The Statin Target HMG-Coenzyme a Reductase (Hmgcr) Regulates Sleep Homeostasis in Drosophila

Statins, HMG Coenzyme A Reductase (HMGCR) inhibitors, are a first-line therapy, used to reduce hypercholesterolemia and the risk for cardiovascular events. While sleep disturbances are recognized as a side-effect of statin treatment, the impact of statins on sleep is under debate. Using Drosophila, we discovered a novel role for Hmgcr in sleep modulation. Loss of pan-neuronal Hmgcr expression affects fly sleep behavior, causing a decrease in sleep latency and an increase in sleep episode duration. We localized the pars intercerebralis (PI), equivalent to the mammalian hypothalamus, as the region within the fly brain requiring Hmgcr activity for proper sleep maintenance. Lack of Hmgcr expression in the PI insulin-producing cells recapitulates the sleep effects of pan-neuronal Hmgcr knockdown. Conversely, loss of Hmgcr in a different PI subpopulation, the corticotropin releasing factor (CRF) homologue-expressing neurons (DH44 neurons), increases sleep latency and decreases sleep duration. The requirement for Hmgcr activity in different neurons signifies its importance in sleep regulation. Interestingly, loss of Hmgcr in the PI does not affect circadian rhythm, suggesting that Hmgcr regulates sleep by pathways distinct from the circadian clock. Taken together, these findings suggest that Hmgcr activity in the PI is essential for proper sleep homeostasis in flies.

A probabilistic model for the ultradian timing of REM sleep in mice

A salient feature of mammalian sleep is the alternation between rapid eye movement (REM) and non-REM (NREM) sleep. However, how these two sleep stages influence each other and thereby regulate the timing of REM sleep episodes is still largely unresolved. Here, we developed a statistical model that specifies the relationship between REM and subsequent NREM sleep to quantify how REM sleep affects the following NREM sleep duration and its electrophysiological features in mice. We show that a lognormal mixture model well describes how the preceding REM sleep duration influences the amount of NREM sleep till the next REM sleep episode. The model supports the existence of two different types of sleep cycles: Short cycles form closely interspaced sequences of REM sleep episodes, whereas during long cycles, REM sleep is first followed by an interval of NREM sleep during which transitions to REM sleep are extremely unlikely. This refractory period is characterized by low power in the theta and sigma range of the electroencephalogram (EEG), low spindle rate and frequent microarousals, and its duration proportionally increases with the preceding REM sleep duration. Using our model, we estimated the propensity for REM sleep at the transition from NREM to REM sleep and found that entering REM sleep with higher propensity resulted in longer REM sleep episodes with reduced EEG power. Compared with the light phase, the buildup of REM sleep propensity was slower during the dark phase. Our data-driven modeling approach uncovered basic principles underlying the timing and duration of REM sleep episodes in mice and provides a flexible framework to describe the ultradian regulation of REM sleep in health and disease.

Regular Caffeine Intake Delays REM Sleep Promotion and Attenuates Sleep Quality in Healthy Men

Acute caffeine intake can attenuate homeostatic sleep pressure and worsen sleep quality. Caffeine intake—particularly in high doses and close to bedtime—may also affect circadian-regulated rapid eye movement (REM) sleep promotion, an important determinant of subjective sleep quality. However, it is not known whether such changes persist under chronic caffeine consumption during daytime. Twenty male caffeine consumers (26.4 ± 4 years old, habitual caffeine intake 478.1 ± 102.8 mg/day) participated in a double-blind crossover study. Each volunteer completed a caffeine (3 × 150 mg caffeine daily for 10 days), a withdrawal (3 × 150 mg caffeine for 8 days then placebo), and a placebo condition. After 10 days of controlled intake and a fixed sleep-wake cycle, we recorded electroencephalography for 8 h starting 5 h after habitual bedtime (i.e., start on average at 04:22 h which is around the peak of circadian REM sleep promotion). A 60-min evening nap preceded each sleep episode and reduced high sleep pressure levels. While total sleep time and sleep architecture did not significantly differ between the three conditions, REM sleep latency was longer after daily caffeine intake compared with both placebo and withdrawal. Moreover, the accumulation of REM sleep proportion was delayed, and volunteers reported more difficulties with awakening after sleep and feeling more tired upon wake-up in the caffeine condition compared with placebo. Our data indicate that besides acute intake, also regular daytime caffeine intake affects REM sleep regulation in men, such that it delays circadian REM sleep promotion when compared with placebo. Moreover, the observed caffeine-induced deterioration in the quality of awakening may suggest a potential motive to reinstate caffeine intake after sleep.

DPSleep: Open-Source Longitudinal Sleep Analysis From Accelerometer Data (Preprint)

UNSTRUCTURED Wearable devices are now widely available to collect continuous objective behavioral data from individuals and to measure sleep. Here we introduce an open-source pipeline for the deep phenotyping of sleep, "DPSleep", that uses algorithms to detect missing data, calculate activity levels, and finally estimate the major Sleep Episode onset and offset. The pipeline allows for manual quality control adjustment and correction for time zone changes. We illustrate the utility of the pipeline with data from participants studied for more than 200 days. Actigraphy-based measures of sleep duration are associated with self-report rating of sleep quality. Simultaneous measures of smartphone use and GPS data support the sleep timing inferences and reveal how phone measures of sleep can differ from actigraphy data. We discuss the uses of DPSleep in relation to other available sleep estimation approaches and provide example use cases that include multi-dimensional, deep dynamic longitudinal phenotyping associated with mental illness.

An Asymmetrical Hypothesis for the NREM-REM Sleep Alternation—What Is the NREM-REM Cycle?

Since the discovery of rapid eye movement (REM) sleep (Aserinsky and Kleitman, 1953), sleep has been described as a succession of cycles of non-REM (NREM) and REM sleep episodes. The hypothesis of short-term REM sleep homeostasis, which is currently the basis of most credible theories on sleep regulation, is built upon a positive correlation between the duration of a REM sleep episode and the duration of the interval until the next REM sleep episode (inter-REM interval): the duration of REM sleep would therefore predict the duration of this interval. However, the high variability of inter-REM intervals, especially in polyphasic sleep, argues against a simple oscillator model. A new “asymmetrical” hypothesis is presented here, where REM sleep episodes only determine the duration of a proportional post-REM refractory period (PRRP), during which REM sleep is forbidden and the only remaining options are isolated NREM episodes or waking. After the PRRP, all three options are available again (NREM, REM, and Wake). I will explain why I think this hypothesis also calls into question the notion of NREM-REM sleep cycles.

DPSleep: Open-Source Longitudinal Sleep Analysis From Accelerometer Data

Wearable devices are now widely available to collect continuous objective behavioral data from individuals and to measure sleep. Here we introduce a pipeline to infer sleep onset, duration, and quality from raw accelerometer data and then quantify relationships between derived sleep metrics and other variables of interest. The pipeline released here for the deep phenotyping of sleep, as the “DPSleep” software package, uses (a) a stepwise algorithm to detect missing data; (b) within-individual, minute-based, spectral power percentiles of activity; and (c) iterative, forward- and backward-sliding windows to estimate the major Sleep Episode onset and offset. Software modules allow for manual quality control adjustment of derived sleep features and correction for time zone changes. In this report, we illustrate the pipeline with data from participants studied for more than 200 days each. Actigraphy-based measures of sleep duration are associated with self-report rating of sleep quality. Simultaneous measures of smartphone use and GPS location data support the validity of the sleep timing inferences and reveal how phone measures of sleep timing can differ from actigraphy data. We discuss the uses of DPSleep in relation to other available sleep estimation approaches and provide example use cases that include multi-dimensional, deep longitudinal phenotyping, extended measurement of dynamics associated with mental illness, and the possibility of combining wearable actigraphy and personal electronic device data (e.g., smartphone, tablet) to measure individual differences across a wide range of behavioral variation in health and disease.

Estimating Burden of Disease Among Blind Individuals With Non-24-Hour Sleep-Wake Disorder

Purpose: To quantify the burden of disease in blind patients with Non-24-H Sleep- Wake Disorder (N24HSWD), utilizing longitudinal sleep diary data. N24HSWD is a circadian disorder characterized by a cyclical pattern of aberrant circadian and sleep-wake cycles that are associated with increased frequency of sleep episodes during the school/work day hours. Daytime sleep episodes would be predicted to decrease the opportunity for school/work participation, significantly impacting the quality of life of the patient.Methods: We used the sleep diary data of daytime sleep from a period of ~90 days in blind individuals that presented with a sleep complaint. These subjects were identified from a group of blind individuals with N24HSWD (n = 121) and a control group of blind individuals without N24HSWD (n = 57).Results: N24HSWD patients had more frequent and longer episodes of daytime sleep as compared to a control group. Using duration of daytime sleep as a surrogate for defining a healthy or unhealthy day, N24HSWD patients also had significantly fewer healthy days, defined by daytime sleep free days (DSFD), days without a sleep episode between 9:00 a.m. and 5:00 p.m, as compared to the control group.Conclusion: Daytime sleep free day (DSFD) is a useful and specific measure of disease burden in patients with N24HSWD and it is predicted to be correlated with the standardized HRQOL-4, Healthy Days measurement.

Sleep Terrors: An Updated Review

Background: Sleep terrors are common, frightening, but fortunately benign events. Familiarity with this condition is important so that an accurate diagnosis can be made. Objective: : To familiarize physicians with the clinical manifestations, diagnosis, and management of children with sleep terrors. Methods: A PubMed search was completed in Clinical Queries using the key terms " sleep terrors" OR " night terrors". The search strategy included meta-analyses, randomized controlled trials, clinical trials, observational studies, and reviews. Only papers published in the English literature were included in this review. The information retrieved from the above search was used in the compilation of the present article. Results: It is estimated that sleep terrors occur in 1 to 6.5% of children 1 to 12 years of age. Sleep terrors typically occur in children between 4 and 12 years of age, with a peak between 5 and 7 years of age. The exact etiology is not known. Developmental, environmental, organic, psychological, and genetic factors have been identified as a potential cause of sleep terrors. Sleep terrors tend to occur within the first three hours of the major sleep episode, during arousal from stage three or four non-rapid eye movement (NREM) sleep. In a typical attack, the child awakens abruptly from sleep, sits upright in bed or jumps out of bed, screams in terror and intense fear, is panicky, and has a frightened expression. The child is confused and incoherent: verbalization is generally present but disorganized. Autonomic hyperactivity is manifested by tachycardia, tachypnea, diaphoresis, flushed face, dilated pupils, agitation, tremulousness, and increased muscle tone. The child is difficult to arouse and console and may express feelings of anxiety or doom. In the majority of cases, the patient does not awaken fully and settles back to quiet and deep sleep. There is retrograde amnesia for the attack the following morning. Attempts to interrupt a sleep terror episode should be avoided. As sleep deprivation can predispose to sleep terrors, it is important that the child has good sleep hygiene and an appropriate sleeping environment. Medical intervention is usually not necessary, but clonazepam may be considered on a short-term basis at bedtime if sleep terrors are frequent and severe or are associated with functional impairment, such as fatigue, daytime sleepiness, and distress. Anticipatory awakening, performed approximately half an hour before the child is most likely to experience a sleep terror episode, is often effective for the treatment of frequently occurring sleep terrors. Conclusion: Most children outgrow the disorder by late adolescence. In the majority of cases, there is no specific treatment other than reassurance and parental education. Underlying conditions, however, should be treated if possible and precipitating factors should be avoided.

Stress Modulates the Balance between Hippocampal and Motor Networks during Motor Memory Processing

The functional interaction between hippocampo- and striato-cortical regions during motor sequence learning is essential to trigger optimal memory consolidation. Based on previous evidence from other memory domains that stress alters the balance between these systems, we investigated whether exposure to stress prior to motor learning modulates motor memory processes. Seventy-two healthy young individuals were exposed to a stressful or nonstressful control intervention prior to training on a motor sequence learning task in a magnetic resonance imaging (MRI) scanner. Consolidation was assessed with an MRI retest after a sleep episode. Behavioral results indicate that stress prior to learning did not influence motor performance. At the neural level, stress induced both a larger recruitment of sensorimotor regions and a greater disengagement of hippocampo-cortical networks during training. Brain-behavior regression analyses showed that while this stress-induced shift from (hippocampo-)fronto-parietal to motor networks was beneficial for initial performance, it was detrimental for consolidation. Our results provide the first experimental evidence that stress modulates the neural networks recruited during motor memory processing and therefore effectively unify concepts and mechanisms from diverse memory fields. Critically, our findings suggest that intersubject variability in brain responses to stress determines the impact of stress on motor learning and subsequent consolidation.

Regular caffeine intake attenuates REM sleep promotion and sleep quality in healthy men

Acute caffeine intake can attenuate homeostatic sleep pressure and worsen sleep quality. Besides, caffeine intake – particularly in high doses and close to bedtime – may also affect circadian-regulated REM sleep promotion, an important determinant of subjective sleep quality. However, it is not known whether such changes persist under chronic caffeine consumption during daytime. Twenty male caffeine consumers (26.4 ± 4 years old, habitual caffeine intake 478.1 ± 102.8 mg/day) participated in a double-blind crossover study. Each volunteer completed a caffeine (3 × 150 mg caffeine daily), a withdrawal (3 × 150 mg caffeine for eight days then placebo), and a placebo condition. After ten days of controlled intake and a fixed sleep-wake cycle, we recorded 8 h of electroencephalography starting 5 h after habitual bedtime (i.e., start on average at 04:22 am which is around the peak of circadian REM sleep promotion). A 60 min evening nap preceded each sleep episode and reduced high sleep pressure levels. While total sleep time and sleep architecture did not significantly differ between the three conditions, REM latency was longer after daily caffeine intake compared to both placebo and withdrawal. Moreover, the accumulation of REM sleep proportion was slower, and volunteers reported more difficulties at awakening after sleep and feeling more tired upon wake-up in the caffeine condition compared to placebo. Our data indicate that besides acute also regular daytime caffeine intake affects REM sleep regulation in men. We have evidence that regular caffeine intake during daytime weakens circadian sleep promotion when compared to placebo. Moreover, the observed caffeine-induced deterioration in the quality of awakening may suggest a potential motive to reinstate caffeine intake after sleep.