ENDOCRINOLOGY RESEARCH AND CLINICAL DEVELOPMENTS

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ENDOCRINOLOGY RESEARCH AND CLINICAL DEVELOPMENTS

MELATONIN, SLEEP AND INSOMNIA

YOLANDA E. SORIENTOEDITOR

Nova Biomedical BooksNew 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

ContentsPreface Chapter I Conditioned Arousal in Insomnia Patients: Physiological, Cognitive, CorticalAn and/or Question? Aisha Cortoos, Elke De Valck and Raymond Cluydts Neuropathology of Insomnia in the Adult: Still an Enigma! Jean-Jacques Hauw and Chantal Hausser-Hauw 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 A Novel Disease Condition Presenting with Insomnia and Hypersomnia Asynchronization Jun Kohyama Aggression in Older Adult Populations Sarah E. Parsons, Luis F. Ramirez, Philipp Dines, Scott Magnuson and Martha Sajatovic 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 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 vii 1 35

Chapter II Chapter III

69

Chapter IV

103 135

Chapter V

Chapter VI

161

Chapter VII

191 205

Chapter VIII

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 Melatonin and Nocturia Kimio Sugaya, Saori Nishijima, Katsumi Kadekawa and Minoru Miyazato Melatonin and Other Sleep-Promoting Melatoninergic Drugs Under the Aspects of Binding Properties and Metabolism Rdiger Hardeland Melatonin for Medical Treatment of Childhood Insomnias Jan Froelich and Gerd Lehmkuhl Melatonin: Its Significance with Special Reference to Sedation and Anesthesia Argyro Fassoulaki, Anteia Paraskeva and Sophia Markantonis Sleep Disturbance in Obsessive-Compulsive Disorder Enrico Pessina, Sylvia Rigardetto, Umberto Albert, Filippo Bogetto and Giuseppe Maina Effects of Sunbathing on Insomnia, Behavioural Disturbance and Serum Melatonin Level Keiko Ikemoto 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

Chapter X

Chapter XI

273 291

Chapter XII Chapter XIII

303 315

Chapter XIV

Chapter XV

329 337

Chapter XVI

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 Index

357

375

PrefaceMelatonin 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 doesnt 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

Preface

ix

intended to clarify the effects of instrumental SMR conditioning (ISC) on sleep quality as well as on declarative memory performance with todays 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 sleepwakefulness 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 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 characteristicsInsomnia 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) Effect size (r)

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

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

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

Conditioned Arousal in Insomnia Patients

17

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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Aisha Cortoos, Elke De Valck and Raymond Cluydts

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 V) 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.

Conditioned Arousal in Insomnia Patients Procedure

19

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 (p2). Finally, in order to examine possible associations between sleep and arousal, a Spearman Rank correlational analysis was performed.

ResultsClinical 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.