Individual Differences In Sleep Research Articles

Managing cabin crew fatigue during ultra-long range operations

IntroductionUltra-long range (ULR) flights have the potential to increase fatigue-related risk for cabin crew, if the extended flight times are associated with extended wakefulness, sleep loss and higher levels of crew fatigue. ULR flights may also require longer opportunities for recovery sleep. This study evaluates the utilization of fatigue risk mitigations for cabin crew operating the Auckland – Chicago ULR route with a two-day layover.Methods65 cabin crew (45 women; aged 20–59 years) wore an actigraph and completed a sleep/duty diary for 3 local nights prior to, throughout, and for 3 local nights after a ULR trip. Crewmembers rated their fatigue (Samn-Perelli Crew Status Check), sleepiness (Karolinska Sleepiness Scale), and workload (OW; NASA-TLX) at key times during each flight. Jet lag was rated each day at home and during layover.ResultsFatigue and sleepiness were highest at top-of-descent and after landing and were higher on the inbound flight than on the outbound flight. For every hour of additional sleep in-flight, top-of-descent fatigue ratings decreased by 0.24 points and top-of-descent sleepiness ratings decreased by 0.38, whereas top-of-descent fatigue and sleepiness ratings increased by 0.24 points with every 10-point increase in OW ratings. Crew slept more in the 24-hours prior to the outbound (M = 8.5 h) and inbound flights (M = 9.1 h) compared to pre-trip baseline days (M = 8.2 h). Post-trip, crew slept more during the first day (M = 9.9 h) compared to baseline, with 95% taking a daytime nap. Jet lag ratings decreased daily on return home but were still higher on the fourth day than on the day of the outbound flight.DiscussionCabin crew prepare for ULR flights by obtaining more sleep prior to departure. However, large individual differences in sleep and declining jet lag ratings across pre-trip days suggest that some crewmembers may still be recovering from a previous trip. Further refinement of in-flight sleep strategies and workload mitigations could be considered for managing fatigue risk at top-of-descent. Findings also highlight the importance of a protected period of post-trip rest to facilitate cabin crews' recovery from the effects of sleep restriction and circadian disruption associated with this ULR trip.

Hunt for mammalian sleep-regulating genes

Genetics is one of the various approaches adopted to understand and control mammalian sleep. Reverse genetics, which is usually applied to analyze sleep in gene-deficient mice, has been the mainstream field of genetic studies on sleep for the past three decades and has revealed that various molecules, including orexin, are involved in sleep regulation. Recently, forward genetic studies in humans and mice have identified gene mutations responsible for heritable sleep abnormalities, such as SIK3, NALCN, DEC2, the neuropeptide S receptor, and β1 adrenergic receptor. Furthermore, the protein kinase A-SIK3 pathway was shown to represent the intracellular neural signaling for sleep need. Large-scale genome-wide analyses of human sleep have been conducted, and many gene loci associated with individual differences in sleep have been found. The development of genome-editing technology and gene transfer by an adeno-associated virus has updated and expanded the genetic studies on mammals. These efforts are expected to elucidate the mechanisms of sleep–wake regulation and develop new therapeutic interventions for sleep disorders.

Live fast, die young and sleep later: Life history strategy and human sleep behavior.

Background and objectivesLife History Theory (LHT) describes trade-offs that organisms make with regard to three investment pathways: growth, maintenance and reproduction. In light of the reparative functions of sleep, we examine sleep behaviors and corresponding attitudes as proximate manifestations of an individual’s underlying relative prioritization of short-term reproduction versus long-term maintenance.MethodologyWe collected survey data from 568 participants across two online studies having different participant pools. We use a mixture of segmented and hierarchical regression models, structural equation modeling and machine learning to infer relationships between sleep duration/quality, attitudes about sleep and biodemographic/psychometric measures of life history strategy (LHS).ResultsAn age-mediated U- or V-shaped relationship appears when LHS is plotted against habitual sleep duration, with the fastest strategies occupying the sections of the curve with the highest mortality risk: < 6.5 hr (short sleep) and > 8.5 hr (long sleep). LH ‘fastness’ is associated with increased sleepiness and worse overall sleep quality: delayed sleep onset latency, more wakefulness after sleep onset, higher sleep–wake instability and greater sleep duration variability. Hedonic valuations of sleep may mediate the effects of LHS on certain sleep parameters.Conclusions and implicationsThe costs of deprioritizing maintenance can be parameterized in the domain of sleep, where ‘life history fastness’ corresponds with sleep patterns associated with greater senescence and mortality. Individual differences in sleep having significant health implications can thus be understood as components of lifelong trajectories likely stemming from calibration to developmental circumstances. Relatedly, hedonic valuations of sleep may constitute useful avenues for non-pharmacological management of chronic sleep disorders.Lay Summary: Sleep is essential because it allows the body to repair and maintain itself. But time spent sleeping is time that cannot be spent doing other things. People differ in how much they prioritize immediate rewards, including sociosexual opportunities, versus long-term goals. In this research, we show that individual differences in sleep behaviors, and attitudes toward sleep, correspond with psychological and behavioral differences reflecting such differing priorities. Orientation toward sleep can thus be understood as part of the overall lifetime strategies that people pursue.

Discovering genetic variants contributing to sleep dysfunction in presymptomatic Alzheimer’s mice

AbstractBackgroundDisordered sleep is frequently observed in Alzheimer’s disease patients. Sleep loss is associated with increased Aβ and tau accumulation in both AD patients and model organisms. Furthermore, cognitively intact individuals with impaired sleep are at higher risk for AD. Although individual differences in sleep are known to be highly heritable, little is known of the genetic factors associated with sleep dysfunction in aging and AD and if these contribute to disease development.MethodSleep was assessed at a presymptomatic age (6‐7 months) in a panel of genetically diverse mice carrying familial AD mutations, which better models complex etiology of human AD (AD‐BXDs; Neuner et al 2019). Sleep‐wake activity was measured for five consecutive days using the PiezoSleep tracking system across 25 AD‐BXD strains and their nontransgenic littermates (Ntg‐BXD).ResultAD‐BXD mice slept significantly less during the dark cycle compared to Ntg‐BXDs. Additionally, reduction of sleep was observed during the transition from dark to the light cycle, suggesting disruption of circadian function. Females slept less than males regardless of AD mutation status. We identified a significant quantitative trait locus (QTL) on chromosome 9 associated with total sleep, this region is syntenic with a regions on the human chromosome 11, harboring six sleep‐associated human GWAS SNPs, demonstrating the relevance of this region to human biology. Additionally, we identified a QTL for hourly sleep at ZT14 that mapped to intron 1 of the gene Kirrel3 of chromosome 9 (∼20 mb downstream of the sleep‐QTL). Differential gene expression implicates Kirrel3 as a novel target‐gene for validation.ConclusionWe provide the first evidence that genetic factors interact with AD mutations to influence sleep behavior, and identified two regions causally associated with variation in sleep in the AD‐BXDs. Mouse‐to‐human comparison suggest that both region are relevant to humans, demonstrating the value of the AD‐BXDs as a translational AD model. Future work will leverage genome engineering to correct sleep‐associated variants to test the delay or prevention of cognitive deficits onset apparent in the AD‐BXDs by 14 months of age. These studies may identify novel therapeutic targets to treat AD dementia.

The impact of structured sleep schedules prior to an in-laboratory study: Individual differences in sleep and circadian timing.

IntroductionMany sleep and circadian studies require participants to adhere to structured sleep-wake schedules designed to stabilize sleep outcomes and circadian phase prior to in-laboratory testing. The effectiveness of this approach has not been rigorously evaluated, however. We therefore investigated the differences between participants’ unstructured and structured sleep over a three-week interval.MethodsTwenty-three healthy young adults completed three weeks of sleep monitoring, including one week of unstructured sleep and two weeks of structured sleep with consistent bed and wake times. Circadian phase was assessed via salivary dim light melatonin onset (DLMO) during both the unstructured and structured sleep episodes.ResultsCompared to their unstructured sleep schedule, participants’ bed- and wake times were significantly earlier in their structured sleep, by 34 ± 44 mins (M ± SD) and 44 ± 41 mins, respectively. During structured sleep, circadian phase was earlier in 65% of participants (40 ± 32 mins) and was later in 35% (41 ± 25 mins) compared to unstructured sleep but did not change at the group level. While structured sleep reduced night-to-night variability in sleep timing and sleep duration, and improved the alignment (phase angle) between sleep onset and circadian phase in the most poorly aligned individuals (DLMO < 1h or > 3h before sleep onset time; 25% of our sample), sleep duration and quality were unchanged.ConclusionOur results show adherence to a structured sleep schedule results in more regular sleep timing, and improved alignment between sleep and circadian timing for those individuals who previously had poorer alignment. Our findings support the use of structured sleep schedules prior to in-laboratory sleep and circadian studies to stabilize sleep and circadian timing in healthy volunteers.

Differences in affordance-based behaviors within an isolated and confined environment are related to sleep, emotional health and physiological parameters

Astronauts are required to operate within isolated, confined and extreme environments (ICE). Isolated, confined and controlled (ICC) environments, such as the NASA Human Exploration Research Analog (HERA) site, provide ways of studying and predicting behavioral changes that occur in response to prolonged exposure to ICE environments. An important aspect of behavior is affordance perception. An affordance refers to a possibility for action. Affordance perception and related behavior may be affected by sleep, emotional health and stress. The inability to accurately perceive changes in affordances may increase the risk adopted during a task, possibly compromising mission success. PurposeInvestigate changes in affordance perception during a 30-day exposure to an ICC environment and investigate the relationship between affordance perception and sleep, emotional health and physiological markers of stress. MethodsSixteen subjects completed five sessions of the perception-action coupling task (PACT), a novel tablet-based affordance perception task, on days 3, 10, 17, 24 and 5-days post-mission. The 15-min PACT presents a series of virtual balls and apertures varying in ball to aperture size ratio (B-AR) from 0.2 to 1.8. Subjects determined whether the ball could fit through the aperture and responded based on their perception of this action possibility. Participants also completed an emotional health questionnaire, the Mental Health Checklist (MHCL) throughout the mission. Actigraphy was used to collect sleep measures. Multiple ANOVA were conducted to assess changes in PACT response time (RT), accuracy (ACC) and lapses across time and to assess the role of individual differences in sleep, MHCL measures and salivary biomarkers of stress on performance. ResultsA significant main effect of time was observed on PACT RT (F4, 60 = 3.631, p = .010, n2p = .195) which was faster on day 24 (0.738 ± 0.088s) than day 17 (0.768 ± 0.092s). No differences were observed between other timepoints. ACC and lapses did not vary during the mission (p > .05). Individual differences in sleep duration, sleep efficiency, MHCL measures and salivary biomarkers related to individual differences in aspects of PACT performance. ConclusionModest changes in PACT performance were observed during a 30-day ICC exposure. Individual differences in performance may relate to individual differences in sleep and emotional health.

Human Circadian Phenotyping and Diurnal Performance Testing in the Real World.

In our continuously developing 'around the clock' society, there is a need to increase our understanding of how changes in biology, physiology and psychology influence our health and performance. Embedded within this challenge, is the increasing need to account for individual differences in sleep and circadian rhythms, as well as to explore the impact of time of day on performance in the real world. There are a number of ways to measure sleep and circadian rhythms from subjective questionnaire-based methods to objective sleep/wake monitoring, actigraphy and analysis of biological samples. This paper proposes a protocol that combines multiple techniques to categorize individuals into Early, Intermediate or Late circadian phenotype groups (ECPs/ICPs/LCPs) and recommends how to conduct diurnal performance testing in the field. Representative results show large differences in rest-activity patterns derived from actigraphy, circadian phase (dim light melatonin onset and peak time of cortisol awakening response) between circadian phenotypes. In addition, significant differences in diurnal performance rhythms between ECPs and LCPs emphasizes the need to account for circadian phenotype. In summary, despite the difficulties in controlling influencing factors, this protocol allows a real-world assessment of the impact of circadian phenotype on performance. This paper presents a simple method to assess circadian phenotype in the field and supports the need to consider time of day when designing performance studies.

M32 - PER3 POLYMORPHISMS, MORNINGNESS-EVENINGNESS AND DEPRESSION: PRELIMINARY EVIDENCE IN A BRAZILIAN FAMILY-BASED COHORT, THE BAEPENDI HEART STUDY

Background There is a significant interest in the contribution of the circadian timing system to individual differences in a wider range of behaviour. This is in part because sleep complaints and disturbances of the circadian timing system are common in psychiatric disorders. Based on diurnal preference, people can be divided into chronotypes with demonstrated differences in sleep-wake patterns and a variety of circadian rhythms, behavioral rhythms, and diurnal variation in mood. Specifically, greater eveningness has been related to greater depression. The human PER3 gene contains a variable number tandem repeat (VNTR) which is associated with diurnal preference: the longer allele (five tandem repeats) has been reported to associate with greater morningness, and the shorter allele (four tandem repeats) with greater eveningness. We have investigated the PER3 polymorphism and its relationship to sleep, circadian and depression characteristics in a Brazilian family-based cohort. Methods Baependi is a small rural town in Brazil that provides a window of opportunity to study the influence of sleep circadian patterns in a highly admixed rural population with a conservative lifestyle. Here, we studied 786 subjects (mean age±SD 46.5±16.2, 42% female). Blood samples were collected from all participants. The Per3 length polymorphism was genotyped using PCR followed by gel electrophoresis. We tested for associations between the PER3 polymorphism and sleep characteristics, daytime sleepiness, and chronotype using the Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale and Morningness-Eveningness Questionnaire, respectively. Depressive symptoms were assessed using the Beck Depression Inventory [BDI-II]). Results Our genotyping data showed that 36% of the subjects were homozygous for the shorter allele (4/4), 51% of the participants were heterozygous (4/5) and 12% of the subjects were homozygous for the longer allele (5/5). Allele frequency was 0.62 for the 4-repeat and a 0.38 for the 5-repeat. The percentages of the chronotypes Morning type (M-type), Neither type (N-type) and Evening type (E-type) were 5%, 46% and 7%, respectively. We observed an increase of the depression symptoms in evening types [F(2, 1014)=4.8, p=0.007]. On the other hand, no such associations were observed the PER3 genotype. There were no significant differences in the MEQ score [F(2, 317)=0.46, p=0.63], daytime sleepiness [(F(2, 317)=0.23, p=0.79)], sleep efficiency [(F(2, 317)=2.59, p=0.07)] and sleep characteristics [(F(2, 317)=1.92, p=0.14)] between the PER3 genotypes. Discussion We observed an association between eveningness and depression. Identifying factors contributing to individual differences in sleep and to describe how these factors are associated with physiological and psychological profiles may aid our understanding of the role of sleep and the circadian system in mental health. On the other hand, we were not able to replicate the association between the PER3 VNTR polymorphism and chronotype, which has been confirmed independently in multiple populations worldwide (including in Brazil). Neither did we observe any association with depression. CNPq – PVE 400791/2014-5.

Fixed sleep schedules prior to an in‐lab study: Individual differences in sleep and circadian timing

Fixed sleep schedules prior to an in‐lab study: Individual differences in sleep and circadian timing

Sleepiness and Behavioral Risk-Taking: Do Sleepy People Take More or Less Risk?

ABSTRACTBackground: Although sleep loss has been implicated in risk-taking behavior, it is unclear how individuals’ current propensity to fall asleep, known as sleepiness, influences risk-taking. Because sleepiness is not only driven by recent sleep but also by factors such as circadian rhythm and current stimulation, it may be an important contributor to risk-taking as it reflects the more immediate sleep-wake state. Participants: One hundred thirty participants were recruited from a large Midwestern U.S. university. Methods: Participants completed a short personality survey, reported their current sleepiness on the Stanford Sleepiness Scale, and then completed the Balloon Analog Risk Task, a computerized risk-taking measure in which participants earned real money for their performance. Results: There was little support for a linear relation between sleepiness and risk-taking, but the evidence indicated a robust curvilinear relation. Even after controlling for important individual differences in sleep and risk-taking, participants who were moderately sleepy took longer to complete the risk-taking task, pumped balloons more, and exploded more balloons than those who were either low or high on sleepiness. Conclusions: The curvilinear relation between sleepiness and risk-taking sheds light on inconsistencies in prior findings linking sleepiness and sleep loss to risk-taking behavior. Moreover, current sleepiness appears to have unique implications for risk-taking.

Are Individual Differences in Sleep and Circadian Timing Amplified by Use of Artificial Light Sources?

Within the human population, there is large interindividual variability in the timing of sleep and circadian rhythms. This variability has been attributed to individual differences in sleep physiology, circadian physiology, and/or light exposure. Recent experimental evidence suggests that the latter is necessary to evoke large interindividual differences in sleep and circadian timing. We used a validated model of human sleep and circadian physiology to test the hypothesis that intrinsic differences in sleep and circadian timing are amplified by self-selected use of artificial light sources. We tested the model under 2 conditions motivated by an experimental study (Wright et al., 2013): (1) a "natural" light cycle, and (2) a "realistic" light cycle that included attenuation of light due to living indoors when natural light levels are high and use of electric light when natural light levels are low. Within these conditions, we determined the relationship between intrinsic circadian period (within the range of 23.7-24.6 h) and timing of sleep onset, sleep offset, and circadian rhythms. In addition, we simulated a work week, with fixed wake time for 5 days and free sleep times on weekends. Under both conditions, a longer intrinsic period resulted in later sleep and circadian timing. Compared to the natural condition, the realistic condition evoked more than double the variation in sleep timing across the physiological range of intrinsic circadian periods. Model predictions closely matched data from the experimental study. We found that if the intrinsic circadian period was long (>24.2 h) under the realistic condition, there was significant mismatch in sleep timing between weekdays and weekends, which is known as social jetlag. These findings indicate that individual tendencies to have very delayed schedules can be greatly amplified by self-selected modifications to the natural light/dark cycle. This has important implications for therapeutic treatment of advanced or delayed sleep phase disorders.

Individual differences in self-reported difficulty sleeping across the menstrual cycle.

The effect of menstrual cycle phase on sleep has been studied for decades; however, individual differences in the associations between sleep and menstrual phase have not been well studied. In addition, the associations between changes in sleep and other physiological and psychological factors that vary as a function of menstrual phase have not been thoroughly assessed. This study explored individual differences in daily self-reports of difficulty sleeping across the menstrual cycle, as well as associations between daily changes in difficulty sleeping and psychological/vegetative and somatic symptoms. Participants (n = 213 females, mean age = 21.29 ± 4.01years) completed daily online questionnaires assessing` sleep, psychological and physical symptoms for two menstrual cycles. Two patterns of menstrual cycle-related self-reported difficulty sleeping emerged in addition to women who showed no cyclical change in self-reported difficulty sleeping: a perimenstrual increase and a mid-cycle increase. All psychological/vegetative symptoms and some of the somatic symptoms showed significant associations with self-reported difficulty sleeping. These findings highlight the importance of examining individual differences in sleep across the menstrual cycle and the significant contribution of a wide range of menstrual cycle-related psychological/vegetative and somatic symptoms.

Separating the effects of ethnicity and socio-economic status on sleep practices of 6- to 7-month-old infants

Infant sleep undergoes significant re-organization throughout the first 12months of life, with sleep quality having significant consequences for infant learning and cognitive development. While there has been great interest in the neural basis and developmental trajectories of infant sleep in general, relatively little is known about individual differences in infant sleep and the socio-economic and cultural sources of that variability. We investigated this using questionnaire sleep data in a large, unique multi-ethnic sample of 6–7month-olds (n=174), with families from South Asian ethnic groups in the UK (Indian, Pakistani and Bangladeshi) being especially well represented. Consistent with previous data from less variable samples, no effects of SES on sleep latency or nocturnal sleep duration emerged. However, perinatal risk factors and ethnic differences did predict daytime sleep, sleep fragmentation and sleep-onset time. While these results should be interpreted with caution due to several limitations, they likely demonstrate that even when socio-economic status and ethnicity are much less confounded than in previous studies, they have a surprisingly limited impact on individual differences in sleep patterns in young infants.

Phasic Sleep Events Shape Cognitive Function after Traumatic Brain Injury: Implications for the Study of Sleep in Neurodevelopmental Disorders

The biological functions of sleep have long eluded the medical and research community. In four consecutive issues of AIMS Neuroscience, original and review manuscripts were recently published regarding the mechanisms and function of sleep. These articles highlight the well-timed topic of quantitative sleep markers and cognitive functioning as one of extensive interest within the field of neuroscience. Our commentary on the original research performed by Cote, Milner, and Speth (2015) brings attention to the importance of examining individual differences in sleep and cognition in subjects with traumatic brain injury (TBI), and provides support for conducting similar sleep analyses in neurodevelopmental disorders.

Sleep and need for recovery in shift workers: do chronotype and age matter?

This study examined associations of chronotype and age with shift-specific assessments of main sleep duration, sleep quality and need for recovery in a cross-sectional study among N = 261 industrial shift workers (96.6% male). Logistic regression analyses were used, adjusted for gender, lifestyle, health, nap behaviour, season of assessment and shift schedule. Shift workers with latest versus earliest chronotype reported a shorter sleep duration (OR 11.68, 95% CI 3.31–41.17) and more awakenings complaints (OR 4.84, 95% CI 4.45–11.92) during morning shift periods. No associations were found between chronotype, sleep and need for recovery during evening and night shift periods. For age, no associations were found with any of the shift-specific outcome measures. The results stress the importance of including the concept of chronotype in shift work research and scheduling beyond the concept of age. Longitudinal research using shift-specific assessments of sleep and need for recovery are needed to confirm these results.Practitioner Summary: Chronotype seems to better explain individual differences in sleep than age. In view of ageing societies, it might therefore be worthwhile to further examine the application of chronotype for individualised shift work schedules to facilitate healthy and sustainable employment.

No Associations between Interindividual Differences in Sleep Parameters and Episodic Memory Consolidation.

Sleep and memory are stable and heritable traits that strongly differ between individuals. Sleep benefits memory consolidation, and the amount of slow wave sleep, sleep spindles, and rapid eye movement sleep have been repeatedly identified as reliable predictors for the amount of declarative and/or emotional memories retrieved after a consolidation period filled with sleep. These studies typically encompass small sample sizes, increasing the probability of overestimating the real association strength. In a large sample we tested whether individual differences in sleep are predictive for individual differences in memory for emotional and neutral pictures. Between-subject design. Cognitive testing took place at the University of Basel, Switzerland. Sleep was recorded at participants' homes, using portable electroencephalograph-recording devices. Nine hundred-twenty-nine healthy young participants (mean age 22.48 ± 3.60 y standard deviation). None. In striking contrast to our expectations as well as numerous previous findings, we did not find any significant correlations between sleep and memory consolidation for pictorial stimuli. Our results indicate that individual differences in sleep are much less predictive for pictorial memory processes than previously assumed and suggest that previous studies using small sample sizes might have overestimated the association strength between sleep stage duration and pictorial memory performance. Future studies need to determine whether intraindividual differences rather than interindividual differences in sleep stage duration might be more predictive for the consolidation of emotional and neutral pictures during sleep.

Morningness–eveningness—An overview

Individual differences in sleep and sleep timing (chronotype/morningness–eveningness) have received much attention during the last two decades. Important aspects of morningness–eveningness are age and gender as well as environmental variables such as latitude and timing of sunrise. This overview considers parts of the biological basis, that determines chronotype and views biological and social and environmental factors together as having an important influence on the circadian typology. In the second part of the talk, correlates of monringness–eveningness with personality traits as well as with health-related variables are presented, such as worse school achievement, and less healthier lifestyle.

Sleep restriction and emotion, electroencephalography (EEG) and dream recall, and insomnia and punctuality

Sleep restriction and emotion, electroencephalography (EEG) and dream recall, and insomnia and punctuality

Sleep, Diurnal Preference, Health, and Psychological Well-being: A Prospective Single-Allelic-Variation Study

Individual differences in sleep and diurnal preference associate with physical and mental health characteristics, but few genetic determinants of these differences have been identified. A variable number tandem repeat (VNTR) polymorphism in the PERIOD3 (PER3) gene (rs57875989) has been reported to associate with diurnal preference, i.e., preferred timing of waking and sleep. Here, the authors investigate in a prospective single-candidate genetic variant study whether allelic variation for this polymorphism associates also with reported actual sleep timing and sleep duration, as well as psychological and health measures. Six hundred and seventy-five subjects, aged 20 to 35 yrs, completed questionnaires to assess sleep and psychological and health characteristics and were genotyped for the PER3 VNTR. Homozygosity for the longer allele (PER35/5) of the VNTR was associated with increased morning preference, earlier wake time and bedtime, and reduced daytime sleepiness. Separate analyses of work and rest days demonstrated that the increase in time in bed during rest days was greatest in PER35/5 homozygotes. PER3 genotype modified the effects of sleep timing and duration on fluid intelligence and body mass index. Genotype was not associated with physical or psychological characteristics as assessed by the SF-36 Health Questionnaire, the General Health Questionnaire, the Big Five Inventory, the Behavioral Inhibition System–Behavioral Activation System scales, and the Positive and Negative Affect Scale, even though these measures varied significantly with diurnal preference as assessed by the Morningness-Eveningness Questionnaire. Whereas diurnal preference also predicts mental health and psychological characteristics, as well as sleep timing, the PER3 VNTR specifically affects measures of sleep timing and may also modify the effects of sleep on health outcome measures. (Author correspondence: a.lazar@surrey.ac.uk)

Molecular Mechanisms of Sleep and Wakefulness

Major questions on the biology of sleep include the following: what are the molecular functions of sleep; why can wakefulness only be sustained for defined periods before there is behavioral impairment; what genes contribute to the individual differences in sleep and the response to sleep deprivation? Behavioral criteria to define sleep have facilitated identification of sleep states in a number of different model systems: Drosophila, zebrafish, and Caenorhabditis elegans. Each system has unique strengths. Studies in these model systems are identifying conserved signaling mechanisms regulating sleep that are present in mammals. For example, the PKA-CREB signaling mechanism promotes wakefulness in Drosophila, mice, and C. elegans. Microarray studies indicate that genes whose expression is upregulated during sleep are involved in macromolecule biosynthesis (proteins, lipids [including cholesterol], heme). Thus, a key function of sleep is likely to be macromolecule synthesis. Moreover, in all species studied to date, there is upregulation of the molecular chaperone BiP with extended wakefulness. Sleep deprivation leads to cellular ER stress in brain and the unfolded protein response. Identification of genes regulating sleep has the potential for translational studies to elucidate the genetics of sleep and response to sleep deprivation in humans.