Sleep Traits Research Articles

Compared to an active control condition, in persons with multiple sclerosis two different types of exercise training improved sleep and depression, but not fatigue, paresthesia, and intolerance of uncertainty

BackgroundIn persons with multiple sclerosis (MS), physical activity favorably impacts on psychological well-being. The aims of the present study were to investigate the influence of physical activity on depression, fatigue, sleep, paresthesia, and personality traits (intolerance of uncertainty), and to explore, if endurance training or coordinative training are superior to an active control condition. Methods92 female individuals with MS (mean age: 37.36 years; mean EDSS: 2.43) took part in this intervention study. Participants were randomly assigned either to endurance training, coordinative training, or to an active control condition. At baseline, 4 weeks, and 8 weeks later at the end of the study, participants completed questionnaires on sleep, depression, fatigue, paresthesia and intolerance of uncertainty. Exercise training interventions took place three times/week for 45 min/session. Participants in the active control condition also met with the same duration and frequency. ResultsSleep complaints and symptoms of depression decreased over time, but more so in the exercising groups, compared to the active control group. No changes over time and between groups were observed for fatigue, paresthesia, and intolerance of uncertainty. ConclusionsBoth endurance and coordinative exercising had the potential to favorably impact on some aspects of cognitive-emotional processing, while also an active control condition appeared to have a positive impact.

Investigating causal relations between sleep traits and risk of breast cancer in women: mendelian randomisation study

ObjectiveTo examine whether sleep traits have a causal effect on risk of breast cancer.DesignMendelian randomisation study.SettingUK Biobank prospective cohort study and Breast Cancer Association Consortium (BCAC) case-control genome-wide association study.Participants156...

Twin-based heritability of actimetry traits.

There is a critical need for phenotypes with substantial heritability that can be used as endophenotypes in behavioral genetic studies. Activity monitoring, called actimetry, has potential as a means of assessing sleep and circadian rhythm traits that could serve as endophenotypes relevant to a range of psychopathologies. This study examined a range of actimetry traits for heritability using a classic twin design. The sample consisted of 195 subjects from 45 monozygotic (MZ) and 50 dizygotic (DZ) twin pairs aged 16-40 years. Subjects wore both a research-grade actimeter (GENEActiv) and a consumer-oriented device (FitBit) for 2 weeks. Sleep and circadian traits were extracted from GENEActiv data using PennZzz and ChronoSapiens software programs. Sleep statistics for a limited number of FitBit-collected traits were generated by its accompanying mobile app. Broad sense heritability was computed on a set of 33 MZ and 38 DZ twin pairs with complete data using both OpenMX and SOLAR software. These analyses yielded a large number of actimetry-derived traits, 20 of which showed high heritability (h2 > 0.6), seven of which remain significant after Bonferroni correction. These results indicate that actimetry enables assessing a range of phenotypes with substantial heritability that may be useful as endophenotypes for genetic studies.

Genetic studies of accelerometer-based sleep measures yield new insights into human sleep behaviour

Sleep is an essential human function but its regulation is poorly understood. Using accelerometer data from 85,670 UK Biobank participants, we perform a genome-wide association study of 8 derived sleep traits representing sleep quality, quantity and timing, and validate our findings in 5,819 individuals. We identify 47 genetic associations at P < 5 × 10−8, of which 20 reach a stricter threshold of P < 8 × 10−10. These include 26 novel associations with measures of sleep quality and 10 with nocturnal sleep duration. The majority of identified variants associate with a single sleep trait, except for variants previously associated with restless legs syndrome. For sleep duration we identify a missense variant (p.Tyr727Cys) in PDE11A as the likely causal variant. As a group, sleep quality loci are enriched for serotonin processing genes. Although accelerometer-derived measures of sleep are imperfect and may be affected by restless legs syndrome, these findings provide new biological insights into sleep compared to previous efforts based on self-report sleep measures.

Inter-relationship between sleep quality, insomnia and sleep disorders in professional soccer players

ObjectiveInsufficient sleep duration and quality has negative effects on athletic performance, injury susceptibility and athlete development. This study aimed to assess the sleep characteristics of professional Qatar Stars League (QSL)...

Abstract MP27: The Association Between Psychosocial Factors and Sleep Among African-American Men and Women, the Jackson Heart Sleep Study

Background: Emerging evidence suggests that sleep traits and disorders are strong predictors of cardiovascular disease (CVD), particularly among African-Americans. Identifying determinants of insufficient sleep among African-Americans may help to target interventions and potentially reduce CVD burden. Psychosocial factors may be particularly relevant to sleep health among African-Americans; however, more research is needed using objective and well-validated sleep assessments. We investigated associations of individual and aggregate psychosocial factors (e.g. stress, depression, anxiety) with objectively-measured sleep traits and insomnia; and examined differences by sex among African-Americans. Methods: Between 2012 and 2016, Jackson Heart Sleep Study (JHSS) participants (N=913) underwent 7-day wrist actigraphy, had a clinic visit and completed questionnaires. Actigraphy-based measures included short sleep duration (&lt;6 hours), low sleep efficiency (&lt; 85%), and wake after sleep onset (WASO). Insomnia was assessed by the Women’s Health Initiative Insomnia Rating Scale (WHIIRS ≥10). A composite psychosocial factors variable was created based on the number of high-level factors that the participant reported: top quintile of stress (Perceived Stress Scale ≥ 18), high depressive symptoms (Center for Epidemiologic Studies Depression Scale-20, excluding restless sleep, ≥ 16), and top quintile of anxiety (State-Trait Anxiety Inventory score ≥ 38). Linear and logistic regression models were fit to test associations between psychosocial factors and sleep outcomes, adjusted for demographics, socioeconomic status, body mass index (BMI), and physical activity. Psychosocial factors and sex interactions were tested in adjusted models. Results: JHSS participants had a mean age of 63.4 years (standard deviation: 10.7), 33.6% were male, 53.6% had a college degree and the mean BMI was 31.9 kg/m 2 (6.9). Short sleep and low sleep efficiency were common, 26.1% and 30.0%, respectively. The average WASO was 54.5 (23.5) minutes. Psychosocial factors (composite and individually) were associated with insomnia. Adverse psychosocial factors were associated with a higher odds of insomnia, adjusted odds ratio (aOR)=1.65 (95% confidence interval: 1.39, 1.95). High anxiety, but not stress or depressive symptoms were associated with a short sleep duration, aOR=2.00 (1.34, 2.98). There was no evidence of associations between psychosocial factors and sleep efficiency or WASO in the overall sample. However, in males only, high anxiety and stress were associated with lower sleep efficiency, P ≤0.05 for all. Conclusion: Stress and negative emotional state, anxiety and depressive symptoms were associated with insomnia. Short sleep duration was specifically associated with anxiety. Psychosocial factors may be a point of intervention for improving sleep health, particularly among men.

Can the elite slalom kayaker’s performance be correlated with anthropometric, nutritional, genetic, psychological as sleep traits?

Abstract AIMS The aims of this study were to investigate and characterize the anthropometric, nutritional, genetic, psychological and sleep variables of slalom kayakers, and to verify the correlation of these variables with the slalom kayakers’ performance. METHODS Ten elite Brazilian team slalom kayakers participated of this study. Nutritional analysis was made by the Food Record (three days), 24 Hour Dietary Recall and Food Frequency Questionnaire. The ACE I/D, AGTMet235Thr, ACTN3R577X and BDKRB2+9/-9 were genotyped for genetic profile. The Profile of Mood States (POMS) and Sports Competition Anxiety Test (SCAT) were applied to investigate the psychological variables. The Pittsburgh Sleep Quality Index (PSQI), Epworth Sleep Scale (ESS) and Morningness-eveningness questionnaire (MEQ) were used for sleep traits analysis. Performance trials were performed on a white-water course with 24 gates, and finish time was considered as the variable related to performance. RESULTS Significant correlations were obtained between Performance Time Trial and %Fat (r=0.77), Energy (r=-0.75), Protein (r=-0.76), Carbohydrate (r=-0.72), Vitamin B6 (r=-0.87), Vitamin A (r=-0.82), Thiamine (r=-0.77), Riboflavin (r=-0.71), Magnesium (r=-0.86) and Phosphorus (r=-0.74) intake, besides the Fatigue mood domain (r=0.73) and the SCAT score (r=0.67). Athletes genotyped with the I, T, R and +9 alelle also presented better performances. CONCLUSIONSIn summary, the novel results provided by this study reinforce the necessity of considering several aspects during athlete development in order to achieve better performance in competitions.

0016 Sleep Traits Accentuate the Association of Genetic Markers with Obesity: Results from the UK Biobank

0016 Sleep Traits Accentuate the Association of Genetic Markers with Obesity: Results from the UK Biobank

Functional Assays to Screen and Dissect Genomic Hits: Doubling Down on the National Investment in Genomic Research.

The National Institutes of Health have made substantial investments in genomic studies and technologies to identify DNA sequence variants associated with human disease phenotypes. The National Heart, Lung, and Blood Institute has been at the forefront of these commitments to ascertain genetic variation associated with heart, lung, blood, and sleep diseases and related clinical traits. Genome-wide association studies, exome- and genome-sequencing studies, and exome-genotyping studies of the National Heart, Lung, and Blood Institute-funded epidemiological and clinical case-control studies are identifying large numbers of genetic variants associated with heart, lung, blood, and sleep phenotypes. However, investigators face challenges in identification of genomic variants that are functionally disruptive among the myriad of computationally implicated variants. Studies to define mechanisms of genetic disruption encoded by computationally identified genomic variants require reproducible, adaptable, and inexpensive methods to screen candidate variant and gene function. High-throughput strategies will permit a tiered variant discovery and genetic mechanism approach that begins with rapid functional screening of a large number of computationally implicated variants and genes for discovery of those that merit mechanistic investigation. As such, improved variant-to-gene and gene-to-function screens-and adequate support for such studies-are critical to accelerating the translation of genomic findings. In this White Paper, we outline the variety of novel technologies, assays, and model systems that are making such screens faster, cheaper, and more accurate, referencing published work and ongoing work supported by the National Heart, Lung, and Blood Institute's R21/R33 Functional Assays to Screen Genomic Hits program. We discuss priorities that can accelerate the impressive but incomplete progress represented by big data genomic research.

Variation in sleep and metabolic function is associated with latitude and average temperature in Drosophila melanogaster.

Regulation of sleep and metabolic homeostasis is critical to an animal's survival and under stringent evolutionary pressure. Animals display remarkable diversity in sleep and metabolic phenotypes; however, an understanding of the ecological forces that select for, and maintain, these phenotypic differences remains poorly understood. The fruit fly, Drosophila melanogaster, is a powerful model for investigating the genetic regulation of sleep and metabolic function, and screening in inbred fly lines has led to the identification of novel genetic regulators of sleep. Nevertheless, little is known about the contributions of naturally occurring genetic differences to sleep, metabolic phenotypes, and their relationship with geographic or environmental gradients. Here, we quantified sleep and metabolic phenotypes in 24 D. melanogaster populations collected from diverse geographic localities. These studies reveal remarkable variation in sleep, starvation resistance, and energy stores. We found that increased sleep duration is associated with proximity to the equator and elevated average annual temperature, suggesting that environmental gradients strongly influence natural variation in sleep. Further, we found variation in metabolic regulation of sleep to be associated with free glucose levels, while starvation resistance associates with glycogen and triglyceride stores. Taken together, these findings reveal robust naturally occurring variation in sleep and metabolic traits in D. melanogaster, providing a model to investigate how evolutionary and ecological history modulate these complex traits.

Characterizing sleep spindles in 11,630 individuals from the National Sleep Research Resource

Sleep spindles are characteristic electroencephalogram (EEG) signatures of stage 2 non-rapid eye movement sleep. Implicated in sleep regulation and cognitive functioning, spindles may represent heritable biomarkers of neuropsychiatric disease. Here we characterize spindles in 11,630 individuals aged 4 to 97 years, as a prelude to future genetic studies. Spindle properties are highly reliable but exhibit distinct developmental trajectories. Across the night, we observe complex patterns of age- and frequency-dependent dynamics, including signatures of circadian modulation. We identify previously unappreciated correlates of spindle activity, including confounding by body mass index mediated by cardiac interference in the EEG. After taking account of these confounds, genetic factors significantly contribute to spindle and spectral sleep traits. Finally, we consider topographical differences and critical measurement issues. Taken together, our findings will lead to an increased understanding of the genetic architecture of sleep spindles and their relation to behavioural and health outcomes, including neuropsychiatric disorders.

0027 A GENETIC LINK BETWEEN SLEEP AND PSYCHIATRIC TRAITS

There is mounting evidence of a relationship between sleep and psychiatric traits. Sleep and circadian disturbances are commonly observed in psychiatric conditions. However, genetic studies linking these traits are limited. To systematically study the genetic links and highlight potential causal relationships, we performed genetic correlation studies of sleep and circadian traits with psychiatric traits. Previously we performed genome-wide association studies for a variety of self-reported sleep and circadian traits in the UK Biobank (in up to 115,000 people). To probe the biological links between sleep and circadian traits with psychiatric traits, we performed genetic correlation of our GWAS results with publicly available GWAS for psychiatric traits, including neuroticism, depressive symptoms, and subjective well-being using linkage disequilibrium score regression (LDSC). We found a significant and strong genetic correlation between insomnia and increased neuroticism (rg=0.47, p=7.01x10-23) and depressive symptoms (rg=0.50, p=2.30x10-17). We found neuroticism was also genetically correlated with difficulty getting up in the morning (rg 0.28, p=4.46x10-10), short sleep duration (rg=0.29, p=1.31x10-6), and increased daytime sleepiness (rg 0.21, p=1.25x10-5) and daytime napping (rg=0.20, p=2.91x10-5). We found no genetic correlation between neuroticism and self-reported chronotype, snoring, or sleep apnea. We also found similar genetic links between our sleep traits and depressive symptoms. We were able to link the genetic underpinnings of insomnia with those of psychiatric traits, suggesting a strong biological link between sleep and psychiatric traits. Moving forward it will be important to probe the causal links between these traits.

0011 ARTIFICIAL SELECTION FOR LONG AND SHORT SLEEP DURATION IN DROSOPHILA MAPS TO BROAD DEVELOPMENTAL AND SIGNALING PATHWAY GENES

Although many candidate genes have been identified for sleep, the extent to which naturally occurring polymorphisms can alter sleep duration is unknown. Here we applied an artificial selection scheme to a natural population of flies in order to determine how far night sleep duration could be driven up or down. We created an outbred population from ten Drosophila Genetic Reference Panel lines with variable sleep duration. From this outbred population, we created two short and two long-sleeping populations. We measured sleep in 100 males and 100 females of each population every generation, choosing the most extreme 25 sleepers of each sex as parents for the next generation. We maintained two additional populations as unselected controls. We used whole-genome sequences across seven generations to identify allelic variants responsible for the phenotypic changes. After 13 generations of selection, long sleepers averaged 9.97 hours more nightly sleep than short sleepers. Mean 24-hour sleep was 198.9 ± 9.5 minutes in short sleepers, comparable to severe short-sleeping flies engineered with single-gene mutations; yet these flies were created from combinations of naturally occurring alleles. Selection for night sleep altered other sleep traits such as day sleep duration and night average bout length, but the numbers of night bouts were reduced in both long and short sleepers, increasing the consolidation of sleep. Flies from these populations also had normal lifespan, suggesting that there is little physiological consequence to being a natural long or short sleeper. Whole-genome sequences revealed thousands of changes in polymorphic allele frequencies between any two generations of selection. However, regressing allele frequency change across generations reduced the number of candidate polymorphisms to 126, implicating 80 candidate genes. Many of these genes could be connected via known physical and genetic interactions with several conserved developmental and signaling pathways such as the EGFR and Wnt pathways. Sleep duration can be driven to very high or low levels, suggesting that extreme short or long sleepers may exist in nature. Highly conserved broad developmental and signaling pathways influence natural variation in sleep duration. Intramural Research Program, National Institutes of Health, NHLBI.

Genome-wide association analyses of sleep disturbance traits identify new loci and highlight shared genetics with neuropsychiatric and metabolic traits.

Chronic sleep disturbances, associated with cardiometabolic diseases, psychiatric disorders and all-cause mortality, affect 25-30% of adults worldwide. Although environmental factors contribute substantially to self-reported habitual sleep duration and disruption, these traits are heritable and identification of the genes involved should improve understanding of sleep, mechanisms linking sleep to disease and development of new therapies. We report single- and multiple-trait genome-wide association analyses of self-reported sleep duration, insomnia symptoms and excessive daytime sleepiness in the UK Biobank (n = 112,586). We discover loci associated with insomnia symptoms (near MEIS1, TMEM132E, CYCL1 and TGFBI in females and WDR27 in males), excessive daytime sleepiness (near AR-OPHN1) and a composite sleep trait (near PATJ (INADL) and HCRTR2) and replicate a locus associated with sleep duration (at PAX8). We also observe genetic correlation between longer sleep duration and schizophrenia risk (rg = 0.29, P = 1.90 × 10-13) and between increased levels of excessive daytime sleepiness and increased measures for adiposity traits (body mass index (BMI): rg = 0.20, P = 3.12 × 10-9; waist circumference: rg = 0.20, P = 2.12 × 10-7).

Systems Genetic Analyses Highlight a TGFβ-FOXO3 Dependent Striatal Astrocyte Network Conserved across Species and Associated with Stress, Sleep, and Huntington's Disease.

Recent systems-based analyses have demonstrated that sleep and stress traits emerge from shared genetic and transcriptional networks, and clinical work has elucidated the emergence of sleep dysfunction and stress susceptibility as early symptoms of Huntington's disease. Understanding the biological bases of these early non-motor symptoms may reveal therapeutic targets that prevent disease onset or slow disease progression, but the molecular mechanisms underlying this complex clinical presentation remain largely unknown. In the present work, we specifically examine the relationship between these psychiatric traits and Huntington's disease (HD) by identifying striatal transcriptional networks shared by HD, stress, and sleep phenotypes. First, we utilize a systems-based approach to examine a large publicly available human transcriptomic dataset for HD (GSE3790 from GEO) in a novel way. We use weighted gene coexpression network analysis and differential connectivity analyses to identify transcriptional networks dysregulated in HD, and we use an unbiased ranking scheme that leverages both gene- and network-level information to identify a novel astrocyte-specific network as most relevant to HD caudate. We validate this result in an independent HD cohort. Next, we computationally predict FOXO3 as a regulator of this network, and use multiple publicly available in vitro and in vivo experimental datasets to validate that this astrocyte HD network is downstream of a signaling pathway important in adult neurogenesis (TGFβ-FOXO3). We also map this HD-relevant caudate subnetwork to striatal transcriptional networks in a large (n = 100) chronically stressed (B6xA/J)F2 mouse population that has been extensively phenotyped (328 stress- and sleep-related measurements), and we show that this striatal astrocyte network is correlated to sleep and stress traits, many of which are known to be altered in HD cohorts. We identify causal regulators of this network through Bayesian network analysis, and we highlight their relevance to motor, mood, and sleep traits through multiple in silico approaches, including an examination of their protein binding partners. Finally, we show that these causal regulators may be therapeutically viable for HD because their downstream network was partially modulated by deep brain stimulation of the subthalamic nucleus, a medical intervention thought to confer some therapeutic benefit to HD patients. In conclusion, we show that an astrocyte transcriptional network is primarily associated to HD in the caudate and provide evidence for its relationship to molecular mechanisms of neural stem cell homeostasis. Furthermore, we present a unified systems-based framework for identifying gene networks that are associated with complex non-motor traits that manifest in the earliest phases of HD. By analyzing and integrating multiple independent datasets, we identify a point of molecular convergence between sleep, stress, and HD that reflects their phenotypic comorbidity and reveals a molecular pathway involved in HD progression.

Associations of self-reported and objectively measured sleep disturbances with depression among primary caregivers of children with disabilities.

ObjectiveThe objective of this study was to determine the association between sleep and depression using both self-reported (subjective) and actigraphic (objective) sleep traits.MethodsA cross-sectional study was conducted among 175 female primary caregivers of children with disabilities receiving care at a rehabilitation center in Punta Arenas, Chile. The eight-item Patient Health Questionnaire was used to ascertain participants’ depression status. The Pittsburgh Sleep Quality Index was used to define subjective, or perceived, sleep quality. Wrist-worn actigraph monitors, worn for seven consecutive nights, were used to characterize objective sleep quality and disturbances. Interviewer-administered questionnaires were used to collect information on sociodemographic and lifestyle factors. Linear regression models were fit using continuous sleep parameters as the dependent variables and depression status as the independent variable. Multivariable models were adjusted for body mass index, marital status, smoking status, education level, and children’s disabilities.ResultsUsing an eight-item Patient Health Questionnaire score ≥10, 26.3% of participants presented with depression. Depressed women were more likely to self-report overall poorer (subjective) sleep compared to non-depressed women; however, differences in sleep were not consistently noted using actigraphic (objective) sleep traits. Among the depressed, both sleep duration and total time in bed were significantly underestimated. In multivariable models, depression was negatively associated with sleep duration using both subjective (β=−0.71, standard error [SE] =0.25; P=0.006) and objective sleep (β=−0.42, SE =0.19; P=0.026).ConclusionThe association between sleep and depression differed comparing subjective and objective methods of assessment. Research strategies allowing for the integration of both perceived and objective measures of sleep traits are encouraged.

Neurofibromin Loss of Function Drives Excessive Grooming in Drosophila.

Neurofibromatosis I is a common genetic disorder that results in tumor formation, and predisposes individuals to a range of cognitive/behavioral symptoms, including deficits in attention, visuospatial skills, learning, language development, and sleep, and autism spectrum disorder-like traits. The nf1-encoded neurofibromin protein (Nf1) exhibits high conservation, from the common fruit fly, Drosophila melanogaster, to humans. Drosophila provides a powerful platform to investigate the signaling cascades upstream and downstream of Nf1, and the fly model exhibits similar behavioral phenotypes to mammalian models. In order to understand how loss of Nf1 affects motor behavior in flies, we combined traditional activity monitoring with video analysis of grooming behavior. In nf1 mutants, spontaneous grooming was increased up to 7x. This increase in activity was distinct from previously described dopamine-dependent hyperactivity, as dopamine transporter mutants exhibited slightly decreased grooming. Finally, we found that relative grooming frequencies can be compared in standard activity monitors that measure infrared beam breaks, enabling the use of activity monitors as an automated method to screen for grooming phenotypes. Overall, these data suggest that loss of nf1 produces excessive activity that is manifested as increased grooming, providing a platform to dissect the molecular genetics of neurofibromin signaling across neuronal circuits.

Intimate Partner Violence Is Associated with Stress-Related Sleep Disturbance and Poor Sleep Quality during Early Pregnancy.

ObjectivesTo examine the associations of Intimate partner violence (IPV) with stress-related sleep disturbance (measured using the Ford Insomnia Response to Stress Test [FIRST]) and poor sleep quality (measured using the Pittsburgh Sleep Quality Index [PSQI]) during early pregnancy.MethodsThis cross-sectional study included 634 pregnant Peruvian women. In-person interviews were conducted in early pregnancy to collect information regarding IPV history, and sleep traits. Adjusted odds ratios (aOR) and 95% confidence intervals (95%CIs) were calculated using logistic regression procedures.ResultsLifetime IPV was associated with a 1.54-fold increased odds of stress-related sleep disturbance (95% CI: 1.08–2.17) and a 1.93-fold increased odds of poor sleep quality (95% CI: 1.33–2.81). Compared with women experiencing no IPV during lifetime, the aOR (95% CI) for stress-related sleep disturbance associated with each type of IPV were: physical abuse only 1.24 (95% CI: 0.84–1.83), sexual abuse only 3.44 (95%CI: 1.07–11.05), and physical and sexual abuse 2.51 (95% CI: 1.27–4.96). The corresponding aORs (95% CI) for poor sleep quality were: 1.72 (95% CI: 1.13–2.61), 2.82 (95% CI: 0.99–8.03), and 2.50 (95% CI: 1.30–4.81), respectively. Women reporting any IPV in the year prior to pregnancy had increased odds of stress-related sleep disturbance (aOR = 2.07; 95% CI: 1.17–3.67) and poor sleep quality (aOR = 2.27; 95% CI: 1.30–3.97) during pregnancy.ConclusionLifetime and prevalent IPV exposures are associated with stress-related sleep disturbance and poor sleep quality during pregnancy. Our findings suggest that sleep disturbances may be important mechanisms that underlie the lasting adverse effects of IPV on maternal and perinatal health.

How to Understand Sleep and Sleep Problems in Patients with Prader-Willi Syndrome?

Sleep problems occur frequently among patients with Prader-Willi syndrome (PWS). The most common problem is excessive daytime sleepiness (EDS) that are closely related to of sleep-related breathing disorder (SRBD) such as obstructive sleep apnea (OSA) and congenital hypoventilation syndrome. Obesity, craniofacial dysmorphism and muscular hypotonia of patients with PWS may increase the risk of SRBD. Sleep apneas can interrupt the continuity of sleep, and these disruptions result in a decrease in both the quality and quantity of sleep. In addition to SRBD, other sleep disorders have been reported, such as hypersomnia, a primary abnormality of the rapid eye movement (REM) sleep and narcolepsy traits at sleep onset REM sleep. Patients with PWS have intrinsic abnormalities of sleep-wake cycles due to hypothalamic dysfunction. The treatment of EDS and other sleep disorders in PWS are similar to standard treatments. Correction of sleep hygiene such as sufficient amount of sleep, maintenance of regular sleep-wake rhythm, and planned naps are important. After comprehensive evaluation of sleep disturbances, CPAP or surgery should be recommended for treatment of SRBD. Remaining EDS or narcolepsy-like syndrome are controlled by stimulant medication. Bright light therapy might be beneficial for disturbed circadian sleep-wake rhythm caused by hypothalamic dysfunction.

Noninvasive dissection of mouse sleep using a piezoelectric motion sensor

BackgroundChanges in autonomic control cause regular breathing during NREM sleep to fluctuate during REM. Piezoelectric cage-floor sensors have been used to successfully discriminate sleep and wake states in mice based on signal features related to respiration and other movements. This study presents a classifier for noninvasively classifying REM and NREM using a piezoelectric sensor. New methodVigilance state was scored manually in 4-s epochs for 24-h EEG/EMG recordings in 20 mice. An unsupervised classifier clustered piezoelectric signal features quantifying movement and respiration into three states: one active; and two inactive with regular and irregular breathing, respectively. These states were hypothesized to correspond to Wake, NREM, and REM, respectively. States predicted by the classifier were compared against manual EEG/EMG scores to test this hypothesis. ResultsUsing only piezoelectric signal features, an unsupervised classifier distinguished Wake with high (89% sensitivity, 96% specificity) and REM with moderate (73% sensitivity, 75% specificity) accuracy, but NREM with poor sensitivity (51%) and high specificity (96%). The classifier sometimes confused light NREM sleep – characterized by irregular breathing and moderate delta EEG power – with REM. A supervised classifier improved sensitivities to 90, 81, and 67% and all specificities to over 90% for Wake, NREM, and REM, respectively. Comparison with existing methodsUnlike most actigraphic techniques, which only differentiate sleep from wake, the proposed piezoelectric method further dissects sleep based on breathing regularity into states strongly correlated with REM and NREM. ConclusionsThis approach could facilitate large-sample screening for genes influencing different sleep traits, besides drug studies or other manipulations.