levels between the two groups at baseline. At the start of the study, all patients considered their nocturnal urination to be bothersome. In both the melatonin- and rilmazafone-treated groups, the mean number of nocturnal urinations was significantly decreased (P < 0.001) after 4 weeks compared with baseline (Fig. 12). The mean number of daytime urinations, however, was unchanged. The mean QOL score was significantly improved in both groups (melatonin, P = 0.004; rilmazafone, P < 0.001) compared with baseline.


265 Daytime urination Nighttime urination QOL score

12 p < 0.01

p < 0.01

p < 0.01

p < 0.01

9

6

3

0 Before

after Melatonin

Before

after

Rilmazafone

Figure 12. The number of daytime and nighttime urinations, and QOL score before and after four weeks treatment in the melatonin- and rilmazafone-treated groups.

The mean serum melatonin level in the melatonin-treated group was significantly increased (from 5.6 ± 5.2 pg/ml to 87.2 ± 71.7 pg/ml, P < 0.001) after 4 weeks of melatonin administration, however, the mean level in the rilmazafone-treated group did not change after 4 weeks of rilmazafone administration (Fig. 13). There was no change in the HANP and BNP levels following administration of either melatonin or rilmazafone. pg/ml 100

p < 0.001

Melatonin HANP BNP

80

60

40

20

0

Before

after Melatonin

Before

after

Rilmazafone

Figure 13. The daytime melatonin, HANP and BNP levels before and after four weeks treatment in the melatonin- and rilmazafone-treated groups.

With regard to patients‘ impression of the effectiveness of the study medication, seven patients (35%) in the melatonin-treated group rated the treatment as either excellent or good and nine (45%) rated it as fair. In the rilmazafone-treated group, an excellent or good rating was reported by 10 (45%) patients and a fair rating by four (18%). There was no significant difference between the effectiveness ratings between the two groups. Before administration of melatonin or rilmazafone, all patients considered their nocturia to be bothersome. After 4 weeks of treatment, 14 (70%) patients from the melatonin-treated group and 11 (50%)

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patients from the rilmazafone-treated group considered their nocturia to be no longer bothersome. In one (5%) patient from the melatonin-treated group and two (9%) from the rilmazafone-treated group an unsteady feeling was sometimes noted when they woke at night to urinate, however these side effects were slight and the patients continued with the study treatment for 4 weeks. After administration for 4 weeks, 12 (60%) patients in the melatonintreated group wanted to continue therapy. This number was significantly larger than the six patients (27%) who wanted to continue rilmazafone therapy (P = 0.032). The reason for not wanting to continue therapy with either melatonin or rilmazafone was little or no effectiveness in eight (40%) patients from the melatonin-treated group and 10 (45%) patients from the rilmazafone-treated group. In eight (36%) patients from the rilmazafone-treated group, the fear of becoming unable to sleep without hypnotics was a reason for not wishing to continue with the medication. The three patients who had noted unsteadiness when they woke at night to urinate reported this as a reason for not wishing to continue with the medication.

Melatonin for Treatment of Nocturia In the present study, we compared the effectiveness of melatonin and rilmazafone hydrochloride in nocturia. In elderly patients who did not have an excessive intake of water and whose plasma natriuretic peptide levels were not very high, the efficacy of melatonin was almost equal to that of rilmazafone. The percentage of patients who assigned an excellent or good rating was, however, larger in the rilmazafone-treated group and the percentage that assigned a rating of fair or better was larger in the melatonin-treated group, although there was no significant difference between the two groups. The percentage of patients who came to consider nocturia as non-bothersome was larger (not statistically significant) in the melatonin-treated group and a significantly higher percentage of patients given melatonin hoped to continue with it compared with those given rilmazafone. Although the patients were randomly divided into the two groups, the study was unblinded and the patients knew which medicine they were using. Few patients were concerned about using melatonin, probably because it is available as a supplement, but several patients were concerned about using rilmazafone because they were worried about the potential risk of becoming dependent on hypnotics. Hypnotics have been reported to be useful for treating nocturia [21,22,40,49]. Fujikawa et al. [40] reported that minor tranquillizers are especially effective for controlling nocturia in patients with low HANP levels. It has also been reported that patients taking nitrazepam (a medium-acting hypnotic) have less difficulty returning to sleep compared with those who take triazolam (an ultra-short acting hypnotic), and that nitrazepam may be more appropriate for elderly patients who awaken because of nocturia [21]. Some patients, however, refuse to use hypnotics due to their fear of becoming dependent, even though they have insomnia. Sleep disorders can cause nocturia, while nocturia is one of the most bothersome urological symptoms and also results in sleep disturbance [1,3,10]. It is, therefore, common for patients to be uncertain whether nocturia is the cause of their sleep disturbance or if it is the sleep


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disturbance that leads to nocturia and for these patients, rilmazafone, a medium-acting hypnotic, has been shown to be effective [49]. Melatonin is produced by the pineal gland and is one of the strongest natural antioxidants; it is also closely involved in the timing of sleep in humans [42-45]. In our previous study, the night-time serum melatonin level was significantly lower in elderly persons than younger persons, and the serum melatonin level of elderly persons with nocturia was lower than that of elderly persons without nocturia [28]. Moreover, we found a significant correlation between daytime and night-time serum melatonin levels [28]. Administration of melatonin was reported safely to improve nocturia in patients with bladder outlet obstruction [47], while treatment with melatonin (3 mg/day) for up to 6 months improved sleep quality and decreased sleep onset latency in patients with insomnia [48].

Conclusion The serum melatonin level was increased by administration of melatonin (2 mg/day), but not by rilmazafone (2 mg/day), suggesting that the decrease of nocturnal urination after treatment with rilmazafone did not depend on the serum melatonin level. This suggests that melatonin and rilmazafone have different mechanisms of action. However, they were both found to be effective for treating nocturia in the elderly. We suggest, therefore, that when choosing a therapy for nocturia, physicians not only consider lower urinary tract function but also sleep disturbance.

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[24] Takahashi, S., Tajima, A., Matsushima, H., Kawamura, T., Tominaga, T., & Kitamura, T. (2006) Clinical efficacy of an alpha1A/D-adrenoceptor blocker (naftopidil) on overactive bladder symptoms in patients with benign prostatic hyperplasia. Int J Urol, 13,15-20. [25] Matthiesen, T.B., Rittig, S., Nørgaard, J.P., Pedersen, E.B., & Djurhuus, J.C. (1996) Nocturnal polyuria and natriuresis in male patients with nocturia and lower urinary tract symptoms. J Urol, 156, 1292-1299. [26] Carter, .PG., Cannon, A., McConnell, A.A., & Abrams, P. (1999) Role of atrial natriuretic peptide in nocturnal polyuria in elderly males. Eur Urol, 36, 213-220. [27] Hirayama, A., Fujimoto, K., Akiyama, T., & Hirao, Y. (2006) Decrease in nocturnal urinary levels of arginine vasopressin in patients with nocturnal polyuria. Urology, 68, 19-23. [28] Sugaya, K., Nishijima, S., Oda, M., Owan, T., Miyazato, M., & Ogawa, Y. (2008) Biochemical and body composition analysis of nocturia in the elderly. Neurourol Urodyn, 27, 205-211. [29] Okamoto, M., Fukui, M., Kurusu, A., Shou, I., Maeda, K., Hamada, C., & Tomino, Y. (2006) Usefulness of a body composition analyzer, InBody 2.0, in chronic hemodialysis patients. Kaohsiung J Med Sci, 22, 207-210. [30] van Kerrebroeck, P., Abrams, P., Chaikin, D., Donovan, J., Fonda, D., Jackson, S., Jennum, P., Johnson, T., Lose, G., Mattiasson, A., Robertson, G., Weiss, J. & Standardisation Sub-committee of the International Continence Society. (2002) The standardisation of terminology in nocturia: report from the Standardisation Subcommittee of the International Continence Society. Neurourol Urodyn, 21, 179-183. [31] Passino, C., Severino, S., Poletti, R., Piepoli, M.F., Mammini, C., Clerico, A., Gabutti, A., Nassi, G., & Emdin, M. (2006) Aerobic training decreases B-type natriuretic peptide expression and adrenergic activation in patients with heart failure. J Am Coll Cardiol, 47, 1835-1839. [32] Anand, I.S., Ferrari, R., Kalra, G.S., Wahi, P.L., Poole-Wilson, P.A., & Harris, .PC. (1991) Pathogenesis of edema in constrictive pericarditis. Studies of body water and sodium, renal function, hemodynamics, and plasma hormones before and after pericardiectomy. Circulation, 83, 1880-1887. [33] Bock, S.J., & Boyette, M. Stay young the melatonin way. New York, Lynn Sonberg Book Associates, 1995. [34] Bulpitt, C.J., Fletcher, A.E., Thijs, L., Staessen, J.A., Antikainen, R., Davidson, C., Fagard, R., Gil-Extremera, B., Jääskivi, M., O'Brien, E., Palatini, P., & Tuomilehto, J. (1999) Symptoms reported by elderly patients with isolated systolic hypertension: baseline data from the SYST-EUR trial. Systolic Hypertension in Europe. Age Ageing, 28, 15-22. [35] McKeigue, P.M., & Reynard, J.M. (2000) Relation of nocturnal polyuria of the elderly to essential hypertension. Lancet, 5, 486-488. [36] Yilmaz, A., Kayardi, M., Icagasioglu, S., Candan, F., Nur, N., & Gültekin, F. (2005) Relationship between serum leptin levels and body composition and markers of malnutrition in nondiabetic patients on peritoneal dialysis or hemodialysis. J Chin Med Assoc, 68, 566-570.

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[37] Al-Jaser, T.A., & Hasan, A.A. (2006) Fluid loss and body composition of elite Kuwaiti soccer players during a soccer match. J Sports Med Phys Fitness, 46, 281-285. [38] Kraemer, M. (2006) A new model for the determination of fluid status and body composition from bioimpedance measurements. Physiol Meas, 27, 901-919. [39] Reynard, J.M., Yang, Q., Donovan, J.L., Peters, T.J., Schafer, W., de la Rosette, J.J., Dabhoiwala, N.F., Osawa, D., Lim, A.T., & Abrams, P. (1998) The ICS-‗BPH‘ study: uroflowmetry, lower urinary tract symptoms and bladder outlet obstruction. Br J Urol, 82, 619-623. [40] Fujikawa, K., Kasahara, M., Matsui, Y., & Takeuchi, H. (2001) Human atrial natriuretic peptide is a useful criterion in treatment of nocturia. Scand J Urol Nephrol, 35, 310-313. [41] Umlauf, M.G., & Chasens, E.R. (2003) Sleep disordered breathing and nocturnal polyuria: nocturia and enuresis. Sleep Med Rev, 7, 403-411. [42] Brzezinski, A. (1997) Mechanisms of disease: melatonin in humans. N Engl J Med, 336, 186-195. [43] Dijk, D.J., & Cajochen, C. (1997) Melatonin and the circadian regulation of sleep initiation, consolidation, structure, and the sleep EEG. J Biol Rhythms, 12, 627-635. [44] Zhdanova, I.V., & Tucci, V. (2003) Melatonin, circadian rhythms, and sleep. Curr Treat Options Neurol, 5, 225-229. [45] Zhdanova, I.V. (2005) Melatonin as a hypnotic: pro. Sleep Med Rev, 9, 51-65. [46] Yamaguchi, O. (1999) Mechanism and treatment of nocturia in the elderly persons. Urological Review, 2, 2-5. [47] Drake, M.J., Mills, I.W., & Noble, J.G. (2004) Melatonin pharmacotherapy for nocturia in men with benign prostatic enlargement. J Urol, 171, 1199-1202. [48] Siegrist, C., Benedetti, C., Orlando, A., Beltrán, J.M., Tuchscherr, L., Noseda, C.M., Brusco, L.I., & Cardinali, D.P. (2001) Lack of changes in serum prolactin, FSH, TSH, and estradiol after melatonin treatment in doses that improve sleep and reduce benzodiazepine consumption in sleep-disturbed, middle-aged, and elderly patients. J Pineal Res, 30, 34-42. [49] Sugaya, K. (1991) Pharmacological evaluation of rilmazafone hydrochloride in urological clinics: Effect of rilmazafone hydrochloride on nocturia. Pharma Medica, 9, 81-86. [50] Sugaya, K., Nishijima, S., Miyazato, M., Ashitomi, K., Hatano, T., & Ogawa, Y. (2002) Effects of intrathecal injection of tamsulosin and naftopidil, alpha-1A and -1D adrenergic receptor antagonists, on bladder activity in rats. Neurosci Lett, 328, 74-76. [51] Sugaya, K. (2002) Medical diseases and lower urinary tract symptom (2). LUTS without lower urinary tract diseases in the elderly. Voiding disorders digest, 10, 196200. [52] Ishihama, H., Momota, Y., Yanase, H., Wang, X., de Groat, W.C., & Kawatani, M. (2006) Activation of alpha1D adrenergic receptors in the rat urothelium facilitates the micturition reflex. J Urol, 175, 358-364. [53] Sugaya, K., Nishijima, S., Tasaki, S., Kadekawa, K., Miyazato, M., & Ogawa, Y. (2007) Effects of propiverine and naftopidil on the urinary ATP level and bladder activity after bladder stimulation in rats. Neurosci Lett, 429, 142-146.


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Chapter XI

Melatonin and Other Sleep-Promoting Melatoninergic Drugs Under the Aspects of Binding Properties and Metabolism Rüdiger Hardeland* Institute of Zoology and Anthropology, University of Göttingen, Göttingen, Germany

Abstract In humans and other diurnally active mammals, melatonin acts as a sleep-promoting agent, but, for practical purposes, its short half-life in the circulation has been a major obstacle. Two different approaches have intended to overcome this problem, the development of slow-release pills and of other melatoninergic agonists, such as ramelteon and agomelatine, representing two non-indolic analogs of melatonin. With regard to sleep, melatonin and these analogs are acting in the same way, via the membrane-bound, high-affinity melatonin receptors MT1 and MT2 in the suprachiasmatic nucleus, which controls the hypothalamic sleep switch. Ramelteon displays a considerably higher receptor affinity, in conjunction with a much longer lifetime in the circulation, plus a contribution of one of its metabolites, M-II, to the melatoninergic actions. The affinities of agomelatine are close to those of melatonin, but the half-life of the analog is longer. In addition, agomelatine was shown to inhibit the serotonin receptor subtype 5-HT2C, an effect associated with additional antidepressive actions. In spite of the similarities with regard to sleep, several profound differences between the three compounds may be of importance. The use of slow-release melatonin should exert a much broader spectrum of effects, since this indoleamine acts, in addition to MT1 and MT2, via other binding sites, too, such as subtypes of the nuclear receptors ROR and *

Correspondence: Professor R. Hardeland, Institute of Zoology and Anthropology, University of Göttingen, Berliner Str. 28, D-37073 Göttingen, Germany. Tel.: +49-551-395414 (office); +49-551-393660 (laboratory); Fax: +49-551-395438; E-mail: [email protected]

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Rüdiger Hardeland RZR, quinone reductase 2, calmodulin, calreticulin and mitochondrial binding proteins. The actions of ramelteon and agomelatonine seem to be much more specific for the membrane receptors, although binding to the last-mentioned proteins has not yet been tested. Another profound difference concerns the metabolism of the agonists. The nonindolic compounds are hydroxylated, dealkylated or further oxidized in positions not homologous to those of the natural indoleamine. The entire kynuric pathway of melatonin metabolism is absent in ramelteon and agomelatine. Since biological effects have been ascribed to the melatonin-derived kynuramines AFMK (N1-acetyl-N2-formyl5-methoxykynuramine) and AMK (N1-acetyl-5-methoxykynuramine), this sector of melatonin‘s actions is missing. To date it is difficult to judge whether the full spectrum of melatonin‘s effects represents an advantage of the parental compound, when only sleep promotion is intended, or whether the higher selectivity of the analogs for membrane receptors will turn out to be a favorable property. However, the poorly understood actions of metabolites from ramelteon and agomelatine, including disproof or proof of toxicity, may be relevant for a future decision on the most suitable compound.

Introduction In vertebrates, the indoleamine melatonin (= N-acetyl-5-methoxytryptamine; Figure 1) acts as a chronobiotic, which mediates the information ―darkness― and which is capable of phase-shifting circadian oscillators [1-4]. Although melatonin is synthesized in numerous sites, including vegetative organs and immune cells, and although it acts systemically on a multitude of tissues [4-7], the fraction produced and secreted by the pineal gland is of utmost chronobiological importance. At least in mammals, the pineal-derived melatonin most widely determines the circadian rhythm of this hormone in the circulation. Although the indoleamine can be also releasd in high concentrations post-prandially from the gastrointestinal tract [8, 9], such diurnally occurring melatonin surges are chronobiologically relatively ineffective because they appear in the more or less silent zone of the circadian phase-response curve [4, 10]. In its role as a chronobiotic, melatonin acts by controlling the circadian master oscillator or pacemaker, the suprachiasmatic nucleus (SCN), where the membrane-bound, G-protein coupled receptors MT1 and MT2 are found in high density [11-14]. Although the two receptors can partially substitute for each other and likewise act by lowering cAMP levels via the Gi protein, their preferential actions can be distinguished. Effects via MT1 mainly consist of suppressions of neuronal firing, whereas those via MT2 cause phase shifts in the circadian system [4, 14-16]. These differences may be partially due to multiple, parallel signaling mechanisms also involving Gβγ and Gq proteins [4]. In the rat, phase-shifting was reported to require phospholipase C and protein kinase C activation [16,17]. The effects of melatonin on the SCN influence a host of oscillations downstream of the pacemaker. In diurnally active species, initiation and support of sleep are one of the most relevant effects. One should clearly distinguish this role from the actions of other sleepinducing compounds, such as benzodiazepines and ―z-drugs― like zolpidem, zopiclone, zaleplon or eszopiclone. Contrary to these frequently prescribed sleeping pills, melatonin – or other melatoninergic substances – do not act via direct central inhibition as mediated by GABAA receptors. They rather cause indirect effects via the SCN-mediated control of the hypothalamic sleep switch [18-20]. Secondary GABAergic effects involving the sleep switch

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are not excluded, but rather highly likely. However, they are regionally specific and not generalized. This difference implies that melatonin acts a truly hypnotic agent only in diurnal species. Sedative effects observed at higher dosage in nocturnally active mammals involve additional actions, such as antiexcitatory suppression of calcium signaling and inhibition of neuronal NO synthase [19], and have to be discriminated from the chronobiological control of sleep via SCN and sleep switch, although all these actions may be intertwined in diurnal species, too, especially upon pharmacological administration of melatonin or other melatoninergic drugs. O CH3

N H

H3CO

N H

Melatonin O CH3

N H

H3CO

O CH3

N H

H3CO O

HO

N H

N H

Indolinone tautomer of 2-hydroxymelatonin

6-Hydroxymelatonin HO H3CO N

N H

CH3 O

Cyclic 3-hydroxymelatonin O N H

H3CO

O CH3

O

NH

N H

H3CO

CH3

O

NH2

CHO

N1-Acetyl-N2-formyl-5-methoxykynuramine (AFMK)

N1-Acetyl-5-methoxykynuramine (AMK)

Figure 1. An overview of the main metabolic routes of melatonin. For further compounds originating from the metabolites shown see especially refs. [4], [6] and [32].

The use of melatonin itself as a sleeping pill was for a while only of limited success. Although there can be no doubt that the rise in melatonin secretion by the pineal gland is associated with an increase in sleep propensity [20, 21], the clinical outcome of melatonin administration was sometimes at or below the borderline of demonstrability and controversial [20, 22-24]. The main reason for the poor outcome has to be sought in the very short half-life of circulating melatonin. Two different approaches aimed to circumvent this problem. One consisted in the development of a slow-release formulation [25-28]. This led to the production of the melatonin pill CircadinTM (provided by Neurim, Israel), which has been recently approved by the European Medicines Agency (April 2007). The second line focussed on the production of new melatoninergic agonists with a longer half-life and, if

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possible, with a higher receptor affinity. In addition, these drugs should also exhibit a sufficient selectivity, i.e., for purposes of a sleeping pill, to be specific for MT 1 and MT2 receptors, whereas a pharmacological discrimination between these two receptor sutypes was not required. Although numerous agonists had been developed, only a few of them were clinically studied. This chapter will mainly refer to two compounds which are clinically used or tested and compare them with melatonin. The first one is agomelatine, which has been developed by Servier, France. In this compound {chemical name: N-[2-(7-methoxynaphth-1yl)ethyl] acetamide}, the indolic moiety is replaced by naphthalene (Figure 2). Although this drug is not exclusively melatoninergic, but also acts as an antagonist at the serotonin receptor subtype 5-HT2C, it has sleep-promoting properties. Especially because of its additional antidepressive effects [summarized in refs. 19, 20] it may become approved in the future. The second one is ramelteon {Rozerem®; TAK-375; chemical name: (S)-N-[2-(1,6,7,8-tetrahydro2H-indeno[5,4-b]furan-8-yl)ethyl] propionamide}, developed by Takeda Pharmaceutical Company Ltd, Osaka, Japan. This tricyclic non-indolic substance (Figure 3) has been approved for the treatment of insomnia by the Food and Drug Administration of the USA (July 2005). A third melatonin analog shall be also briefly considered, namely, β-methyl-6chloromelatonin (LY 156735), developed by Eli Lilly (Figure 2). Among the substances compared in this chapter, this drug is chemically most closely related to melatonin. A few studies have been conducted on the suitability of this compound for the treatment of insomnia and jet lag [29-31], but the overall clinical evidence has remained rather limited. O CH3

N H

H3CO

N H

Cl

ß-Methyl-6-chloromelatonin

O N H

H3CO

CH3

Agomelatine

O

O N H

HO

CH3

N H

H3CO

CH3

OH

S 21517

S 21540

Figure 2. Chemical structures of β-methyl-6-chloromelatonin, agomelatine and two main agomelatine metabolites.


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The comparison of the drugs mentioned is not primarily aiming to establish kind of a rank order in terms of sleep promotion. Instead, the reader‘s attention shall be directed to the pharmacological and, perhaps, toxicological consequences of differences between these compounds, with regard to receptor affinity and selectivity, bioavailability, metabolic routes, as well as to the profoundly distinct metabolites and their properties. Such differences, especially those concerning metabolism, may become decisive for judging the long-term safety of the respective drugs, which has not yet been sufficiently studied to date.

Binding Sites, Receptor Affinity and Half-Life Melatonin is one of the most systemically, pleiotropically acting regulatory agents in a vertebrate body [4, 6, 7]. This statement refers to both a multitude of target cells in numerous organs and various sites of different intracellular localization. In addition, secondary effects by metabolites of melatonin may contribute to the action spectrum of this compound [recently summarized in refs. 4, 32]. Especially the indolic derivatives seem to participate in an interplay with other central nervous regulatory systems, in particular, the serotoninergic network [32]. In addition to the afore-mentioned membrane receptors MT1 and MT2, binding sites of high or lower affinity have been identified or preliminarily described, such as the enzyme quinone reductase 2 (QR2 = NRH:quinone oxidoreductase 2 = NQO2; NRH = dihydronicotinamide riboside; Ki = 24 pM) [33-35], the nuclear receptors RORα1, RORα2, RZRα and RZRβ, which belong to the retinoic acid receptor subfamily [36-38], calmodulin [39-43], calreticulin [44], two other, functionally not yet characterized nuclear binding proteins, one of them with homology to calreticulin [44], and, at least, two mitochondrial binding sites, one of lower affinity associated with the inhibition of the mitochondrial permeability transition pore (IC50 = 0.8 µM) [45], the other with higher affinity (Kd = 150 pM) at the amphipathic ramp of complex I [46]. With regard to QR2, the precise role of melatonin binding is unclear. It has been speculated whether this may be related to protective actions of melatonin. At elevated concentrations, between 600 nM and 300 µM, melatonin inhibits the enzyme [47], but another ligand, resveratrol, is inhibitory already at 34 nM [48]. It should also be noted that QR2 displays an affinity to N-acetylserotonin, very close to that of melatonin [47]. N-Acetylserotonin is, at the same time, the most important melatonin precursor and one of its metabolites, but it also exhibits properties of a mainly serotoninergic agonist with actions independent of melatonin [32]. Uncertainties exist with regard to the affinity of melatonin to calmodulin. Contrary to other determinations, one recent study reported half-saturations in the millimolar range [42]. Leaving this point open, one could, however, conclude that most/many of the binding sites mentioned should be partially of fully saturated upon pharmacological doses of melatonin, as occurring after oral or rectal administration. There can be no doubt that the chronobiotic, i.e., phase shifting, and most other profound chronobiological effects are mediated by the membrane receptors MT1 and MT2. To what extent the other binding sites may also be of chronobiological relevance – not necessarily as chronobiotics, but as up- or downregulators of downstream processes – remains uncertain,

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not only in terms of affinity, but also with regard to the fact that some of them are found in extrapineal melatonin-synthesizing cells such as leukocytes, and to low circadian amplitudes of tissue melatonin [49, 50]. In humans, the affinities of melatonin to its membrane receptors (Ki = 80.7 and 383 pM, for MT1 or MT2, respectively [51]) are different, but in a concentration range attained or surpassed during the nocturnal peak in young or middle aged, healthy subjects. The difference indicates that the onset of suppression of neuronal firing may occur a little bit earlier than phase shifting, but this consideration has also to take into account the shape of the phase response curve for melatonin. When melatonin is administered to insomniacs, the higher pharmacological concentrations occurring after intake of the drug will rapidly saturate both receptors more or less simultaneously. This should also hold for prolonged-release preparations of melatonin. The affinities of agomelatine are a little bit higher, but still in the same range as those of melatonin (Ki = 61.5 pM and 268 pM, for human MT1 and MT2, respectively [52]). As already mentioned, this drug is not exclusively melatoninergic, but also displays properties of a 5-HT2C antagonist (IC50 = 270 nM), whereas it binds only moderately to 5-HT2B and shows negligible affinity for 5-HT2A and 5-HT1A receptors [52-54]. Little is known, or data may not have been published, about affinities to other melatonin binding sites. On the other hand, agomelatine does not show significant affinities to muscarinic, histaminergic, adrenergic, and dopaminergic receptor subtypes [55]. The unspecificity of agomelatine, which may appear, at first glance, as a severe disadvantage, could, however turn out to be of particular or even exceptional value, because the 5-HT2C inhibitory action, which causes secondary rises in fronto-cortical norepinephrine and dopamine concentrations [54], is associated with antidepressive actions [19, 20, 52, 54-57]. With regard to its melatoninergic actions, agomelatine is also capable of phase shifting circadian rhythms, including elderly subjects [58], and to promote sleep [19, 20, 56, 57]. Thus, the drug combines antidepressive effects with normalizations and appropriate timing of sleep, which is otherwise a problem in depressed patients in general and, especially, under the influence of various conventional antidepressants. β-Methyl-6-chloromelatonin (LY 156735) is, among the compounds discussed here, that one most closely related to melatonin. It also displays a high affinity to the membrane receptors MT1 and MT2 (Ki = 81 pM for MT1, and 42 pM for MT2). As with 6chloromelatonin [59], the affinity to MT2 is higher in this case. On this basis, one might assume that it could be one of the most efficient melatoninergic chronobiotics, and, in fact, phase shifting by this drug was demonstrated [31]. Its effects on sleep have been tested, but remained rather marginal [29, 30], what is reminiscent of the natural hormone when given as a single, rapidly releasing preparation. Ramelteon contrasts with melatonin by a higher affinity to the membrane receptors (Ki = 14 pM and 112 pM for human MT1 and MT2, respectively) [51]. It has no relevant affinity to QR2 (Ki = 2.65 µM), nor to γ-aminobutyric acid (GABA), dopamine, norepinephrine, acetylcholine, and opiate receptors, and only negligible affinity to the majority of serotonin receptors, with the only exception of a very moderate binding to 5-HT1A (Ki = 5.6 µM) [51, 60, 61]. Another property that strongly distinguishes ramelteon from melatonin is the considerably longer half-life in the circulation of 1 - 2 hours [18-20, 62], whereas the


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indoleamine has a half-life in the range of 20 - 30 min, sometimes even less, and maximally 45 min, depending on circadian time of administration and dosage [19, 63]. Moreover, one of the metabolites formed from ramelteon, usually referred to as M-II, attains much higher concentrations than the parent compound, eventually up to the 20- or even 100-fold, possesses properties of a melatoninergic agonist with about one tenth of ramelteon‘s affinity, and has an even longer half-life in the range of a 2 - 5 hours [18, 19, 62]. Moreover, ramelteon, which is more lipophilic than melatonin, is very efficiently taken up (gastrointestinal absorption rate about 84%). All these properties contribute to a higher bioavailability and efficacy. The half-life of agomelatine is also higher [64], but the superior bioactivity of ramelteon is not attained, under the aspects of both lifetime and receptor affinity. The persistence of β-methyl-6-chloromelatonin in the circulation is, with about 1 h half-life [29], also higher than that of the parent compound, since the 6-chlorinated drug (cf. Figure 2) cannot be hydroxylated at C-atom 6 by hepatic P450 monooxygenases, as is the case with melatonin.

Profound Differences in Metabolism and Their Consequences The metabolism of melatonin is highly complex [4, 7, 10, 32, 65], although this fact is not always perceived by researchers. In this regard, one has to distinguish between circulating and tissue melatonin. The hormone, as released from the pineal gland to the circulation, or entering the blood via oral or enteral administration, is mainly metabolized by hepatic P450 monooxygenases to 6-hydroxymelatonin, which is conjugated and preferentially excreted as 6-sulfatoxymelatonin. When giving melatonin in pharmacological doses, either orally or enterally, it is important to be aware that much of the indoleamine is also loaded to the gastrointestinal tract, which can act at the same time as a source and sink of melatonin [10], and where the indoleamine can undergo enterohepatic cycling without being metabolized [10, 66]. Especially pharmacological concentrations of melatonin seem to enter many other tissues, by virtue of its amphiphilicity, which allows this indoleamine to cross any membrane. In extrahepatic tissues, a substantial fraction of melatonin can be metabolized via other pathways, and since tissue melatonin exceeds the circulating amounts by orders of magnitude [9, 10], the relevance of the alternate pathways should not be underrated. A potentially important route is that of pyrrole ring cleavage, which leads to 5-methoxylated kynuramines (Figure 1) [10, 65] and their secondary products [4, 67, 68]. The most actual estimations assume that about one third of total melatonin may be metabolized via the kynuric pathway [69]. This conclusion is insofar important, as the kynuric metabolites are also bioactive compounds [4]. Additionally, several bioactive indolic metabolites are formed in the central nervous system [32], but, in quantitative terms, the relevance can be hardly judged on the basis of the available data. Moreover, 2- and 3-hydroxylated indolic metabolites are formed under oxidative conditions [70], such as cyclic 3-hydroxymelatonin and 2-hydroxymelatonin, which is in equilibrium with its indolinone tautomer (Figure 2), compounds which have been frequently found in cells or as excretion products after exposure to oxidants or to radiation.

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A look at the structural formulas of the melatoninergic agonists discussed here shows that none of them can be metabolized in the same way as the natural hormone, melatonin. In the most closely related compound, β-methyl-6-chloromelatonin (Figure 2), hydroxylation at C-atom 6 is impossible because of the chlorine atom at this position. Therefore, an analog of the major melatonin metabolite, 6-hydroxymelatonin, cannot be formed. This difference is likely to explain the longer half-life of the synthetic analog in the circulation. A full spectrum of metabolites from the chlorinated agonist has not been published. It seems possible that kynuramine analogs are generated in the metabolism of β-methyl-6-chloromelatonin, because the related 6-chloromelatonin is as easily oxidized via pyrrole ring cleavange as melatonin itself, at least in radical generating systems [71]. Whether or not β-methyl-6-chloromelatonin is equally well accepted as a substrate by melatonin-cleaving enzymes, such as indoleamine 2,3-dioxygenase and myeloperoxidase [4], is still inknown. The naphthalenic analog, agomelatine (Figure 2), exhibits, for fundamental reasons, even more profound deviations in its metabolism. Formation of kynuric compounds and derivatives is principally impossible, since a pyrrole ring is absent in the molecule. Two major metabolites have been described, N-[2-(7-hydroxynaphth-1-yl)ethyl] acetamide (= S21517) and N-[2-(3-hydroxy-7-methoxynaphth-1-yl)ethyl] acetamide (= S21540) (Figure 2) [53]. Dealkylation at the methoxy group, as occurring in S21517 formation, is similarly possible with melatonin [6], by the action of respective cytochrome P450 subforms, such as CYP2C19 and CYP1A2. The resulting 7-hydroxylated compound S21517 is, in structural terms, more serotonin-like and, in fact, exhibits affinity to 5-HT2C receptors. Whether additional serotoninergic effects via different receptor subtypes may exist should be a matter of further investigation. With regard to its molecular structure, S21517 should not substantially contribute to melatonergic effects. While agomelatine is an efficient inhibitor of 5-HT2C receptors, the 3-hydroxylated metabolite S21540 shows considerably weaker binding to this subtype [53]. It should also be noted that the hydroxylation at this position is profoundly different from corresponding reactions in the metabolism of melatonin, although hepatic P450 monooxygenases are responsible for these reactions with melatonin and agomelatine as well. This deviation is an unavoidable consequence of the replacement of the indolic moiety by a naphthalene group. The metabolism of ramelteon (Figure 3) differs even more from that of melatonin and the other melatoninergic agonists mentioned before. The various changes in the molecule, compared to melatonin, lead to specific consequences for reactions that are allowed or not allowed. The furan ring, which replaces the 5-methoxy group, largely prevents dealkylation and is maintained in metabolites M-II, M-III and M-IV. However, this ring can be oxidized, as is the case in metabolite M-I (Figure 3). Although this creates a structure partially reminiscent of N-acetylserotonin, a serotoninergic activity is rather unlikely, because the newly formed carboxyl group changes the biochemical and physical properties of the molecule considerably. The replacement of the N-acetyl residue by an N-propionyl group makes deacylation less likely, as it is occurring in the case of melatonin by actions of a specific melatonin deacetylase or less specific aryl acylamidases, including the aryl acylamidase activity of choline esterase [4, 32]. Although the unspecific enzymes can also remove other acyl residues, such metabolites from ramelteon have not been described, but one should take the possibility into account that resulting primary amines may be easily


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oxidized and give rise to further products. The presence of an N-propionyl group is reason for another type of oxidation reaction that is impossible in the N-acetylated amines, namely, a hydroxylation at C2 of the propionamide, which is found in metabolites M-II and M-IV. This hydroxyl group seems to be decisive for a change in live-time and, thus, blood plasma concentrations. The much longer half-life of M-II and the concentrations exceeding that of ramelteon by more than one order of magnitude, as mentioned in the previous section, are obviouly caused by this molecular difference, since the two compounds are otherwise identical. Another significant change in the chemical design of ramelteon concerns the replacement of the pyrrole ring-containing indole by an indene. As in the naphthalenic agomelatine, the 5-atom ring devoid of a nitrogen fully prevents ring opening, so that the kynuric metabolism is excluded. However, this also leads to a change in oxidation of the ring system, taking place at a position comparable to that of the N-atom in the indole, which would not allow such a reaction. Obviously, P450 subforms which are capable of hydroxylating melatonin at C-atom 6 do not accept ramelteon in the same way, and the isoenzymes responsible for the indene oxidation, as found in metabolites M-III and M-IV, may be worth of further investigation. With regard to the formation of M-IV, one should also note that two different sequences of oxidation steps are possible (Figure 3). O CH3 N H

O

Ramelteon

O

O HOOC

CH3

CH3 N H

HO

N H

O

OH

M-II

M-I

O

O

CH3

CH3 N H

O

N H

O

OH

M-III

O

Figure 3. The metabolism of ramelteon.

M-IV

O

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The different metabolism of ramelteon does not only exclude pathways known from melatonin. Apart from the kynuric route, hydroxylations corresponding to C-atoms 6, 2, and 3 of melatonin are not observed. However, the design of the molecule creates a situation that is highly unusual for drug metabolites: aliphatic hydroxylation to M-II generates a product which exceeds by far the blood levels of the parent compound and additionally exhibits melatoninergic properties. Although its affinity to MT1 and MT2 receptors is by one order of magnitude lower than that of ramelteon, this should be compensated by the higher concentrations attained. Therefore, M-II must be concluded to substantially contribute to the melatoninergic effects of ramelteon. A further aspect of metabolism which may be relevant to all three synthetical agonists discussed here concerns possible long-term toxicity. Even in the absence of acute toxicity, chlorinated aromates, naphthalenes and other polycyclic aromates may be problematic in the long run. These are necessary general considerations, especially for a hydroxylatable naphthalene, which is anyway under suspicion of eventual carcinogenicity. In the case of ramelteon, information provided by Takeda [72] indicates a no-effect level for the induction of hepatic tumors in male mice that was only 3 times of the concentration of the metabolite M-II measured after the therapeutic dose. Since M-II is structurally very similar to the parent compound, its eventual toxicity has to be taken into consideration. Moreover, micronuclei formation was observed with ramelteon, in Chinese hamster lung cells, after metabolic activation [72]. The same information sheet mentions no mutagenicity in the Ames test, but does not refer in this case to metabolic activation, which should be routinely done with this assay, too, including respective tests for M-II. In summary, acute toxicity is presumably not a problem with the compounds discussed, except for some diseases or co-treatments with other drugs for different medicinal purposes [18]. Nevertheless, their suitability for long-term treatment would require further substantiation. With good reasons, the paucity of information available on extended treatment with ramelteon has been criticized [73]. This is even more valid for agomelatine and β-methyl-6-chloromelatonin. Therefore, these drugs should be prescribed for long-term treatment, even in trials, only with caution.

Versatility Versus Selectivity: Advantage or Disadvantage? The remarkable pleiotropy of melatonin [4, 6, 7, 74, 75] is based on several, collectively exceptional properties: (i) wide distribution of receptors and other binding sites, (ii) multiplicity of binding sites found in different subcellular compartments, (iii) parallel signaling, (iv) cross-talking between signaling pathways, and (v) involvement of bioactive metabolites. This full spectrum of actions, which should be considered biologically meaningful for an agent with orchestrating functions, clearly exceeds in many ways the role of a sleep-promoting substance and, presumably, even that of a chronobiotic. Therefore, investigators from the sleep research field may question whether such a multiplicity of actions is really desired for treating insomnia, or may even regard this as a disadvantage. Without any doubt, a drug like ramelteon is much more specific for the membrane receptors MT1 and MT2. As outlined above, several other actions of melatonin related to QR2, to


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calmodulin, to direct radical reactions and activities of metabolites are excluded in the case of ramelteon. To a certain extent, especially with regard to metabolism, this seems to be valid for agomelatine as well, although the respective informations are scarce. Binding of βmethyl-6-chloromelatonin to intracellular proteins has been insufficiently studied to date – or, at least, not been published. While, on the one hand, actions not mediated by MT1 and/or MT2 may appear superfluous at first glance for a soporific drug, one should, on the other hand, also consider sleep induction and support as being related to readjustments of the circadian system, e.g., after a jet lag, for returning to a desired phase in shift workers, or in cases of circadian dysfunctions. Under these conditions, the full spectrum of orchestrating effects as exerted by melatonin, which affects more or less the entire body, may be thought to be advantageous. Therefore, a decision on this point is not that easy. Whatsoever, the efficacy of a compound like ramelteon justifies its prescription to insomniacs, at least, for short-term treatment. In the case of agomelatine, the situation is insofar different as the main reason for its use is the combination of antidepressive and hypnotic effects, whereas the other compounds including melatonin can counteract depression only if the disorder is caused by pathologically dysphased circadian rhythms [19, 20, 56, 57]. For β-methyl-6-chloromelatonin, no real advantage was apparent in comparison to melatonin [29-31]. Selectivity for receptor types should not be mistaken as total absence of pleiotropic effects. Even if a presumably purely MT1/MT2-specific agonist like ramelteon is administered, its actions are by far not restricted to the SCN, but should be found in numerous places of the body where these receptors are also located, including vasculature, immune cells and various vegetative organs [4, 6, 14, 74, 75]. In other words, a host of additional effects has to be expected in parallel to the hypnotic action, including influences on vasomotor and immune functions. In this regard, ramelteon shares properties with melatonin, but, by virtue of its higher receptor affinities and prolonged lifetime, its actions should be expected to be stronger and longer-lasting. Whether this has to be regarded as an advantage or a disadvantage can be hardly judged at the moment. Perhaps, an extension in bioavailability of the natural compound melatonin by slow-release formulations may appear as a safer way for treatment than the use of a synthetic agonist with elevated affinity and a long-lived metabolite of uncertain properties.

Conclusion The melatoninergic agonists discussed here differ with respect to receptor affinity, selectivity, pharmacokinetics and metabolism. The compound with highest affinity and selectivity, ramelteon, has the additional advantage of extended persistence in the blood, but in conjunction with these properties, attention seems due with regard to the metabolite M-II, which is also melatoninergic, attains much higher plasma levels, and should be more thoroughly investigated. Agomelatine shows affinities similar to those of melatonin, is less selective, has a somewhat longer lifetime and is converted to two metabolites whose properties require further detailed studies, the dealkylated one with regard to eventual other serotoninergic

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actions, and both of them under toxicological aspects. An advantage of agomelatine may exist in its additional antidepressive effects, which are combined with the sleep-promoting properties. β-Methyl-6-chloromelatonin does not seem to be superior to melatonin in terms of hypnotic efficacy. Therefore, the bottomline is whether any of these compounds should be preferred to melatonin as a sleeping pill. In the case of agomelatine, such an advantage may concern the treatment of depression, especially when this disorder is not related to circadian dysfunctions, but the decision on a future clinical application has to depend on long-term safety. This might be critical with a naphthalenic compound and its structurally similar metabolites. In the case of ramelteon, higher affinity and extended bioavailability may be seen as the main advantages, but, on the other hand, an extended bioavailability has been achieved also in the case of melatonin, with the prolonged-release formulation of CircadinTM. So one could ask what is preferable, a chemically designed drug of longer half-life, for which, however, longterm studies are urgently required, or a natural compound which has proved remarkably well tolerable? Also in the case of melatonin, some investigators have recommended caution, and the concerns were frequently directed to doses of the hormone which were smaller than those recommended for the synthetic drugs. To many investigators, this appears highly inconsequent. However, one should also take notice of the fact that melatonin has already been given in much higher doses. For more than a year, ALS patients received either 30 or 60 mg/day orally as slow-release pills [76], or 300 mg/day enterally as suppositories [77]. The aim was, of course, delay of disease progression, but no negative experiences were made in these studies. On the contrary, melatonin was well tolerated even at the extreme doses, along with hypnotic effects, from which the patients also profited. Although these high amounts would not be recommended for a normal sleeping pill, such findings should largely dispel the concerns of some researchers about the use of melatonin.

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[37] Carlberg, C. Gene regulation by melatonin. Ann NY Acad Sci 2000; 917, 387-396. [38] Tomás-Zapico, C; Coto-Montes, A. A proposed mechanism to explain the stimulatory effect of melatonin on antioxidative enzymes. J Pineal Res 2005; 39, 99-104. [39] Benítez-King, G; Huerto-Delgadillo, L; Antón-Tay, F. Binding of 3H-melatonin to calmodulin. Life Sci 1993; 53, 201-207. [40] Benítez-King, G; Ríos, A; Martínez, A; Antón-Tay, F. In vitro inhibition of Ca2+/calmodulin-dependent kinase II activity by melatonin. Biochim Biophys Acta 1996; 1290, 191-196. [41] Benítez-King G. Melatonin as a cytoskeletal modulator: implications for cell physiology and disease. J Pineal Res 2006; 40, 1-9. [42] Turjanski, AG; Estrin, DA; Rosenstein, RE; Mccormick, JE; Martin, SR; Pastore, A; Biekofsky, RR; Martorana, V. The interaction between melatonin and calmodulin: a NMR and molecular dynamics study. In: Pandi-Perumal, SR; Cardinali, DP, editors. Melatonin – From Molecules to Therapy. New York, Nova Science; 2007; pp. 47-68. [43] Landau, M; Zisapel, N. The low affinity binding of melatonin to calmodulin: use of computational methods to explain its physiological relevance. In: Pandi-Perumal, SR; Cardinali, DP, editors. Melatonin – From Molecules to Therapy. New York, Nova Science; 2007; pp. 69-79. [44] Macías, M; Escames, G; Leon, J; Coto, A; Sbihi, Y; Osuna, A; Acuña-Castroviejo, D. Calreticulin – melatonin. An unexpected relationship. Eur J Biochem 2003; 270, 832840. [45] Andrabi, SA; Sayeed, I; Siemen, D; Wolf, G; Horn, TF. Direct inhibition of the mitochondrial permeability transition pore: a possible mechanism responsible for antiapoptotic effects of melatonin. FASEB J 2004; 18, 869-871. [46] Hardeland, R; Poeggeler, B; Pappolla, MA. New vistas on mitochondrial electron flux rates and aging. Cell, Comment: http://www.cell.com/content/article/comments?uid= PIIS0092867408000627. [47] Delagrange, P; Boutin, JA. Therapeutic potential of melatonin ligands. Chronobiol Int 2006; 23, 413-418. [48] Buryanovskyy, L; Fu, Y; Boyd, M; Ma, Y; Hsieh, TC; Wu, JM; Zhang, Z. Crystal structure of quinone reductase 2 in complex with resveratrol. Biochemistry 2004; 43, 1417-1426. [49] Hardeland, R; Coto-Montes, A; Poeggeler, B. Circadian rhythms, oxidative stress and antioxidative defense mechanisms. Chronobiol Int 2003; 20, 921-962. [50] Hardeland, R. Antioxidative protection by melatonin – Multiplicity of mechanisms from radical detoxification to radical avoidance. Endocrine 2005; 27, 119-130. [51] Kato, K; Hirai, K; Nishiyama, K; Uchikawa, O; Fukatsu K, Ohkawa, S; Kawamata, Y; Hinuma, S; Miyamoto, M. Neurochemical properties of ramelteon (TAK-375), a selective MT1/MT2 receptor agonist. Neuropharmacology 2005; 48, 301-310. [52] Bourin, M; Mocaër, E; Porsolt, R. Antidepressant-like activity of S 20098 (agomelatine) in the forced swimming test in rodents: involvement of melatonin and serotonin receptors. J Psychiatry Neurosci 2004; 29, 126-133.

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[68]

[69]

[70]

[71]

[72] [73] [74] [75] [76]

[77]

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Chapter XII

Melatonin for Medical Treatment of Childhood Insomnias Jan Froelich and Gerd Lehmkuhl Hospital and Health Center for Psychiatry and Psychotherapy of the Child and Adolescence of the University to Cologne, Germany

Introduction Sleep disorders in childhood and adolescence are regarded as a common manifestation of symptoms of a disorder, mostly transitory in nature and in many cases caused by unsatisfactory sleep hygiene or maladjusted parent-child interaction during the falling asleep and sleeping through the night process. Furthermore, sleep disorders could exhibit comorbid symptoms with manifestations of psychiatric and neurological diseases [16, 17]. In these cases, they are often chronic and partially also serious in nature. In most cases, during consultation behaviorial therapeutic measues are indicated and are also sufficient. With manifestations of chronic disorders, medicinal measures play an important role [45]. Thus far, the use of an antihistamine, benzodiazepine or a neuroleptic can only be used with reservation or at least in the short term due to long-term side effects, the potential for dependency and substantial negative impacts on daytime alertness and memory functions [45]. With melatonin as an endogenous sleep-inducing hormone, for the first time a pharmacological treatment method essentially free of side effects could be offered for children. This paper summarizes the current, however still relatively narrow-based findings. The literature search is based on Medline-Search, in which substantial papers have been stored since 1985. Due to the still very provisional study status however, this could not consider exclusively randomized studies.

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Physiology and Pathophysiologiy of Melaton in Secretion Melatonin is a so-called indolamine and is produced in the pineal gland. Melatonin is synthesized from tryptophan, which for its part is converted into serotonin and then is enzymatically transformed into melatonin [31]. Melatonin synthesis is initiated by the connection of noradrenaline to adrenergic ß-1 receptors. Essentially, melatonin synthesis depends on the availability of tryptophan, which is dependent on nutritional factors, as well as on medicinal influences. Fluvoxamin, a serotonin reuptake inhibitor, increases the amplitude and duration of the melatonin plasma peak [57]. Melatonin plays a significant role in the synchronization of circadian rhythms [2], starting from the second half of the first year of life, in particular the sleep/wake rhythm. Melatonin secretion reaches its high point at the age of 3-6 years old and then decreases by adulthood by around 80% [55]. Influences of sex hormons on secretion, in particular during puberty, are not known [66]. Multiple effects are attributed to the hormone: It works to facilitate falling asleep on the one hand and on the other it is a circadian pacesetter and acts as a phase shifter. Both effects are used therapeutically in sleep medicine. These also include antioxidant effects, which can be used partially therapeutically with sucess in neonatology for septic and asphytic newborns [19,23]. Furthermore, effects in the oncology area are described as inhibitory, but also partly as a having a proliferative influence on tumor growth [4] as well as immunomodulatory effects[59]. Also, melatonin is inolved in endogenous body temperature regulation [7]. Arendt and Skene [2] attibute a chronobiotic effect to the hormone, since apart from influencing the sleep/wake rhythm, it also influences other vital parameters such as body temperature and cortisol secretion. The endogenous 24-hour melatonin profile is a reliable marker for circadian phase position. In order to examine this, it is not necessary to record the complete daily profile. It is sufficient to determine the melatonin increase in the evening with darkened light. This happens before falling asleep [35]. There is a high degree of dependence of hormone production on light conditions. Exposure to bright light during the night leads to a rapid decrease in melatonin secretion [34] and can lead in this way to a phase shift of the sleep/wake rhythm [11]. The inter-individual variation in regard to the volume of secreted melatonin is considerable and is either genetically-caused [68] or dependent on environmental factors, which can already have an intrauterine impact [30]. The melatonin secretion rhythm is generated by a endogenous clock, which is localized in the nucleus suprachaismatieus of the hypothalamus. The day/night cycle is the crucial exogenous interval timer of melatonin secretion. The most important neurotransmitter, which regulates melatonin secretion in the pineal gland, is noradrenaline, which is released at night in response to stimulating signals in the nucleus suprachiasmaticus. These assumptions are supported in human trials [6]. ß-1-receptor blockers and the Alpha-2 receptor blocker clonidin as well as alpha-methyl-para tyrosine, which reduces the pre-synaptic catecholamine concentration, suppress the nocturnal melatonin secretion. Conversely, melatonin secretion is enhanced by drugs, which increase the synaptic catecholamine availability, such as MAO

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inhibitors or tricyclic antidepressives. In addition, animal testing indicates that other neurotransmitters such as GABA, neuro-peptide Y dopamine and glutamate suppress melatonin secretion. To what extent these findings also apply to humans is still unclear [9]. A correlation of noctural melatonin secretion to sleep stages could thus far not be determined. Only a few studies are available on the effects of exogenous melatonin administration on sleep architecture. Overall, only a little influence seems to exist unlike, for example with conventional hypnotics [72]. In two studies it was reported that Melatonin has no effect on sleep stages 2, 3 and with adults patients middle-aged and older with Insomnia [20,25]. In other studies on patients with and without sleep disorders there was found tendentially a prolongation of sleep stage 2 as well as a shortening of sleep stages 3 and 4. During the non-REM sleep stage 1 and the REM sleep stage they remain unimpaired [69]. In a subsequent study no effects on sleep architecture could be determined [71]. Rajaratnam et al. [50] found likewise no influence on REM sleep by melatonin administration with, in contrast, a decrease of sleep stage 3 and an increase in sleep stage 2. Brezinski et al. [5] examined the influence of melatonin on the sleep structure and found only small changes. A reduction in sleep latency by 4 minutes showed up as well as an increase in overall sleep by 12.8 minutes and an improvement in sleep efficiency by 2.2%. Kunz [32] found, on the other hand, an increase in REM sleep after melatonin administration and have applied it already for treatment of a REM sleep condition disorder. Salti et al. [54] describe a connection between ultradian fluctuations of melatonin concentration and the REM sleep phases. In the neurological area, neurodegenerative diseases such as Parkinson‘s or Alzheimer‘s are accompanied by a partially dramatically decreased endogenous melatonin secretion. With both diseases serious problems falling asleep are present [72]. Sleeplessness without concomitant disease appears likewise to be partly connected with decreased melatonin seretion [24]. For psychiatric illnesses, there are a few findings on changes in melatonin secretion. Thus, with inpatient treatment of depressive patients a decrease in melatonin release was found in comparison to the healthy control persons [8, 33]. Lewy et al. [33] reported high melatonin concentrations with bipolar patients in manic phases as opposed to depressive phases and assumed that the amplitude of melatonin secretion indicated illness-induced changes of the noradrenergic function. Recent studies show, however, no changes in melatonin secretion in relation to melatonin peak as well as melatonin increase [63]. Heterogeneous results are also available from other psychiatric illnesses such as Schizophrenia and Anorexia nervosa [3].

Melatonin in the Treatment of Sleep Disorders In the clinically therapeutic area, the administration of melatonin causes a reduction in the time to fall asleep [66]. A precisely time-controlled administration before the individual‗s usual bed time can therapeutically positively initiate an earlier endogenous melatonin distribution and thus e.g. cause the readjustment of the sleep phase shifts [12].

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The majority of published studies were performed in selective patient groups during childhood and under a few systematic conditions, to the extent that their significance and/or validity is limited. Jan and Freeman [29] summarize in their overview the significant treatment results. The experiences are mainly with manifestations of pediatric neurological illneses [62]. Zhadanova et al. [70] reported, for example, on the results of melatonin treatment with 13 children with Angelman Syndrome and comorbid present sleep disorders. The main complaint picture was one of delayed falling asleep times, frequent nightly waking episodes with increased motor activity as well as early morning awakening. A six-day treatment with Melatonin (0.3 mg/kg per body weight) led to an actigraphically proven, highly-significant decrease in nocturnal movments and to an increase in total sleep time. A systematic examination of the possible influence on falling asleep time was not performed in this study. McArthur & Budden [37] treated 9 patients with Rett Syndrome with melatonin in a double-blind, placebo-controlled crossover study. Before treatment, the majority of children exhibited actigraphically increased prolonged falling asleep times, reduced total sleep times as well as noctural sleep interruptions. Under melatonin treatment (0.1-0.2 mg/kg per body weight) over three weeks the falling asleep time was significantly reduced, not however the other variables named in comparison to the placebo. Coppola et al. [10] in a placebocontrolled study obtained through melatonin administration of an average of 3-9 mg with mentally retarded children and adolescents with seizures and sleep disorders a significant reduction in the falling asleep times in comparison with the placebo, while on the other hand there was no specific influence on nocturnal awakening. Pillar and Mitarbeiter [48] actigraphically examined the sleep behavior of psychomotor retarded children of school age under average melatonin medication of 3 mg. Under this treatment, nocturnal sleep time was prolonged by an average of approximately 1.5 hours and sleep efficiency was increased from 69% to 88%. At the same time, the daily sleep of 3.2 hours regressed to 1.7 hours so that the total sleep time remained stable over 24 hours. This was hereby in addition accompanied by a substantial improvement in the quality of life of the parents as well as the children. Jan & O'Donnell [27] demonstrated in their study mainly the positive effect of melatonin treament on children with sleep disorders in their behavior during the day. Okawa et al. [43] reported on the positive effects of melatonin treatment on adolescents with sleep disorders in their school attendance. Espezel et al. [15] likewise saw positive effects of Melatonin treatment on children and adolescents with vision problems. The consequences of improved sleep were favorable for mood and alertness. In one earlier study of Jan et al. [26] with multiple-handicapped children with sleep disorders positive effects on memory and learning and social behavior were reported. In a recent study with craniopharyngeoma patients, silimar connections could be found between a reduced nocturnal melatonin secretion and intensified daytime fatigue [41]. In the pediatric neuropsychiatric area, there are promising approaches for melatonin treatment with vigilance-impaired and hyperkinetic children with sleep disorders if these are induced medicinally by methylphenidate. In particular, the prolonged falling asleep times with the children could be significantly reduced and the effects continued beyond the end of treatment [61, 73].


295

Van der Heijden et al. [65] treated 105 children ages 6-12 years old, who were afflicted by ADHD as well as a chronic falling asleep disorder, for 4 weeks within the scope of a double-blind, placebo-controlled study with melatonin. The falling asleep time decreased significantly under the verum condition as opposed to the placebo with a simultaneously significant pre-shifting of the evening endogenous melatonin secretion. In addition, the total sleep time increased significantly. Surprisingly however, there was no signficant change in the problem behaviors and cognitive dimensions. Garstang & Wallis [21] performed a randomized, placebo-controlled, double-blind treatment study with melatonin with 11 autistic children. In the verum group there was a severe decrease in the falling asleep latencies, a significant decrease in the nocturnal waking episodes as well as a significant increase in the sleep time in comparison to the untreated condition and in comparison to the placebo. Gianotti et al. [22] examined the long-term efficacy of melatonin treatment with 25 autistic children from the ages of 2-9 years old. During the 6-month treatment, sleep problems raised with all subjects in a sleep questionnaire and a sleep log improved. After discontinuing melatonin administration, with 16 children there was a reexacerbation of the sleep problem at the starting level. The re-start of treatment however was also again effective. With children, who experienced a continuous improvement in their sleep problems due to melatonin treatment, the treatment effects could be confirmed in 12- and 24-month follow-ups. Significant side effects did not occur during the treatment. Szeinberg et al. [60] describe positive effects of a long-term treatment over 6 months with 33 adolescents from the ages of 10-18 years old with sleep phase delay. The treatment was accompanied by an earlier sleep start and a longer total sleep duration. At the same time, there was a decrease in school difficulties. Serious side effects could not be determined. Furthermore, reports exist on successful melatonin treatments with bipolar disorder [52], with 20 children with manifestations of various pediatric psychiatric disorders [38] as well as with Asperger Autism [44]. Smits et al. [58] finally proved sleep phase accelerated effects with 62 children with chronic idiopathic insomnia. Also their psychophysiological state of health was affected favorably.

Effect Profile and Side Effects Pharmacokinetically, after approximately one ingestion of quick-acting, synthetic melatonin, maximum plasma concentration occurs, and then biphascially decreases again [47]. Jan et al. [27] therefore recommend ingestion approximately 20-30 minutes before going to bed. Great importance is attached however to an environmental structure promoting falling asleep, primarily darkened light conditions. The clinical effect of melatonin treatment starts independent of the dosage within a few days after the beginning of treatment. Dodge & Wilson [14] with their treatment collective with children with development delay initially determined a dosage of 5 mg as having a satisfactorily sleep-inducing effect. Paavonen et al. [44] argue that a two-week treatment attempt is sufficient to ensure that the effectiveness of a treatment can be assessed.


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Tolerance of the treatment in the present, non-systematic studies in general is good and here also with prolonged treatment, no loss of effect and few or no side effects occur [40, 53]. A significant toxicity with overdosages has thus far not been observed, as well as no teratogenic effects [49]. There are still no long-term studies available on tolerance [67]. These overall positive experiences however contradict single reports on the negative effects of melatonin administration with children, such as the triggering of cerebral seizures [56, 59]. There are now also reports on an anti-convulsive effect [46]. With inappropriate dosing times, serious sleep disorders can also be triggered [39]. Also a rapid recurrence of the previous sleep disorder was reported after discontinuation of the medication [42]. Other temporary side effects may result as well from the treatment, for example disorientation, headaches, dizziness, nausea, tachycardia as well as pruritus [28, 44] and negative immunomodulatory effects on asthmatic illnesses [59]. Due to the immunomodulatory effect of melatonin, the National Sleep Foundation moreoever recommends that melatonin be used in any case with the presence of lymphoproliferative diseases [cited no. 45]. Table 1. Treatment Results with Melatonin in Childhood.

Study

Illness Picture

Zhadanova et al. 1999

Angelman Syndrome

McArthur & Budden, 1998

Rett-Syndrome

Coppola et al. 2004

Jan & O‘Donnell, 1996

Mentally-retarded children with cerebral seizures Psychomotor-retarded children Non-retarded children

Espezel et al. 1996

Vision-impaired children

Various Sleep Disorders

Jan et al. 1999

Multiply-handicapped children

Various Sleep Disorders

Zotter et al. 2001 Tion Plan G 2003

ADHS + Comorbidities

Sleep disorders caused by Methylphenidate

Pillar et al. 2000

Complaint Picture < TST > Body movement in sleep > SOL > SOL < TST > Sleep interruptions Various Sleep Disorders Various Sleep Disorders Various Sleep Disorders

Procedures

Results_________

- Actigraphy > TST - 6 d melatonin, 0.3 mg/kg < Body movement per body weight in sleep ____________ ___ -Actigraphy < SOL - 3 weeks of melatonin - 0.1-0.2mg/kg per body weight___________ - Clinic treatment study < SOL - 3-9 mg melatonin ___ - Actiraphy > TST - 3 mg melatonin > SEI ___ - Clinical treatment study Effects on daytime behavior ___ - Clinical treatment study Effects on daytime Behavior ___ - Clinical treatment study Effects on memory, learning and social behavior ___ - Case Report >SOL

TST Total Sleep Time; SOL Sleep Onset Latency; SEI Sleep Efficiency Index

The influence of sexual maturity and sex hormones was proven in animal testing [13]. Concerning this aspect, the available study results indicate for example that the sexual maturity changes between Tanner stages 1-5 are accompanied by a significant decrease in melatonin secretion.


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Also the influence of the female menstrual cycle has been described. During Menopause there occurs a further decrease in melatonin secretion, which could possible correlate to changes in the gonadotropin concentrations [51]. A three-month administration of melatonin, for example, with some young, healthy volunteers resulted in massive reduction in spermatogenesis, which was also still detected 6 weeks after discontinuing the drug [36]. Application of the drug with children and adolescents should also again be critically reflected against the background of this still very uncertain study. Table 1 gives an overview of the results of the significant treatment studies performed thus far.

Discussion The results thus far available on the treatment of childhood sleep disorders with melatonin are unfortunately still very much incomplete and must therefore suggest an urgent need for further studies, especially treatment studies. Therefore, neither a binding dosage recommendation can be made for children, nor is there sufficient knowledge on the short or long-term side effects or intolerances that can be expected. Overall, the available findings are characterized by small, selected patient numbers, diagnostic uncertainty and the summary of different sleep disorders in a study. Furthermore, it appears problematic that thus far only children with central nervous system injuries more or less were treated so that the opportunity to compare sleep disorders in children without brain injury is limited. In addition, the applied objective measurement criteria are considered by many as too non-specific, both in terms of subjective sleep and vigilance variables as well as objective measured parameters. There are, for example, almost no polysomnographic findings, which examined a relationship between a change in melatonin secretion and the sleep stage structure. Thus far, the methodical approach to actigraphic discharges is limited. Studies on the effect of successful treatment on daytime vigilance is likewise missing. Also, there are no findings available on sleep disorders with children with manifestations of psychiatric disorders or with behavioral disorders without concomitant somatic findings. Questions on side effects or the development of tolerance must also remain open. Long-term treatment results and a review of the treatment process are also absent. Future systematic studies with precisely definied sleep disorders and somatic comorbidities must take the cited criticims into consideration in order to empirically substantiate and justify treatment with melatonin. Van den Heuvel et al. [64] dampen the overall positive expectations that are associated with the sleep-inducing effect of melatonin. In their critical analysis, they argue that a therapeutic effect can only be expected with low serum melatonin concentrations, administration on the day no sleep-inducing effect follows and the effects are in fact motivation-dependent or are dependent on the body position as well as occur with some limitation with young people and women.

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Buscemi et al. [6] also see the effects of treatment as rather limited. In a meta-analysis of 15 randomized, controlled studies, for example, no significant changes could be measured in the falling asleep latencies. In summary, the currently available results on the use of melatonin for the treatment of childhood sleep disorders, despite the still preliminary findings, are naturally of high interest. The precise mechanism is still unclear, with high probability however both that it induces sleep as well as makes the sleep phases rhythmic. Accordingly, there is the indication of successful administration mainly with falling asleep problems and sleep phase shifts. Lower efficacy is expected with sleeping through the night problems as well as waking problems. For most children with central nervous system injuries with partly serious, chronic sleep disorders, various behavior-related or pharmacological treatments can be carried out with rapid and significant treatment success without the occurrence of significant side effects. Even with long-term treatment a decrease in the effect does not seem to occur. It is recommended that dosage determination be made individually in accordance with the present state of knowledge and that a dosage range be set between 1 and 10 mg and be given just before falling asleep. Zhadanova identifies a physiological dose of < 1 mg as clinically effective [72]. Finally, it should be noted that drug treatment approaches are to continue to be understood as subordinate and temporary therapeutic approaches or with permanent use should be reserved primarily for severe neurological illnesses with comorbid sleep disorders [18].

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Chapter XIII

Melatonin: Its Significance with Special Reference to Sedation and Anesthesia Argyro Fassoulaki1, Anteia Paraskeva2 and Sophia Markantonis3 Professor and Chairperson in Anesthesiology, Aretaieio Hospital, Medical School, University of Athens1 Instructor in Anesthesiology, Aretaieio Hospital, Medical School, University of Athens2 Assistant Professor, Laboratory of Biopharmaceutics and Pharmacokinetics, School of Pharmacy, University of Athens, Athens, Greece3

Abstract Melatonin has been used to relief preoperative anxiety and stress. Several investigators reported that melatonin produces preoperatively anxiolysis and sedation. Patients undergoing laparoscopic cholecystectomy and pretreated with melatonin or midazolam exhibited less anxiety and increased sedation preoperatively compared with the controls. Similarly, patients undergoing gynecological laparoscopic surgery and premedicated with 5 mg of melatonin or with 15 mg of midazolam, or placebo were sedated in contrast to the control group. Psychomotor impairment after premedication was observed only in patients treated with midazolam. However, these effects are not reproducible by other studies. In elderly patients undergoing elective surgery 5 mg of melatonin or placebo given by mouth decreased anxiety scores to a similar degree. Melatonin premedication did not enhance the induction of anesthesia with sevoflurane as assessed by the bispectral index (BIS) monitor. Regarding the effect of sedative interventions and anesthesia on the endogenous melatonin release, acupuncture and acupressure may or may not affect melatonin levels. Also the inhalation anesthetic sevoflurane has been reported to decrease or to have no effect on endogenous melatonin. The different results may be attributed to the great variability associated with the measurements in melatonin levels, the different anesthetic techniques and coadministration of other agents, different populations in the relevant studies and other

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Argyro Fassoulaki, Anteia Paraskeva and Sophia Markantonis undetermined factors. Nevertheless, the interaction of sedative and anesthetic techniques with melatonin and vice versa is challenging and provocative in understanding the underlying mechanisms of sedation and anesthesia.

1. Introduction Melatonin is produced by the pineal gland from the aminoacid L-tryptophan, mainly during night as its secretion is regulated by darkness. In the pineal gland L-tryptophan is catalyzed to 5-hydroxytryptophan by tryptophan-5-hydroxylase, which is subsequently decarboxylated to serotonin by L-aromatic amino acid decarboxylase. Serotonin is metabolized to N-acetylserotonin by N-acetyltransferase, which in turn is methylated by hydroxyindole-O-methyltranferase to melatonin. As soon as melatonin is synthesized it is released into the general circulation. Its half life varies between 30 and 60 minutes. Melatonin is metabolized to 6-hydroxymelatonin of which the greater part is metabolized to 6-hydroxymelatonin sulfate and only 10% to 6-hydroxymelatonin glucuronide. There are other minor metabolites and a small percentage of melatonin is excreted unchanged in the urine (1). Melatonin exerts its effects by binding to the MT1 and MT2 membrane receptors, which are coupled to the G-proteins. The MT1 and MT2 receptors are mapped to different chromosomes and consist of 350 and of 363 aminoacids respectively. The MT3 melatonin receptor is involved in intraocular pressure regulation (1). The hormone maintains the normal circadian rhythms, induces sleep and is a potent free radical scavenger. Its plasma levels reflect the activity of the pineal gland and are highest prior to bedtime. Melatonin has been used to relieve preoperative anxiety and stress. Several studies have investigated the effect of melatonin in the preoperative setting and its efficacy with respect to the relief of fear and stress. These effects are significant as melatonin is not associated with respiratory depression, heavy sedation or nausea and vomiting, effects produced by premedicants such as benzodiazepines and opioids. On the other hand a potential effect of sedative and anesthetic drugs and techniques on melatonin levels may interfere positively or negatively with normal uninterrupted sleep. The present article reviews the work investigating the role of exogenous melatonin as premedicant and/or as an adjunct in patients receiving anesthesia as well as the literature available on the effect of sedative and anesthetic techniques and drugs on endogenous melatonin release.

2. Effect of Melatonin on Anesthesia 2a. Relief of Preoperative Stress - Premedication Melatonin has been used as premedicant to relieve preoperative anxiety and stress. In a prospective randomized double-blind controlled trial patients undergoing laparoscopic cholecystectomy received either 5 mg of melatonin or 15 mg of midazolam or placebo

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sublingually, 90 minutes before surgery. Those patients treated with melatonin or midazolam exhibited less anxiety and increased sedation preoperatively compared with patients in the placebo group. However, postoperatively neurophysiological performance was similar in the three groups (2). In another double-blind placebo-controlled trial also comparing melatonin to midazolam patients were premedicated with 5 mg of melatonin or 15 mg of midazolam, or placebo 100 min before the operation. The premedicants were administered sublingually. The authors reported that melatonin and midazolam treatments produced sedation in contrast to the placebo treatment. Anterograde recall was impaired only in the midazolam group (3). In a dose response study patients were pretreated with 0.05, 0.1 and 0.2 mg/kg of sublingual midazolam or melatonin. At 90 min sedation was observed in 33.3%, 33.3% and 66.7% of midazolam group respectively, while for the same doses of sublingual melatonin 41.7%, 33.3% and 66.7% of patients were sedated. Psychomotor impairment preoperatively was observed in those patients treated with midazolam but not in patients treated with melatonin or placebo (4). In both Naguib studies midazolam but not melatonin premedication was associated with psychomotor impairment before operation. Melatonin in contrast to midazolam did not enhance postoperative sedation and was not associated with cognitive and psychomotor dysfunction. Nevertheless, these effects are not reproducible in all studies. Elderly patients (>65 years) undergoing elective surgery received 10 mg of melatonin or placebo by mouth. Anxiety scores were decreased to a similar degree in both the melatonin and placebo groups (5). Another study that failed to demonstrate a beneficial effect of melatonin as sedative was conducted in children undergoing magnetic resonance imaging. Melatonin 3 or 6 mg given orally for the smaller (<12 kg) or bigger (>12 kg and < 40 kg) children respectively neither shortened the onset time nor prolonged the duration of sedation produced by chloral hydrate in the smaller or temazepam and droperidol for the bigger children respectively (6). Several reasons may account for these differences such as the route, the dose and the time of melatonin administration.

2b. Melatonin and General Anesthesia Melatonin has been reported to exhibit a hypnotic effect and to enhance the intravenous induction of anesthesia by thiopental and propofol. In animal studies (rats) intravenous administration of melatonin produced loss of righting reflex in a dose dependent manner. In the same study intravenous melatonin increased the threshold of paw withdrawal after pinching the rat at the paw, effect similar to that produced by intravenous propofol. The response to tail clamping was abolished in 43% of rats injected intravenously with 257 mg/kg melatonin, in 100% of rats treated with 20 mg/kg intravenous propofol, and in 71% of rats treated with 20 mg/kg intravenous thiopental. Thus melatonin exhibits hypnotic and antinociceptive effects but the doses required are much higher than the doses of thiopental and propofol (7).

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In another animal study the analogue of melatonin 2-bromomelatonin given to rats intravenously produced loss of the response to tail clamping and of the righting reflex (8). These effects were found to be dose dependent and 6-10 times less potent than the same effects produced by propofol. Also in rats melatonin given orally in a dose of 20 mg/kg enhanced the loss of righting reflex produced by ketamine and thiopental and prolonged their effect. The onset of anesthesia was assessed by the loss of righting reflex. It appears that there is a synergistic effect of melatonin with these anesthetics. However, melatonin had no effect on the anesthesia produced by ether (9). Thiopental, propofol or melatonin injected into the internal jugular vein of rats in ED95 doses required to loose the righting reflex, i.e. 23.8 mg/kg, 14.9 mg/kg and 312 mg/kg respectively, produced EEG changes on the processed EEG. All drugs decreased the relative spectral edge 95% and the relative approximate entropy. However, melatonin was associated with a slower onset and a longer duration of these EEG parameters (10). Not only experimental studies but studies in humans as well support the efficacy of melatonin as an adjunct to the drugs producing general anesthesia. In a double-blind randomized study 200 adults were assigned to receive by mouth either 0.2 mg/kg melatonin or placebo. Melatonin given 50 minutes before induction of anesthesia was found to decrease the thiopental and propofol ED50 doses required to abolish the eyelash reflex and the response to a verbal stimulus. After melatonin premedication the relative potency of thiopental was increased by 1.3 and that of propofol by 1.7 compared to the relative potencies recorded after placebo premedication (11). Incremental doses of 10 mg of propofol required to obtain a BIS value of 45 were decreased when patients were premedicated with 3 or 5 mg of melatonin given orally 100 minutes before surgery. The mean doses of propofol required were 115 ± 19.5 mg, 114 ± 20.9 mg and 134 ± 25 mg in the 3 and 5 mg melatonin groups and the placebo group respectively. The dose of propofol required to bring the BIS value down to 45 was similar after melatonin 3 or 5 mg. Melatonin decreased the dose of propofol required to abolish the eyelash reflex and the responses to verbal stimuli (12). However, all studies do not demonstrate an enhancement of anesthetics by melatonin. Melatonin premedication in patients anesthetized with inhalation induction using sevoflurane in oxygen did not enhance the induction of anesthesia as assessed by the bispectral index (BIS) monitor. BIS indicates the level of anesthesia at the cerebral cortex and BIS values were not affected in the melatonin treated group as compared to the controls. The dose of melatonin was 9 mg given sublingually, and the patients studied were outpatients and did not receive any premedication except for melatonin as determined by the study protocol (13).

2c. Effect of Melatonin on Postoperative Outcome In addition to its sedative effect melatonin has anti-inflammatory and analgesic actions, rendering this hormone a useful premedicant drug with an impact on the postoperative pain control (14). In a randomized, double-blind, placebo-controlled trial, women scheduled for abdominal hysterectomy received 5 mg of melatonin orally the evening before operation and one hour


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before surgery. A control group was treated identically but received placebo instead. Patients treated with melatonin exhibited less postoperative pain up to 36 hours postoperatively as expressed by the VAS scores and consumed less morphine up to 48 hours postoperatively (15). These results appear to be very optimistic for melatonin administered preoperatively only. Also, since all patients had access to PCA morphine it is hard to explain why the patients in the placebo group experienced more pain since they had the choice to consume more morphine. Melatonin 5 mg administered orally the night before operation and one hour preoperatively was found to decrease morphine requirements after abdominal hysterectomy in the highly anxious patients by 30% or more. This effect was not observed in the mildly anxious patients (16). Tourniquet pain during intravenous regional anesthesia for hand surgery causes patient discomfort and requires rescue analgesia. Melatonin premedication 10 mg given 90 minutes before surgery produced less pain due to tourniquet, decreased the doses of opioid and of diclofenac during the first postoperative hours and prolonged the time to the first analgesic after surgery (17). Nevertheless, there is a great variability among studies exploring the relationship between anesthesia and sedation on one hand and melatonin on the other. The oral route of administration of melatonin is one of the sources of variability. In recent years, administration of exogenous melatonin, primarily by the oral route, has been used to explore the effect of melatonin in humans. This approach was especially used to reveal melatonin‘s sedative and/or hypnotic properties (18,19). However, oral melatonin administration is disadvantageous because of its poor and unpredictable bioavailability (5% - 56%) (20,21) as a result of extensive first-pass hepatic extraction and inconsistent absorption from the gastrointestinal tract (20,22-23). This may result in serum melatonin concentrations differing up to 25-fold among subjects after application of the same dose (19,24-25), giving a possible explanation for some of the inconsistencies in reported results (21). Furthermore, from a theoretical point of view, 6-sulphatoxymelatonin excretion may not reflect serum melatonin levels after its oral application, because of a variable first pass effect among subjects (21). Lane and Moss concluded from pharmacokinetic studies that 30–60% of oral melatonin is metabolized to 6-hydroxymelatonin in the liver during the first pass (23), and this portion of melatonin never enters the general circulation. Poor formulation and/or poor quality of some orally administered melatonin products have been found to result in unpredictable melatonin release. Certain products have shown excessive friability, failure to disintegrate and dissolve, and excessive variation in hardness. In vitro release profiles of the two controlled-release products were found to be substantially different (26). Differences in the pharmacokinetic profile of melatonin following its oral administration have been observed in obese subjects due to an apparent volume of distribution greater than the extracellular volume (20% of the total body weight) (20,27), while in patients with cirrhosis decreased elimination resulting in elevated serum melatonin levels has been found (28). Also, delayed elimination has been reported in patients with stomach ulcers resulting in higher blood levels (28).

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3. Effect of Anesthesia and Traditional Sedative Techniques on Melatonin General anesthetics may modulate several multisynaptic neuronal functions. Whether anesthetics affect pineal melatonin secretion and eventually serum melatonin levels has been the objective of several studies in animals and humans. In anesthetized patients possible changes in melatonin levels by anesthetics may interfere with the nocturnal rise in melatonin and normal biological rhythms. In New Zealand white rabbits pentobarbital had no effect when administered in the late light and early dark period. In similar experiments with ketamine melatonin secretion was enhanced. In contrast, halothane anesthesia decreased melatonin levels (29). The effect of anesthetic and sedative drugs on melatonin levels in humans has been studied by several investigators. In children undergoing ambulatory surgery under general anaesthesia thiopental 5 mg/kg or midazolam 0.4 mg/kg did not significantly change plasma melatonin levels measured in samples obtained 5, 10 and 20 minutes after drug administration (30). Regarding inhalation anesthesia in adults, isoflurane in concentrations as high as 5% increased while 7% inspired concentration of sevoflurane decreased plasma levels of melatonin (31). The authors attributed the increase in melatonin levels found after isoflurane anesthesia to the stimulation of the sympathetic nervous system by isoflurane. Nevertheless, they provided no possible explanation for the decrease in melatonin plasma levels found after sevoflurane anesthesia. The study included a limited number of patients, nine in each group (31). Other investigators have also reported increased melatonin levels after isoflurane anesthesia. Patients undergoing elective gynecological procedures under general anesthesia with thiopental and isoflurane exhibited elevated melatonin levels that persisted during the first 8 hours postoperatively, i.e. the period of last blood sample collection. Patients undergoing the same surgical procedure under propofol anesthesia also exhibited an increase in melatonin levels, which however declined during the 8 hours recovery period during which blood sampling was discontinued (32). These results are in contrast to the results of a recent study in which sevoflurane was administered as the sole anesthetic agent in women undergoing dilatation and curettage of the uterus. Blood samples to measure serum melatonin levels were collected before, immediately after as well as 2, 4, 8, and 24 hours postoperatively. The variation in melatonin values did not differ with respect to time or to group effect when compared with a group of healthy volunteers (33). The authors attributed their findings to the fact that the operation was a minor one and to the high variability of measured melatonin levels. The investigators collected blood samples before and immediately after surgery, as well as 2, 4, 8 and 24 hours postoperatively; they did not measure melatonin levels in serum around or after midnight. Thus possibly lower melatonin night-time levels might have escaped detection. However, all patients reported no sleep disturbances as the quality, duration and type of sleep, continuous versus intermittent, did not differ before and after sevoflurane anesthesia. Melatonin levels in saliva and 6-hydroxymelatonin sulphate in the urine were determined in ten patients undergoing general anesthesia and in nine patients undergoing subarachnoid


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anesthesia for minor knee surgery. Samples were collected at 21:00, 22:00, 23:00 and 24:00 on the day before surgery as well as on the day of surgery. Melatonin secretion in saliva was decreased during the first postoperative evening when compared to saliva melatonin levels measured the preoperative evening (34). A significant decrease was also found in the 6hydroxymelatonin sulphate urine excretion, a melatonin metabolite. Since the authors collected successive samples during the night they demonstrated an abnormal circadian rhythm of melatonin postoperatively. Surgical patients appear to exhibit disturbances in melatonin release and circadian rhythm. Cronin et al reported significantly lower melatonin serum levels during the first postoperative night in samples collected hourly versus the samples collected on the second and third postoperative night (35). These patients had hysterectomy or myomectomy and received general anesthesia plus an epidural catheter to control postoperative pain. In patients operated for cancer of the colon melatonin concentrations in the gut tissue were elevated in samples collected during the day and night, the day-time levels being 10 times higher than the day-time levels in plasma (36). In contrast in minor surgical procedures melatonin levels in plasma did not change. Perioperative fluctuations in plasma melatonin levels may be induced by several factors as type of anesthesia, though according to the data available there is no strong evidence supporting such changes. The type of surgery, major versus moderate or minor surgical procedures, may play a role along with the secretion of other hormones when the surgical stress is major. Attributing postoperative sleep disturbances to melatonin and circadian rhythm is rather simplistic, as anesthesia itself, the response to surgical trauma, food deprivation and most importantly inadequate pain relief bring about a disruption in body functions, particularly those of the central nervous system. Possible derangements of melatonin secretion postoperatively may be associated with sleep disturbances occurring in the surgical patient. Melatonin replacement in the first postoperative days may help to improve or to restore normal sleep patterns during the postoperative period. Also, applying techniques which may increase melatonin secretion may be useful to treat anxiety and sleep disturbances. Acupuncture and acupressure techniques reduce anxiety, relieve stress and may improve normal sleep. In an open clinical trial 18 adults suffering from insomnia received two sessions of acupuncture per week for five weeks. When the study was completed, concentrations of 6-sulphatoxymelatonin, the major metabolite of melatonin in urine, were increased during the periods midnight to 8 AM and decreased from 8 AM to 3 PM when compared to the pretreatment concentrations (37). Sleep improvement was noted during night. (37). In another study stress decrease after application of acupressure on the extra 1 acupoint was not associated with significant changes in serum melatonin levels. In fact melatonin was decreased one hour after the intervention by 30% but this decrease was not statistically significant (38). However, in this study acupressure was applied only once, thus the melatonin response was acute. The great variability in measured values and the small number of volunteers studied, twelve altogether, may have prevented the detection of a possible statistically significant decrease in melatonin after this intervention (38).

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There is no agreement between studies investigating the sedative and hypnotic effects of melatonin or the effect of anesthesia and traditional sedation techniques on plasma melatonin levels. Ιnsufficient standardization of analytical methods for the determination of melatonin blood levels, experimental conditions (anesthetic techniques), selection of volunteers/patients for study populations, inclusion and exclusion criteria (e.g. co-administered drugs) in research protocols, have led to areas of controversy and generally difficulties for conclusions to be drawn with regard to it‘s therapeutically/ clinical applications. Apart from inconsistencies that arise from assay methods used to quantify melatonin (and its metabolite, 6-sulphatoxymelatonin) in biological fluids fluctuations in melatonin concentrations may be due to certain patient factors. Firstly, the amount of melatonin produced is genetically determined and its secretion is regulated by a circadian rhythm (concentrations remain low during the day, begin to increase at 20:00, peak at 01:00 – 04:00 and fall to basal levels by 10:00). Therefore, melatonin levels vary as a result of differences in sample collection times (39). Also levels in plasma and saliva are affected by posture, increasing when a subject moves from a supine to a standing position and decreasing when these positions are reversed, probably as a result of the influence of gravity which causes a decrease in plasma volume on standing and an increase in plasma volume on lying down (40). Secondly, the quantity of melatonin synthesized in the pineal gland is also influenced by age. Increased levels found in children are considered to be due to faster metabolism and greater synthesis and secretion by the pineal gland, compared with adults. Peak night-time serum concentrations decrease rapidly between the ages of 6 and 20 years remain stable between 20 – 40 years and then slowly decline. However, a study investigating the melatonin pharmacokinetics in premenopausal versus postmenopausal healthy female volunteers showed no difference between these two populations (41). Finally, certain co-administered drugs have been found to affect plasma concentrations of melatonin by inhibiting its synthesis e.g. clonidine (42), atenolol (43), propranolol (44), dihydropyridines (nifedipine) (45), while calcium channel blockers prevent the release of melatonin from pineal gland into the circulation (46) and noradrenaline reuptake inhibitors (desipramine, oxprotiline) increase its release. Fluvoxamine (serotonin reuptake inhibitor) (47) and caffeine (48) increase the bioavailability of melatonin by inhibiting CYP2D6, CYP1A2, while prostaglandin synthesis inhibitors decrease its secretion (42).

4. Conclusion Emphasis should be made on the need to standardize analytical methods for melatonin assay, experimental conditions (anesthetic techniques), selection of volunteers/patients for study populations, inclusion and exclusion criteria in research protocols on melatonin, so as to avoid confusion and aid in the interpretation of results. Melatonin as adjunct therapy may decrease the doses of anesthetics required to provide general anesthesia. This hormone may be also effective for pre-operative sedation and anxiolysis. More studies are required to confirm the efficacy of melatonin as a premedicant and an adjunct durg to general anesthesia. The Natural Standard Research collaboration


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(www.naturalstandard.com) based on scientific evidence classifies the relevant studies on the use of melatonin in anesthesia and as a premedicant drug as grade C, indicating that there is unclear scientific evidence for its use (www.mayoclinic.com, May 1, 2008).

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Karasek M, Winczyk K. Melatonin in humans. J Physiol Pharmacol 2006;57:19-39. Acil M, Basgul E, Celiker V, Karagöz AH, Demir B, Aypar U. Perioperative effects of melatonin and midazolam premedication on sedation, orientation, anxiety scores and psychomotor performance. Eur J Anaesthesiol 2004;21:553-557. Naguib M, Samarkandi AH. Premedication with melatonin: a double-blind, placebocontrolled comparison with midazolam. Br J Anaesth 1999;82:875-880. Naguib M, Samarkandi AH. The comparative dose-response effects of melatonin and midazolam for premedication of adult patients: a double-blinded, placebo-controlled study. Anesth Analg 2000;91:473-479. Capuzzo M, Zanardi B, Schiffino E, Buccoliero C, Gragnaniello D, Bianchi S, Alvisi R. Melatonin does not reduce anxiety more than placebo in the elderly undergoing surgery. Anesth Analg 2006;103:121-123. Sury MRJ, Fairweather K. The effect of melatonin on sedation of children undergoing magnetic resonance imaging. Br J Anaesth 2006;97:220-225. Naguib M, Hammond DL, Schmid PG III, Baker MT, Cutkomp J, Queral L, Smith T. Pharmacological effects of intravenous melatonin: comparative studies with thiopental and propofol. Br J Anaesth 2003;90:504-507. Naguib M, Baker MT, Spadoni G, Gregerson M. The hypnotic and analgesic effects of 2-Bromomelatonin. Anesth Analg 2003;97:763-768. Budhiraja S, Singh J. Adjuvant effect of melatonin on anesthesia induced by thiopental sodium, ketamine, and ether in rats. Methods Find Exp Clin Pharmacol 2005;27:697699. Naguib M, Schmid PG, Baker MT. The electroencephalographic effects of IV anesthetic doses of melatonin: comparative studies with thiopental and propofol. Anesth Analg 2003;97:238-243. Naguib M, Samarkandi AH, Moniem MA, Mansour EED, Alshaer AA, Al-Ayyaf HA, Fadin A, Alharby SW. The effects of melatonin premedication on propofol and thiopental induction dose-response curves: a prospective, randomized double-blind study. Anesth Analg 2006;103:1448-1452. Turkistani A, Abdullah KM, Al-Shaer AA, Mazen KF, Alkatheri K. Melatonin premedication and the induction dose of propofol. Eur J Anaesthesiol 2007;24:399402. Evagelidis P, Paraskeva A, Petropoulos G, Staikou C, Fassoulaki A. Melatonin premedication does not enhance induction of anaesthesia with sevoflurane as assessed by bispectral index monitoring. Singapore Med J 2009:50:78-81. Ebadi M, Govitrapong P, Phansuwan-Pujito P, Nelson F, Reiter RJ. Pineal opioid receptors and analgesic action of melatonin. J Pineal Res 1998;24:193-200.

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[15] Caumo W, Torres F, Moreira NL, Auzani JAS, Monteiro CA, Londero G, Ribeiro DFM, Hidalgo MPL. The clinical impact of preoperative melatonin on postoperative outcomes in patients undergoing abdominal hysterectomy. Anesth Analg 2007;105:1263-1271. [16] Caumo W, Levandovski R, Hidalgo MPL. Preoperative anxiolytic effect of melatonin and clonidine on postoperative pain and morphine consumption in patients undergoing abdominal hysterectomy: a double-blind, randomized, placebo-controlled study. J Pain 2009;10:100-108. [17] Mowafi HA, Ismail SA. Melatonin improves tourniquet tolerance and enhances postoperative analgesia in patients receiving intravenous regional anesthesia. Anesth Analg 2008;107:1422-1426. [18] Brzezinski A. Melatonin in humans. N Engl J Med 1997;336:186–195. [19] Waldhauser F, Waldhauser M, Lieberman HR, Deng MH, Lynch HJ, Wurtman RJ. Bioavailability of oral melatonin in humans. Neuroendocrinology 1984;39:307–313. [20] Fourtillan JB, Brisson AM, Gobin P, Ingrand I, Decourt JP, Girault J. Bioavailability of melatonin in humans after day-time administration of D(7) melatonin. Biopharm Drug Dispos. 2000;21:15-22. [21] Di WL, Kadva A, Johnston A, Silman R. Variable bioavailability of oral melatonin. N Engl J Med. 1997;336:1028-1029. [22] DeMuro RL, Nafziger AN, Blask DE, Menhinick AM, Bertino JS Jr. The absolute bioavailability of oral melatonin. J Clin Pharmacol 2000;40:781-784. [23] Lane EA, Moss HB. Pharmacokinetics of melatonin in man: first pass hepatic metabolism. J Clin Endocrinol Metab 1985;61:1214–1216. [24] Waldhauser F, Kovács J, Reiter E. Age-related changes in melatonin levels in humans and its potential consequences for sleep disorder. Exp Gerontol 1998;33:759–772. [25] Aldhous M, Franey C, Wright J, Arendt J. Plasma concentrations of melatonin in man following oral absorption of different preparations. Br J Clin Pharmacol 1985;19:517– 521. [26] Hahm H, Kujawa J, Augsburger L. Comparison of melatonin products against USP's nutritional supplements standards and other criteria. J Am Pharm Assoc (Wash). 1999;39:27-31. [27] Fourtillan JB, Brisson AM, Fourtillan M, Ingrand I, Decourt JP, Girault J. Melatonin secretion occurs at a constant rate in both young and older men and women. Am J Physiol Endocrinol Metab 2001;280:E11-22. [28] Iguchi H, Kato KI, Ibayashi H. Melatonin serum levels and metabolic clearance rate in patients with liver cirrhosis. J Clin Endocrinol Metab 1982;54:1025-1027. [29] Pang CS, Mulnier C, Pang SF, Yang JCS. Effects of halothane, pentobarbital and ketamine on serum melatonin levels in the early scotophase in New Zealand white rabbits. Biol Signals Recept 2001;10:310-316. [30] Muñoz-Hoyos A, Heredia F, Moreno F, García JJ, Molina-Carballo A, Escames G, Acuña-Castroviejo D. Evaluation of plasma levels of melatonin after midazolam or sodium thiopental anesthesia in children. J Pineal Res 2002; 32:253-256.


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[31] Arai YCP, Ueda W, Okatani Y, Fukaya T, Manabe M. Isoflurane increases but sevoflurane decreases blood concentrations of melatonin in women. J Anesth 2004;18:228-231. [32] Reber A, Huber PR, Ummenhofer W, Gürtler CM, Zurschmiede C, Drewe J, Schneider M. General anaesthesia for surgery can influence circulating melatonin during daylight hours. Acta Anaesthesiol Scand 1998;42:1050-1056. [33] Fassoulaki A, Kostopanagiotou G, Meletiou P, Chasiakos D, Markantonis S. No change in serum melatonin, or plasma -endorphin levels after sevoflurane anesthesia. J Clin Anesth 2007;19:120-124. [34] Kärkelä J, Vakkuri O, Kaukinen S, Huang WQ, Pasanen M. The influence of anaesthesia and surgery on the circadian rhythm of melatonin. Acta Anaesthesiol Scand 2002;46:30-36. [35] Cronin AJ, Keifer JC, Davies MF, King TS, Bixler EO. Melatonin secretion after surgery. Lancet 2000;356:1244-1245. [36] Vician M, Zeman M, Herichová I, Juráni M, Blazícek P, Matis P. Melatonin content in plasma and large intestine of patients with colorectal carcinoma before and after surgery. J Pineal Res 1999;27:164-169. [37] Spence DW, Kayumov L, Chen A, Lowe A, Jain U, Katzman MA, Shen J, Perelman B, Shapiro CM. Acupuncture increases nocturnal melatonin secretion and reduces insomnia and anxiety: a preliminary report. J Neuropsychiatry Clin Neurosci 2004;16:19-28. [38] Fassoulaki A, Paraskeva A, Kostopanagiotou G, Tsakalozou E, Markantonis S. Acupressure on the extra 1 acupoint: the effect on bispectral index, serum melatonin, plasma -endorphin, and stress. Anesth Analg 2007;104:312-317. [39] Middleton B. Measurement of melatonin and 6-sulphatoxymelatonin. Methods Mol Biol 2006;324:235-254. [40] Deacon S, Arendt J. Posture influences melatonin concentrations in plasma and saliva in humans. Neurosci Lett 1994;167:191-194. [41] Markantonis SL, Tsakalozou E, Paraskeva A, Staikou C, Fassoulaki A. Melatonin pharmacokinetics in premenopausal and postmenopausal healthy female volunteers. J Clin Pharmacol 2008;48:240-245. [42] Claustrat B, Brun J, Chazot G. The basic physiology and pathophysiology of melatonin. Sleep Med Rev 2005;9:11-24. [43] Van Den Heuvel CJ, Reid KJ, Dawson D. Effect of atenolol on nocturnal sleep and temperature in young men: reversal by pharmacological doses of melatonin. Physiol Behav. 1997;61:795-802. [44] Stoschitzky K, Sakotnik A, Lercher P, Zweiker R, Maier R, Liebmann P, Lindner W. Influence of beta-blockers on melatonin release. Eur J Clin Pharmacol

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[45] Zhao ZY, Touitou Y. Pineal perfusion with calcium channel blockers inhibits differently daytime and nighttime melatonin production in rat. Mol Cell Endocrinol

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Chapter XIV

Sleep Disturbance in Obsessive-Compulsive Disorder Enrico Pessina*, Sylvia Rigardetto, Umberto Albert, Filippo Bogetto and Giuseppe Maina Department of Neurosciences, Mood and Anxiety Disorders Unit, University of Turin, Turin, Italy

Abstract Introduction: Obsessive-Compulsive Disorder (OCD) is a common, chronic disorder which results in marked distress and impairment of social and occupational functioning. Sleep disturbance often accompanies mental disorders, but there have been few studies of sleep disturbance in OCD. These have produced contradictory findings, with some reporting sleep disruption, and others a normal sleep pattern. The aim of the present study is to examine sleep patterns in OCD, to establish the frequency of the different types of insomnia (early, middle and late insomnia) in a sample of patients with OCD. The study also intends to determine whether the presence of a comorbid mood disorder influence frequency and type of insomnia. Methods: all patients with a primary diagnosis of OCD (according to DSM-IV criteria) consecutively referred to the Mood and Anxiety Disorder Unit, Department of Neuroscience, University of Turin, from January 2003 to June 2008, were recruited. Frequency and severity of the different types of insomnia were evaluated on the basis of the Hamilton Depression Rating Scale (HDRS) specific items score (item 4-5-6). A statistical comparison between OCD patients with and without insomnia was performed to examine whether there was any difference in clinical features.

*

Corresponding author: Enrico Pessina, Department of Neurosciences, Mood and Anxiety Disorders Unit, University of Turin, Italy, Via Cherasco 11 – 10126 Torino, Italy, Tel. +39.011.6335425, Fax +39.011.673473, e-mail address: [email protected]

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Enrico Pessina, Sylvia Rigardetto, Umberto Albert et al. Then a statistical comparison between patients with and without depressive comorbidity was performed to examine whether there was any difference in prevalence and type of insomnia. Results: The sample included 315 OCD patients. More than a half of the sample suffered from any type of insomnia. The most frequent type of insomnia was early insomnia (about 44,8%). We didn‘t find a positive correlation between the severity measured with total Y-BOCS score or obsessions and compulsions sub-score clinical and socio-demographic features and insomnia. The presence of any comorbid depressive disorder increased the frequency of insomnia. Conclusions: Insomnia, especially the early one, is a common symptom in OCD patients with or without comorbid depressive disorders. Late insomnia is typical of OCD with comorbid major depression.

Introduction Sleep disturbance often accompanies mental disorders, and among insomniac subjects, about 30% have a psychiatric diagnosis [1;2]. Anxiety disorders are known to be associated with difficulties in initiating and maintaining sleep, and this association has been widely studied, although the ethio-pathogenetic issues regarding the association of the two groups of symptoms are not well elucidated [3;4]. Obsessive-Compulsive Disorder (OCD) is classified in the Diagnostic and Statistic Manual for Mental Disorders IV Edition - Text Revised (DSM-IV-TR) as an anxiety disorder, characterized by recurrent and persistent thoughts, impulses or images that are experienced as intrusive, that are not simply excessive worries about real-life problems, and that are recognized as a product of one‘s mind and not based on reality, causing marked distress and impairment of social and occupational functioning. Obsessive thoughts evoke anxiety and compulsive behaviours or mental acts aimed at decreasing discomfort, or at preventing some dreaded event or situation: they are not actually connected to the issue or they are excessive, and they must be applied rigidly. The patients, at some point during the course of illness, become aware of the fact that those obsessions and compulsions are unreasonable and excessive. Moreover they are time consuming (more than one hour per day) and they cause marked distress. It is worth noting that insomnia is not included in the diagnostic criteria of OCD. OCD is a relatively common disorder: the lifetime prevalence is at 2-3% of the population [5;6]; the course is predominantly chronic. There have been relatively few studies examining sleep in patients with obsessivecompulsive disorder and these have produced contradictory findings with some reporting sleep disruption, and others a normal sleep pattern. Based on epidemiological findings, insomnia related to OCD had a prevalence of 0.2% while the prevalence of OCD with insomnia was 1.2% .[7;8] The evidence emerging from clinical sample nevertheless is that about 30% of patients suffer from some kind of insomnia [9]. Thus, we can assume that it is a well established fact that sleep disturbances are recognized to occur; however, their type and nature have been little studied and the contribution of comorbid depression has been difficult to disentangle from that of OCD. As a matter of fact, it is well known that individuals with OCD tend to suffer from comorbid depression at some time during the course of their illness. The proportion of patients fulfilling

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the criteria of Major Depressive Episode (MDE), often considered to be secondary to the OCD, has been estimated at between one-third [10] and two-thirds [11] of all cases, though detailed multivariate analysis of a large epidemiological sample suggested the proportion to be approximately 17% [12]. It is often when depressive symptoms supervene that individuals with OCD seek treatment for the first time. Similarly, it is a common finding in clinical samples the emerging of depressive symptoms after OCD onset. Moreover, the risk of developing a depressive episode tends to increase progressively with the duration of the Obsessive-Compulsive Disorder [13]. This topic represents a significant challenge for clinicians in the study of OCD and sleep disorders. Consequently, after investigating sleep architecture and neuro-endocrine features, researchers are called to understand if there is a common pathway, such as abnormalities in the serotoninergic system, implicated in the etiology of OCD and in the disregulation of sleep, or if the comorbidity with depression could shed light on the clinical and biological profile of sleep disruption. Three rather recent studies investigated the comorbidity between OCD and depressive symptoms, providing indirect evidence about sleep pattern in depressed OCD patients. In a study carried out in 2004, Moritz and colleagues [9], with the aim of assessing the distribution of depressive symptoms in a large OCD sample (162 patients) and of analyzing the dimensional structure of the Hamilton Depression Rating Scale (HDRS) in OCD, found Major Depressive Disorder according to DSM-IV criteria in approximately one third of the patients. Sleep problems occurred in approximately one fifth of all patients, with the following distribution: 20.4% early insomnia, 14.2% middle insomnia and 13.6% late insomnia. It is interesting to point out the presence of ordering behavior and aggressive thoughts, as associated to more sleep problems. Fineberg and coworkers [14], compared the clinical characteristics of a group of about 50 OCD patients with comorbid depression to an equivalent group of patients with MDD, examining between-group differences on the individual MADRS item scores. The study has demonstrated a difference between the depressive symptom profile of OCD patients with comorbid depression and that of severity-matched MDD patients. It is interesting that the OCD group was less symptomatic on items that measure a vegetative response to depression, such as sleep and appetite disturbance, that appear specific to MDD alone. This may suggest a different biological contribution from brain systems modulating sleep and appetite in this form of depression. The items in which symptoms of depression showed to be common to the two groups, were inner tension and pessimism, closer to core symptoms of OCD. To conclude, it is important to mention a recent work that tries to shine light on the issue of comorbidity [15]: in this study, investigating a large sample (124 patients) of unmedicated and not-primarily depressed patients with OCD, an electroencephalographic investigation and an anti-5HT challenge test (tryptophan depletion) were used, in order to clarify whether comorbidity with depression is associated with abnormalities of sleep. This study indicates that neurobiological disturbances are different in primary OCD as compared with primary depression. Assuming that changes of sleep architecture indicate underlying neurobiological abnormalities, a relatively decreased 5-HT neurotransmission should be one contributing factor explaining the sleep abnormalities in depression, whereas not in OCD. The non specific disturbances of sleep continuity in OCD patients reported in the above mentioned

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study might be explained by a psycho-physiological hyper-arousal as a consequence of negative feelings, tension and anxiety associated with the obsessions and compulsions. This view is supported by the weak, but positive correlation between the severity of obsessions and compulsions and sleep continuity measures. The recent biological research is focusing on specific facets of the problem, such as sleep architecture and neuroendocrine features: formerly Authors [16; 17; 18; 19] led studies about electro-encephalographic profiles of sleep in small OCD patients groups, finding weak, not peculiar and not unanimous evidence of decreased total sleep time, decreased REM efficiency and shortened REM latency. Recently retrospective studies identified a possible association between OCD and sleep onset REM periods [20] or a circadian rhythm sleep disorder known as delayed sleep phase syndrome (DSPS), an uncommon condition in the general adult population in which patients go to bed and get up much later than normal, unable to shift their sleep to an earlier time[21; 22]. There is also some evidence for abnormalities in the circadian secretion of melatonin in patients with OCD [23], more pronounced in patients with more severe OCD based on higher Y-BOCS scores, and for alterations in sleep onset related to nocturnal GH secretion [24], and ACTH secretion [25], confirming an altered function of the somatotrophic axis in OCD. Although there have been many studies investigating biological aspects of sleep, no real attention was paid to the patients sleeping pattern. Therefore we need to understand if patients are actually suffering from insomnia or not, and if depression could influence this symptom. Consequently the aim of our study is to examine sleep pattern in a large sample of OCD patients (N= 315) and to establish the frequency of the different types of insomnia. Furthermore our intention is to determine the influence of comorbid depression on prevalence and phenomenology of insomnia.

Methods Subjects Subjects for this study were recruited from all patients with a principal diagnosis of OCD according to DSM-IV criteria consecutively referred to the Anxiety and Mood Disorders Unit, Department of Neuroscience, University of Turin (Italy) over a period of 5 years (January 2002- December 2007). Diagnoses were established by means of a structured clinical interview, the SCID-I [26]. The Yale-Brown Obsessive-Compulsive Scale rating had to exceed 16 points [27]. Furthermore, patients had to be at least 18 years of age, and be willing to voluntarily participate to the study. Informed consent from patients was obtained after the procedure had been fully explained. Exclusion criteria were considered a current or previous diagnosis of organic mental disorder, schizophrenia or other psychotic disorder, or having an uncontrolled or serious medical condition.


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Diagnostic and Symptomatological Evaluation A systematic face-to-face interview that consisted of structured and semi-structured components was used to collect data. Diagnostic evaluation and Axis I comorbidities were recorded by means of the Structured Clinical Interview for the DSM-IV Axis I Disorders [28]. All socio-demographic and illness characteristics were obtained through the administration of a semi-structured interview, developed and used in previous studies [29-3031] with a format that covered the following areas: a) Socio-demographic data: age, sex, marital status (single, married, divorced, widowed), years of education. b) Onset and course of OCD: disease onset was dated within a 1-month period as the first occurrence of obsessive and compulsive symptoms, and when at least one of them caused marked distress, was time consuming (more than one hour a day) or interfered with the person‘s normal daily functioning (normal routine, occupational and social activities). An attempt was made to date onset of OCD to a 4-week period, but if there was uncertainty, a close relative of the patient was interviewed and a range was plotted and its mid-point was used in the analysis. The onset was considered abrupt when the symptoms reached clinically significant intensity within 1 week of onset. All other types of onset were considered insidious. When present, the interval occurred between the two moments (symptoms onset and disorder onset) of the patients‘ clinical history was registered. The course of the disorder was considered episodic when at least one circumscribed symptom-free interval (6 months) was present; all other types of course were considered chronic, according to a definition we used in previous studies. c) Obsessive-compulsive symptomatology: for each subject up to three primary obsessions and compulsions were listed using the Y-BOCS Symptom Check List. To evaluate presence, degree and type of insomnia (early, middle or late) we considered the specific items (items 4, 5 and 6) of Hamilton Rating Scale for Depression (HAM-D) [32]. presence of insomnia: score ≥ 1 to item 4.5 or 6 of HAM-D) mean score for each item. The interview and all the ratings were completed by psychiatrists with at least 4 years experience in anxiety and mood disorders. Each interviewer underwent a training program in the use of the interview instruments, which included direct observation of experienced interviewers, direct supervision of interviews, and inter-rater reliability. High reliability and diagnostic concordance have been documented in previous reports [31-33].

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Statistical Analysis We conducted analyses to determine: 1) if there was any difference in clinical features between OCD patients with and without insomnia; 2) if the presence of insomnia in OCD was correlated with actual comorbidity with mood disorders (Major Depressive Episode, Dysthymic Disorder and Depressive Disorder Not Otherwise Specified) A statistical comparison between OCD patients with and without insomnia was performed to examine whether there was any difference in clinical features. Then a statistical comparison between patients with and without depressive comorbidity was performed to examine whether there was any difference in prevalence and type of insomnia. Our study was designed to provide descriptive information; therefore, primarily descriptive statistics were used to analyze the data. Between-group comparison of categorical variables was made with Pearson‘s Chi-square test. Continuous variables were compared by using Student‘s t test for two-class comparisons Given the exploratory nature of our study, we decided to use a 2-tailed significance level of p<.05. Bonferroni‘s correction was applied when needed.

Results Patients with a principal diagnosis of OCD enrolled in the study were 315. The demographic and clinical characteristics of the sample are presented in table 1 and table 2. In our sample, 170 OCD patients out of 315 (54.0%) suffered from insomnia. Figure 1 represents the distribution of the subtypes of insomnia in the sample. Among these, 76 patients (24.1%) suffered from two or more types of insomnia. Prevalence of the subtypes of insomnia in the OCD sample was, respectively, 44.8% of patients suffering from early insomnia, 21.9% from middle insomnia and 18.4% from late insomnia. Figure 2 represents mean scores at each item for insomnia (4: early insomnia, 5 middle insomnia, 6 late insomnia) of the HAM-D. Mean scores of early insomnia were significantly higher than both middle (p<0.001) and late insomnia (p<0.001). There were no statistically significant differences between mean scores of item 5 and item 6 (p=0.924). The clinical characteristics of the sample according to presence of insomnia are presented in table 3. The only statistically significant difference was the prevalence of aggressive obsessions; anyway, after Bonferroni‘s correction the difference was no longer statistically relevant. Table 4 reports the differences in terms of prevalence of insomnia and its subtypes according to the presence or the absence of an actual depressive disorder in comorbidity with OCD.


60

321

54,0

50

44,8

40 30

21,9

18,4

20 10 0 At least one type of insomnia

Early insomnia

Middle Insomnia

Late Insomnia

Figure 1. prevalence of subtype of insomnia in the OCD sample (n=315).

0,7

0,6 0,6 0,5 0,4

0,3 0,3

0,2 0,2 0,1 0 Item 4 (early insomnia)

Item 5 (middle Insomnia)

Item 6 (late insomnia)

Item 4 score vs item 5 score: p<0.001 Item 4 score vs item 6 score: p<0.001 Item 5 score vs item 6 score: p=0.924 Figure 2. Mean scores of HAM-D item 4 – 5 – 6 in OCD sample (n=315).

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Enrico Pessina, Sylvia Rigardetto, Umberto Albert et al. Table 1. Demographic and clinical characteristics of the sample.

a

Index age, mean (±SD), y Educational level, mean (±SD), y Marital status, n (%) Single Married Divorced Widowed Gender, n (%) Males Females Age at onset, mean (±SD), y: OCD OCSa Type of onset, n (%) Insidious Abrupt Type of course, n (%) Chronic Episodic Y-BOCS, mean (±SD) Total score Obsession subscore Compulsion subscore HAM-D, mean (±SD) Positive family history, n (%) OCD Other Anxiety disorders Mood disorders Schizophrenia

Total N=315 34.9 (11.9) 12.1 (4.2) 165 (52.4) 133 (42.2) 14 (4.4) 3 (1.0) 159 (50.5) 156 (49.5) 22.7 (9.4) 17.2 (8.8) 214 (67.9) 101 (32.1) 257 (81.6) 58 (18.4) 24.8 (6.4) 13.1 (3.3) 11.8 (4.2) 11.3 (6.3) 67 (21.3) 35 (11.1) 89 (28.3) 13 (4.1)

OCS = Obsessive-compulsive symptoms

Table 2. Obsessive-compulsive phenomenology according to the Y-BOCS Symptoms Check List in the sample. Obsessions, n (%) Aggressive Contamination Sexual Hoarding/saving Religious Symmetry/order Somatic Miscellaneous Compulsions, n (%) Checking Cleaning Repeating Ordering Counting Hoarding/collecting Miscellaneous

Total N=315 174 (55.2) 171 (54.3) 54 (17.1) 45 (14.3) 85 (27.0) 151 (47.9) 98 (31.1) 199 (63.2) 197 (62.5) 169 (53.7) 159 (50.5) 66 (21.0) 85 (27.0) 39 (12.4) 181 (57.5)


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Table 3. Comparison of clinical characteristic of obsessive-compulsive patients (315) with or without insomnia. OCD (n=145) Age at onset, mean (±SD), OCD OCSa Type of onset, n (%) Insidious Abrupt Type of course, n (%) Chronic Episodic Y-BOCS, mean (±SD) Total score Obsession subscore Compulsion subscore

Obsessions, n (%) Aggressive Contamination Sexual Hoarding/saving Religious Symmetry/order Somatic Miscellaneous Compulsions, n (%) Checking Cleaning Repeating Ordering Counting Hoarding/collecting Miscellaneous

21.8 (8.5) 17,3 (7.7) 93 (64.1) 52 (35.9)

OCD with insomnia (n=170) 23.4 (10.2) 17,2 (9,7)

123 (84.8) 22 (15.2) 24.5 (7.1) 12.8 (3.5) 11.9 (4.5)

2

/t

1.507 -0.058

df

313 313

p

0.133 0.954

121 (71.2) 49 (28.8)

1.780

1 0.186

134 (78.8) 36 (21.2)

1.878

1 0.191

25.0 (5.8) 13.4 (3.0) 11.7 (4.0)

0.752 1.479 -0.400

313 313 313

0.452 0.140 0.689

71 (49.0) 78 (53.8) 23 (15.9) 21 (14.5) 37 (25.5) 67 (46.2) 42 (29.0) 90 (62.1)

103 (60.6) 93 (54.7) 31 (18.2) 24 (14.1) 48 (28.2) 84 (49.4) 56 (32.9) 109 (64.1)

4.275 0.026 0.310 0.009 0.293 0.322 0.577 0.141

1 1 1 1 1 1 1 1

0.041 0.910 0.653 1.000 0.612 0.574 0.466 0.707

94 (64.8) 76 (52.4) 75 (51.7) 35 (24.1) 30 (20.7) 18 (12.4) 78 (53.8)

103 (60.6) 93 (54.7) 84 (49.4) 50 (29.4) 36 (21.2) 21 (12.4) 103 (60.6)

0.600 0.165 0.167 1.105 0.011 0.000 1.478

1 1 1 1 1 1 1

0.734 0.484 0.735 0.311 1.000 1.000 0.253

* not significant after Bonferroni‘s correction (a=0.003)


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Table 4. prevalence of insomnia in OCD: comparison between OCD patient without actual depressive disorder and OCD with an actual depressive disorder (Major Depressive Episode, Dysthymic Disorder or Depressive Disorder Not Otherwise Specified). OCD (112) N (%) Presence of insomnia Early insomnia Middle insomnia Late Insomnia ≥2 subtypes of insomnia

OCD + actual mood disorder (203)

2

df

p

41 (36.6)

129 (63.5)

21.086

1

<0.001

36 (32.1) 8 (7.1) 8 (7.1) 12 (10.7)

105 (51.7) 61 (30.0) 50 (24.6) 64 (31.5)

11.193 22.139 14.694 17.079

1 1 1 1

0.001 <0.001 <0.001 <0.001

Conclusion In the field of the interaction between sleep and psychiatric disorders, OCD is probably one of the least treated topics. This study to our knowledge is the largest study of sleep in OCD so far, and one of the few investigating clinical features of sleep in obsessivecompulsive disorder. As far as socio-demographic and clinical features are concerned, our sample was representative of the OCD population described in the scientific literature. We found that patients with OCD show abnormalities of sleep: more than 50% of our sample suffered from insomnia, about 24% reporting two or more types of insomnia. Our results did not confirm previous preliminary findings of the literature about clinical predictors of sleep disturbances in OCD [9; 15]: we didn‘t find a positive correlation between the severity measured with total Y-BOCS score or obsessions and compulsions sub-scores and sleep clinical measures, neither between specific symptomatic dimensions and insomnia. Aggressive obsessions showed a trend toward significance that disappeared after Bonferroni‘s correction. Concerning specific subtypes of insomnia, early insomnia was the most common kind of sleep disruption in our sample (44.8%), followed by middle (21.9%) and late (18.4%) insomnia. Early insomnia was also the most severe type of insomnia found in the sample. The findings mentioned above are difficult to compare with data presented in the literature, since they are scarce and extracted from small samples. Both epidemiological and clinical findings suggest a lower prevalence of sleep disturbances in OCD patients [7; 8; 9]. Moritz and colleagues, for example, found a similar distribution of subtypes of insomnia, but with lower rates, respectively 20.4% for early insomnia, 14.2% of middle insomnia and 13.6% of late insomnia. The finding of a prevalent early sleep disruption in OCD sample might be partly explained by a psycho-physiological hyper-arousal as a consequence of negative feelings, tension and anxiety associated with the obsessions and compulsions. Nevertheless, this hypothesis could not answer for any case of early insomnia nor for middle and late insomnia. Moreover, it has to be emphasized that nearly all our patients had a moderate to severe OCD (mean Y-BOCS total score: 24.8±6.4), in almost all cases lasting for


325

many years and that 64% of the patients suffered from depression, 45% fulfilling criteria for Major Depressive Episode and 55% for depressive disorder other than MDE, with a mean HAM-D score of 11.3 (± 6.3). The comorbidity with depressive symptoms showed to be common in patients with severe OCD [8; 14; 15]: in fact the disorder could frequently be associated with secondary depressive symptoms. Since sleep abnormalities are a consistent finding in depression, it is important to compare clinical sleep measures of OCD patients with and without depressive symptoms. Any type of depression was significantly related to the presence of any kind of insomnia, consistently with the data of the scientific literature [8; 14; 15]. In conclusion, our results about prevalence of insomnia are quite different from those presented in the literature: the explanation could be found in the characteristics of the sample studied. We lead the investigation on a clinical sample of moderate to severe OCD patients with high rates of depressive symptoms. These features evidently could predispose patients to insomnia, as a consequence both of negative feelings and inner tension disturbing the sleep and of the comorbidity with depression of which insomnia is a core symptom. As mentioned above, the strength of the present study is supported by the investigation of clinical features of sleep in OCD with and without comorbid depression, carried out on a wide sample. The main limitations of this study are the retrospective design and the fact that the sleep record had not involved the use of standardized instruments apart from the three specific sub-items of the Hamilton Depression Rating Scale. Therefore, the two major conclusions from this study remain that OCD patients seem to exhibit significant rates of insomnia, and that depressive symptoms, either in the context of a Major Depressive Episode or in that of a depressive disorder other than MDE, produce a worsening of sleep abnormalities.

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Enrico Pessina, Sylvia Rigardetto, Umberto Albert et al. combination in the treatment of obsessive-compulsive disorder. American Journal of Psychiatry, 2005 162, 151–161. Ohayon, MM. Epidemiological study on insomnia in a general population. Sleep, 1996 19(Suppl. 3), 7–15. Papadimitiu, GA; Linkowski, P. Sleep disturbance in anxiety disorders. International Review of Psychiatry, 2005 17(4), 229–236. Moritz, S; Meier, B; Hand, I; Schick, M; Holger, J. Dimensional structure of the Hamilton Depression Rating Scale in patients with obsessive – compulsive disorder. Psychiatry Research, 2004 125, 171–180. Robins, LN; Helzer, JE; Weissman, MM; Orvaschel, H; Gruenberg, E; Burke, JD Jr.; Regier, DA. Lifetime prevalence of specific psychiatric disorders in three sites. Archives of General Psychiatry, 1984 41, 949 – 958. Pigott, TA; L‘Heureux, F; Dubbert, B; Bernstein, S; Murphy, DL. Obsessive compulsive disorder: comorbid conditions. Journal Clinical. Psychiatry, 1994 55, 1527. Andrews, G; Slade, T; Issakidis, C. Deconstructing current comorbidity: data from the Australian National Survey of Mental health and Well-being. British Journal of Psychiatry, 2002 181, 306 – 314. Diniz, JB; Rosario-Campos, MC; Shavitt, RG; Curi, M; Hounie, A; Brotto, SA; Miguel, EC. Impact of age at onset and duration of illness in the expression of comorbidities in obsessive-compulsive disorder. Journal of Clinical Psychiatry, 2004 65, 22-27. Fineberg, NA; Fourie, H;, Gale, TM; Sivakumaran T. Comorbid depression in obsessive compulsive disorder (OCD): Symptomatic differences to major depressive disorder. Journal of Affective Disorders, 2005 87, 327 – 330. Voderholzer, U; Riemann, D; Huwig-Poppe, C; Kuelz, AK; Kordon, A; Bruestle, K; Berger, M; Hohagen, F. Sleep in obsessive compulsive disorder Polysomnographic studies under baseline conditions and after experimentally induced serotonin deficiency. European Archives Psychiatry Clinical Neuroscience, 2007, 257, 173–182. Rapoport, J; Elkins, R; Langer, DH; Sceery, W; Buchsbaum, MS; Gillin, JC; Murphy, DL; Zahn, TP; Lake, R; Ludlow, C; Mendelson, W. Childhood obsessive compulsive disorder. American Journal of Psy chiatry, 1981 138, 1545-1554. Insel, TR; Roy, BF; Cohen, RM; Murphy, DL. Possible development of the serotonin syndrome in man. American Journal of Psychiatry, 1982 139, 154–155. Hoaghen , F; Lis, S; Krieger, S; Winkelman, G; Riemann, D; Fritsch-Montero, R; Rey, R; Aldenhoff, J; Berger; M. Sleep EEG of patients with obsessive-compulsive disorder. European Archives of Psychiatry and Clinical Neuroscience, 1994 243, 273-278. Robinson D, Walsleben, J; Pollack, S; Lerner, G. Nocturnal polysomnography in obsessive-compulsive disorder. Psychiatry Research, 1998 80, 257–263. Kluge , M; Schussler, P; Dresler, M; Yassouridis, A; Steiger, A. Sleep onset REM periods in obsessive-compulsive disorder. Psychiatry Research, 2007a 152, 29–35. Turner, J; Sumanmukhopadhyay D; White S; Fineberg NA. A prospective study of delayed sleep phase syndrome in patients with severe resistant obsessive-compulsive disorder. World Psychiatry, 2007 6, 108-111.


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[22] Mukhopadhyay, S; Fineberg, NA; Drummond, L; Turner, J; White, S; Wulff, K; Ghodse, H. Delayed Sleep Phase in Severe Obsessive-Compulsive Disorder: A Systematic Case-Report Survey. CNS Spectr, 2008 13(5), 406-413 . [23] Monteleone, P; Catapano, F; Del Buono, G. Circadian rhythms of melatonin, cortisol and prolactin in patients with obsessive compulsive disorder. Acta Psychiatrica Scandinavica, 1994 89, 411-5. [24] Kluge, M; Schussler, P; Weikel, J; Dresler, M; Zuber, V; Querfurt, F. Altered nocturnal growth hormone (GH) secretion in obsessive compulsive disorder. Psychoneuroendocrinology, 2006 31, 1098–1104. [25] Kluge, M; Schussler, P; Kunzel, H E; Dresler, M; Yassouridis, A; Steiger, A. Increased nocturnal secretion of ACTH and cortisol in obsessive-compulsive disorder. Journal of Psychiatric Research, 2007b 41, 928–933. [26] First, MB; Spitzer RL, Gibbon M, et al. Structured Clinical Interview for DSM-IV (SCID) Axis I Disorders. Washington, DC: American Psychiatric Press; 1997. [27] Goodman, WK; Price, LH; Rasmussen, SA; Mazure, C; Fkeischmann, RL; Hill, CL; Charney, DS. The Yale Brown Obsessive Compulsive scale, I: development, use and reliability. Archives of General Psychiatry 1989; 46, 1006-1011. [28] Goodman, WK; Price, LH; Rasmussen, SA; Mazure, C; Fkeischmann, RL; Hill, CL; Charney, DS. The Yale Brown Obsessive Compulsive scale, I: validity. Archives of General Psychiatry, 1989 46, 1012-1016. [29] Bogetto, F; Venturello, S; Albert, U. Gender-related clinical differences in obsessive compulsive patients. European Psychiatry, 1999 14, 434-441. [30] Albert, U; Maina, G; Ravizza, L; Bogetto F. An exploratory study on obsessivecompulsive disorder with and without a familial component: are there any phenomenological differences? Psychopathology, 2002 35, 8-16. [31] Albert, U; Maina, G; Forner, F; Bogetto, F. DSM-IV obsessive-compulsive personality disorder: prevalence in patients with anxiety disorders and in healthy comparison subjects. Comprehensive Psychiatry, 2004 45, 325-332. [32] Hamilton, M. A rating scale for depression. Journal of Neurological and Neurosurgical Psychiatry, 1960 23, 56-62. [33] Maina, G; Albert; Gandolfo, S. Personality disorders in patients with burning mouth sindrome. Journal of Personality Disorders 2005 19(1), 80-88.



Chapter XV

Effects of Sunbathing on Insomnia, Behavioural Disturbance and Serum Melatonin Level Keiko Ikemoto* Department of Neuropsychiatry, Fukushima Medical University School of Medicine, 1 Hikarigaoka, Fukushima, 960-1295, Japan

Abstract It has been suggested that sunbathing may increase the amplitude of the sleep-wake rhythm and nocturnal serum melatonin secretion, and have effects on insomnia as well. A case report of a patients with epilepsy, cerebral palsy, and severe mental and intellectual disabilities (SMID) with severe behavioral disturbance is presented, in which the sleep-wake-cycle (SWC) was markedly improved by a sunbathing for seven months. The schedule included a sunbathing for 30 minutes in the morning, and a walk with a sunbathing for 10～30 minutes in the afternoon. Reduction of frequency of excitement and pyrexia was also observed, and the latter effect persisted for more than six months after the completion of this schedule. In the present case, being similar to the effects of light therapy for insomnia in elderly persons, low level of nocturnal melatonin level exhibited a tendency toward normalization. These findings show that a sunbathing is an effective and simple method for the treatment of insomnia and behavioral disturbance associated with severe mental retardation. The effects of light therapy and / or a sunbathing on insomnia and serum melatonin level, particularly in individuals with brain damages, are reviewed based on the literatures.

Keywords: melatonin, light therapy, insomnia, mental retardation, sunbathing, dementia

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Keiko Ikemoto

Introduction Patients with brain damages, e. g., those with certain types of mental retardation or dementia, frequently manifest behavioral disturbances, including insomnia, disturbance of sleep-wake cycle (SWC), wandering, excitement and hyperactivity. In addition to various types of pharmacotherapy, combinations of melatonin administration and / or light therapy, have been used to reduce these signs and symptoms [1-3]. In this review, a case report of a patient with severe mental and intellectual disabilities (SMID) with behavioural disturbance, epilepsy, and cerebral palsy is presented, in which the SWC was markedly improved by sunbathing for seven months [4]. In this case, a sunbathing was performed instead of light therapy, since the patient could neither understand the effects of light therapy nor remain in front of illumination equipment for long because of hyperactivity, and also tended to break the equipment. Sunbathing, which affects plasma melatonin level, and reinforcing social synchronizing factors as well as light synchronizing factors might comprise a simple and safe method for improving the SWC in patients with behavioural disturbance [5].

Case The case is 39-year-old male with profound mental retardation, epilepsy (secondary generalized seizure), and cerebral palsy (incomplete right hemiplegia), i. e., SMID with severe behavioral disturbance.

Clinical History Neonatal asphyxia occurred during a difficult delivery. He failed to develop communication skills, and manifested excitement with a loud voice, throwing of things, and violence towards others. Behavioural disturbance worsened as he developed. At 13 years of age, he was admitted to a special ward for SMID accompanied by severe behavioural disturbances. Though hypnotics were prescribed for insomnia following admission, he woke easily in response to even small sounds, shouted in a loud voice, and rapped on doors. When his excitement at night worsened, the doses of hypnotics were increased , but this proved ineffective. Instead, the following day, the risk of falling was increased because of unsteadiness. Assignment to a private room after each episode of excitement and walking with a nurse were ineffective in obtaining sedation. Repeated episodes of pyrexia (3-4 times per month) and phlegmon of the legs were observed. EEG examination revealed a basic rhythm with poorly organized irregular α waves (8～12Hz, 20～30μV) intermingled with irregular slow waves in the left hemisphere, especially in the central region, and bilateral β waves. Multi-focal small spikes were frequently observed (right > left). Generalized 3 Hz spike-and-wave complexes appeared for 1 second, though their reproducibility was poor.

Effects of Sunbathing on Insomnia…

331

MRI demonstrated a small and thick skull. The left fronto-temporo-occipital and right parietal area contained vacuolar regions, indicating, old infarction. There was also lateral ventricular enlargement (left > right) and atrophy of the left ventral brainstem suggesting probable secondary change involving Wallerian degeneration of the corticospinal tract. To improve insomnia, sunbathing was initiated. During this period, the same dosages of drugs (sodium valproate 1000mg, phenobarbital 100mg, levomepromazine 25 mg, diazepam 15mg, nitrazepam 5mg and flunitrazapam 1mg) were maintained.

Treatment Schedule From April, 2007, sunbathing for 30 min in the morning and a walk with sunbathing for 10～30 min in the afternoon were performed. The latter was considered exercise. Walking was combined with sunbathing because the patient easily tired of staying in the same place for a long time. Exercise was performed for 10～30 min depending on the patient's willingness to exercise and satisfaction. The hospital was located at 39 degrees 24 min of North latitude. Illumination in the patient‘s room was about 10000 Lx on sunny days and more than 3000 Lx on cloudy days from spring to autumn. A location with illumination above 2000 Lx was chosen for him to spend the daytime hours. His SWC was checked from March, 2007, by observing sleep states and daytime activities to assess the effects of sunbathing. Serum levels of melatonin and cortisol were measured before, and 5 and 7 months after the beginning of the investigation to determine whether these levels were affected by sunbathing. Quality of sleep and level of excitability were assessed according to standardized criteria, and compared with the same months of the previous year. Sleeping well was defined as sleeping until the morning with disturbed sleep limited to less than 30 min and waking no earlier than 4:00 in the morning. Excitement was defined as the existence of episodes for which isolation was required due to restlessness and excitement.

Results On all the days when both sunbathing and exercise were performed, the patient slept well. The order of frequency of sleeping well in April to October, 2007 was as follows: sunbathing and exercise (100%, 22 days / 22 days) > sunbathing alone (87%, 27 / 31) > exercise alone (73%, 47 / 64) > neither treatment (62%, 26 / 42). In April to October, 2006 (the previous year), the frequency of sleeping well was lower for days with exercise alone (66%, 62 / 94) or neither treatment (55%, 55 / 92). The frequency of excitement during the period of examination was lowest (4%, 1 / 21) on days when both sunbathing and exercise were performed. The frequency was 19% (6 / 31) on days with sunbathing alone, 23% (15 / 64) with exercise alone, and 26% (11 / 42) with neither treatment. In the previous year, the frequency of excitement was higher without

Keiko Ikemoto

332

sunbathing, i. e., 30% (28 / 94) with exercise alone and 43% (40 / 92) with neither treatment. Since sunbathing and exercise were markedly effective for insomnia and behavioural disturbance, we terminated the examination at the end of October, 2007. The time course of sleeping well and excitement is shown in Figure 1. The SWC of the patient was remarkably improved as shown in Figure 2.

1 00 80 60

sleep well

%

exc it eme nt

40 20 0 May

Apr

Ju n

Jul

Aug

Se p

Oc t

Figure 1. Relationship between frequencies of sleeping well and excitement during the period of sunbathing. Frequency of sleeping well increased while that of excitement decreased as sunbathing continued.

(a) Pre-sunbathing 2

4

6

8

10

12

14

16

18

20

22

24

(b) After sunbathing for 6 months 2

4

6

8

10

12

14

16

18

20

22

24

・・・・・deeply asleep ・・・・・drowsy in bed ・・・・・awake in bed

Figure 2. Sleep-wake-cycle. (a) Sleep log (based on nurses‘ observation). A month before the start of sunbathing. (b) Sleep log. Six months after the start of sunbathing.


333

After the start of sunbathing and exercise, the frequencies of pyrexia and repetitive phlegmon of the legs, as well as epileptic seizures were reduced. From October, 2007, there were no episodes of pyrexia episode for more than 6 months [2].

Serum Levels of Melatonin and Cortisol Before the investigation began (March 19, 2007), the serum melatonin level was low at 0:00 (9.5pg/mL). After 5 months (August 28, 2007), it had increased to 16 pg/mL, within the standard range (10-127 pg/mL [6]), and after 7 months (October 29, 2007), it remained 14 pg/mL, also within the standard range [6]. The serum melatonin levels at time 12:00 on March 19, August 28 and October 29 were consistently <2.8 pg/mL, the standard level (2.8～5.6 pg/mL [6]). Serum cortisol level at time 0:00, though lower than the standard level (3.8～18.4μg/dl; report from BML, Tokyo, Japan), increased during the investigation (levels on March 19, August 28 and October 28 were 2.6→2.9→3.4μg/dl). The level at 12:00 consistently remained in the standard range (11.8→8.9→11.6μg/dl).

Effect of Sunbathing In the present case of SMID accompanied by behavioural disturbance, sunbathing appeared to be effective for the treatment of insomnia. Its effect included, i) improvement of the SWC; ii) reduction of the frequency of excitement; iii) reduction of the frequency of pyrexia, suggesting improvement of immune function; and iv) reduction of the frequency of epileptic seizures. MRI findings demonstrated infarction of the cerebral cortex and atrophy of the brainstem, suggesting injury of the ascending reticular formation which plays roles in determining the SWC [7]. This was a possible cause of sleep disturbance in the present case. During the period of sunbathing, serum levels of melatonin, an endogenous sleep-inducer, and cortisol at time 0:00 tended to increase to normal levels, although sampling number and reproducibility were insufficient for definitive analysis. Sunbathing, a simple and safe method, is thought to reinforce social synchronizing factors as well as light synchronizing factors [5]. In the present case, similar to the effect of light therapy for insomnia in elderly persons, low melatonin level exhibited a tendency toward normalization [3]. Generally, mentally retarded people typically exhibit poor sleep efficiency and reduced nocturnal plasma melatonin levels. This state is similar to that of the elderly, in whom decrease in amplitude of the sleep-wake rhythm and decreased levels of melatonin secretion are observed [4]. Exposure to bright light suppresses the production of melatonin, increases nocturnal melatonin secretion, and contributes to regulation of the circadian rhythm. The mechanism of elevation of nocturnal melatonin level in the present case remains to be explored.

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Effects of Melatonin on Insomnia and Behavioural Disturbance Mental Retardation Several reports have described clinical trials of administration of exogenous melatonin to individuals with intellectual disabilities (ID) to improve insomnia and behavioural disturbance. Niederhofer et al. (2003) reported that oral administration of 0.1 or 3 mg melatonin, 30 minutes before bedtime, to mentally retarded subjects with sleep deficits facilitated sleep [8]. Dodd et al. (2008) reported that melatonin administration to three adults with moderate to severe ID changed circadian rhythm and improved challenging behaviour, though no significant effect was noted with regard to either quantity or quality of sleep [9]. Braam et al. (2008) reported that melatonin was, compared with placebo, effective for chronic insomnia in individuals with ID, including significant advance of mean sleep onset time and decrease in sleep latency [10]. Ishizaki et al. (1998) reported that melatonin at bedtime was efficacious in 42 of 50 patients with developmental disorders and sleep disorders (3-28 years of age; 41 males and 9 females; autism in 27 patients, mental retardation in 20 patients, and SMID in 3 patients), i. e., that excitability was often improved in patients with emotional / behavioural disturbance, whose sleep disorder was also improved, while stereotyped behavior and school/work refusal remained almost unchanged [11]. In these studies, the dosage of melatonin administered ranged from 2.5～6 mg per day [9-11]. In patients with severe behavioural disturbance, wrist actigraphy could not be performrd because the patients easily broke the device due to impaired mental function and behavioural problems. Sunbathing and / or phototherapy improves the SWC and reduces behavioural disturbance, possibly by increasing nocturnal melatonin secretion. Melatonin might be a key substance in improvement of the SWC and behavioural disturbance in cases of application of sunbathing and / or light therapy.

The Elderly and Persons with Dementia In comparison with mental retardation, the insomnia of patients with dementia has been studied in greater detail. Mishima et al. reported that insufficient environmental illumination diminished melatonin secretion in the elderly [12], and that administration of artificial bright light and melatonin improved the circadian rhythm of institutionalized demented elderly persons [3]. It has also been reported that morning bright light reduced insomnia and behavioural disturbance including delirium [13]. There are numerous reports indicating that melatonin is effective for sleep disturbance in the elderly and patients with dementia [14-15], while, there is as yet insufficient evidence to conclude that melatonin improves cognitive function [15].


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Conclusions Sunbathing and / or phototherapy appears to be useful for treating insomnia in individuals with brain damage including certain types of mental retardation and dementia. Melatonin, insomnia, behavioural disturbance, and sunbathing should be further studied in larger numbers of patients with mental retardation, to obtain evidence for the effectiveness of sunbathing in treating insomnia and behavioural disturbance in the mentally retarded.

References [1]

Guilleminault, C., McCann, C.C., Quera-Salva, M., & Cetel, M. (1993) Light therapy as treatment of dyschronosis in brain impaired children. Eur J Pediatr, 152: 754-759. [2] Lindblom, N., Heiskala, H., Kaski, M., Leinonen, L., & Laakso, M.L. (2002) Sleep fragmentation in mentally retarded people decreases with increasing daylength in spring. Chronobiol Int, 19: 441-459. [3] Mishima, K., Okawa, M., Hozumi, S., & Hishikawa, Y. (2000) Supplementary administration of artificial bright light and melatonin as potent treatment for disorganized circadian rest-activity and dysfunctional autonomic and neuroendocrine systems in institutionalized demented elderly persons. Chronobiol Int. 17: 419-432. [4] Ikemoto, K., Hirano, S., Sugiura, M., Suzuki, Y., Tobai, H., Takahashi, Y., Kurio, Y., Okawa, M., & Shibuya, H. (2006) Effect of a sunbathing on insomnia and behavioral disturbance of mental retardation: A case report. Sleep and Biological Rhythms, 4: 175178. [5] Okawa, M., Nanami, T., Wada, S., & Shimizu, T. (1987) Four congenitally blind children with circadian sleep-wake rhythm disorder. Sleep, 10: 101-110. [6] Waldhauser, F., Weiszenbacher, G., Tatzer, E., Gisinger, B., Waldhauser, M., Schemper, M., & Frisch, H. (1988) Alterations in nocturnal serum melatonin levels in humans with growth and aging. J Clin Endocrinol Metab, 66: 648-652. [7] Magoun, H.W. The waking brain, 2nd ed. Illinois: Charles C Thomas Springfield, 1963. [8] Niederhofer, H., Staffen, W., Mair, A., Pittschieler, K. (2003) Brief report: melatonin facilitates sleep in individuals with mental retardation and insomnia. J Autism Dev Disord, 33: 469-472. [9] Dodd, A., Hare, D.J., & Arshad, P. (2008) The use of melatonin to treat sleep disorder in adults with intellectual disabilities in community settings - the evaluation of three cases using actigraphy. J Intellect Disabil Res, 52: 547-553. [10] Braam, W., Didden, R., Smits, M., & Curfs, L. (2008) Melatonin treatment in individuals with intellectual disability and chronic insomnia: a randomized placebocontrolled study. J Intellect Disabil Res, 52: 256-264. [11] Ishizaki, A., Sugama, M., & Takeuchi, N. (1999) Usefulness of melatonin for developmental sleep and emotional / behavior disorders- studies of melatonin trial on 50 patients with developmental disorders. No To Hattatsu. 31: 428-437. (in japanese)

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[12] Mishima, K., Okawa, M., Shimizu, T., & Hishikawa, Y. (2001) Diminished melatonin secretion in the elderly caused by insufficient environmental illumination. J Clin Endocrinol Metab, 86: 129-134. [13] Mishima, K., Okawa, M., Hishikawa, Y., Hozumi, S., Hori, H., & Takahashi, K. (1994) Morning bright light therapy for sleep and behavior disorders in elderly patients with dementia. Acta Psychiatr Scand, 89: 1-7. [14] Singer, C., Tractenberg, R.E., Kaye, J., Schafer, K., Gamst, A., Grundman, M., Thomas, R., & Thal, L.J. (2003) Alzheimer's Disease Cooperative Study.: A multicenter, placebo-controlled trial of melatonin for sleep disturbance in Alzheimer's disease. Sleep, 26: 893-901. [15] Riemersma-van der Lek, R.F., Swaab, D.F., Twisk, J., Hol, E.M., Hoogendijk, W.J., & Van Someren, E.J. (2008) Effect of bright light and melatonin on cognitive and noncognitive function in elderly residents of group care facilities: a randomized controlled trial. JAMA, 299: 2642-2655.



Chapter XVI

Neuroimaging Insights into Insomnia Martin Desseilles†a, b, d, Thien Thanh Dang-Vua, c, Manuel Schabuse, Kerstin Hoedlmoser e, Camille Piguet d, Maxime Bonjean a,f, Sophie Schwartzd and Pierre Maqueta, c a

b

University of Liège, Belgium Hopitaux Universitaire de Genève (HUG), Geneva Switzerland c Centre Hospitalier Universitaire (CHU), Liège d University Medical Centre, Geneva, Switzerland e University of Salzburg, Salzburg, Austria f University of California, San Diego, USA

Abstract Insomnia is a frequent symptom or syndrome defined by complaints of trouble in initiating or maintaining sleep or of nonrestorative sleep. This causes significant impairments in several areas of daytime functioning including mood, motivation, attention and vigilance. Significant advances in our neurobiological knowledge of insomnia have been brought by electrophysiological data (e.g. electroencephalography (EEG) and by functional neuroimaging data (e.g. single photon emission computed tomography (SPECT), positron emission tomography (PET) acquired during wakefulness, transition from waking to non rapid-eye-movement (NREM) sleep and REM sleep itself. Indeed it has been shown that idiopathic insomnia is characterized by a specific pattern of regional brain activity: (i) during the transition from waking to NREM sleep: failure to decrease brain activity in the ascending reticular activating system, medial prefrontal cortex, limbic/paralimbic areas (including insular cortex, amygdala,

†

Correspondance: Martin Desseilles, MD, PhD, Cyclotron Research Centre, University of Liege, Batiment B30, 8, allée du 6 Aout – B-4000 Liege (BELGIUM), Tel: +32 4 366 23 16; Fax: +32 4 366 29 46, E-mail: [email protected]

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Martin Desseilles, Thien Thanh Dang-Vu, Manuel Schabus et al. hippocampus, anterior cingulate), thalamus and hypothalamus, (ii) during NREM sleep: deactivation of the parietal and occipital cortices, and basal ganglia, and (iii) during wakefulness: deactivation in brainstem reticular formation, thalamus, hypothalamus, prefrontal, left superior temporal, parietal and occipital cortices. This specific distribution of brain activity might relate to (i) specific impairments in daytime functioning (e.g. hypoactivity in prefrontal cortex during wakefulness is consistent with reduced attentional abilities), (ii) hyperarousal hypothesis as a common pathway in the pathophysiology of insomnia (e.g. overall cortical hyperarousal characterized by an increase in EEG beta/gamma activity (14-35 / 35-45 Hz) at sleep onset and during NREM sleep) and (iii) the potentially overlapping pathophysiology with major depressive disorder as this illness has shown similarly altered cortical patterns (e.g. both illnesses have impairments in limbic/paralimbic areas as well as in basal ganglia). The goal of this chapter is to show that combining recent neurophysiological and neuroimaging data on human sleep offers new insights into the pathophysiological mechanisms of insomnia and potentially opens new therapeutic perspectives.

Keywords: insomnia, sleep, REM, NREM, functional neuroimaging, cognitive neuroscience, hyperarousal, major depressive disorder, brain.

1. Introduction In healthy humans, functional and structural neuroimaging has been successfully used to characterize normal stage and pathological conditions of sleep, as reviewed elsewere (DangVu, Desseilles et al. 2007; Desseilles, Dang-Vu et al. 2008). Here we focus on the brain imaging studies devoted to insomnia. Insomnia is characterized by complaints of repeated difficulty in initiating or maintaining sleep or of nonrestorative sleep, which cause clinically significant distress or impairment in cognitive, social, and occupational, or other important areas of functioning (Cortoos, Verstraeten et al. 2006). Insomnia therefore presents with subjective symptoms. Insomnia can arise directly from sleep/wake regulatory dysfunction or indirectly from comorbid behavioral, psychiatric, neurological, immune, or endocrine disorders, including disturbances secondary to the use of drugs. In this respect, insomnia appears to be a 24-h disorder because it is not restricted to sleep complaints alone but can affect several aspects of daytime functioning as well. Importantly, insomnia is a common disorder in our society, with 10% to 20% of the general population reporting insomnia complaints and related impairment of daytime functioning (Ohayon 2002). We should note that prevalence of insomnia increases with several factors such as: age (increase in older), gender (more frequent in women), occupational status (increase in people undergoing particular private or professional pressure), and medical condition (substance users, neurological or psychiatric comorbid condition). Insomnia can be either acute or chronic and either idiopathic or secondary to several conditions including physical disease or mental illnesses. Several manuals (American Psychiatric Association 1994; American Academy of Sleep Medicine 2005) propose a classification of different subtypes of insomnia but full description of these subtypes goes beyond the aim of our chapter.

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The hyperarousal hypothesis of insomnia has gained growing attention as an integrative approach to the mechanism of insomnia (Perlis, Giles et al. 1997). This hypothesis presupposes interplay between psychological and physiological factors in the onset and maintenance of insomnia. It postulates that subjects who tend to focus cognitively on the insomnia and start to ruminate about their sleep complaint are prone to perpetuate the disorder, especially when it is associated to maladaptive behaviors such as prolongation of bedtime or daytime napping. We will first review the structural and functional imaging findings in insomnia. Then we will describe successively the functional imaging of drug response, daytime functioning impairment and the hyperarousal hypothesis. Because depression is often associated with insomnia (Tsuno, Besset et al. 2005) we review hereafter the data pointing to some common underlying neurophysiological mechanisms for both sleep and mood regulation.

2. Structural and Functional Imaging in Insomnia Structural imaging make possible to detect small differences in brain morphology associated with a particular condition. In particular, voxel-based morphometry (VBM) is based on high-resolution magnetic resonance imaging (MRI) scans and allows comparisons of grey and white matter across the brain and between groups. Proton magnetic resonance spectroscopy (1H-MRS) allows to assess the regional brain content in different compounds such as gamma-aminobutyric acid (GABA). Only one study has assessed the structural anatomy of idiopathic (or primary) insomnia by using VBM (Riemann, Voderholzer et al. 2007). Riemann and collaborators used MRI (1.5 Tesla) in 8 unmedicated patients suffering from chronic idiopathic insomnia (3 males; mean age (standard deviation) of 48.4 (16.3) years) and 8 good sleepers matched for age, sex, body mass index, and education level. They found that patients have a significant reduction of hippocampal volumes bilaterally (see Figure 1), as compared to the good sleepers (Riemann, Voderholzer et al. 2007). Because of the size of the study sample, the results should be interpretated with caution. However, findings are congruent with the empirical data on (i) sleep-dependent encoding capacity of the hippocampus (Walker 2009) and (ii) impaired sleep-related memory consolidation in idiopathic insomnia (Nissen, Kloepfer et al. 2006). The first study on neurochemical differences in patients with insomnia was recently conducted using 1H-MRS in 16 non-medicated individuals (8 women) with idiopathic insomnia (mean age (SD) = 37.3 (8.1) years) and 16 (7 women) normal sleepers (37.6 (4.5) years) (Winkelman, Buxton et al. 2008). Average brain GABA levels were nearly 30% lower in patients as compared to controls and were negatively correlated with wake after sleep onset (WASO). Since GABA is a major inhibitory neurotransmitter, this result may be consistent with the increase of brain glucose metabolism in several areas covered by this 1HMRS study, such as the thalamus (Nofzinger, Buysse et al. 2004). Nevertheless an important methodological limitation of this study is the lack of anatomical specificity that limits further interpretations.

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Several functional imaging techniques make possible to assess regional brain activity at rest, between two distinct conditions during a task or in association with any physiological process. While single photon emission computed tomography (SPECT) and positron emission tomography (PET) show the distribution of radioisotope emitting single gamma photons or compounds labeled with positron-emitting isotopes, functional magnetic resonance imaging (fMRI) measures the variation in brain perfusion related to neural activity by using a method based on the assessment of the blood-oxygen-level-dependent (BOLD) signal. The latter reflects the relative decrease in deoxyhemoglobin concentration that follows the local increase in cerebral blood flow in an activated brain region. To our knowledge, only a few studies have assessed the functional neuroanatomy of idiopathic insomnia disorder by recording brain activity during NREM sleep. Nofzinger et al. used 18fluorodeoxyglucose (18FDG) PET to measure regional brain metabolism (indexed by cerebral metabolic regional glucose consumption, CMRglu) in 7 patients with idiopathic insomnia and 20 healthy age-matched and gender-matched subjects during waking and NREM sleep (Nofzinger, Buysse et al. 2004). Insomnia patients showed a global CMRglu increase during the transition from waking to sleep onset as compared to healthy subjects, suggesting that there is an overall cortical hyperarousal in insomnia. Moreover, insomniac patients exhibited less reduction of relative CMRglu from waking to NREM sleep in the ascending reticular activating system, hypothalamus, insular cortex, amygdala, hippocampus, anterior cingulate, and medial prefrontal cortices, as illustrated in Figure 1. An increased metabolism was also observed in the thalamus, which might reflect persistent sensory processing and information processing as well as subsequent shallower sleep. In contrast, during wakefulness, decreased metabolism was found in subcortical (thalamus, hypothalamus, and brainstem reticular formation) as well as in cortical regions (prefrontal cortex bilaterally, left superior temporal, parietal, and occipital cortices). These findings suggest that insomnia might involve abnormally high regional brain activity during sleep, associated with reduced brain metabolism during waking. The observed reduction in prefrontal cortex activity during wakefulness is consistent with reduced attentional abilities and impaired cognitive flexibility resulting from inefficient sleep and is consistent with a chronic state of sleep deprivation (Thomas, Sing et al. 2000; Drummond and Brown 2001; Durmer and Dinges 2005). Another early study by Smith et al. (Smith, Perlis et al. 2002), which compared 5 insomniacs with 4 normal sleepers using SPECT, found no significant regional increase during NREM sleep but reduced regional cerebral blood flow (rCBF) in frontal medial, occipital, and parietal cortices, as well as in the basal ganglia during this period (see Figure 1). Interestingly, in Nofzinger‘s study, decreases in activity in these same regions were also found in insomniacs, but during wakefulness. However, some methodological limitations in the Smith‘s study need to be considered. Firstly, the blood flow was only sampled during the first NREM cycle. Therefore, the observed decreased metabolism in insomniacs might reflect cortical hypoarousal during the initial phases of NREM sleep following sleep onset, while it remains possible that the patients were more aroused over later NREM sleep cycles, which would be more consistent with higher beta activity later at night (Perlis, Merica et al. 2001). Secondly, the blood flow was measured after a longer duration of NREM sleep in insomnia patients than in healthy subjects, leading to a possible underestimation of activity in the


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patients because blood flow decreases over long NREM periods. Because of such methodological limitations, these preliminary results cannot rule out the hyperarousal hypothesis of idiopathic insomnia. Four of the insomnia patients from the Smith‘s study were rescanned after they had been treated by cognitive behavioral therapy (which included sleep restriction and stimulus control (Smith, Perlis et al. 2005). After treatment, sleep latency was reduced by at least 43%, and there was a global 24% increase in CBF with significant increases in the basal ganglia. The authors proposed that such increase in brain activity might reflect the normalization of sleep homeostatic processes.

Figure 1.Structural and functional abnormalities in insomnia. Regional cerebral metabolism during NREM sleep in idiopathic insomnia. Nofzinger et al. found increased regional metabolism (18FDG PET) from waking to NREM sleep in patients with idiopathic insomnia (Nofzinger, Buysse et al. 2004). Smith et al. found reduced regional cerebral blood flow (SPECT) in the basal ganglia in insomniacs (Smith, Perlis et al. 2002; Smith, Perlis et al. 2005). Altena et al. found a hypoactivity duringletter fluency and category fluency task in frontal areas (Altena, Van Der Werf et al. 2008). Riemann et al. found a cortical grey matter loss in both hippocampus (Riemann, Voderholzer et al. 2007). Adapted from Desseilles et al., SLEEP, 2008.

Similarly, a recent fMRI study showed that 21 old patients suffering from chronic insomnia, compared to 12 matched controls, displayed a hypoactivation of the medial and inferior prefrontal cortical areas (BA9, 44-45) (Altena, Van Der Werf et al. 2008). The prefrontal abnormalities were revealed by using a category and a letter fluency task during a waking fMRI acquisition before and after a 6 weeks period of nonpharmacological sleep therapy. This therapy included cognitive behavioral therapy, body temperature and bright

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light interventions, sleep hygiene and physical activity counseling. There were no significant behavioral differences between groups, allowing thus the interpretation in term of differential recruitment of brain areas. Interestingly, abnormalities recovered after a nonpharmacological sleep therapy (n = 10) but not after a wait list period (n = 10). Theses results should be refined by using larger samples of well diagnosed patients and matched controls in protocols combining structural, neuropsychological, neuroendocrine, neurochemical, functional imaging and polysomnographic studies. Hopefully, these interesting initial results will inspire further investigation on the effects of psychotherapy on brain functioning in insomnia.

3. Functional Imaging of Hypnotic Drugs Response in Healthy Individuals To our knowledge, there is no neuroimaging study of hyponotic drugs response in insomniacs but only in healthy subjects. In addition, most of the studies studied the effect of acute and not chronic administration. Functional neuroimaging allows some insights into the mechanisms of several sedative drugs, although the neuroimaging data are still sparse. Most of the studies concern the class of benzodiazepines (see Table 1). For instance, lorazepam administration markedly decreases regional brain glucose metabolism in thalamus and occipital cortex during wakefulness (Volkow, Wang et al. 1995; Schreckenberger, Lange-Asschenfeldt et al. 2004). In the former study, changes in metabolic activity in thalamus were significantly related to lorazepaminduced sleepiness and were partially reversed by flumazenil, a benzodiazepine antagonist (Volkow, Wang et al. 1995). It was suggested that benzodiazepine-induced changes in thalamic activity may account for their sedative properties. This is reinforced by a study in normal subjects that finds a close relationship between bilateral thalamic activity and alpha rhythm, generally considered to be the marker of restful wakefulness. Both glucose metabolism and alpha rhythms are reduced under lorazepam in bilateral thalamus (Schreckenberger, Lange-Asschenfeldt et al. 2004). Another type of short-acting benzodiazepine, triazolam, is correlated with a decrease in blood flow in the basal forebrain and amygdaloid complexes during NREM sleep (Kajimura, Nishikawa et al. 2004). These results suggest that hypnotic effect of the benzodiazepines may be mediated mainly by deactivation of the forebrain control system for wakefulness and also by the anxiolytic effect induced by deactivation of the amygdaloid complexes (Kajimura, Nishikawa et al. 2004). The impairment of episodic memory encoding by this drug, on the other hand, is associated with dose-related deactivation in prefrontal cortex, medial temporal lobe and left anterior cingulate cortex (Mintzer, Kuwabara et al. 2006). Midazolam, another drug of this class with short half-life and known to cause anterograde amnesia in healthy subjects, diminishes functional connectivity in posterior cingulate cortex (Greicius, Kiviniemi et al. 2008) in resting state analysis of fMRI data. PET studies found decrease of cerebral blood flow in prefrontal cortex, insula, temporal lobe, and associative areas comparing before and after infusion of midazolam (Veselis, Reinsel et al. 1997; Bagary, Fluck et al. 2000; Reinsel, Veselis et al. 2000).

Table 1. Functional imaging of hypnotic drugs response in healthy individuals.

From top to bottom: sorted by treatment and then by date of publiscation. From left to right: reference of the study, modality of brain imaging, state in which the study is conductied and task paradigm used, number of studied subjects, placebo-controlled study, and main result of the study (PFC = prefrontal cortex; ACC = Anterior cingulated cortex; OFC = orbitofrontal cortex; DLPFC = dorsolateral prefrontal cortex).

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During sleep induced by zolpidem (an imidazopyridine hypnotic relatively selective for alpha-1 subunit of the omega-1 (BZ1) receptor of the gamma-aminobutyric acid type A) in healthy subjects, rCBF decreases compared to pacebo in the anterior cingulate cortex during REM sleep while it decreases in the prefrontal cortex and the insula during NREM sleep (Finelli, Landolt et al. 2000). Another study finds metabolic decreases in the metbolism in the cingulate, the thalamus and the putamen during NREM sleep (Gillin, Buchsbaum et al. 1996). Data on the sedative effect of opiates are rare. One study aimed at comparing the general effect of hydromorphone (μ-receptor agonist) and butorphanol (agonist/antagonist with κ component of activity) found different pattern of activation in a SPECT study: hydromorphone compared to plabebo elicited activation of the anterior cingulate cortex, thalamus and amygdala bilaterally, while butorphanol produced a more diffuse pattern (Schlaepfer, Strain et al. 1998). Despite these interesting results, none of these reports has studied the placebo-controlled effects of sedative agents in a large sample of well diagnosed insomniac patients compared to healthy subjects matched. It is also remarquable that while antidepressant are widely used for the treatement of insomnia, outside of depression context, at our knowledge no brain imaging studies of antidepressants use in idiopathic insomnia patients exists. The same observation applies for over the counter drugs such as melatonine or diphenhydramine. Additionaly, another striking feature is the absence, for a large part of the studies, of EEG control for the state of vigilance that could inform us if the subjects were actually sleeping or not.

4. Daytime Functioning Impairments Poor sleep may have detrimental consequences on daytime functioning such as altered mood and motivation, decreased attention and vigilance, low levels of energy and concentration, and increased daytime fatigue (Bonnet and Arand 1997). Several studies have suggested cognitive abnormalities in patients with idiopathic insomnia such as sleep-related attentional bias (Spiegelhalder, Espie et al. 2008) or impaired sleep-related memory consolidation (Nissen, Kloepfer et al. 2006). Nevertheless, few behavioral studies have found abnormal performances and, even, several studies found similar performances, e.g. using category and letter fluency task (Altena, Van Der Werf et al. 2008). Putatively, an hyperarousal and a high level of perfectionism in these patients could mask performance decreases due to poor sleep (Vincent and Walker 2000; Drummond, Smith et al. 2004). The specific distribution of brain activity or structure shown in patients with insomnia might relate to specific impairments in daytime functioning, e.g. hypoactivity in prefrontal cortex during wakefulness is consistent with reduced attentional abilities or reduced hippocampal volume is consistent with impaired sleep-related memory consolidation. The extensive review of the impact of sleep deprivation is beyond the scope of this chapter. Nevertheless, insomnia could be considered as a chronic sleep deprivation and the growing body of evidence indicating the involvement of sleep in several functions suggests that sleep deprivation is an interesting domain to investigate in order to better understand the pathophysiology of insomnia (Ellenbogen 2005). For instance, sleep deprivation has several


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effects on neural functioning (Boonstra, Stins et al. 2007) and is considered as a neurobiological and physiological stressor (McEwen 2006) having an impact on cognition (Durmer and Dinges 2005), memory (Walker and Stickgold 2004; Walker and Stickgold 2005) as well as emotion (Sterpenich, Albouy et al. 2009; Walker 2009) and metabolism (Copinschi 2005). Interestingly, several sources of evidence show that (i) sleep difficulties are common among persons with suicidal ideations, suicide attempts and suicide completion (Sabo, Reynolds et al. 1991; Roberts, Roberts et al. 2001; Smith, Perlis et al. 2004); (ii) sleep disturbances are strongly linked to aggressive and impulsive behavior, as well as mood lability (Pakyurek, Gutkovich et al. 2002); (iii) sleep deprivation is associated with panic and anxiety, which is independently linked with suicidal ideations and suicide attempts in humans (Friedman, Smith et al. 1999). Recently short sleep (less than 5 hours of sleep) was associated with suicidal ideation and attempts among adults in the general population (Goodwin and Marusic 2008). Overall, these results are of first importance since insomnia, a chronic deprivation of sleep, has been linked to depression (Riemann and Voderholzer 2003; Tsuno, Besset et al. 2005) (see below).

5. Hyperarousal Hypothesis in Insomnia 5.1. Insomnia and Hyperarousal According to the International Classification of Sleep Disorders (ICSD-2), idiopathic insomnia ―is a lifelong inability to obtain adequate sleep that is presumably due to an abnormality of the neurological control of the sleep-wake system.‖(American Academy of Sleep Medicine 2005). Idiopathic insomnia is thought to reflect an imbalance between arousal and sleep promoting systems, which results in a global cortical hyperactivity as evidenced by EEG studies (see below). In line with the elevated arousal levels, several studies have reported increased alertness using the multiple sleep latency test as well as increased tension and anxiety during wakefulness, associated with a reduction of total sleep duration (Bonnet and Arand 1997). In addition, quantitative EEG recordings in idiopathic insomnia patients are characterized by an increase in EEG beta/gamma activity (14-35 / 3545 Hz) at sleep onset and during NREM sleep (Perlis, Merica et al. 2001) and are thus congruent with an overall cortical hyperarousal in idiopathic insomnia. Insomnia would therefore result from a conditioned state of central nervous system (CNS) arousal, which enhances a variety of sensory and cognitive phenomena that are normally suppressed or at least diminished at sleep onset. Uncommon high-frequency activity associated with sleep onset might thus contribute to the frequent misperception of insomniacs of not being asleep while objective EEG parameters indicate otherwise (Perlis, Merica et al. 2001). In addition, specific distribution of brain activity shown in patients with insomnia might relate to hyperarousal hypothesis as a common pathway in the pathophysiology of insomnia (e.g.

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overall cortical hyperarousal characterized by an increase in beta/gamma activity at sleep onset and during NREM sleep) (see above).

5.2. Locus Coeruleus and Arousal Much evidence in the regulation of alterness is available for the noradrenergic locus coeruleus. The importance of arousal is patent because of its undeniable link to other phenomena such as sleep, attention, anxiety, stress and motivation (Aston-Jones and Cohen 2005). Contrarily to reduced arousal that leads to sleepiness, increased arousal (e.g. elicited by the sudden appearance of an environmentally salient event or a strongly motivating memory) can facilitate behavior but in the limit can also lead to distractibility and anxiety (Aston-Jones and Cohen 2005). Traditional theories of locus coeruleus (LC) – norepinephrine (NE) function have attached this structure to arousal (Berridge and Waterhouse 2003). Recently, Aston-Jones and Cohen proposed a role for the LC system in optimizing behavioral performance, which in turn may explain effects traditionally interpreted in terms of arousal (Aston-Jones and Cohen 2005). In their theory, they detail the two modes of activity that the LC neurons exhibit: phasic and tonic. Phasic LC activation is driven by the outcome of taskrelated decision processes (highly salient and arousing stimuli) and is proposed to facilitate ensuing behaviors and to help optimizing task performance (or exploitation). Interestingly, LC neuronal activity has recently been shown to fire synchronously and phasically with the cortical slow oscillation in rats suggesting a role in modulating cortical function even during the deepest stages of sleep (Yeshenko, Moelle et al. 2006). Accordingly a recent fMRI study has shown that slow oscillations were associated with the activation of a brainstem area compatible with the LC during slow wave sleep (SWS) in humans (Dang-Vu, Schabus et al. 2008). Tonic LC activation, when utility in the task wanes, is associated with disengagement from the current task and a search for alternative behaviors (or exploration). Interestingly, in monkeys, both orbitofrontal cortex (OFC) and anterior cingulate cortex (ACC), which are thought to monitor task-related utility, give projections to LC (Aston-Jones and Cohen 2005). In addition, these two areas receive inputs from a wide array of sensorimotor areas (Carmichael and Price 1995), the same areas that have been shown with increased activity in depression (Nofzinger, Buysse et al. 2004). LC was involved in diurnal rhythm (Schmidt, Collette et al. 2009), sleep and wakefulness (Steriade, McCormick et al. 1993). Low levels of LC activity facilitate sleep and disengagement from the environment (Aston-Jones and Cohen 2005). This recent integrative theory of LC is in good accordance with the relative increase of CMRglu from waking to NREM sleep in the anterior cingulate of patients suffering from insomnia (Nofzinger, Buysse et al. 2004) and with the increased activity during REM sleep in frontal and sensorimotor cortices in patients suffering from depression (Nofzinger, Buysse et al. 2004) (see below). Overall, we hypothesize that the increase of activity in frontal regions subserving the monitoring of task-related utility could be associated with an increase of firing of LC neurons in tonic mode thus increasing arousal. This hypothesis still has to be further documented.


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6. Insomnia and Depression Depression is the most common primary diagnosis in patients suffering from insomnia (Benca 2000). Of all psychiatric conditions associated with insomnia, depression (in particular unipolar depression) is the most frequently diagnosed one (Tsuno, Besset et al. 2005). Depressed patients frequently report increased daytime fatigue and tend to compensate with daytime napping. Patients with bipolar disorder, on the other hand, report insomnia while depressed, but also hypersomnia, with extended nocturnal sleep periods, difficulty in awakening, and excessive daytime sleepiness (Benca 2000). Thus, sleep disturbances appear to vary even across depression subtypes. Recently short sleep duration (less than 5 hours by 24 hours) was associated with suicidal ideation and attempts among adults in the general population independently of the effects of comorbid mental disorders (Goodwin and Marusic 2008). In addition, depression is associated with other sleep disorders like obstructive sleep apnea syndrome (Schroder and O'Hara 2005). Here, we only focus on the links between depression and insomnia. Specifically, indications of hyperarousal in both conditions suggest shared neurophysiological mechanisms underlying both sleep and mood regulation (Roth, Roehrs et al. 2007).

6.1. Hyperarousal Hypothesis in Depression In depressed patients, modifications of the sleep architecture is characterized by reduced slow wave sleep (SWS), early onset of the first episode of REM sleep, and increased phasic REM sleep (Thase 1998). Gillin et al. postulated that depression is closely linked to an abnormal increase in some aspects of physiological arousal (Gillin, Buchsbaum et al. 2001). Consistent with this hypothesis, total scores on the Hamilton Depression Rating Scale (HDRS) as well as sleep disturbance in depression, a distinct symptoms cluster included in the HDRS, have been found to correlate with increased metabolism and regional cerebral blood flow during wakefulness in a large set of cerebral areas including limbic structures, anterior cingulate, thalamus, and basal ganglia (Milak, Parsey et al. 2005). Intriguingly, total sleep deprivation is the only known therapeutic intervention in depression that has proven antidepressant effects within 24 hours. Sleep deprivation can have rapid beneficial effects, but unfortunately only for about half of the depressive population, with depressive symptoms reappearing after 1 night of recovery sleep (Tsuno, Besset et al. 2005). One hypothesis is that sleep deprivation can transiently counteract global hyperarousal in the responder population (Clark, Brown et al. 2006). Since hyperarousal has also been described in insomnia, this may be a common pathway underpinning the close relationship between sleep and mood disorders. Evidence for reciprocal relationship between sleep and depression is twofold: sleep disturbances often accompany depression whereas chronic insomnia is a risk factor for the development of depression (Lustberg and Reynolds 2000). Subclinical sleep EEG alterations may persist in patients at risk for a depressive episode, thus offering further evidence of a close link between sleep and mood regulation.


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In addition to this main hypothesis, several other hypotheses have been made in order to explain the huge frequency of depression in patients suffering from insomnia (Benca and Peterson 2008): including (i) deficits in monoaminergic neurotransmission, (ii) abnormalities in circadian genes, (iii) overactivity of the hypothalamic–pituitary–adrenal (HPA) axis, and (iv) impaired functioning of plasticity-related gene cascades. i)

Deficits in monoaminergic neurotransmission. Classically, during sleep, EEG activity normally shows progressive transitions from ―light‖ sleep to ―deep sleep‖, and the alternation across the night of NREM sleep (including SWS) with episodes of REM sleep. This latter stage is initiated when the monoamines (serotonergic and noradrenergic) activity decreases and cholinergic activity increases, and ceases with the opposite changes (Pace-Schott and Hobson 2002). Depressed patients present several characteristics including increased REM sleep propensity (leading to reduced REM latency), increased proportion of REM sleep, an increase of REM density (i.e. number of eye movements), and a decrease of time spent in SWS (Benca, Obermeyer et al. 1992). Depression symptomatology and sleep characteristics may be exacerbated when levels of monoaminergic neurotransmitters are decreased. Conversely, antidepressant drugs that increase monoaminergic drive seem to reverse these abnormalities (Thase 1998; Argyropoulos and Wilson 2005). ii) Abnormalities in circadian genes. Circadian genes, involved in the control of biological rhythms, are another link between depression and insomnia. The central pacemaker within the suprachiasmatic nuclei (SCN) of the anterior hypothalamus controls circadian rhythms (Glass, Hauser et al. 1993). Chronotype or circadian type refers to the preference in sleep habits and the level of alertness across the day. There is a continuum between ―morningness‖ with subjects waking up early and being more alert in the first part of the day and ―eveningness‖ with subjects going to bed late and being more alert in the late evening hours. Among the genes supposed to work together with the SCN pacemaker, irregularities in the circadian locomotor output cycles kaput (clock) gene might have a major influence on sleep patterns. Recent studies showed that a polymorphism (C to T nucleotide substitution) in the 3 flanking region of the human clock gene is associated with diurnal preferences of human healthy subjects, with higher eveningness in subjects carrying at least one copy of the C allele (Benedetti, Serretti et al. 2003). Depressed patients who have a C/C variant polymorphism in their clock gene, compared to patients without this variant, experience more frequently lifetime insomnia, present higher recurrence of initial insomnia, and experience worse insomnia during antidepressant treatment (Serretti, Benedetti et al. 2003; Serretti, Cusin et al. 2005; Artioli, Lorenzi et al. 2007). In addition to clock gene, period gene (per) and timeless gene (tim) have been involved in mental disorders (Lamont, Legault-Coutu et al. 2007). iii) Overactivity of the hypothalamic–pituitary–adrenal (HPA) axis. Hypothalamus is also involved in HPA axis abnormalities that are considered as a final common pathway for many depressive symptoms. HPA overactivation has been involved in the development of mood disorders and sleep disturbance (Nestler, Barrot et al. 2002; Steiger 2007; Bao, Meynen et al. 2008). Corticotrophin-releasing hormone


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(CRH) neurons in the paraventricular nucleus of the hypothalamus play a key role in HPA axis activity. Several evidences link insomnia and depression since, in depression, corticotrophin-releasing hormone (CRH) neurons in the paraventricular nucleus (PVN) of the hypothalamus are activated, CRH mRNA is increased in the PVN, antidepressants decrease CRH levels, and CRH antagonists are proposed in the treatment of depression (Steiger 2007; Bao, Meynen et al. 2008) while, on the sleep side, growth hormone inhibits the HPA axis, growth hormone-releasing hormone (GHRH) stimulates NREM sleep, CRH reduces NREM cycles, suppresses SWS and may enhance REM sleep (Holsboer, von Bardeleben et al. 1988; Tsuchiyama, Uchimura et al. 1995; Steiger 2007). iv) Impaired functioning of plasticity-related gene cascades. The synaptic homeostasis hypothesis proposed by Tononi and Cirelli states that plastic processes occurring during wakefulness result in a net increase in synaptic strength in many brain networks. According to this hypothesis, the role of NREM sleep might be to downscale synaptic strength to a baseline level that (1) is energetically sustainable, (2) makes efficient use of gray matter space, and (3) is beneficial for learning and memory (Massimini, Ferrarelli et al. 2005; Tononi and Cirelli 2006). On the one hand, homeostatic regulation of the total synaptic weight impinging on neurons could be impaired in insomnia and in depression. On the other hand, sleep deprivation might increase plasticity-related gene expression during wakefulness, consequently potentially strengthens synapses in brain networks closely involved in mood regulation, and thus accounting for the acute antidepressant effects of sleep deprivation therapies (Manji, Quiroz et al. 2003; Zarate, Singh et al. 2006).

7. Neuroimaging of Sleep in Depression A pioneering study by Ho et al. examined NREM using PET in 10 patients with depression and 12 controls (Ho, Gillin et al. 1996). The depressed patients showed higher CMRglu during NREM sleep in the pons, posterior cingulate, amygdala, hippocampus, and occipital and temporal cortices. There was a significant reduction of relative CMRglu in medial-orbital frontal and anterior cingulate cortices, caudate nucleus, and medial thalamus. These early findings support the hypothesis that hyperarousal in depression affects a network of limbic and posterior cortical regions, but also that the decreased medial frontal and striatal metabolism may be a hallmark of depression (Drevets, Price et al. 1997). More recent studies have confirmed that depressed patients have relatively persistent ―elevated‖ activity measured by CMRglu across many brain regions during sleep compared to presleep wakefulness (REM: 24 depressed patients compared to 14 controls (Nofzinger, Buysse et al. 2004); NREM: 12 depressed patients compared to 13 controls (Germain, Nofzinger et al. 2004). Regions more activated during REM sleep included frontal, parietal, premotor, and sensorimotor cortices, as well as the insula, the ventral pallidum, and the midbrain reticular formation (Nofzinger, Buysse et al. 2004). Regions more activated during NREM sleep included the temporal and occipital cortices, as well as the insula, posterior cingulate, cerebellum, and thalamus (Germain, Nofzinger et al. 2004). However, increased metabolism

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was also found in prefrontal cortex (unlike (Ho, Gillin et al. 1996). These results are again consistent with a general hyperactivation of arousal systems in depression that may underlie both sleep disturbances such as insomnia as well as nonrestorative sleep complaints in depressed patients. Increased rapid eye movement density (number of REMs per minute of REM sleep) was found to correlate with depression severity and clinical outcomes (Buysse, Tu et al. 1999). In humans, REM bursts are classically thought to reflect ponto-geniculo-occipital (PGO) waves, possibly associated with orienting responses and arousal processes during sleep (Peigneux, Laureys et al. 2001; Wehrle, Czisch et al. 2005). An 18FDG PET study assessed cerebral glucose consumption in a group of 13 medication-free depressed patients during REM sleep (Germain, Buysse et al. 2004). The average REM count (an automated analog of REM density) was found to positively correlate with the metabolism in a network of regions involved in emotional regulation and emotion-induced arousal (medial and ventrolateral prefrontal cortex) as well as in regions linking emotion and attentional systems (striate cortex, precuneus, and posterior parietal cortex) (Vuilleumier and Driver 2007). Whether the increased activity in these regions may drive hyperarousal during REM sleep remains unclear. However, these results might not be specific to depression because no control data were provided in that study and because the observed activation pattern overlapped with results of healthy controls from other studies (Braun, Balkin et al. 1998; Peigneux, Laureys et al. 2001). Overall, the specific distribution of brain activity shown in patients with insomnia might relate to the potentially overlapping pathophysiology with major depressive disorder as this illness has shown similarly altered cortical patterns (e.g. both illnesses have impairments in limbic/paralimbic areas as well as in basal ganglia).

8. Summary Because currently available data are limited and not perfectly consistent, any conclusion about the cerebral correlates of insomnia during NREM sleep has to remain tentative. Whilst there is some evidence for decreased activity in cortical areas during early NREM sleep as well as during wakefulness, several subcortical regions involved in sleep/wake regulation, including limbic and paralimbic regions, were found to be more active during the transition from waking to sleep states. Current data generally support the hyperarousal theory of insomnia with increased neuronal activity during NREM sleep being a possible key factor contributing to sleep misperception and disturbances occurring in insomnia. Interestingly, recent integrative theory of the noradrenergic activity, previously linked to arousals, might be a future target for upcoming studies. Depression is often associated with insomnia, as well as with hyperarousal characterized by persistent ―elevated‖ activity across many brain regions during NREM sleep. Strong evidence for hyperarousal in both idiopathic insomnia and depression, together with persistent alterations in sleep architecture in remitted depression, corroborate common neurophysiological mechanisms underlying sleep and mood regulation.


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Changes in brain functions after insomnia treatments have to be assessed more carefully in future neuroimaging studies by using larger samples of well diagnosed patients and matched controls in protocols combining structural, neuropsychological, neuroendocrine, neurochemical, functional and polysomnographic approach. In addition, early studies suggest that functional imaging could be coupled with pharmacological or psychotherapeutic treatments in order to assess the neurophysiological response to such interventions, and thus allow a better understanding of the neural mechanisms underlying the recovery from idiopathic insomnia.

Acknowledgments M.D. is supported by the Fonds Léon Frédéricq, the Horlait-Dapsens Foundation and a BCNBP-Lundbeck grant (Belgian College of Neurophsychopharmacology and Biological Psychiatry). M.D., P.M and T.T.D.-V are supported by the Fonds National de la Recherche Scientifique (FNRS - Belgium). S.S. is supported by the Swiss National Science Foundation. Additional support was provided by the University of Liège and the Queen Elisabeth Medical Foundation. K.H. and M.S. are supported by the Austrian Science Fonds (FWF). MB acknowledges support from HHMI, and NIH-NSF.

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Chapter XVII

Neuroimaging Insights into the Dreaming Brain Martin Desseilles†a, b,, Thien Thanh Dang-Vub, c, Manuel Schabusb,d, Virginie Sterpenicha, Laura Mascettib, Ariane Foretb, Luca Matarazzob, Pierre Maquetb, c, and Sophie Schwartza a

University of Geneva, Geneva, Switzerland b University of Liège, Belgium c Centre Hospitalier Universitaire (CHU), Liège, Belgium d University of Salzburg, Salzburg, Austria

Abstract Dreams are sensory, cognitive, and emotional experiences that occur spontaneously during sleep. Dream reports tend to be more frequent, vivid, and longer during rapid eye movement (REM) sleep than during non-REM sleep. This is why our current neurobiological knowledge about dreaming primarily derives from functional neuroimaging data acquired during REM sleep (e.g. electroencephalography, positron emission tomography, and functional magnetic resonance imaging). Recent neuroimaging results showed that REM sleep is characterized by a specific pattern of regional brain activity: (i) activation of the thalamus, pons, temporo-occipital and limbic/paralimbic areas (encompassing amygdala, hippocampal formation and anterior cingulate cortex), and (ii) deactivation of the dorsolateral prefrontal and inferior parietal cortices. This heterogenous distribution of brain activity might relate to some characteristic dream features (e.g. amygdala activation is consistent with frequent threatrelated emotions in dream reports). Reciprocally, specific dream features suggest the

†

Correspondance: Dr. Martin Desseilles, Cyclotron Research Centre, University of Liege, Batiment B30, 8, allée du 6 Aout – B-4000 Liege (BELGIUM), Tel: +32 4 366 23 06; Fax: +32 4 366 29 46, E-mail: [email protected]

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Martin Desseilles, Thien Thanh Dang-Vu, Manuel Schabus et al. activation of specific brain regions during sleep. Based on these observations, we previously proposed that a neuropsychological or cognitive neuroscience approach to dreaming can usefully contribute to the interpretation of neuroimaging maps of sleep. The goal of this chapter is to show that connecting recent neurophysiological and neuroimaging data on human sleep and the content of dreams offers new insights into the brain correlates of dreaming and possibly into dream functions.

Keywords: dreaming, sleep, Rapid Eye Movement (REM), functional neuroimaging, neuropsychology, cognitive neuroscience, brain, amygdala.

Introduction Dreaming represents an important facet of human experience. Dreams consist in sensorymotor, verbal, cognitive and emotional experiences, most often arranged in a narrative manner. Multisensory content predominantly involves visual and auditory modalities. Dreamed motor behaviors are frequent and diverse, including physical activities like selfmotion (walking, running, jumping) and interacting with objects. Verbal content might include written and spoken language (heard or produced by the dreamer). Cognitive content encompasses several aspects of executive functions (planning, reasoning, etc.), memory (elements in dreams involve retrieval from recent or more remote memory), as well as spatial navigation abilities, among others. Many emotional experiences in dreams are intense and possibly biased toward negative emotions. Yet, probably all the categories of dream experience described above are also subjected to many alterations and distortions that are unlikely to occur in real waking life (Hobson, Stickgold et al. 1998; Schwartz and Maquet 2002). Despite the implausibility of many dream elements with respect to the real world, the dreamer usually remains unaware of being in a dream and he/she experiences the dream as a world analog (Johnson, Kahan et al. 1984). Because of these distinctive properties among others, the study of dreaming offers a fascinating opportunity to better understand the varieties of conscious experiences across dramatic changes in brain states. Below, we first provide some historical background for a neuroscience conception of dreaming. We then review the available functional neuroimaging data that describe regional cerebral activity during normal human REM sleep, as well as the likely activating neurophysiological mechanisms underlying this pattern of activity. Finally, we discuss how these results might be interpreted in cognitive terms based on common dream features. This integrated view contributes to the characterization of the neural correlates of dreaming and may provide important elements for the understanding of the organization and functions of dreaming.

Modern History of Dream Research In the modern occidental era, pioneering scientific experimentations on dreaming started during the second half of the 19th century (Macario 1857/1978; Maury 1862; Saint-Denys

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1867/1977; Delboeuf 1885/1993). In those days (as today), introspective dream reports were considered as a valuable material for scientific enquiry, because they provide unique information about what was perceived, felt, or thought in the dream. Many experiments were designed to determine what factors might influence the dream content and what rules may determine the dream scenario. These promising developments were stopped at the beginning of the 20th century, because of two major events in the history of psychology. On the one hand, after the publication of Freud‘s psychoanalytic masterpiece in 1900 (―The Interpretation of Dreams‖), studies relying exclusively on the manifest content of dreams were discredited on behalf of a quest of the ―true‖ dream, i.e., the latent content hidden beneath the apparent dream (Freud 1955). On the other hand, the advent of behaviorism was detrimental to the study of dreaming because it denied the existence of mental experiences such as dreams. Hence, both the emphasis on dream phenomenology and the use of introspective dream reports initiated in the late 19th century were rapidly challenged; the former by psychoanalysis and the latter by behaviorism. A next turning point for the history of dreaming occurred in late 1950s, when two concomitant events renewed the interest for a scientific approach to dreaming: (i) the discovery of an objective indicator of the dreaming state and (ii) a new cognitive approach to the phenomenology of dreams (for review, Foulkes 1996). Between 1953 and 1957, in a laboratory at the University of Chicago, Nathaniel Kleitman and his two students, Eugene Aserinsky and William Dement made a revolutionary discovery. They observed that dreaming was related to recurrent periods of high cortical activity during sleep (i.e., high-frequency/low-amplitude electroencephalographic (EEG) activity, analogous to resting wake state) accompanied by rapid eye movements (REM), and increased heart rate and respiratory activity (Aserinsky and Kleitman 1953; Dement and Kleitman 1957). These REM periods were also associated with a paradoxical muscular atonia (Jouvet 1994). Later studies showed that, compared to non-REM periods, dreams collected after REM awakenings are reported more frequently, are better recalled, longer, more emotionally loaded and perceptually vivid, and they contain more bizarre features (Aserinsky and Kleitman 1953; Hobson, Pace-Schott et al. 2000). Thus, REM sleep was considered as a state of high cerebral and low physical activation that would provide a neurophysiological marker of dreaming. Not surprisingly, this discovery was extremely influential because it opened new perspectives for the scientific study of dreaming. Critically, the discovery of REM sleep also demonstrated that sleep is not an homogenous state of mental and cerebral quiescence, but that some sustained periods of elevated neurophysiological activity underlying the production of dream experiences were distributed across the sleep night (Aserinsky and Kleitman 1953). While the generation of dreams was first supposed to be restricted to REM sleep, it is increasingly believed that dreaming does not rely on REM-generating brain structures and may also occur during nonREM sleep, especially late in the sleep night (Foulkes 1962; Antrobus 1983; Cicogna, Cavallero et al. 1991; Solms 2000; Fosse, Stickgold et al. 2001; Fosse, Stickgold et al. 2004; Manni 2005). Yet, REM sleep might reasonably be considered as a facilitating neurophysiological state for dreaming to occur, even though dreams are not exclusively experienced during this sleep stage.

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The exact same year that Aserinsky and Kleitman wrote their inaugural article on REM sleep, Calvin S. Hall (1953/1966) published The Meaning of Dreams in which he described and classified phenomenological characteristics from thousands of dreams from college students. Based on this first investigation, Hall and Van De Castle (1966) later developed a detailed coding system for quantifying the manifest content of dreams (e.g., characters, settings, objects, emotions, social interactions) which was updated in recent investigations (Schneider and Domhoff 2009). From then on, the phenomenological content of the dreams was again considered as useful descriptions of cognitive processes at play during sleep.

Functions of Dreaming The conception of dreaming has considerably changed through history, which led to many different hypothesized functions of the dreams (Lavie and Hobson 1986; Barbera 2008). Currently, the function of dreaming remains still controversial. For instance, several theories encompassing the mind-brain reductionism claim that dreaming is simply a random by-product of REM physiology related to ―unlearning‖ in an otherwise overloaded brain (Hobson and McCarley 1977; Crick and Mitchison 1995). Contrarily, others proposed it has fundamental functional significance. For instance, dreams might echo dynamic functions like reprocessing and further consolidation of novel and individually relevant features encountered during previous waking experience (Cipolli, Fagioli et al. 2004). Besides the potential benefits for long-term storage of freshly encoded information proposed by the latter theory, Jouvet (1998) proposed that dreaming involves the genetic reprogramming of cortical networks maintaining psychological individuality despite potentially unfavorable pressures arising during waking experiences. Another model, the ―threat simulation‖ model pinpointed the evolutionary context for explaining the realistic representation of fear in nightmares and its potential adaptive function (Revonsuo 2000). In this model, illusory feeling of reality simulating threatening events could afford the rehearsal of threat perception and avoidance in an entirely harmless situation and without any detrimental consequences (Revonsuo 2000; Valli, Revonsuo et al. 2005). Extending this evolutionary hypothesis, Franklin and Zyphur (2005) suggested that REM sleep may act as a ―virtual rehearsal mechanism‖, an important function in the early brain development, congruent with the prominent presence of REM sleep in new-born baby and infants. According to these authors, the optimization of brain development and connectivity in young organisms would benefit from adaptively experiencing rich and vivid environments during dreams. Lastly, following on psychoanalytical models, authors suggested that dreaming is a process of internal activation, arising from a person‘s affective and emotional history (Mancia 2005). We will close this introduction with a more practical note about challenges that the study of dreaming imposes to scientific enquiry. One first main constraint with dream reports is that the dreamer is the unique observer of his/her own dream experiences and is the unique reporter of the dreams. In other words, dream content is obtained introspectively through memory recall. Consequently, numerous confounding factors may influence the accuracy of dream reports including forgetting, reconstruction mechanisms, verbal description


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difficulties, and censorship. The researchers must be aware of these limitations and should minimize them by using suitable strategies (Schwartz and Maquet 2002).

Neuroimaging View in REM Sleep Physiology Since the 1990‘s, human brain imaging became a key player in the sleep field. Based on the hypothesis that dreaming mechanisms are most powerfully engaged during REM sleep, neuroimaging studies have shown that the distribution of brain activity during REM sleep is not homogeneous, thus providing important insights into the putative cerebral underpinnings of dreaming. Sustained (tonic) versus transient (phasic) activations have been highlighted in REM and non-REM sleep. The neuroimaging methods that have been most widely used include positron emission tomography (PET) and more recently functional magnetic resonance imaging (fMRI). Unlike PET, fMRI allows repeated, non-invasive and highresolution measurements of functional changes in the human brain. However, fMRI is associated with some constraints that make this method relatively complicated to use for sleep studies (e.g. total head immobilization, high noise level, effect of the magnetic field on the EEG). As we discuss below, both these imaging techniques had major impacts on our understanding of the cerebral bases of dreaming.

Distribution of Brain Activity during REM Sleep Early neuroimaging data first confirmed the sustained neuronal activity observed with EEG (Steriade and McCarley 1990; Jones 1991) by showing a high-level of cerebral energy requirements (Maquet, Dive et al. 1990) and a widespread increase of cerebral blood flow (Madsen, Holm et al. 1991; Madsen, Schmidt et al. 1991; Madsen and Vorstrup 1991) during REM sleep. As compared to wakefulness and/or non-REM sleep, REM sleep is characterized by a specific ―landscape‖ or pattern of brain activation. Regional cerebral blood flow (rCBF) increases (activations) were found in the pontine tegmentum, thalamus, basal forebrain, amygdala, hippocampus, anterior cingulate cortex, and temporo-occipital areas. Regional deactivations were found in the dorsolateral prefrontal cortex (DLPF), posterior cingulate gyrus, precuneus, and the inferior parietal cortex (Maquet, Peters et al. 1996; Braun, Balkin et al. 1997; Nofzinger, Mintun et al. 1997; Maquet 2000; Maquet 2005). Deactivations in regions that subserve important executive and attentional functions during wakefulness demonstrate that the functional neuroanatomy of REM sleep significantly differs from that observed during wakefulness. Activations in limbic and paralimbic structures, including amygdaloid complexes, hippocampal formation, and anterior cingulate cortex (ACC) during REM sleep in humans (Maquet, Peters et al. 1996; Braun, Balkin et al. 1997; Nofzinger, Mintun et al. 1997) are consistent with available animal data (e.g. Calvo, Badillo et al. 1987; Lydic, Baghdoyan et al. 1991; Calvo, Simon-Arceo et al. 1996) and suggest that memory consolidation processes, in particular emotional memories, may occur during REM sleep (Wagner, Gais et al. 2001; Hu,

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Stylos-Allan et al. 2006; Wagner, Hallschmid et al. 2006; Sterpenich, Albouy et al. 2007; Nishida, Pearsall et al. 2009; Sterpenich, Albouy et al. 2009; Walker 2009). While a large body of data support the involvement of sleep in memory (for review, see Dang-Vu, Desseilles et al. 2006), the relationship between processes related to memory consolidation and those underlying dream experience is still poorly understood (e.g. Schwartz 2003; Cipolli, Fagioli et al. 2004; Frank and Benington 2006; Wamsley and Antrobus 2009). In an important study, Braun and colleagues (1998) found that, during REM sleep, activation within the temporo-occipital regions showed some characteristic functional dissociations. Indeed, extrastriate cortex (visual association areas) activation significantly correlated with striate cortex (primary visual cortex) deactivation during REM sleep, whereas their activities are usually found to positively correlate during wakefulness (Braun, Balkin et al. 1997). For these authors, opposite interactions between low- and high-level visual areas during REM sleep might indicate that internal visual information is processed within a closed system (extrastriate areas and paralimbic projections, among others) dissociated from interactions with the environment (via striate cortex and prefrontal cortex, both deactivated during REM sleep) (Braun, Balkin et al. 1998). These early PET results are also consistent with the observation that patients with cortical blindness (after primary visual cortex or perichiasmatic lesions) report that they still dream with visual images (Solms 1997). Yet, some recent fMRI studies suggest that rapid eye movements during REM sleep might be associated with increased BOLD response in V1 (Hong, Harris et al. 2009; Miyauchi, Misaki et al. 2009). On the other hand, because several studies found that auditory stimuli may be processed to some extend during sleep (Perrin, Garcia-Larrea et al. 1999; Portas, Krakow et al. 2000; Atienza, Cantero et al. 2001; Czisch, Wetter et al. 2002; Wehrle, Kaufmann et al. 2007), we would predict that external auditory stimulation during sleep may effectively synchronize the activation of the primary and associative auditory cortices. Some regions are hypoactive during REM sleep when compared to wakefulness, in particular portions of the parietal and DLPF cortices (the temporo-parietal junction, the inferior parietal lobule, and the inferior and middle frontal gyri of the DLPF) (Maquet, Peters et al. 1996; Braun, Balkin et al. 1997). Conversely, activity in the superior parietal lobe and in the superior and medial prefrontal cortices is not different from that during waking. Interestingly, transcranial magnetic stimulation data evidenced a reduction of cerebral functional connectivity during non-REM sleep as well as a drastic reduction of interhemispheric connectivity after awakenings from REM sleep (Bertini, De Gennaro et al. 2004; Massimini, Ferrarelli et al. 2005). These findings suggest that REM (and non-REM) sleep is characterized by a specific landscape of activation, with regional increases and decreases of brain activity, associated with a disruption of effective connectivity. As we discuss in more detail below, such functional peculiarities during REM sleep may also underlie some distinctive features in dream experiences.

Transient Activations during REM Sleep In animals (Marini, Gritti et al. 1992; Datta 1995) as well as in humans (Maquet, Peters et al. 1996; Braun, Balkin et al. 1997), REM sleep is believed to be generated by cholinergic


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processes arising from brainstem structures (pedunculopontine tegmentum and laterodorsal tegmentum) that mediate some widespread cortical activation via a ventral pathway innervating the basal forebrain and a dorsal pathway innervating the thalamus (Steriade and McCarley 2005). In animals, rapid eye movements during REM sleep co-occur with ―pontogeniculo-occipital‖ (PGO) waves. These PGO waves are observed in many regions of the animal brain, but are most easily recorded in the pons, the lateral geniculate bodies of the thalamus and the occipital cortex. PGO waves are bioelectrical phasic potentials occurring during the transition from non-REM sleep to REM sleep or during REM sleep itself (Callaway, Lydic et al. 1987). Potentially important functional roles have been attributed to these waves, including the promotion of brain development and the facilitation of brain plasticity (Datta 1999). Several lines of evidence suggest the existence of PGO waves in humans: direct intracerebral recordings in epileptic patients (Salzarule, Liary et al. 1975), surface EEG (Salzarule, Liary et al. 1975), magnetoencephalography (MEG) (Inoue, Saha et al. 1999). In addition, neuroimaging studies using PET and fMRI also found correlations during REM sleep, but not during wakefulness, between spontaneous eye movements and rCBF in the occipital cortex and the lateral geniculate bodies of the thalamus (Peigneux, Laureys et al. 2001; Wehrle, Czisch et al. 2005). This was confirmed in a recent event-related fMRI study (Miyauchi, Misaki et al. 2009). In sum, these brain imaging data in humans are congruent with early studies in animals showing that REM sleep is generated by cholinergic processes arising from the pons and projecting to the cortex via the thalamus and the basal forebrain. On the other hand, human studies suggest that the amygdala and more largely, the limbic/paralimbic system might orchestrate cortical activity underpinning the processing of internally-generated cortical information within functionally segregated areas. The ensuing network may be shaped by transient activation from PGO-like waves and could thus underlie important functions such as brain plasticity and memory. Because they produce widespread subcortical and cortical activities, such phasic neural events may trigger mental activities during sleep (e.g. dreams).

Integration of Brain Mapping with Dreaming Data While the equation ―REM sleep = dreaming‖ effectively reduces the characterization of the neural correlates of dreaming to a comparison between REM sleep and waking or NREM sleep, it is important to keep in mind that neither dreaming nor REM sleep are stable, homogeneous and unique states. Indeed, dreaming might best be described along a continuum, from thought-like mentations typical of early NREM sleep to florid and vivid dreamlike experiences typical during REM sleep (Cavallero, Cicogna et al. 1992; Stickgold, Malia et al. 2001). In addition, some studies suggested the presence of a shift toward more dreamlike hallucinations and fewer directed thoughts both by REM and by time spent in sleep (Fosse, Stickgold et al. 2001; Stickgold, Malia et al. 2001; Fosse, Stickgold et al. 2004; Nielsen 2004). These findings suggest that REM sleep is not a necessary but a facilitating condition for dreaming to occur.

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We have previously proposed that the specific distribution of sustained brain activity during REM sleep may relate to specific dream features and that, reciprocally, specific dream features provide important information about specific brain activities during sleep (Schwartz and Maquet 2002). Below, we show how sensory, cognitive and emotional experiences in the dreams are consistent with the global patterns of brain activity during REM sleep. Dream reports contain a variety of sensations across different modalities. The most prevalent sensory modality is vision (nearly 100 percent of the dream contain at least one visual element) and audition (40 to 60 percent), while movements and tactile sensations (15 to 30 percent) or smell and taste (less than 1 percent) are less frequent (Calkins 1893; Strauch, Meier et al. 1996). Activation in visual occipital and auditory temporal cortices during REM sleep might thus provide a neural substrate for visual and auditory elements in dreams (Braun, Balkin et al. 1997; Hong, Harris et al. 2009). Congruently, patients with extrastriate occipito-temporal lesions report cessation of visual dream imagery (Solms 1997). When compared to real-life spectrum of emotions, emotional content in dream reports tend to be predominantly negatively-loaded with a high proportion of fear- or anxiety-related emotions (Valli and Revonsuo 2009). During wakefulness, the amygdala is known to respond to threatening stimuli, stressful situations, or novelty. Its high activity during REM sleep could reflect the intensity of emotions in dreams (Maquet, Peters et al. 1996; Maquet and Phillips 1998). Very strong negative emotions in dreams may be associated with nightmares. Several theories suggested that dreaming may be beneficial for the regulation of emotional states (for a comprehensive review see Nielsen and Levin 2007). Hartmann proposed that a central function of dreams, in particular nightmares, might be the regulation of emotions through contextualizing, or finding a picture context for, an individual‘s emotional concern (Hartmann 1996). Contextualizing creates new associations to the emotion, the result of which would be emotionally adaptive. Another ―mood regulatory theory‖ of dreaming was proposed by Kramer. Based on the observation that limbic activity and affective arousal (e.g. heart and respiratory rates) increase during REM sleep, the model suggests that dreaming would allow to progressively suppress these emotional surges across successive REM periods. This would be achieved by decreasing the intensity and variability of the associated emotion thanks to a problem-solving dream structure that unfolds across the night and enables a form of emotional problem solving that would ultimately ameliorate mood (Kramer 1991; Kramer 1993). In general, the notion that intervening dream activity regulates mood is supported by evidence that dreams are influenced by immediate pre-sleep emotional experiences (Piccione, Thomas et al. 1976; Kramer 1993; Nielsen, Kuiken et al. 2004) and that some contents or emotions in the dreams may affect subsequent waking state mood (Kramer 1982). Combining an evolutionary perspective of the function of dreaming with the empirical evidence concerning the frequency of negatively loaded dreams (e.g. nightmares and post-traumatic dreams), Revonsuo and colleagues recently suggested that dreaming might serve to simulate responses to threatening events in a totally secure environment. Such active rehearsal would enhance threat-avoidance skills that would ultimately help the dreamer to respond in an adapted and efficient way to dangerous real-life events (Revonsuo 2000; Valli and Revonsuo 2009). More recently, Nielsen and colleagues have described an ―affective network dysfunction‖ (AND) model that integrates most of the elements from the prior models above to explain the putative function of nightmares (Levin


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and Nielsen 2007; Nielsen and Levin 2007). In short, the AND states that nightmares result from a ―dysfunction in a network of affective processes that, during normal dreaming, serves the adaptive function of fear memory extinction‖ (Nielsen and Levin 2007, p. 300). The model stipulates that dreaming may promote the consolidation of fear extinction memories by (1) activating features of fearful memories (largely independently from their episodic, realworld contexts); (2) reorganizing these features by creating novel simulated contexts in which the conditioned stimuli are presented without their pairing with the unpleasant unconditioned stimulus, but rather in non-fearful, contexts; and (3) allowing the experience of these modified emotional reactions to such recombined dream features that would foster the extinction of conditioned responses. By identifying an affective network (i.e. hippocampus, amygdala, anterior cingulate, medial prefrontal cortex) whose dysfunction might account for different types of dysphoric dreaming—from occasional bad dreams to non-traumatic nightmares to replicative post-traumatic nightmares, the AND is a sophisticated model that integrates both cognitive and neural explanatory levels. Cognitive features of dreams are characterized by bizarreness, discontinuity and incongruity of dream content, uncritical acceptance of bizarreness, alteration in spatiotemporal perception, the delusional belief of being awake during dreams, the lack of control of the dreaming scenario, and the lack of distinction between first- and third-person perspectives (Hobson, Stickgold et al. 1998; Maquet, Ruby et al. 2005). Regional deactivation of the prefrontal and parietal cortex might account for a large portion of these cognitive characteristics (Maquet, Ruby et al. 2005). Indeed, the PFC is functionally divided into distinct subregions, each of them underpinning the monitoring of precise cognitive processes during wakefulness (Miller, Freedman et al. 2002). For instance, the DLPFC is involved in the selection of stimulus-response associations according to contextual signals, past events, and internal goals. The deactivation of this area during REM sleep is congruent with the apparent lack of control of dreaming scenarios and the uncritical acceptance of bizarreness and incongruity. In addition, the DLPF and the inferior parietal lobule, both deactivated during REM sleep, take part in the ventral attentional network (Corbetta and Shulman 2002). During wakefulness, this network is involved in a bottom-up attentional control aiming at reorienting the focus of attention toward an unexpected incoming salient stimulus, most often behaviorally relevant. REM sleep is characterized by a decrease of the noradrenergic tone in the locus coeruleus (LC). Since this structure sends important projections to the inferior parietal cortex (Morrison and Foote 1986) and is involved in selective attention to salient unexpected stimuli (Aston-Jones, Rajkowski et al. 2000), a relative quiescence of the ventral attentional network is congruent with the fact that external stimuli delivered during REM sleep are either ignored or automatically incorporated into the dream narrative, instead of interrupting the flow of the dream storyline (Foulkes 1966; Burton, Harsh et al. 1988). Paraphrasing Freud‘s suggestion (Freud 1955), we could suggest that dream is the guardian of REM sleep. The lateral and inferior PFC is involved in the retrieval of episodic memory during wakefulness (i.e. the ability to recollect personally experienced events anchored within a particular spatio-temporal context) (Cabeza and Nyberg 2000). The hypoactivity of these areas during REM sleep is congruent with the fact that only a very small percentage of dream reports that contain residues of previous waking activity could be considered as representing

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the exact replay of full memory episodes (Fosse, Fosse et al. 2003; Schwartz 2003). Taken together it seems that isolated episodic elements are reactivated during sleep (most likely via the activation of the hippocampus, limbic structures, and posterior cortical areas), but these elements do not form replicates of real life episodes (because of the deactivation of the DLPFC among other possible causes). The dreamers often attribute thoughts, emotions, and intentions to the characters who appear in their dreams (Kahn and Hobson 2005). Neuroimaging studies of ―theory of mind‖ tasks (i.e. the ability to attribute intentions, thoughts, and feelings to oneself and to others) during wakefulness suggest the role of the medial prefrontal cortex (mPFC) in such highlevel mental activity (Frith and Frith 2003; Gallagher and Frith 2003; Harris, Todorov et al. 2005). The mPFC has been shown to stay as active during REM sleep as during wakefulness (Maquet, Peters et al. 1996) and could therefore contribute to the persistence of the ability to represent others‘ mind during REM sleep dreaming. Contrasting with preserved activity in mPFC, activity in inferior parietal regions (including the temporo-parietal junction, see above) decreases during REM sleep. Because these regions are believed to contribute to a unified representation of the self and of selfversus others- perspective (Farrer, Franck et al. 2003; Ruby and Decety 2004), deactivation in these regions would be consistent with dream reports showing that the self can participate to the dream scenario both in a first-person (the self sees and acts) and in a third-person perspective (the dreamer sees the self acting in the dream) without any distinction (Maquet, Ruby et al. 2005).

Dream, REM Sleep and Psychiatric Illnesses Because several psychiatric illnesses may involve sensory, emotional and cognitive abnormalities, it has been suggested that psychiatric disorders may share some common underlying mechanisms with dreaming (in healthy subjects) and REM sleep features. For instance, some authors proposed that the dreaming would provide a valid model for psychosis because both ―conditions‖ share many bizarre features (Scarone, Manzone et al. 2008). Others have even proposed that REM sleep could be a potential endophenotype (Gottesmann and Gottesman 2007). Endophenotypes represent measurable component invisible to the naked eye along the pathway between a disease and the genotype. This is thus a kind of intermediate phenotype between the phenotype and the genotype that can be either neurophysiological, biochemical, endocrinological, neuroanatomical, cognitive or neuropsychological (Gottesman and Gould 2003) and that can help identify the genes responsible for a particular mental illness. For instance, the specific absence of REM sleep rebound after REM sleep deprivation in schizophrenic patients might be an endophenotype (Zarcone, Azumi et al. 1975). Interestingly, a recent study suggests that dream content characteristics in schizophrenia may reflect neurocognitive processes specific to this condition (Lusignan, Zadra et al. 2009). Thus quantitative study of dream reports in schizophrenic patients may represent an alternative to discover an endophenotype subtending impairments of emotional processing in this condition.


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Similarly, REM sleep has been considered as an endophenotype in major depression (Modell and Lauer 2007). For instance, in this later illness, the increased activity in the amygdala during REM sleep (Nofzinger, Nichols et al. 1999) might be congruent with the increased pressure of REM sleep (Adrien 2002) observed since the activity within this structure has been linked to an augmentation of REM sleep in animals (Calvo, Badillo et al. 1987). Compared to NREM sleep, REM sleep was shown to increase cognitive distortions and in particular negative self-appraisals in patients suffering from anxious depression (McNamara, Auerbach et al. 2009), supporting the REM sleep deprivation therapy in these patients. Alternatively, through successive REM periods, depressed subjects showed a decrease of negative and an increase of positive affect in dreams suggesting that dreaming may actively moderate mood overnight in these subjects (Cartwright, Luten et al. 1998). Refining these observations, the same group showed that depressed subjects who increased REM sleep pressure through repetitive REM sleep deprivation had an antidepressant effect if they were able to construct well-organized dreams (Cartwright, Baehr et al. 2003). Overall, these studies suggest that during REM sleep an interaction between cognition and emotion regulates neuronal networks involved in emotional processing and mood disorders.

Conclusions In this review, we have shown that the conception of dreaming as intimately linked to brain activity was relatively popular among scientists in the late 19th century. It is only recently and after the discovery of REM sleep, that modern brain imaging techniques emerged as major tools to better understand the neural mechanisms of dreaming. We demonstrated that some general perceptual, cognitive, and emotional characteristics in dream reports are compatible with the pattern of regional activity during REM sleep revealed by neuroimaging studies. While early brain imaging studies (most of them using PET) could only picture mean levels of regional cerebral activity during sleep stages, a few recent neuroimaging studies, in particular functional MRI studies, showed that it is now possible to capture more transient, dynamic changes of brain activity with a high anatomical resolution. Future studies using these advanced imaging methods will further improve our knowledge of brain functions during sleep, and will undoubtedly redefine and tighten the links between brain processes and the varieties of dream experiences.

Acknowledgments M.D., P.M, L.M., L.M., A.F. and T.T.D.-V are supported by the Fonds National de la Recherche Scientifique (FNRS - Belgium). S.S. is supported by the Swiss National Science Foundation. M.S. was supported by the Austrian Science Fonds (FWF). Additional support was provided by the University of Liège, the Queen Elisabeth Medical Foundation and the Fonds Léon Frédéricq, the Horlait-Dapsens Foundation and a BCNBP-Lundbeck grant (Belgian College of Neuropsychopharmacology and Biological Psychiatry).

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Index # 5-hydroxytryptophan, 304

A abdomen, 121 abnormalities, 44, 50, 73, 145, 146, 260, 263, 317, 318, 324, 325 absorption, 279, 307, 312 academics, 232 accidents, 71, 72, 123, 134 acclimatization, 110 accuracy, 77, 83, 84 acetylcholine, 49, 278 acid, 74, 140, 148, 158, 206, 277, 278, 304 ACTH, 56, 206, 207, 209, 211, 213, 214, 216, 218, 220, 223, 224, 318, 327 actin, 144 activation, 3, 11, 31, 46, 54, 55, 63, 66, 73, 98, 111, 115, 121, 122, 207, 211, 225, 269, 274, 282, 286 acupuncture, xiii, 303, 309 acute, 31, 40, 49, 51, 55, 58, 60, 63, 65, 75, 113, 120, 125, 136, 137, 138, 146, 148, 150, 151, 153, 157, 208, 209, 212, 216, 240, 282, 301, 309 acute confusional state, 153 acute infection, 120 acute mountain sickness, 55, 65 adaptation, 81, 92, 93 addiction, 74 adenocarcinoma, 51 adenosine, 53, 54, 55, 56, 61 adenosine triphosphate, 53 ADHD, 80, 83, 84, 85, 86, 87, 88, 94, 95, 97, 295, 302

adipocyte, 38 adjustment, 76, 89, 134, 228, 234, 239, 240 adolescence, xiii, 96, 106, 114, 125, 220, 230, 232, 235, 242, 243, 244, 246, 250, 291 adolescents, vii, xi, 107, 108, 109, 116, 124, 125, 130, 131, 134, 227, 228, 230, 231, 233, 235, 237, 240, 241, 242, 243, 244, 245, 246, 247, 294, 295, 297, 299, 301, 302 adrenal gland, 131 adrenaline, 251, 254 ADS, 234 adult, ix, xi, 70, 81, 98, 108, 111, 123, 124, 128, 135, 137, 148, 151, 206, 208, 215, 219, 224, 228, 230, 234, 241, 242, 246, 249, 251, 268, 300, 311, 318 adult population, ix, 70, 108, 135, 137, 151, 318 adulthood, 106, 146, 230, 235, 242, 243, 292 adults, vii, xi, 73, 94, 98, 106, 107, 108, 109, 125, 129, 138, 145, 146, 149, 151, 154, 156, 159, 160, 227, 228, 229, 230, 237, 240, 241, 242, 244, 245, 268, 293, 299, 306, 308, 309, 310, 325, 334, 335 adverse event, 144 aetiology, 42, 50 affective disorder, 95, 109, 117, 131, 147, 159, 240, 245 AFMK, xii, 274 afternoon, xiv, 12, 76, 105, 116, 125, 212, 329, 331 ag(e)ing, aging, ix, xi, 37, 40, 67, 94, 135, 136, 137, 138, 147, 150, 155, 205, 208, 214, 216, 217, 250, 287, 302, 335 agent, xii, 118, 141, 264, 273, 275, 282, 285, 308 agents, xiii, 41, 74, 118, 143, 144, 148, 241, 260, 263, 264, 277, 303 aggregates, 60 aggression, ix, 108, 115, 116, 135, 136, 137, 138, 139, 140, 142, 143, 144, 145, 146, 151, 155, 156, 157, 241

376

Index

aggressive behavior, x, 111, 135, 136, 137, 138, 141, 151 aggressiveness, 111, 120 aging process, 147 agonist, 74, 118, 212, 277, 279, 280, 283, 286, 287, 288 aid, 141, 242, 310 AIDS, 146, 154 akathisia, 136, 149 akinesia, 51 alanine, 261 alanine aminotransferase, 261 albumin, 261 alcohol, 17, 55, 71, 73, 76, 140, 233, 244 alcohol dependence, 233 alcohol withdrawal, 140 alcoholics, 111, 113 alcoholism, 146 alertness, xiii, 2, 10, 27, 29, 49, 56, 109, 115, 116, 124, 139, 286, 291, 294 algae, 115 algorithm, 95 allele, 42 allocortical, 58 alpha, viii, 2, 4, 9, 10, 17, 18, 21, 22, 23, 24, 27, 28, 29, 46, 47, 48, 64, 73, 84, 85, 86, 87, 88, 95, 96, 97, 99, 209, 251, 260, 268, 270, 292 alpha activity, 85, 209 ALS, 284, 289 ALT, 261 altered state, 40, 56 alternative, ix, 92, 103, 115, 121, 143, 154 alternative behaviors, 143 alternatives, 75, 148, 149, 288 alters, 226, 300 Alzheimer disease, 37, 40, 47, 48, 67, 156, 158 American Psychiatric Association, 71, 93, 140, 153, 228, 229, 243, 325 American Psychological Association, 76 amines, 280 amino, 271, 304 amino acid, 271, 304 amino acids, 271 aminoglycosides, 140 amphetamines, 140 amplitude, ix, xiv, 79, 89, 90, 91, 103, 113, 115, 130, 208, 260, 292, 293, 329, 333 amygdala, 41, 52, 66 amyloid, 44 amyloid plaques, 44

amyotrophic lateral sclerosis, 289 anabolism, 212 anaesthesia, 308, 311, 313 analgesia, 307, 312 analgesic, 306, 307, 311 analog, xii, 219, 224, 273, 276, 280, 286 anatomy, 63, 152 anemia, 120 anesthetics, 306, 308, 310 Angelman Syndrome, 294, 296 anger, 137, 146 angina, 239 angioplasty, 145 animal models, 216 animal studies, 210, 305 animals, 81, 111, 117, 210, 212, 213, 214, 215, 288, 308 anorexia, 298 anorexia nervosa, 298 ANOVA, 19, 21 ANP, 251, 253, 257, 261, 264, 265 antagonism, 211, 213, 214, 217, 218 antagonist, xi, 58, 118, 205, 211, 212, 213, 216, 220, 226, 260, 276, 278, 288 antagonists, 132, 213, 241, 251, 260, 263, 264, 270 anterior pituitary, 209 antibody, 48, 50, 64, 66 anticholinergic, 139, 140, 149, 264 anticonvulsants, 143, 144 antidepressant, 118, 119, 129, 132, 148, 150, 209, 221, 288 antidepressant medication, 129, 148, 150 antidepressants, 74, 115, 118, 140, 143, 144, 145, 150, 208, 232, 278, 288 antidiuretic hormone, 251 antigen, 60 antihistamines, 74, 140 antioxidant, 110, 127, 263, 284, 289, 292 antioxidative, 287 antipsychotic drugs, 148, 155 antipsychotics, 74, 143, 144, 149, 150, 159 antisense, 210, 219 antiserum, 222 antisocial behavior, 108, 125 antispasmodics, 140 anxiety disorder, ix, xi, 71, 78, 101, 115, 116, 121, 133, 135, 138, 146, 148, 150, 159, 228, 249, 250, 316, 326, 327 APA, 76, 77 apathy, 120

Index apnea, 42, 259 apoptosis, 43, 59 apoptotic effect, 287 appetite, 145, 236, 239, 317 application, 144, 284, 288, 307, 309, 334 appraisals, 77 arginine, 55, 225, 251, 253, 254, 255, 256, 257, 258, 261, 262, 269 argument, 26 aripiprazole, 144, 148, 149 arousal, vii, viii, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 14, 15, 18, 19, 20, 21, 25, 26, 27, 28, 29, 30, 32, 34, 48, 49, 57, 62, 73, 76, 79, 84, 112, 210, 263, 318, 324 arrhythmias, 148 artery, 40, 54, 138 arthritis, 39 aspartate, 49, 50, 261 asphyxia, 330 assessment, viii, 1, 3, 25, 31, 44, 83, 97, 98, 130, 137, 151, 228, 233, 235, 240, 244 assumptions, 19, 292 asthma, 301 astrocytes, 41, 45, 47 asymmetry, 87, 99 ataxia, 42, 74 Athens, 15, 34, 303 atoms, 282 ATP, 53, 260, 270 atrial natriuretic peptide, 251, 261, 269, 270 atrophy, 38, 41, 42, 43, 44, 45, 47, 51, 67, 331, 333 atropine, 140 attacks, 123, 233, 240 attention problems, 108 attentional bias, 5, 6, 31 attitudes, 7, 32 auditory hallucinations, 147 autism, 299, 334 autistic spectrum disorders, 299 autoantibodies, 50 autogenic training, 6, 32, 78 autoimmune, 51, 139 autoimmunity, 50, 66 automaticity, 6 automation, 64 autonomic activity, 76 autonomic nervous system, 109, 115, 116, 121, 122, 126 autopsy, 44, 55, 65, 240, 246 autosomal dominant, 42, 54

377

availability, ix, 54, 111, 135, 137, 148, 292 averaging, 74, 139 avoidance, ix, 103, 115, 116, 232, 287 awareness, 5, 151 axonal, 37, 40

B babies, 104 back, 80, 81, 115, 116, 239 bacteria, 39 bacterium, 110 barbiturates, 140 barriers, 97 basal forebrain, 46, 49, 63 basal ganglia, 42, 44, 54, 55, 61, 128 basic research, 31, 78, 206 Beck Depression Inventory (BDI), 15, 34, 92, 94 behavior therapy, 99 behavioral disorders, 297 behavioral effects, 157 behavioral problems, 108, 139 behavioural disorders, 101 behaviours, 152, 228, 316 Belgium, 1, 69 beliefs, 5, 7, 32, 77 beneficial effect, 7, 74, 217, 305 benefits, 7, 8, 81, 93, 111, 129, 144, 242 benign, 51, 250, 260, 263, 264, 268, 269, 270, 271 benign prostatic hyperplasia, 269, 271 benign prostatic hypertrophy, 268 benzodiazepine, xiii, 74, 144, 158, 270, 291 benzodiazepines, 8, 74, 117, 139, 140, 144, 150, 216, 274, 304 beta blocker, 150 beta blockers, 140, 313 beverages, 17 bias, 5, 6, 31 bile, 288 bilirubin, 261 binding, xii, 50, 210, 219, 273, 277, 278, 280, 282, 286, 287, 297, 304 bioactive compounds, 279 bioavailability, 277, 279, 283, 284, 307, 310, 312, 314 biochemistry, xii, 250, 254, 261 biofeedback, viii, 70, 77, 78, 79, 93, 96, 98, 100 biological rhythms, ix, 103, 109, 115, 116, 308 biopsychology, 30 biosynthesis, 53

378

Index

bipolar, 17, 90, 146, 147, 148, 149, 151, 158, 159, 233, 236, 293, 295, 301 bipolar disorder, 146, 147, 148, 149, 151, 158, 159, 233, 236, 295, 301 birth, 104, 124, 129 BIS, xiii, 303, 306 bladder, xi, 249, 250, 257, 259, 260, 261, 263, 264, 267, 268, 269, 270, 271 bladder outlet obstruction, 259, 260, 263, 267, 270, 271 blood, 50, 52, 58, 77, 87, 88, 116, 121, 131, 149, 251, 254, 255, 257, 258, 261, 271, 279, 281, 282, 283, 299, 307, 308, 310, 313 blood flow, 257, 258 blood plasma, 281 blood pressure, 77, 121, 251, 254, 255, 257 blood sampling, 308 blood urea, 261 blood urea nitrogen, 261 blood vessels, 52 body composition, 252, 256, 258, 269, 270 body mass, 252, 258 body mass index (BMI), 17, 252, 255, 258 body temperature, 4, 14, 30, 31, 109, 111, 113, 116, 127, 128, 130, 288, 292 body weight, 106, 107, 252, 255, 294, 296, 307 BOLD, 57, 87, 88 borderline, 239, 275 bowel, 39 boys, 105, 107, 108, 233, 239 brain abnormalities, 145 brain activity, 12, 73, 77, 83 brain damage, xiv, 329, 330, 335 brain functions, 116 brain imagery, 55 brain injury, 37, 40, 50, 61, 208, 220, 297 brain natriuretic peptide (BNP), 251, 261, 264 brain stem, 39, 43, 44, 46, 47, 48, 49, 50, 52, 53, 56, 57, 60, 63, 64, 136, 331, 333 brainstem nuclei, 64 breathing, 49, 115, 121, 270 broad spectrum, 289 brothers, 42, 61 Brussels, 16, 17, 19 bulbar, 46, 47, 48, 49 bullying, 239 burn, 53 burning, 327 burnout, 112, 113, 116, 117, 129 burnout scores, 129

bypass, 138

C Ca2+, 219, 287 caffeine, 13, 17, 76, 310, 314 calcium, 275, 310, 313, 314 calcium channel blocker, 310, 313 calmodulin, xii, 274, 277, 283, 287 calreticulin, xii, 274, 277 cAMP, 274 cancer, 5, 31, 50, 51, 59, 71, 97, 133, 138, 153, 260, 264, 309 cancer treatment, 133 candidates, 15, 114, 150 CAP, 73 car accidents, 70 carbohydrate, 45 carboxyl, 280 carcinogenicity, 282 carcinoma, 59, 60, 313 cardiac arrhythmia, 148 cardiac involvement, 62 cardiovascular disease, xi, 129, 249, 250, 260, 264 cardiovascular system, 150 caregiver, 136, 137, 139, 143, 156 caregivers, x, 135, 137, 138, 141, 151, 156 case study, 65, 212 catatonia, 149 catecholamine, xii, 206, 249, 257, 260, 292 catecholamines, 257, 260 catharsis, 238 catheter, 309 cation, 289 cats, viii, 53, 70, 81, 87, 133, 214 cell, 36, 38, 47, 51, 53, 60, 66, 287 cell body, 47 cell transplantation, 66 Census Bureau, 136, 152 central nervous system, 38, 59, 62, 73, 210, 279, 286, 297, 298, 309 cerebellar ataxia, 42 cerebellum, 42, 43, 44, 50, 52, 57 cerebral blood flow, 58 cerebral cortex, 9, 43, 45, 61, 306, 333 cerebral palsy, xiv, 329, 330 cerebrospinal fluid, 37, 118, 132 cerebrovascular disease, 145 cerebrum, 42 c-fos, 53, 59, 65

Index channels, 18, 62, 74, 89 chemical composition, 41 chest, 89, 146 chewing, 111, 115, 119, 121, 133 childbirth, 250 childhood, xiii, 106, 112, 118, 129, 239, 246, 291, 294, 297, 298, 301 Chinese medicine, 119, 121, 133 Chi-square, 320 chloride, 74 chlorine, 280 chlorpromazine, 140, 154 cholecystectomy, 304 cholesterol, 106 cholinesterase, 144, 261 cholinesterase inhibitors, 144 chorea, 36, 38, 49, 50, 51, 59 chromosome, 212 chromosomes, 304 chronic disorders, xiii, 291 chronic fatigue syndrome, 112, 113, 116, 117, 118, 119, 120, 121, 129, 130, 131, 132, 133 chronic pain, 78 chronobiology, 301 chronotherapy, 115, 119 cingulated, 54, 55, 57 circadian amplitude, 130, 278 circadian clock, 109, 115, 116, 117, 118, 119, 122, 123, 126, 130, 134, 285 circadian cycles, 115 circadian oscillator, 127, 130, 274 circadian rhythm, 4, 36, 37, 38, 39, 59, 65, 72, 104, 109, 110, 112, 113, 114, 115, 117, 119, 125, 126, 130, 131, 209, 212, 218, 225, 244, 270, 274, 278, 283, 292, 298, 300, 304, 309, 310, 313, 318, 333, 334 circadian rhythm sleep disorders, 117 circadian rhythmicity, 39, 225 circadian rhythms, 36, 38, 59, 65, 109, 110, 112, 115, 125, 126, 130, 218, 244, 270, 278, 283, 292, 304 circadian timing, 130 circulation, xii, 59, 273, 274, 278, 279, 280, 304, 307, 310 cirrhosis, 307 cis, 63 citalopram, 150, 157, 159 classes, 41, 74, 143, 144 classification, 37, 44, 59, 60, 71, 93, 99, 101, 125, 229, 250, 268

379

cleavage, 279 clinical approach, 104 clinical depression, 119 clinical disorders, 78, 81 clinical presentation, 40, 141 clinical symptoms, 92, 235, 240 clinical trial, 95, 117, 133, 151, 157, 159, 209, 286, 309, 334 clinical trials, 133, 157, 159, 334 clinically significant, 70, 235, 319 clinician, 147, 242, 243 clinics, 150, 270 clonidine, 140, 310, 312 clusters, 51, 73, 216 CMAI, 136 CNS, 73, 75, 132, 207, 288, 327 Cochrane, 133, 156, 159 coding, 93 codon, 42, 43, 44, 63 cognition, 5, 59, 137, 138, 142, 148, 150, 155, 224, 302 cognitive activity, 4, 11, 31 cognitive alterations, 8 cognitive behavioral therapy, viii, 69, 79, 151 cognitive deficit, 143, 147 cognitive deficits, 143, 147 cognitive dimension, 295 cognitive disorders, 138 cognitive dysfunction, 112 cognitive function, 61, 125, 143, 334 cognitive impairment, 74, 137, 139, 142, 145, 146, 150 cognitive performance, 85, 86, 96, 100, 128 cognitive process, 6, 73 cognitive processing, 73 cognitive system, 3 cognitive therapy, 7, 77 coherence, 79 cohort, 112, 124, 129, 230 collaboration, 310 college students, 108, 126 colon, 309 coma, 50, 55 combined effect, 32 communication, 94, 96, 141, 330 communication skills, 330 community, 123, 125, 136, 142, 152, 153, 154, 155, 158, 251, 325, 335 comorbidity, xiv, 230, 244, 246, 316, 317, 320, 325, 326

380

Index

compatibility, 92 competence, 240 complete blood count, 261 components, vii, viii, xi, 1, 2, 3, 6, 7, 8, 11, 13, 21, 25, 28, 29, 64, 75, 80, 95, 113, 145, 205, 212, 234, 319 composition, 41, 136, 223, 252, 255, 258 compounds, xii, 95, 145, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 289 compulsive personality disorder, 327 computer use, 231 concentration, 72, 106, 139, 222, 278, 282, 292, 293, 295, 308 concordance, 239, 319 concrete, 114 conditioned response, 7, 13, 15, 82 conditioned stimulus, 82 conditioning, viii, 7, 69, 78, 79, 81, 82, 83, 85, 88, 89, 91, 93, 96, 100, 101 conduct disorder, 108 conductance, 6 conflict, 113 confounding variables, 236 confusion, 114, 150, 310 congestive heart failure, 257 conjugation, 150 connectivity, 65 consciousness, 40, 56, 138, 139 consensus, 130, 131, 159, 227 consent, 16, 232, 264, 318 consolidation, 88, 91, 99, 270 constant rate, 312 constrictive pericarditis, 269 consumption, 17, 270, 312 continuity, 76, 207, 209, 215, 243, 317 contracts, 229 control group, viii, ix, xi, xiii, 2, 6, 16, 19, 20, 21, 26, 28, 29, 55, 70, 78, 79, 83, 84, 88, 89, 90, 91, 92, 117, 249, 251, 254, 255, 256, 257, 258, 259, 303, 307 controlled studies, 77, 150, 298 controlled trials, 119, 159 contusion, 37 conversion, 44 coping strategies, 2, 126 corona, 37 coronary artery bypass graft, 138 coronary heart disease, 267 corpus callosum, 51

correlation, 4, 5, 10, 25, 27, 28, 29, 61, 84, 87, 118, 215, 250, 262, 267, 293 correlational analysis, 19, 25 correlations, 15, 25, 28, 36, 38, 56, 57, 207, 254 cortex, viii, 40, 41, 45, 46, 48, 49, 51, 52, 53, 54, 55, 56, 57, 65, 69, 81, 82, 101, 128, 213 corticobasal degeneration, 63 corticosteroids, 50, 116, 140 corticosterone, 109, 116, 209, 210, 225 corticotropin, xi, 205, 206, 207, 217, 219, 220, 221, 222, 223, 224, 225 cortisol, viii, xi, 1, 4, 11, 13, 18, 19, 21, 25, 27, 28, 29, 31, 38, 39, 115, 125, 127, 129, 205, 206, 207, 208, 209, 211, 212, 214, 216, 217, 218, 219, 220, 221, 223, 224, 225, 292, 298, 301, 302, 327, 331, 333 costs, 141, 143 coupling, 113, 114 cranial nerve, 51 creatinine, 110, 256, 261 Creutzfeldt-Jakob disease, 36, 41, 42, 44, 58, 60, 61, 62, 63, 66 CRH, xi, 205, 206, 209, 210, 211, 212, 213, 214, 216, 217, 223 critical analysis, 297 cross-sectional study, 268 cross-talk, 282 crying, 146, 232 CSF, 39, 44, 50 CST, 88 cues, 3, 6, 9, 15, 109, 113, 122, 134 cultivation, 121 curettage, 308 curing, 70 curriculum, 236 cycles, vii, 9, 18, 19, 25, 53, 55, 81, 111, 115, 136, 209, 215 cycling, 279 cyst, 37 cystitis, 260, 264 cysts, 37, 66 cytochrome, 280 cytometry, 45

D daily living, 125, 142 danger, 3, 137, 149 death, 38, 42, 51, 144, 157, 228, 232, 239, 240 debt, 125, 224

Index declarative memory, viii, 69, 88, 89, 99, 131 defecation, 109 defense, 285, 287 defense mechanisms, 287 deficiency, 10, 105, 106, 213, 214, 224, 326 deficit, 54, 78, 80, 84, 88, 95, 97, 100, 115, 239, 301, 302 deficits, 106, 116, 142, 143, 147, 213, 334 definition, vii, 18, 229, 319 degenerate, 45 dehydrogenase, 261 delirium, ix, 36, 135, 137, 138, 139, 140, 141, 153, 154, 334 delirium tremens, 36 delta wave, 40, 43, 52 delusions, 139, 143, 146, 147 dementia, 38, 44, 48, 63, 128, 135, 136, 137, 139, 142, 143, 144, 146, 147, 148, 151, 152, 153, 155, 156, 157, 158, 159, 329, 330, 334, 335, 336 demographic characteristics, 233 demographic data, 319 demography, 158 demyelination, 51 dendrites, 47 density, 38, 40, 57, 207, 211, 212, 215, 219, 274, 285 depolarization, 10, 27 deposition, 65, 67 deposits, 37, 42, 43, 44, 64 depressed, 146, 147, 148, 156, 159, 207, 208, 209, 210, 211, 216, 217, 218, 220, 221, 223, 225, 234, 235, 239, 240, 244, 278, 288, 298, 302, 317 depressive disorder, xiv, 70, 115, 116, 147, 159, 228, 234, 244, 245, 246, 316, 320, 324, 325, 326 depressive symptomatology, 240 depressive symptoms, 145, 233, 234, 235, 236, 237, 238, 240, 246, 317, 325 deprivation, 4, 7, 12, 14, 34, 36, 53, 59, 65, 77, 89, 107, 113, 209, 211, 213, 214, 216, 219, 220, 222, 223, 224, 225, 226, 230, 240, 309 derivatives, 277, 280 desipramine, 301, 310 destruction, 136 desynchronization, 104, 109, 110, 111, 113, 114, 126, 128 detection, 44, 61, 308, 309 detoxification, 287 developed countries, ix, 135, 136 developmental disabilities, 299 developmental disorder, 334, 335

381

deviation, 280 diabetes, xi, 37, 38, 51, 125, 148, 150, 249, 250, 260, 264 diabetes insipidus, 37 diabetes mellitus, xi, 249, 250, 260, 264 Diagnostic and Statistical Manual of Mental Disorders, 93, 153, 229, 243 diagnostic criteria, 30, 71, 95, 155, 229, 316 dialysis, 269 diarrhea, 39 diastolic blood pressure, 255 diet, 122, 148 differentiation, 3, 147 diffusion, 42, 52, 61 diffusion tensor imaging, 61 digitalis, 140 dignity, 137 dilatation and curettage, 308 diplopia, 51 direct observation, 319 disabilities, xiv, 300, 329, 330, 334, 335 disability, 145, 229, 246, 335 disabled, 301 discomfort, 55, 71, 155, 307, 316 discordance, 244 discriminant analysis, 33 discrimination, 276 disease progression, 284 diseases, xi, xiii, 36, 41, 49, 55, 208, 249, 270, 282, 291, 293, 296 disease-specific, 60 disinhibition, 136 distillation, 242 distortions, 28, 29 distress, xiv, 5, 70, 92, 143, 156, 230, 236, 241, 243, 315, 316, 319 distribution, 10, 33, 44, 55, 99, 282, 286, 293, 307, 317, 320, 324 divergence, 136 diversity, 64 division, 57, 233 dizziness, 74, 146, 296 DNA, 110 dominance, 16, 29, 111, 128 doors, 330 dopamine, 47, 49, 53, 55, 64, 122, 136, 149, 251, 254, 257, 261, 278, 293 dopamine agonist, 49 dopaminergic neurons, 47, 62 dorsal horn, 58

Index

382

dorsomedial nucleus, 109 dosage, 148, 211, 275, 279, 295, 297, 298, 334 dosing, 149, 268, 296 double-blind trial, 153, 159 dream, 49, 61, 236 drinking, 244 Drosophila, 104, 115 drowsiness, 76, 150 drug interaction, ix, 135, 137, 138, 141, 142, 149, 154 drug therapy, 137 drug toxicity, 154 drug treatment, 298 drug use, 154, 156 drug withdrawal, 139 drugs, 55, 74, 95, 139, 141, 145, 150, 156, 209, 274, 276, 277, 282, 284, 285, 292, 299, 304, 306, 308, 310, 331 DSM, viii, xiv, 1, 30, 34, 71, 92, 96, 100, 155, 220, 229, 238, 246, 315, 316, 317, 318, 319, 325, 327 DSM-II, 92, 100 DSM-III, 92, 100 DSM-IV, viii, xiv, 1, 30, 34, 71, 96, 220, 229, 238, 246, 315, 316, 317, 318, 319, 325, 327 dysarthria, 42, 51 dyskinesia, 149 dyslexia, 238 dysphagia, 42, 51 dysphoria, 107 dysregulation, 6, 112, 113, 116, 122, 134, 219, 235 dysthymia, 16

E eating, 109 economic status, 232, 233, 239 edema, 252, 256, 257, 258, 269 EEG activity, vii, 1, 4, 8, 9, 10, 11, 13, 25, 26, 27, 28, 29, 33, 34, 50, 81, 85, 99 EEG patterns, 10, 75 EKG, 17 elderly population, ix, 135, 136, 138, 141, 144, 149, 151 elders, 146, 149, 151, 158 elective surgery, xiii, 303, 305 electrocardiogram, 89 electrodes, 17, 19, 80, 89, 92 electroencephalogram, 206, 218 electroencephalography, 79, 88 electromyography, 77, 79, 85, 88

electron, 287 elementary school, 104, 105, 106 e-mail, 315 Emergency Department, 141 EMG, 3, 9, 11, 13, 15, 17, 18, 21, 26, 27, 77, 78, 79, 82, 85, 86, 88, 89, 96, 97, 98 emission, 66 emotion, 13, 145, 240 emotional distress, 5, 71, 112 emotional responses, 75 emotional stimuli, 14 emotions, 3, 13, 42 encephalitis, 36, 50, 51, 59, 60, 65, 66 encephalomyelitis, 112, 129 encephalopathy, 63, 66 encoding, 38, 88, 89 endocrine, 64, 107, 125, 146, 206, 208, 209, 215, 216, 217, 218, 220, 223, 224, 225, 241, 317 endocrine disorders, 146 endocrine system, 206 endocrinology, 218 endogenous depression, 224, 225 endurance, 84 energy, 53, 72, 121, 145 enlargement, 260, 263, 264, 270, 331 entorhinal cortex, 52 entropy, 306 enuresis, 270 environment, 2, 3, 7, 13, 27, 137, 140, 145, 232 environmental factors, xi, 42, 76, 249, 250, 292 environmental influences, 131 environmental stimuli, 243 enzymes, 41, 280, 287 EOG, 17, 89 epidemiologic studies, 229 epidemiology, 153 epilepsy, xiv, 78, 80, 83, 85, 86, 96, 97, 100, 299, 329, 330 epileptic seizures, 333 epitope, 45 equilibrium, 279 ERD, 98 esterase, 280 estradiol, 215, 270 estrogen, 215, 218 estrogen replacement therapy, 215 estrogens, xi, 205, 221 etiology, xi, 70, 138, 139, 249, 251, 268, 317 evening, 4, 17, 18, 19, 21, 27, 28, 31, 54, 76, 89, 107, 108, 109, 116, 117, 118, 122, 125, 127, 207,

Index 210, 221, 223, 239, 258, 263, 288, 292, 295, 306, 309 event-related brain potentials, 95 event-related potential, 97 evolution, 9, 25, 33, 51, 56 examinations, xi, 208, 249, 251 excitability, 49, 331, 334 exclusion, 16, 17, 114, 310 excretion, 115, 116, 206, 279, 286, 300, 302, 307, 309 execution, viii, 69, 81 executive function, 142 exercise, 76, 111, 119, 121, 132, 133, 271, 331, 332, 333 experimental condition, 310 exposure, ix, 6, 103, 106, 109, 110, 111, 112, 114, 115, 116, 117, 119, 121, 123, 129, 134, 154, 279, 292, 325, 333 extinction, 82 extraction, 307 extrapineal melatonin, 278 extrapolation, 250 eye, viii, 17, 19, 46, 57, 59, 70, 88, 90, 111, 206, 207, 221, 222, 224, 241 eye movement, viii, 17, 19, 46, 57, 70, 206, 207, 241 eyes, vii, 17, 19, 85, 86, 87, 89

F facial palsy, 51 failure, 236, 307 family, 42, 144, 231, 232, 234, 238, 239, 243, 322 family history, 239, 322 family income, 231 family members, 232, 243 fatal familial insomnia, 42, 52, 59, 62, 63 fatigue, xi, 39, 54, 71, 72, 97, 107, 112, 113, 115, 116, 117, 118, 119, 120, 121, 129, 130, 131, 132, 133, 208, 231, 249, 250, 294 FDA, 74, 118, 144, 149, 159 FDG, 39, 51, 63 fear, 137, 232, 236, 238, 266, 304 feedback, 48, 78, 80, 82, 85, 86, 89, 90, 95, 96, 97, 211, 214 feedback inhibition, 211, 214 feeding, 81, 109, 116, 215, 224 feelings, 6, 42, 145, 318, 324, 325 females, 208, 215, 221, 230, 235, 237, 242, 260, 261, 262, 334 femoral neck, 153

383

ferritin, 55 FES, 87, 88 fetal, 123, 212, 300 fever, 42, 238 FFT, 17, 18 fibers, 36, 37, 39, 48 fibromyalgia, 113, 116, 117, 118, 119, 121, 129, 131, 132, 133 Fisher exact test, 235 flow, 9, 58, 257, 258 fluctuations, 42, 293, 309, 310 fluid, xii, 37, 118, 132, 249, 257, 258, 263, 270 fluid balance, 258 fluoxetine, 145, 149 fluvoxamine, 301, 314 fMRI, 54, 57, 67, 84, 87, 88 focusing, viii, 6, 35, 318 follicle, 215 follicle-stimulating hormone, 215 food, 53, 81, 87, 116, 126, 224, 232, 285, 309 Food and Drug Administration (FDA), 74, 159, 276 food intake, 53 Ford, 285, 286, 298 forebrain, 35, 36, 63, 100, 221, 224 Fourier, 17, 18, 80 Fox, 156 fracture, 153 fragmentation, 25, 28, 29, 38, 81, 335 free radical, 110, 289, 304 free radical scavenger, 289, 304 frontal cortex, 54 frontal dementia, 142 frontal lobe, 42, 45, 50, 54, 64, 87 frontal lobes, 42, 45, 50 FSH, 215, 270 functional analysis, 156 functional electrical stimulation (FES), 87, 88, 99 functional magnetic resonance imaging, 84, 88 functional MRI, 59 furan, 276, 280

G GABA, 40, 45, 74, 136, 145, 216, 278, 293 GABAergic, 36, 41, 46, 62, 212, 214, 216, 219, 274 gait, 111, 119, 121 Gallup, 70, 95 games, 232 Gamma, 33, 99, 244, 325 gamma-aminobutyric acid, 74

384

Index

ganglia, 42, 44, 54, 55, 61, 128 ganglion, 36 gastrointestinal tract, 274, 279, 307 gender, xi, 10, 74, 96, 108, 216, 220, 225, 227, 228, 230, 231, 233, 235, 242, 254 gene, 38, 42, 44, 53, 55, 57, 63, 67, 115, 116, 131, 210, 212, 213, 225, 242 gene expression, 57, 116, 131 general anesthesia, 306, 308, 309, 310 generalizations, 242 generalized anxiety disorder, 16, 150, 159 generation, 82, 106, 110, 121 genes, 14, 36, 38, 116, 131 genetic control, 219 genetic disease, 42 genetics, 217 Geneva, 101 geniculohypothalamic tract, 36 geriatric, 74, 132, 146, 148, 149, 150, 152, 153, 159 gestation, 104, 300 Ghrelin, 216, 221, 224, 225 girls, 105, 107, 108, 233 gland, vii, 36, 37, 38, 304, 310 glial, 37, 45, 47, 64, 66 glial cells, 45, 47 glioma, 54 gliosis, 41, 43, 44, 45, 52, 61 globus, 55, 65, 66, 136 glucocorticoid receptor, 58, 212 glucocorticoids, 208 glucose, 51 glutamate, 49, 293 glutamatergic, 36, 46, 62 glycine, 271 gold, 7, 89, 92 gold standard, 7 gonadotropin, 110, 127, 297 government, iv G-protein, 274, 304 grades, 45, 232 grafting, 138 granule cells, 53 gravity, 310 gray matter, 43, 61 Greece, 63 grey matter, 39, 44, 46, 47, 53 groups, xi, xii, 5, 6, 10, 13, 20, 24, 25, 28, 46, 79, 81, 82, 83, 86, 141, 235, 240, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 261, 262, 264, 265, 266, 286, 294, 305, 306, 316, 317, 318

growth, xi, 205, 206, 212, 214, 217, 219, 220, 221, 222, 223, 224, 225, 226, 230, 244, 292, 301, 302, 327, 335 growth factor, 214, 222 growth hormone, xi, 205, 206, 214, 217, 219, 220, 221, 222, 223, 224, 225, 226, 244, 327 Guam, 63 guidelines, xi, 76, 228, 249, 250 guilt, 236 guilt feelings, 236 gut, 309 gyrus, 52, 54, 55, 57

H H1, 40 H2, 58 habituation, 15 half-life, xii, 150, 273, 275, 278, 280, 281, 284 hallucinations, 42, 49, 51, 60, 139, 143, 146, 147 haloperidol, 144, 148, 149, 150, 153, 154, 157 handicapped, 294, 296 harm, 228, 238, 241 head injuries, 146 headache, 54, 115, 116 health, ix, 70, 74, 76, 106, 119, 121, 122, 123, 124, 125, 128, 132, 133, 134, 135, 137, 138, 141, 231, 239, 240, 244, 246, 263, 268, 295, 301, 326 health care, ix, 70, 122, 135, 137, 143, 151 health problems, 138, 141 health status, 301 heart, 3, 4, 6, 11, 12, 30, 33, 77, 129, 257, 259, 267, 269 heart disease, 267 heart failure, 269 heart rate (HR), 3, 4, 6, 11, 12, 77 heart rate variability, 30 heat, 120 hematocrit, 261 hematuria, 260 hemiplegia, 330 hemisphere, 87 hemodialysis, 258, 269 hemodynamic, 87 hemodynamics, 269 hemoglobin, 261 hepatic encephalopathy, 139 herbal medicine, 119, 260, 263, 264 heterogeneity, 4, 28, 61 heterogeneous, 8, 145

Index high school, ix, 103, 104, 105, 106, 107, 108, 114, 116, 122, 124, 125, 233, 235, 237 hippocampus, 51, 52, 53, 65, 128, 222 histamine, 49 histidine, 222 HIV, 65 HIV infection, 65 homeostasis, 53, 55, 61, 213 homocysteine, 118, 132 homogeneity, 19 homology, 277 homozygosity, 42 hormone, vii, xi, xiii, 38, 67, 110, 127, 205, 206, 208, 211, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 244, 251, 268, 274, 278, 279, 280, 284, 286, 291, 292, 304, 306, 310, 327 hormones, vii, xi, 4, 49, 126, 205, 206, 207, 208, 209, 213, 215, 216, 218, 256, 269, 296, 309 hospital, xi, 138, 154, 227, 228, 239, 331 hospitalization, 137, 138, 145, 154 hospitalizations, 138, 145 hospitalized, 138, 148, 153, 154, 157, 158, 237 hospitals, 251 host, 237, 274, 283 hostility, 147 HPA, xi, 4, 58, 205, 206, 207, 208, 209, 213, 216 HPA axis, 4, 58 HRV, 12 human subjects, 34, 96, 220 humanitarian, ix, 135, 137 Huntington disease, 36, 38, 45, 57 hydrate, 305 hydroxyl, 281 hydroxylation, 280, 281, 282 hygiene, ix, xiii, 7, 32, 76, 103, 106, 114, 117, 119, 232, 236, 238, 242, 291 hyperactivity, 78, 80, 84, 88, 94, 95, 97, 100, 115, 116, 136, 239, 302, 330 hyperhidrosis, 51 hyperplasia, 269, 271 hypersensitive, 115 hypersomnia, 37, 39, 40, 47, 48, 49, 51, 52, 56, 57, 59, 228, 234, 235, 239, 240, 246 hypertension, xii, 42, 119, 249, 255, 257, 258, 260, 269 hypertrophy, 268 hypnagogic state, 81 hyponatremia, 51 hypophysectomized, 222 hypotension, 150

385

hypothalamic-pituitary-adrenal axis, 31, 38, 66, 225 hypothalamus, 36, 37, 38, 39, 43, 45, 49, 52, 53, 56, 59, 63, 65, 67, 109, 209, 212, 213, 216, 225, 292 hypothesis, 11, 13, 27, 47, 57, 62, 126, 128, 208, 214, 219, 241, 324 hypothyroidism, 208 hypoxia, 55 hysterectomy, 306, 307, 309, 312

I ICD, 34, 71, 101 ice, 210, 213, 214, 251 id, 38, 55, 214, 239, 295, 306, 308 identification, 61, 139, 141, 286 IGF, 222 IGF-1, 222 IgG, 51, 52 Illinois, 335 illumination, 128, 330, 331, 334, 336 illusions, 139 imagery, 38, 83, 86, 99 images, 237, 316 imagination, 81, 87 imaging, 37, 57, 61, 84, 88, 94, 139, 305, 311 immune cells, 274, 283 immune function, 283, 333 immunity, 59, 64 immunohistochemistry, 42, 43, 45, 52 immunomodulatory, 292, 296 immunoreactivity, 36, 67, 110, 127 immunotherapy, 66 impairments, 4, 5, 14, 28, 71 implementation, 143 impotence, 42 impulsive, 145 impulsiveness, 115, 116, 120 impulsivity, 94, 108, 111 in situ, 13, 53 in vivo, 210, 222 incidence, 58, 134, 138, 141, 144, 146, 231, 250 inclusion, 8, 64, 92, 310 income, 231, 233 indication, 15, 27, 298 indicators, 4, 271 indices, 268 indirect effect, 274 individual differences, 29 indole, 281 inducer, 263, 333

386

Index

induction, xiii, 121, 127, 128, 282, 283, 299, 303, 305, 306, 311 infancy, 121, 239, 243 infants, 105, 123, 124 infarction, 331, 333 infection, 40, 41, 65, 120, 139 infections, 138 infectious disease, 39 inflammatory, 117, 306 information processing, 8 informed consent, 16, 264 infusions, 209 ingestion, 295 inhalation, xiii, 303, 306, 308 inheritance, 38 inhibition, viii, 9, 14, 35, 39, 46, 69, 74, 81, 84, 94, 99, 146, 211, 214, 222, 274, 277, 287 inhibitor, 46, 113, 148, 236, 280, 292, 310 inhibitors, 46, 111, 112, 118, 144, 293, 310 inhibitory, 6, 41, 46, 57, 110, 127, 133, 277, 278, 292 initiation, 2, 27, 37, 38, 39, 73, 270, 274 injection, 212, 215, 260, 270 injections, 212, 214 injuries, 108, 297, 298 injury, iv, 37, 40, 50, 61, 66, 142, 208, 220, 297, 333 inner tension, 317, 325 innervation, 63 insight, 83, 142, 147, 285 inspiration, 259 instability, 27, 73, 111 institutionalization, 137 institutions, 136, 251 instruction, 6 instruments, 77, 319, 325 insulin, 125, 214 insulin resistance, 125 insulin-like growth factor, 214 integration, 108 intellectual disabilities, xiv, 329, 330, 334, 335 intelligence, 88, 89 intelligence quotient, 88 intensive care unit, 138, 153 interaction, xi, xiii, 22, 24, 30, 109, 141, 205, 206, 209, 214, 216, 222, 287, 291, 304, 324 interaction effect, 22, 24 interaction effects, 24 interactions, ix, 46, 94, 109, 133, 135, 137, 138, 141, 142, 148, 149, 154, 219, 225 interface, 81, 83, 87, 88, 94, 216, 240

interference, 2, 3 interferon, 140 internal clock, 113 internet, 228 interneurons, 41, 47, 53 interrelations, 11 interrelationships, 11 interval, 73, 90, 215, 292, 319 intervention, 6, 7, 73, 76, 77, 115, 116, 121, 128, 151, 157, 218, 228, 240, 309 interview, 15, 34, 82, 92, 100, 108, 136, 230, 235, 237, 240, 318, 319 interviews, 228, 231, 319 intoxication, 71, 139 intraocular, 304 intraocular pressure, 304 intravenous immunoglobulins, 51 intravenously, 305, 306 intrusions, 27, 99, 237 invasive, 258 inversion, 37, 110, 113 ion channels, 74 iron, 54, 59 irritability, 72, 106, 113, 137, 139, 146, 235 ISC, ix, 70, 73, 74, 75, 88, 89, 91, 92, 93 isoenzymes, 281 isolation, 126, 146, 331 isoniazid, 140

J JAMA, 98, 140, 153, 154, 158, 160, 336 Japan, ix, 103, 104, 105, 106, 108, 112, 114, 119, 120, 122, 123, 129, 133, 249, 252, 264, 276, 329, 333 jet lag, 109, 110, 112, 113, 117, 118, 119, 121, 126, 130, 131, 276, 283 junior high, 104, 105, 106, 108, 114, 124, 125 junior high school, 104, 105, 106, 108, 114, 124, 125

K Kampo medicine, 119, 133 ketamine, 306, 308, 311, 312 kinase, 274, 285, 287 kindergarten, 105, 107 kinetics, 288, 300 King, 71, 96, 287, 313 knockout, 41, 214, 224

Index kuru, 44 kynuramines, xii, 274, 279, 288

L lactate dehydrogenase, 261 lamina, 45, 52 language, 139, 142 laparoscopic cholecystectomy, xiii, 303, 304 laparoscopic surgery, xiii, 303 large intestine, 313 large-scale, 151 latency, 5, 12, 16, 34, 73, 74, 82, 91, 109, 126, 207, 211, 212, 216, 220, 230, 293, 318, 334 late-onset, 38, 55, 57, 147, 149, 158 LDH, 261 learning, ix, 70, 78, 84, 85, 91, 93, 96, 111, 147, 294, 296 left hemisphere, 330 leptin, 209, 223, 269 lesions, 36, 37, 39, 40, 41, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 60, 62, 66, 146 lethargy, 71 leukocytes, 278 levodopa, 140 Lewy bodies, 38, 48 libido, 39 lifespan, 104, 208, 218 lifestyle, 8, 104, 108, 109, 110, 111, 114, 122, 125, 126 lifestyles, 111 lifetime, xii, 208, 220, 273, 279, 283, 316 ligand, 277, 286 ligands, 287, 288 light conditions, 292, 295 light-induced, 130 likelihood, 143, 233 limbic system, 35, 47, 49, 50, 51, 52, 53, 54, 56, 57, 64, 136 limitation, 297 limitations, 7, 14, 325 links, 25, 145 lithium, 140, 148, 149 liver, 150, 307, 312 liver cirrhosis, 312 localised, 40, 57 localization, 41, 277, 285 location, 19, 40, 331 locomotion, 109, 121 locomotor activity, 111, 128

387

locus, 46, 47, 49, 52, 55, 60 locus coeruleus, 46, 47, 49, 52, 60 longitudinal studies, 228, 237, 243 longitudinal study, 66, 155, 208, 230, 235, 242 loss of appetite, 39, 109 loss of consciousness, 55 low-grade glioma, 54 low-level, 114 lung, 282 lying, 310

M M.I.N.I, 15, 16 magnetic resonance, 84, 88, 94, 305, 311 magnetic resonance imaging (MRI), 42, 50, 51, 54, 55, 59, 84, 87, 88, 94, 305, 311, 331, 333 major depression, 117, 131, 142, 145, 160, 209, 218, 223, 224, 230, 234, 236, 241, 243, 244, 298, 316 major depressive disorder, 147, 234, 245, 246, 326 maladaptive beliefs, 7 malaise, 72, 107 males, 216, 230, 233, 237, 260, 261, 262, 269, 334 malignant, 51 malnutrition, 269 malondialdehyde, 299 mammalian brain, 216 mammals, xii, 115, 131, 273, 274, 275, 285, 288 management, 7, 74, 75, 96, 98, 117, 130, 133, 138, 141, 143, 147, 149, 150, 151, 154, 156, 157, 159, 228, 232, 241, 242, 243, 246 mandates, 143 mania, 136, 144, 145, 146, 149 manic episode, 149 manic symptoms, 145, 146 manipulation, 12, 26, 113, 209 MAO, 148, 292 marital status, 233, 319 Marx, 152 maternal influence, 104 Matrices, 89, 99 measures, ix, xiii, 10, 12, 13, 19, 21, 70, 75, 83, 136, 207, 219, 291, 318, 324 mechanical ventilation, 138 media, 106, 114, 121 medial prefrontal cortex, 54 median, 40, 143 Medicaid, 154 medical care, 158 medical school, 107

388

Index

medication, 7, 8, 15, 16, 74, 75, 78, 117, 132, 139, 141, 147, 148, 149, 150, 151, 236, 238, 242, 260, 262, 263, 264, 265, 266, 294, 296 medications, 72, 73, 74, 115, 137, 138, 139, 140, 141, 142, 143, 146, 148, 149, 150, 153, 154, 157, 159, 264 medicine, 97, 119, 121, 124, 125, 127, 130, 131, 132, 133, 229, 264, 266, 292, 298 meditation, 121 Medline, xiii, 291 medulla, 46, 47, 48 melatonin receptor agonists, 110 memorizing, 107 memory, ix, xiii, 50, 51, 54, 59, 70, 72, 74, 75, 83, 86, 87, 88, 89, 91, 99, 100, 128, 131, 139, 142, 143, 155, 291, 294, 296 memory loss, 142 memory performance, ix, 70, 75, 83, 86, 91, 100 memory retrieval, 91 men, 11, 16, 17, 28, 42, 54, 113, 129, 210, 211, 212, 214, 215, 216, 218, 219, 220, 221, 222, 225, 250, 251, 254, 255, 257, 264, 267, 268, 270, 288, 300, 312, 313 Mendel, 219 menopause, xi, 205, 208, 215, 218 menstrual cycle, 215, 297 mental activity, 90, 133 mental disorder, ix, xiv, 30, 71, 135, 137, 233, 315, 316, 318, 325 mental health, ix, 119, 122, 132, 135, 137, 227, 229, 238 mental health professionals, 229 mental retardation, xiv, 299, 329, 330, 334, 335 mental status change, 139, 141 mental status changes, 139, 141 mesencephalon, 46, 48, 49, 50, 57 messenger RNA, 225 meta-analysis, 32, 94, 148, 159, 225, 285, 298, 325 metabolic, 14, 34, 43, 57, 107, 125, 139, 150, 208, 224, 275, 277, 282, 312 metabolic rate, 14, 34 metabolism, xii, 36, 41, 274, 277, 279, 280, 281, 282, 283, 286, 310, 312 metabolite, 110, 280, 282, 283, 288, 309, 310 metabolites, xii, 206, 273, 275, 276, 277, 279, 280, 282, 283, 284, 288, 289, 304 methionine, 42, 222 methylphenidate, 95, 97, 294 methylprednisolone, 212

mice, 38, 41, 53, 66, 116, 210, 211, 212, 213, 214, 220, 222, 224, 282 microdialysis, 129, 210, 222 microglial cells, 41 microinjection, 224, 226 microscopy, 41 microstructure, 26, 28, 33, 98 microstructures, 73 midbrain, 47, 53, 59, 65 mind-body, 121 Mini International Neuropsychiatric Interview, 15 Ministry of Education, 126 Minnesota multiphasic personality inventory, 85, 88 mobile phone, 106, 121 modalities, 11, 78, 85, 121, 151 modality, 73 models, 67, 133, 216, 231, 242 modulation, 55, 64, 95 modules, 75 molecular dynamics, 287 molecular pathology, 60 molecular structure, 280 molecules, 53, 56, 119, 121 Møller, 36, 63, 67, 268 monkeys, 111, 128 monotherapy, 268 Monroe, 4, 30 mood, ix, xiv, 30, 40, 71, 72, 85, 87, 94, 108, 109, 128, 135, 137, 138, 142, 146, 148, 158, 218, 231, 232, 234, 236, 237, 294, 315, 319, 320, 324 mood disorder, xiv, 146, 158, 218, 315, 319, 320, 324 morbidity, 101, 141, 145, 146, 153 morphine, 307, 312 morphology, 67 mortality, 71, 138, 141, 144, 145, 146, 148, 153, 158, 267 mortality rate, 146 mortality risk, 267 mothers, 104, 123 motivation, 55, 72, 106, 115, 116, 240, 297 motor activity, 46, 108, 294 motor behavior, viii, 69, 81, 96 motor control, 55, 128 motor function, 98, 251 motor system, 46 movement, 3, 48, 60, 63, 64, 72, 81, 87, 94, 121, 130, 144, 222, 224, 296 movement disorders, 60 MPI, 85

Index mRNA, 38, 53, 212, 213, 219, 226 multiple sclerosis, 146, 212, 218 multivariate, 234, 235, 242, 317 muscle, 2, 3, 4, 11, 12, 13, 17, 27, 46, 49, 51, 76, 77, 90, 113, 258, 260 muscle relaxation, 76 muscles, 3, 30 music, 143 music therapy, 143 mutation, 42, 43, 44, 63, 213 mutations, 43 myeloperoxidase, 280, 289 myocardial infarction, 113, 123, 129, 134, 145, 158 myoclonus, 44, 51

N N-acety, 45, 274, 277, 280, 304 N-acetylserotonin, 277, 280, 304 naphthalene, 276, 280, 282 narcolepsy, 48, 56, 72 National Academy of Sciences, 93 National Institutes of Health, 73, 98 natural food, 285 nausea, 296, 304 neck, 107, 115, 116, 153 negative consequences, 246 negative experiences, 284 negative relation, 237, 242 neocortex, 43 nervous system, 48, 66, 100, 251 network, viii, 35, 40, 46, 52, 56, 57, 67, 83, 277 neuritis, 38 neuroanatomy, 62 neurobiological disturbances, 317 neuroblastoma, 65 neurodegenerative disease, 36, 58, 293 neurodegenerative diseases, 36, 293 neurodegenerative disorders, viii, 35, 49, 52, 64 neuroendocrine, 206, 318, 335 neuroendocrine system, 335 neurofeedback, viii, 70, 77, 79, 83, 88, 93, 94, 95, 96, 97, 100 neurofibrillary tangles, 37, 47 neurogenesis, 128 neuroimaging, 36, 63 neuroleptic, xiii, 159, 291 neuroleptics, 150 neurologic disorders, 58, 59 neurological deficit, 54

389

neurological disease, xiii, 64, 146, 158, 291 neurologist, 158 neuronal cells, 52 neuronal circuits, 128 neuronal density, 53 neuronal loss, 37, 38, 41, 43, 44, 45, 52 neuronal sensitivity, 37 neurons, 10, 27, 36, 37, 38, 43, 45, 46, 47, 49, 54, 55, 56, 58, 60, 62, 66, 121, 126, 136, 212, 216, 219 neuropathology, vii, 37, 52, 60, 61, 67 neuropathy, 51 neuropeptide, 49, 211, 216, 217, 219 Neuropeptide Y, 220 neuropeptides, xi, 205, 206 neuroprotection, 289 Neuropsychiatric Inventory, 156 neuropsychiatry, 128, 155 neuroscience, 97 neurotransmission, 53, 222, 317 neurotransmitter, 41, 292 neurotransmitters, 49, 136, 145, 293 New York, 30, 31, 32, 94, 98, 126, 128, 158, 269, 287, 288 New Zealand, 105, 308, 312 NFT, 78, 79, 83, 84, 85, 86, 87, 88 nicotine, 76 Nielsen, 57, 63 nifedipine, 310 nightmares, 228, 233, 234, 236, 238, 240 NIH, 73, 74, 158 nitrate, 299 nitric oxide, 67 nitrogen, 261, 281, 289 NMDA, 144 N-methyl-D-aspartate, 50 NMR, 287 NO synthase, 275 nocturia, vii, xi, xii, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271 nocturnal polyuria, xi, 249, 250, 255, 256, 257, 259, 260, 269, 270 noise, 76, 113 non-clinical population, 228 non-pharmacological treatments, 75 non-steroidal anti-inflammatory drugs, 117 noradrenaline, 118, 251, 254, 256, 257, 292, 310 norepinephrine, 36, 49, 111, 113, 118, 136, 206, 278 normal aging, 40, 150

Index

390

normal conditions, 116 normalization, xiv, 28, 209, 329, 333 North America, 95, 245, 301 Norway, 110, 227 NSAIDs, 140 nuclear, xii, 40, 45, 47, 273, 277, 286 nuclear receptors, xii, 273, 277 nuclei, 36, 37, 38, 40, 41, 43, 44, 45, 46, 47, 48, 49, 51, 52, 53, 56, 57, 58, 61, 62, 64, 128, 285 nucleus, xii, 36, 37, 39, 40, 41, 43, 45, 46, 47, 48, 49, 53, 54, 55, 56, 62, 65, 104, 109, 116, 123, 126, 209, 216, 225, 273, 274, 285, 292, 300 nurse, 124, 330 nursery school, 105, 107 nurses, 112, 129, 332 nursing, ix, 135, 141, 142, 143, 145, 146, 151, 152, 155, 156, 157, 158, 159 nursing home, ix, 135, 142, 143, 145, 146, 151, 152, 155, 156, 157, 158, 159 nutritional supplements, 312

O obese, 307 obesity, 124 observations, 8, 148, 208, 241, 243 obsessive-compulsive, 316, 319, 322, 323, 324, 325, 326, 327 obsessive-compulsive disorder, 316, 324, 326, 327 obstruction, xi, 249, 250, 271 OCD, xiv, 315, 316, 317, 318, 319, 320, 321, 322, 323, 324, 325, 326 oculomotor, 47 Odds Ratio, 230 oedema, 55 olanzapine, 140, 144, 148, 149 old age, 38 older adults, 94, 125, 145, 146, 149, 151, 154, 156, 159, 160 older people, 58, 74, 153 olfactory, 48 olfactory bulb, 48 oligodendrocytes, 55 oncology, 292 online, 17, 80, 89, 288 onset latency, ix, 6, 9, 13, 27, 34, 70, 75, 78, 79, 85, 91, 92, 106, 124, 229, 260, 263, 267 operant conditioning, 79 opiates, 139, 140 opioid, 122, 307, 311

opioids, 304 optic glioma, 302 orbitofrontal cortex, 52 orexin A, 251 organ, 39 orientation, 3, 228, 311 orthostatic hypotension, 112, 148 oscillation, ix, 10, 82, 103, 111, 113, 114, 115, 116 oscillations, viii, 10, 27, 65, 69, 73, 80, 82, 83, 93, 100, 274 oscillator, 127, 130, 274 osmotic pressure, 251, 254, 257, 261 outpatient, 228, 235 outpatients, 156, 234, 260, 263, 268, 306 ovarian cancer, 50 oxidants, 279 oxidation, 127, 281, 289 oxidation products, 289 oxidative damage, 289 oxidative stress, 287 oxide, 67 oxygen, 14, 55, 87, 88, 306 oxytocin, 67

P P300, 84 pacemaker, 116, 126, 128, 274, 299 pacing, 145, 147 pain, 39, 78, 113, 118, 121, 133, 237, 239, 306, 307, 309, 312 palpation, 113 pancreatic, 38 panic attack, 233, 240 panic disorder, 136, 150, 159 paradox, 8 paradoxical sleep, 221 paralysis, 94 parameter, 5, 11, 26, 77, 80, 85, 90 paraventricular nucleus, 36, 209, 225 parenchyma, 37, 52 parental support, 232 parent-child, xiii, 291 parenting, 238 parents, 17, 84, 85, 86, 87, 106, 124, 232, 236, 238, 239, 294 paresthesias, 146 Parkinson, 36, 38, 39, 47, 48, 57, 58, 60, 61, 64, 66, 156, 293 parkinsonism, 63

Index paroxetine, 149, 159 pars tuberalis, 285 parvalbumin, 41, 60 pathogenesis, 113 pathology, 53, 58, 60, 61, 64, 66, 239, 243 pathophysiology, ix, 54, 62, 103, 104, 114, 152, 211, 217, 288, 313 pathways, 47, 49, 56, 121, 240, 279, 282, 288 PCA, 307 peak concentration, 222 pediatric, 74, 294, 295 pediatrician, 121 pension, 246 pensions, 229 peptide, 38, 216, 220, 222, 251, 256, 261, 264, 266, 269, 270, 293 peptides, xi, 122, 205, 216, 217, 251 perceived control, 5 perception, viii, 2, 3, 5, 10, 12, 13, 20, 26, 29, 32, 34, 65, 73, 75, 241, 260, 261, 264 perceptions, 30, 77 perfusion, 313 periaqueductal gray matter, 43 periodic, 38, 42, 48, 56, 64, 72 periodicity, 73 peripheral nervous system, 11, 51 permeability, 277, 287 personality, 2, 15, 42, 115, 116, 233 personality disorder, 115, 116, 233 personality disorders, 327 personality traits, 2 persuasion, 232 perturbation, 126 pessimism, 317 PET, 39, 40, 42, 51, 58, 59, 63, 64 PET scan, 39, 42 pharmacists, 141 pharmacodynamics, 149, 286 pharmacokinetics, 149, 283, 286, 310, 313, 314 pharmacological treatment, viii, xiii, 69, 83, 131, 149, 291, 298 pharmacology, 288, 301 pharmacotherapy, 7, 73, 84, 99, 157, 159, 160, 270, 330 phase shifts, 118, 132, 274, 293, 298 phenomenology, 34, 95, 246, 318, 322 phenothiazines, 140 phenotype, 42, 43 phenotypes, 41, 42, 63 phenytoin, 140

391

Philadelphia, 101, 124, 125, 127, 130, 131, 132 phospholipase C, 274 photoperiod, 117 phototaxis, 130 physical abuse, 238 physical activity, 13, 106, 108, 111, 114, 122, 128 physical aggression, 136 physical exercise, 264 physical properties, 280, 289 physicians, 15, 70, 134, 142, 244, 267 physiological arousal, viii, 2, 3, 5, 6, 12, 13, 14, 15, 18, 21, 26, 27, 28, 29, 34, 76 physiological regulation, 206 physiology, 55, 138, 287, 288, 299, 313 physiopathology, 55 pilot study, 58, 88, 89, 131, 132, 159, 300 pineal gland, vii, 36, 37, 38, 63, 66, 67, 259, 267, 274, 275, 279, 286, 292, 304, 310 pinealectomy, 299 pituitary, xi, 4, 36, 45, 67, 205, 206, 207, 209, 210, 213, 219, 224 pituitary gland, 36, 67, 209 placebo, xiii, 7, 74, 78, 98, 100, 144, 148, 150, 156, 157, 159, 209, 223, 268, 286, 294, 295, 299, 300, 301, 303, 304, 305, 306, 311, 312, 325, 334, 335, 336 planning, 81, 231, 234, 240 plantar flexion, 55 plasma, xi, xii, 50, 115, 128, 207, 208, 213, 223, 225, 249, 250, 251, 252, 253, 254, 255, 256, 257, 259, 260, 261, 264, 266, 269, 281, 283, 292, 295, 298, 304, 308, 309, 310, 312, 313, 330, 333 plasma levels, 283, 304, 308, 312 plasmapheresis, 51 plasticity, 65, 100, 128 platelets, 261 play, xiii, 6, 8, 26, 29, 38, 42, 47, 49, 53, 54, 55, 56, 70, 213, 217, 241, 291, 309 pleiotropy, 282, 289 polydipsia, 39 polymorphism, 14, 34, 42, 44, 63 polysomnography, viii, 1, 16, 17, 18, 19, 20, 26, 29, 44, 51, 79, 97, 99, 241, 326 polyuria, xi, 249, 250, 255, 256, 257, 259, 260, 269, 270 POMS, 12 pons, 47, 48, 49, 57, 62 poor, 7, 30, 31, 57, 71, 72, 106, 108, 112, 145, 146, 206, 218, 229, 230, 233, 234, 236, 239, 241, 275, 307, 330, 333

392

Index

population, ix, 2, 8, 29, 54, 58, 70, 71, 91, 110, 122, 135, 136, 137, 138, 141, 142, 145, 146, 147, 149, 151, 154, 158, 228, 229, 230, 235, 242, 245, 250, 267, 316, 318, 324, 325, 326 pore, 277, 287 positive correlation, xiv, 10, 25, 26, 88, 109, 206, 316, 318, 324 positive relation, 144, 233 positive relationship, 144, 233 Post Traumatic Stress Disorder, 237 posterior cingulated, 57 postmenopausal women, xi, 205, 215, 218, 224 postmortem, 38 postoperative outcome, 312 postpartum, 123 posttraumatic stress, 228, 234, 241, 245 posttraumatic stress disorder, 228, 234, 241, 245 potassium, 50, 62, 66 potassium channels, 62 power, viii, 2, 9, 10, 14, 18, 21, 22, 23, 24, 25, 27, 28, 29, 30, 33, 41, 69, 73, 75, 80, 83, 88, 94, 96, 213, 219, 226 Praline, 62 preadolescents, 30 predictors, 129, 152, 153, 158, 235, 245, 246, 324 predisposing factors, 2, 13, 14, 15, 29 preference, 108, 110, 119, 125 prefrontal cortex, 36, 54, 55 pregnancy, 17, 104, 123, 215, 299 preschool children, 126 preschoolers, ix, 103, 108, 109, 114 press, 31, 32, 60, 64, 128, 133, 245 pressure, 55, 75, 77, 121, 251, 254, 255, 257, 261, 304 prevention, 128, 240, 325 primary care, 15, 141, 150, 156, 244 prion diseases, 41, 49, 58, 61, 62, 64 proband, 209 probe, 58, 98, 314 problem behavior, 295 problem behaviors, 295 problem solving, 5, 6 procedural memory, 99 prodrome, 139 production, 12, 86, 97, 207, 257, 258, 267, 268, 275, 292, 301, 313, 333 productivity, 71 progesterone, xi, 205, 212, 215, 218 program, 7, 119, 268, 319 progressive supranuclear palsy, 57, 61, 63, 65, 66

prolactin, 209, 216, 220, 223, 270, 327 property, iv, ix, xiii, 103, 123, 136, 274, 278 propofol, 305, 306, 308, 311 propranolol, 310 prostaglandin, 310 prostate, 260 prostatitis, 260, 264 protection, 110, 287 protein, 41, 42, 44, 53, 63, 65, 66, 128, 212, 213, 261, 274, 285 protein kinase C, 274, 285 proteins, xii, 50, 64, 274, 277, 283, 304 proteinuria, 260 protocol, ix, 4, 12, 13, 14, 70, 78, 83, 84, 85, 86, 88, 89, 92, 93, 209, 211, 240, 306 protocols, viii, 70, 83, 88, 97, 100, 151, 211, 310 pruritus, 296 pseudo, 47, 48, 59, 79, 83, 88 PSG, 19, 20, 21, 26, 29, 73, 78, 79, 92, 93 PSP, 45, 47, 52, 61 PSS, 261 psychiatric diagnosis, 228, 316 psychiatric disorder, 9, 72, 82, 101, 151, 231, 235, 239, 240, 295, 297, 324, 325, 326 psychiatric disorders, 9, 82, 101, 151, 231, 235, 240, 295, 297, 324, 325, 326 psychiatric illness, 70, 293 psychiatric patients, 240, 246 psychiatrist, 229, 238 psychiatrists, 319 psychobiology, 129 psychological distress, 113 psychological processes, 9 psychological stress, 209 psychologist, 229, 232 psychology, 240 psychopathology, 70, 147, 236, 239 psychopharmacological, 239 psychoses, 158 psychosis, 136, 139, 142, 143, 145, 147, 148, 150, 154, 155, 156, 157, 159 psychotherapy, 78, 148, 151, 160, 232, 236, 238, 242, 245 psychotic symptoms, 142, 147, 148, 149 psychotropic drugs, 157 psychotropic medications, 143, 154 PTSD, 228, 237, 241, 242 pubertal development, 230 puberty, 125, 215, 292 pulse, 104, 115, 118, 122, 132

Index pulses, 115, 130 pyramidal cells, 49 pyrrole, 279, 280, 281

Q QOL, xi, xii, 249, 250, 261, 262, 264, 265 QT interval, 149, 150 quality of life, vii, x, xi, 1, 70, 75, 135, 137, 138, 143, 155, 249, 250, 294 quartile, 19, 21, 22, 24 questionnaire, 17, 26, 85, 86, 107, 124, 125, 129, 233, 261, 295 questionnaires, viii, 1, 15, 82, 92, 240 quetiapine, 140, 144, 149 quinidine, 140 quinone, xii, 274, 277, 286, 287

R RAGE, 136, 152 range, viii, 7, 27, 69, 81, 90, 115, 121, 136, 142, 146, 147, 208, 213, 216, 229, 230, 277, 278, 279, 298, 319, 333 rape, 237, 244 raphe, 43, 47, 48, 49, 53, 57, 128 rapid eye movement sleep, 59, 88, 111, 221 rat, 46, 59, 61, 65, 111, 128, 210, 212, 213, 219, 220, 222, 223, 225, 226, 270, 274, 285, 305, 313 rating scale, 84, 85, 86, 88, 89, 152, 327 ratings, 84, 85, 86, 87, 97, 157, 265, 319 rats, 38, 46, 53, 61, 118, 128, 132, 209, 210, 211, 212, 213, 214, 215, 216, 218, 219, 221, 222, 223, 224, 225, 226, 260, 270, 271, 288, 301, 305, 306, 311 reactive nitrogen, 289 reactivity, 5 reality, 316 recall, 91, 305 receptor agonist, 74, 110, 118, 212, 287, 288 receptors, xii, 36, 37, 38, 46, 50, 53, 55, 58, 74, 110, 149, 158, 213, 214, 219, 221, 222, 270, 273, 274, 276, 277, 278, 280, 282, 283, 285, 286, 287, 288, 292, 304, 311 recognition, 70, 229, 245 recovery, 14, 33, 110, 129, 130, 208, 210, 213, 214, 221, 224, 225, 308 rectal temperature, 3, 115 red blood cell, 261

393

red blood cells, 261 redistribution, 55 reflection, 12 Reform Act, 143 refractory, 54, 149, 301 regulation, xi, 37, 41, 47, 53, 61, 62, 65, 75, 86, 95, 100, 112, 126, 128, 130, 205, 206, 212, 213, 214, 215, 216, 217, 219, 221, 224, 237, 240, 244, 247, 270, 287, 292, 300, 304, 333 regulators, 87, 206 reinforcement, 81, 99, 143 rejection, 90 relationship, xi, 2, 5, 10, 26, 30, 31, 48, 60, 108, 109, 140, 144, 145, 152, 153, 208, 227, 228, 230, 232, 233, 234, 236, 238, 240, 241, 242, 243, 244, 259, 287, 297, 307 relationships, 124, 228, 233, 235, 237, 241, 242 relaxation, 2, 4, 6, 7, 32, 54, 76, 78, 79, 90, 91, 95, 96, 98, 238 relaxation time, 54 relevance, 58, 241, 245, 277, 279, 285, 287, 289 reliability, 100, 243, 319, 327 remediation, 150 remethylation, 118 renal, 257, 258, 260, 264, 269 renal dysfunction, 260, 264 renal failure, 258 renal function, 269 resistance, 3, 125, 257 respiration, 6, 111, 115, 119, 121 respiratory, 3, 30, 89, 150, 304 respiratory problems, 150 restless legs syndrome, 54, 57, 58, 59, 64, 66, 67 restructuring, 7, 77 retardation, 335 retention, 257, 258 retina, 36 retinohypothalamic tract, 36, 300 retinoic acid, 277 retinoic acid receptor, 277 Rett syndrome, 133, 300 Reynolds, 73, 89, 94, 99, 131, 159, 160, 207, 223 rhythm, viii, xiv, 2, 4, 9, 43, 69, 79, 81, 84, 88, 90, 96, 99, 104, 109, 110, 111, 112, 114, 123, 124, 128, 130, 131, 132, 133, 209, 284, 292, 299, 301, 329, 330, 333, 335 rhythmicity, 123, 127 rhythms, ix, 9, 30, 36, 38, 41, 59, 64, 65, 66, 81, 95, 103, 104, 107, 108, 109, 110, 112, 114, 115, 116, 118, 125, 126, 127, 128, 130, 131, 218, 225, 244,

Index

394

270, 278, 283, 284, 287, 288, 292, 299, 304, 308, 327 risk assessment, 245 risk factors, 129, 145, 155, 158, 228, 240, 245, 268 risks, 144, 152 risperidone, 140, 144, 148, 150, 153, 159 RNA, 50, 53 Rössler, 244 rumination, 2

S safety, x, 5, 117, 135, 137, 138, 140, 147, 157, 277, 284, 285, 286, 298, 302 salicylates, 140 saliva, 19, 308, 310, 313 sample, xiv, 6, 14, 15, 18, 19, 21, 25, 27, 28, 29, 60, 83, 113, 136, 155, 208, 230, 237, 240, 242, 245, 251, 308, 310, 315, 316, 317, 318, 320, 321, 322, 324, 325 schizoaffective disorder, 241 schizophrenia, 144, 146, 147, 149, 158, 234, 235, 241, 293, 318, 322 schizophrenic patients, 147 Schmid, 209, 211, 220, 223, 224, 225, 311 school, ix, 72, 103, 104, 105, 106, 107, 108, 114, 116, 120, 122, 123, 124, 125, 129, 130, 229, 231, 232, 233, 235, 237, 239, 240, 245, 247, 294, 295, 334 school performance, 108, 116 SCN, 104, 109, 110, 122, 274, 283 scores, xiii, 6, 12, 15, 26, 84, 97, 117, 234, 235, 262, 303, 305, 307, 311, 317, 318, 320, 321, 324 SCP, 83, 85, 86, 87, 88, 97 seasonal affective disorder, 109, 117, 131 seasonality, 123 secondary schools, 233 sedation, vii, xiii, 74, 147, 150, 303, 304, 305, 307, 310, 311, 330 sedentary, 112 sedentary behavior, 112 seizure, 51, 85, 330 seizures, 50, 51, 86, 294, 296, 301, 333 selective attention, 3, 5, 6, 84, 94 selective serotonin reuptake inhibitor, 111, 118, 144, 236 selectivity, xiii, 274, 276, 277, 283 senescence, 250 senile, 37, 155 senile dementia, 155

senile plaques, 37 sensitivity, 15, 37, 145, 225, 229 sensorimotor cortex, viii, 69, 81, 101 sensory systems, 56 series, viii, 3, 35, 36, 48, 146, 159 serotonin, xii, 104, 111, 112, 113, 118, 128, 129, 144, 145, 158, 236, 240, 251, 254, 261, 273, 276, 278, 280, 287, 292, 304, 310, 326 serotonin syndrome, 111, 326 sertraline, 150 serum, xiv, 261, 262, 263, 264, 265, 267, 269, 270, 297, 302, 307, 308, 309, 310, 312, 313, 314, 329, 333, 335 severity, xiv, 6, 47, 48, 129, 141, 145, 146, 158, 229, 240, 245, 250, 315, 316, 317, 318, 324, 325 sex, 33, 125, 292, 296, 319 sex differences, 33 sex hormones, 296 sexual activity, 76 sexual development, 299 sexual dimorphism, 213, 214 side effects, xiii, 100, 140, 148, 149, 150, 264, 266, 291, 295, 296, 297, 298 sign, 12, 28, 56, 79, 242, 243 signal transduction, 285 signaling, 222, 274, 275, 282 signaling pathway, 282 signaling pathways, 282 signals, vii, 9, 18, 80, 109, 292 significance level, 320 signs, 11, 39, 42, 44, 48, 50, 51, 54, 64, 137, 227, 228, 242, 246, 330 SIS, 92 sites, xii, 81, 87, 224, 273, 274, 277, 278, 282, 285, 326 skills, 85, 121, 232, 242, 330 skills training, 85 skin, 3, 6, 71, 77, 97, 122, 215 skin cancer, 71 skin conductance, 6 sleep apnea, 17, 72, 259 sleep deprivation, 4, 7, 12, 14, 34, 36, 53, 77, 89, 107, 113, 209, 211, 213, 214, 216, 219, 220, 222, 223, 224, 225, 230, 240 sleep habits, 7, 76, 106, 108, 123, 126 sleep spindle, viii, 40, 44, 45, 54, 59, 69, 81, 83, 88, 91, 92 sleep stage, 9, 18, 34, 73, 113, 206, 207, 208, 211, 214, 215, 219, 223, 293, 297 sleep-inducing, xiii, 274, 291, 295, 297

Index sleeping pills, 71, 274, 301 sleeping problems, 82 sleep-wake cycle, 39, 42, 53, 55, 58, 115, 132, 137, 209, 300, 330 slow-wave, 45, 220, 225 SMR, viii, 69, 78, 79, 80, 81, 82, 84, 85, 86, 87, 88, 89, 91, 92, 93 SNc, 54 sociability, 111, 116 social activities, 116, 210, 319 social behavior, 294 social factors, 116 social promotion, 117 social skills, 121 sodium, 158, 269, 311, 312, 331 software, 17, 18, 19 somatosensory, 213 somatostatin, 38, 212, 213, 214, 216, 217, 219, 220, 221, 224, 225, 226 species, 41, 110, 274, 289 specificity, 229, 243 SPECT, 55 spectral analysis, 10, 29, 33, 63 spectroscopy, 42 spectrum, xii, 11, 13, 17, 48, 66, 125, 144, 228, 240, 273, 277, 280, 282, 283, 289, 299, 325 speculation, 244 spermatogenesis, 297 spinal cord, 36, 46, 47, 48, 50, 260 spindle, viii, 38, 40, 70, 81, 85, 87, 88, 91, 100 SPT, 18, 20 SRIs, 145 stages, viii, 9, 34, 35, 37, 38, 40, 41, 43, 45, 47, 48, 49, 52, 67, 73, 75, 113, 219, 230, 293, 296 STAI, 15, 16, 19, 26, 34 stem cell transplantation, 66 steroid, 116 steroids, xi, 205, 216, 217, 221 stimulus, 7, 8, 76, 79, 82, 96, 104, 115, 130, 213, 306 stress, xiii, 4, 12, 15, 31, 35, 36, 55, 75, 112, 145, 156, 206, 208, 209, 211, 225, 228, 234, 238, 241, 242, 243, 245, 260, 287, 303, 304, 309, 313 stressors, 3 striatum, 41, 43, 45, 52, 57, 136, 210 stroke, 40, 63, 144, 145 strokes, viii, 35, 36, 49 students, ix, 17, 103, 104, 105, 106, 107, 108, 114, 122, 123, 125, 126, 233, 235, 237 substance abuse, 72, 74, 81, 86, 246

395

substance use, 100, 108, 139, 231 substances, 56, 274, 276 substantia nigra, 45, 47, 53, 54, 67 Substantia nigra, 48, 63 substitution, 214 substrates, 100 suffering, viii, 4, 5, 11, 51, 56, 70, 75, 78, 79, 82, 85, 86, 87, 92, 93, 114, 117, 119, 121, 123, 137, 146, 147, 148, 149, 151, 212, 239, 309, 318, 320 suicidal, vii, xi, 108, 111, 227, 228, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246 suicidal behavior, 108, 111, 244, 245, 246 suicidal ideation, 228, 231, 232, 233, 234, 235, 238, 239, 241, 242, 244, 245 suicide, xi, 227, 228, 231, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247 suicide attempters, 235, 247 suicide attempts, 231, 234, 242, 243, 245, 247 suicide completers, 240 sulfate, 304 sulfonamides, 140 sulphate, 308 Sun, 224 sunlight, 109, 111 supervision, 149, 319 supplements, 312 suppression, 46, 47, 49, 61, 81, 121, 130, 222, 223, 275, 278 suprachiasmatic, xii, 36, 37, 54, 104, 123, 273, 274, 285, 300 suprachiasmatic nuclei, 285 suprachiasmatic nucleus, xii, 36, 37, 54, 104, 123, 273, 274, 285, 300 surgery, xiii, 138, 153, 303, 305, 306, 307, 308, 309, 311, 313 sympathetic nervous system, 115, 116, 122, 308 symptomatic treatment, 149 synchronization, 81, 99, 104, 116, 292 syndrome, ix, 17, 37, 48, 51, 54, 56, 57, 62, 63, 64, 85, 103, 106, 112, 114, 118, 120, 127, 132, 133, 137, 145, 146, 149, 155, 259, 300, 302, 318, 326 synergistic effect, 306 synthesis, 36, 37, 212, 285, 292, 310 systolic blood pressure, 255

T T cells, 51 tachycardia, 42, 51, 146, 296

396

Index

tamoxifen, 140 tardive dyskinesia, 149 task performance, 84 teachers, 84, 85, 86, 87, 105, 107, 108, 124 telencephalon, 46, 47, 53 television, 106, 121, 124, 134 television viewing, 106, 124 temperature, 4, 13, 30, 31, 64, 77, 109, 111, 113, 114, 115, 116, 127, 128, 130, 288, 292, 313 temporal lobe, 48, 50, 51, 87 tension, 2, 12, 13, 18, 27, 72, 77, 318, 324 tension headache, 72 teratoma, 65 terminally ill, 153 terminals, 260 testosterone, 38 testosterone levels, 38 thalamus, 9, 40, 41, 42, 43, 44, 45, 46, 49, 52, 53, 55, 56, 58, 59, 62, 64, 65, 87, 214, 221 therapeutic approaches, ix, 59, 103, 104, 114, 298 therapeutic interventions, 5, 8 therapeutic targets, 58, 63 theta, 9, 14, 17, 18, 21, 22, 78, 79, 82, 84, 85, 86, 88, 95, 97, 209, 213 thioridazine, 149 thyroid gland, 208 thyrotropin, 215, 220 time consuming, 316, 319 timing, 65, 109, 123, 126, 130, 131, 134, 237, 259, 267, 278, 301 tinnitus, 78, 81, 85, 95, 119 tissue, 37, 38, 50, 52, 212, 278, 279, 284, 309 Tokyo, 103, 104, 105, 106, 123, 124, 133, 134, 252, 333 tolerance, 288, 296, 297, 312 tourniquet, 307, 312 toxicity, xiii, 74, 154, 274, 282, 296, 301 tractography, 66 training, ix, 6, 7, 32, 70, 76, 78, 79, 80, 81, 82, 83, 84, 85, 87, 88, 92, 94, 95, 96, 97, 100, 121, 132, 236, 269, 319 training block, 82 trait anxiety, 26 traits, 243 tranquilizers, 260, 263, 264 transcription, 210, 225 transformation, 17, 22, 23, 24 transgenic mice, 213, 220 transition, 10, 27, 33, 122, 277, 287 translation, 73, 82, 85, 88

transmission, 55, 65, 145, 213, 214, 221, 241 trauma, 40, 49, 237, 309 traumatic brain injury, 61, 220 treatment methods, 151 tremor, 51 tricyclic antidepressants, 140, 209, 232 triggers, ix, 103 tryptophan, 289, 292, 304, 317 TSH, 39, 270 tufted, 47 tumor, 36, 37, 54, 60, 65, 292 tumor growth, 292 tumors, viii, 35, 54, 146, 282, 298 type 2 diabetes, 125 tyrosine, 53, 67, 292 tyrosine hydroxylase, 53, 67

U ultrasonography, 261, 264 underlying mechanisms, xiii, 304 university students, 106 urea, 261 urea nitrogen, 261 urethra, 260 urethral syndrome, 261, 264 urinary, xi, 110, 206, 249, 250, 251, 254, 256, 260, 262, 263, 267, 268, 269, 270, 271, 285 urinary tract, xi, 249, 250, 260, 262, 263, 267, 268, 269, 270, 271 urine, xii, 249, 251, 254, 255, 256, 257, 258, 259, 261, 264, 267, 268, 304, 308, 309 uroflowmetry, 268, 270 urothelium, 260, 270 uterus, 308

V validation, 34 validity, 95, 100, 294, 327 valine, 42 valproic acid, 140, 148 values, 17, 54, 82, 90, 210, 254, 306, 308, 309 vancomycin, 140 variability, viii, xiii, 2, 11, 14, 29, 30, 63, 80, 85, 121, 133, 215, 303, 307, 308, 309 variables, viii, 2, 13, 15, 17, 18, 29, 74, 75, 84, 88, 96, 114, 118, 125, 206, 216, 230, 234, 242, 294, 297, 320

Index variation, 29, 127, 292, 307, 308 vascular dementia, 142 vasculature, 283 vasoactive intestinal peptide, 38, 222 vasomotor, 283 vasopressin, 38, 67, 211, 218, 223, 225, 251, 253, 254, 255, 256, 257, 258, 261, 262, 269 vasopressin level, 253, 254, 255 venlafaxine, 150 ventilation, 3 vertebrates, 274, 285 vinblastine, 140 vincristine, 140 violence, ix, 135, 137, 152, 330 violent, 147, 241 violent behavior, 147 VIP, 38, 56 viscosity, 261, 271 visual field, 82 vitamin B1, 115, 118 vitamin B12, 115, 118 vitamin B12 deficiency, 118 voice, 330

walking, 12, 263, 264, 271, 330 Wallerian degeneration, 331 warrants, 139 water, 42, 82, 122, 132, 251, 252, 255, 256, 257, 258, 266, 269, 271 weakness, 39, 120 white blood cells, 261 white matter, 39, 51, 61 Wistar rats, 288 women, xi, 10, 11, 16, 28, 42, 54, 92, 129, 132, 205, 208, 211, 212, 213, 214, 215, 216, 217, 218, 219, 224, 230, 234, 250, 251, 254, 255, 257, 264, 268, 297, 306, 308, 312, 313 workers, 10, 17, 113, 117, 118, 124, 283 working memory, 83, 88 workplace, ix, 135 World Health Organization, 71, 101

Y young adults, xi, 125, 227, 230, 237, 244, 299 young men, 210, 211, 214, 218, 222, 225, 313 younger children, 239

W waking, vii, viii, 6, 14, 34, 35, 36, 39, 40, 46, 47, 49, 52, 54, 56, 57, 65, 72, 78, 81, 83, 96, 98, 101, 108, 109, 110, 111, 117, 218, 219, 230, 233, 259, 294, 295, 298, 331, 335

397

Z zebrafish, 110, 128 Zen, 121

in Sleep and Insomnia

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