Catechol-O-methyltransferase Val158Met polymorphism associates with individual differences in sleep physiologic responses to chronic sleep loss

Impact of one night of sleep restriction on sleepiness and cognitive function: A systematic review and meta-analysis

Detrimental consequences of chronic sleep restriction on cognitive function are well established in the literature. However, effects of a single night of sleep restriction remain equivocal. Therefore, we synthesized data from 44 studies to investigate effects of sleep restriction to 2-6 h sleep opportunity on sleepiness and cognition in this meta-analysis. We investigated subjective sleepiness, sustained attention, choice reaction time, cognitive throughput, working memory, and inhibitory control. Results revealed a significant increase in subjective sleepiness following one night of sleep restriction (Standardized Mean Difference (SMD) = 0.986, p < 0.001), while subjective sleepiness was not associated with sleep duration during sleep restriction (β = -0.214, p = 0.039, significance level 0.01). Sustained attention, assessed via common 10-min tasks, was impaired, as demonstrated through increased reaction times (SMD = 0.512, p < 0.001) and attentional lapses (SMD = 0.489, p < 0.001). However, the degree of impaired attention was not associated with sleep duration (ps > 0.090). We did not find significant effects on choice reaction time, cognitive throughput, working memory, or inhibitory control. Overall, results suggest that a single night of restricted sleep can increase subjective sleepiness and impair sustained attention, a cognitive function crucial for everyday tasks such as driving.

Healthy sleep pattern reduce the risk of cardiovascular disease: A 10-year prospective cohort study

OBJECTIVE

To identify the association between quantified sleep factors and the incidence of cardiovascular disease (CVD) through a 10-year prospective cohort study.

METHODS

A total of 45,919 individuals were recruited in this population-based prospective study. The healthy sleep score was constructed by four sleep measures (sleep duration, insomnia symptoms, snoring and daytime sleepiness), which were collected by questionnaire. The hazard ratio (HR) and 95% confidence intervals (CIs) were calculated by the multivariate-adjusted Cox proportional hazards model. Restricted cubic spline analysis was used to examine the dose‒response relationships between healthy sleep scores and outcomes.

RESULTS

During a median follow-up of 10.73 years (interquartile range: 10.08-11.72 years), 10,523 cases of total CVD incidence, 3766 cases of CHD, and 3967 cases of stroke incidence were documented. Our results found that participants who maintained four healthy sleep measures (including no insomnia, snoring, or frequent daytime sleepiness and sleeping 7-8 h/d) had a 12% (HR: 0.88, 95% CI: 0.84-0.93) and 16% (HR: 0.84, 95% CI: 0.78-0.92) lower risk of developing CVD and CHD, respectively, but not stroke. There was a dose‒response relationship between sleep scores and the risk of cardiovascular events. With an increasing healthy sleep score, the risk of cardiovascular events decreases. Compared to those with a sleep score of 0-1, participants with a score of 4 had 27% (HR: 0.73, 95% CI: 0.67-0.79), 25% (HR: 0.75, 95% CI: 0.65-0.87), and 24% (HR: 0.76, 95% CI: 0.66-0.86) reduced risks of CVD, CHD, and stroke, respectively.

CONCLUSIONS

In this large prospective cohort study, a healthy sleep pattern effectively reduced the risk of CVD, CHD, and stroke.

Sleep loss suicidal ideation: the role of trait extraversion

Background: It is known that sleep disturbance is associated with increased suicidal thinking. Moreover, completed suicides, when adjusted for the proportion of the populace that is awake at a given time, are more probable during the late night/early morning hours. Despite these concerns, no studies have examined the role of trait-like individual differences in vulnerability to suicidal ideation during sleep deprivation or insomnia. In two separate studies, we examined whether the trait of extraversion is predictive of changes in suicidal thinking following two nights of sleep deprivation and among individuals meeting the criteria for insomnia.

Methods:Study 1: Twenty-five healthy military personnel (20 males), ages 20–35 completed the NEO-PI-R Extraversion scale and the Suicidal Ideation (SUI) scale of the Personality Assessment Inventory (PAI). Participants completed 77 h of continuous sleep deprivation. After 56 h of sleep deprivation, participants completed the SUI scale a second time. We predicted a change in SUI scores from baseline extraversion. Study 2: 2,061 adults aged 18–79 (900 males) were divided into two groups based on the clinical threshold (≥ 10) on the Insomnia Severity Index (ISI) and completed measures of extraversion and depression, including the suicide item of the Patient Health Questionnaire-9 (PHQ9).

Results:Study 1: After controlling for the caffeine group and changes in PAI Depression, Extraversion scores were used to predict changes in SUI scores using stepwise multiple linear regression. Higher Extraversion was significantly associated with increased non-clinical suicidal ideation following sleep loss, β = 0.463, partial r = 0.512, p = 0.013. Study 2: After controlling for depression, the effect of insomnia on suicidal ideation was moderated by trait extraversion (p < 0.0001). Overall, the presence or absence of insomnia had little effect on individuals low in trait extraversion (i.e., introverts), but insomnia was associated with significantly higher suicidal ideation among high trait extraverted individuals.

Conclusions: Higher trait extraversion was associated with increased vulnerability to suicidal ideation between rested baseline and total sleep deprivation and was associated with greater suicidal ideation among those meeting criteria for clinically severe insomnia. These findings point to a potential trait-like vulnerability factor that may further our understanding of sleep disruption in the phenomenology of suicide.

Genetic Markers of Differential Vulnerability to Sleep Loss in Adults

In this review, we discuss reports of genotype-dependent interindividual differences in phenotypic neurobehavioral responses to total sleep deprivation or sleep restriction. We highlight the importance of using the candidate gene approach to further elucidate differential resilience and vulnerability to sleep deprivation in humans, although we acknowledge that other omics techniques and genome-wide association studies can also offer insights into biomarkers of such vulnerability. Specifically, we discuss polymorphisms in adenosinergic genes (ADA and ADORA2A), core circadian clock genes (BHLHE41/DEC2 and PER3), genes related to cognitive development and functioning (BDNF and COMT), dopaminergic genes (DRD2 and DAT), and immune and clearance genes (AQP4, DQB1*0602, and TNFα) as potential genetic indicators of differential vulnerability to deficits induced by sleep loss. Additionally, we review the efficacy of several countermeasures for the neurobehavioral impairments induced by sleep loss, including banking sleep, recovery sleep, caffeine, and naps. The discovery of reliable, novel genetic markers of differential vulnerability to sleep loss has critical implications for future research involving predictors, countermeasures, and treatments in the field of sleep and circadian science.

Residual, differential neurobehavioral deficits linger after multiple recovery nights following chronic sleep restriction or acute total sleep deprivation

STUDY OBJECTIVES

The amount of recovery sleep needed to fully restore well-established neurobehavioral deficits from sleep loss remains unknown, as does whether the recovery pattern differs across measures after total sleep deprivation (TSD) and chronic sleep restriction (SR).

METHODS

In total, 83 adults received two baseline nights (10-12-hour time in bed [TIB]) followed by five 4-hour TIB SR nights or 36-hour TSD and four recovery nights (R1-R4; 12-hour TIB). Neurobehavioral tests were completed every 2 hours during wakefulness and a Maintenance of Wakefulness Test measured physiological sleepiness. Polysomnography was collected on B2, R1, and R4 nights.

RESULTS

TSD and SR produced significant deficits in cognitive performance, increases in self-reported sleepiness and fatigue, decreases in vigor, and increases in physiological sleepiness. Neurobehavioral recovery from SR occurred after R1 and was maintained for all measures except Psychomotor Vigilance Test (PVT) lapses and response speed, which failed to completely recover. Neurobehavioral recovery from TSD occurred after R1 and was maintained for all cognitive and self-reported measures, except for vigor. After TSD and SR, R1 recovery sleep was longer and of higher efficiency and better quality than R4 recovery sleep.

CONCLUSIONS

PVT impairments from SR failed to reverse completely; by contrast, vigor did not recover after TSD; all other deficits were reversed after sleep loss. These results suggest that TSD and SR induce sustained, differential biological, physiological, and/or neural changes, which remarkably are not reversed with chronic, long-duration recovery sleep. Our findings have critical implications for the population at large and for military and health professionals.

Robust stability of trait-like vulnerability or resilience to common types of sleep deprivation in a large sample of adults

STUDY OBJECTIVES

Sleep loss produces large individual differences in neurobehavioral responses, with marked vulnerability or resilience among individuals. Such differences are stable with repeated exposures to acute total sleep deprivation (TSD) or chronic sleep restriction (SR) within short (weeks) and long (years) intervals. Whether trait-like responses are observed to commonly experienced types of sleep loss and across various demographically defined groups remains unknown.

METHODS

Eighty-three adults completed two baseline nights (10 h-12 h time-in-bed, TIB) followed by five 4 h TIB SR nights or 36 h TSD. Participants then received four 12-h TIB recovery nights followed by five SR nights or 36 h TSD, in counterbalanced order to the first sleep loss sequence. Neurobehavioral tests were completed every 2 h during wakefulness.

RESULTS

Participants who displayed neurobehavioral vulnerability to TSD displayed vulnerability to SR, evidenced by substantial to near perfect intraclass correlation coefficients (ICCs; 78%-91% across measures). Sex, race, age, body mass index (BMI), season, and sleep loss order did not impact ICCs significantly. Individuals exhibited significant consistency of responses within, but not between, performance and self-reported domains.

CONCLUSIONS

Using the largest, most diverse sample to date, we demonstrate for the first time the remarkable stability of phenotypic neurobehavioral responses to commonly experienced sleep loss types, across demographic variables and different performance and self-reported measures. Since sex, race, age, BMI, and season did not affect ICCs, these variables are not useful for determining stability of responses to sleep loss, underscoring the criticality of biological predictors. Our findings inform mathematical models and are relevant for the general population and military and health professions.

The association between sleep-wake ratio and overnight picture recognition is moderated by BDNF genotype

A wealth of studies supports the role of sleep in memory performance. Experimentally controlled studies indicate that prolonged wake after memory encoding is detrimental for memory outcome whereas sleep protects from wake-time interference and promotes memory consolidation. We examined how the natural distribution of wake and sleep between encoding and retrieval associated with overnight picture recognition accuracy among 161 adolescents following their typical sleep schedule with an in-home polysomnography. The memorized pictures varied in their level of arousal (calm to exciting) and valence (negative to positive). Suspecting genotypic influence on the sensitivity for sleep/wake dynamics, we also assessed if these associations were affected by known gene polymorphisms involved in neural plasticity and sleep homeostasis: brain-derived neurotrophic factor (BDNF) Val66Met and Catechol-O-methyltransferase (COMT) Val158Met. In the whole sample, overnight recognition accuracy was associated with the levels of arousal and valence of the pictures, but not with sleep percentage (i.e. the percentage of time spent asleep between memory encoding and retrieval). While the allelic status of BDNF or COMT did not have any main effect on recognition accuracy, a significant moderation by BDNF Val66Met was found (p = .004): the subgroup homozygous for valine allele showed positive association between sleep percentage and recognition accuracy. This was underlain by detrimental influence of wake, rather than by any memory benefit of sleep. Our results complement the mounting evidence that the relation between sleep and memory performance is moderated by BDNF Val66Met. Further studies are needed to clarify the specific mechanisms.

Sleep in the United States Military

The military lifestyle often includes continuous operations whether in training or deployed environments. These stressful environments present unique challenges for service members attempting to achieve consolidated, restorative sleep. The significant mental and physical derangements caused by degraded metabolic, cardiovascular, skeletomuscular, and cognitive health often result from insufficient sleep and/or circadian misalignment. Insufficient sleep and resulting fatigue compromises personal safety, mission success, and even national security. In the long-term, chronic insufficient sleep and circadian rhythm disorders have been associated with other sleep disorders (e.g., insomnia, obstructive sleep apnea, and parasomnias). Other physiologic and psychologic diagnoses such as post-traumatic stress disorder, cardiovascular disease, and dementia have also been associated with chronic, insufficient sleep. Increased co-morbidity and mortality are compounded by traumatic brain injury resulting from blunt trauma, blast exposure, and highly physically demanding tasks under load. We present the current state of science in human and animal models specific to service members during- and post-military career. We focus on mission requirements of night shift work, sustained operations, and rapid re-entrainment to time zones. We then propose targeted pharmacological and non-pharmacological countermeasures to optimize performance that are mission- and symptom-specific. We recognize a critical gap in research involving service members, but provide tailored interventions for military health care providers based on the large body of research in health care and public service workers.

Precision Medicine for Sleep Loss and Fatigue Management

Sleep loss is a widespread phenomenon and a public health threat. Sleep disorders, medical conditions, lifestyles, and occupational factors all contribute to insufficient sleep. Regardless of the underlying cause, insufficient sleep has well-defined consequences and the severity of said consequences partially influenced by individual characteristics. It is here where precision medicine needs to understand and define sleep insufficiency in hopes for personalizing medical approach to improve patient outcomes. Following a discussion on causes and consequences of sleep loss, this article discusses tools for assessing sleep sufficiency, mitigating strategies to sleep loss, and sleep loss in the context of fatigue management.

Dopamine and Wakefulness: Pharmacology, Genetics, and Circuitry

Over the period of decades in the mid to late twentieth century, arousal-promoting functions were attributed to neuromodulators including serotonin, hypocretin, histamine, and noradrenaline. For some time, a relatively minor role in regulating sleep and wake states was ascribed to dopamine and the dopamine-producing cells of the ventral tegmental area, despite the fact that dopaminergic signaling is a major target, if not the primary target, for wake-promoting agents. In recent years, due to observations from human genetic studies, pharmacogenetic studies in animal models, and the increasingly sophisticated methods used to manipulate the nervous systems of experimental animals, it has become clear that dopaminergic signaling is central to the regulation of arousal. This chapter reviews this central role of dopaminergic signaling, and in particular its antagonistic interaction with adenosinergic signaling, in maintaining vigilance and in the response to wake-promoting therapeutics.

Time-on-Task Effect During Sleep Deprivation in Healthy Young Adults Is Modulated by Dopamine Transporter Genotype

Study Objectives

The time-on-task (TOT) effect and total sleep deprivation (TSD) have similar effects on neurobehavioral functioning, including increased performance instability during tasks requiring sustained attention. The TOT effect is exacerbated by TSD, suggesting potentially overlapping mechanisms. We probed these mechanisms by investigating genotype-phenotype relationships on psychomotor vigilance test (PVT) performance for 3 a-priori selected genes previously linked to the TOT effect and/or TSD: dopamine active transporter 1 (DAT1), catechol-O-methyltransferase (COMT), and tumor necrosis factor alpha (TNFα).

Methods

N = 82 healthy adults participated in 1 of 3 laboratory studies. A 10-min PVT was administered repeatedly during 38 h of TSD. We assessed changes in response time (RT) across each minute of the PVT as a function of time awake and genotype. Additionally, cumulative relative RT frequency distributions were constructed to examine changes in performance from the first to the second 5 min of the PVT as a function of genotype.

Results

DAT1, COMT, and TNFα were associated with differences in the build-up of the TOT effect across the 10-min PVT. DAT1 additionally modulated the interaction between TSD and the TOT effect. Subjects homozygous for the DAT1 10-repeat allele were relatively protected against TOT deficits on the PVT during TSD compared to carriers of the 9-repeat allele.

Conclusions

DAT1 is known to regulate dopamine reuptake and is highly expressed in the striatum. Our results implicate striatal dopamine in mechanisms involved in performance instability that appear to be common to TSD and the TOT effect. Furthermore, DAT1 may be a candidate biomarker of resilience to the build-up of performance impairment across TOT due to TSD.

Effects of COMT genotype and tolcapone on lapses of sustained attention after sleep deprivation in healthy young men

Tolcapone, a brain penetrant selective inhibitor of catechol-O-methyltransferase (COMT) devoid of psychostimulant properties, improves cognition and cortical information processing in rested volunteers, depending on the genotype of the functional Val158Met polymorphism of COMT. The impact of this common genetic variant on behavioral and neurophysiological markers of increased sleep need after sleep loss is controversial. Here we investigated the potential usefulness of tolcapone to mitigate consequences of sleep deprivation on lapses of sustained attention, and tested the hypothesis that dopamine signaling in the prefrontal cortex (PFC) causally contributes to neurobehavioral and neurophysiological markers of sleep homeostasis in humans. We first quantified in 73 young male volunteers the impact of COMT genotype on the evolution of attentional lapses during 40 h of extended wakefulness. Subsequently, we tested in an independent group of 30 young men whether selective inhibition of COMT activity with tolcapone counteracts attentional and neurophysiological markers of elevated sleep need in a genotype-dependent manner. Neither COMT genotype nor tolcapone affected brain electrical activity in wakefulness and sleep. By contrast, COMT genotype and tolcapone modulated the sleep loss-induced impairment of vigilant attention. More specifically, Val/Met heterozygotes produced twice as many lapses after a night without sleep than Met/Met homozygotes. Unexpectedly, tolcapone further deteriorated the sleep loss-induced performance deficits when compared to placebo, particularly in Val/Met and Met/Met genotypes. The findings suggest that PFC dopaminergic tone regulates sustained attention after sleep loss according to an inverse U-shape relationship, independently of neurophysiological markers of elevated sleep need.

On-orbit sleep problems of astronauts and countermeasures

Sufficient sleep duration and good sleep quality are crucial to ensure normal physical and mental health, cognition and work performance for the common people, as well as astronauts. On-orbit sleep problem is very common among astronauts and has potential detrimental influences on the health of crewmembers and the safety of flight missions. Sleep in space is becoming a new medical research frontier. In this review we summarized on-orbit sleep problems of astronauts and six kinds of causes, and we presented the effects of lack of sleep on performance as well as mental and physical health, then we proposed seven kinds of countermeasures for sleep disturbance in spaceflight, including pharmacologic interventions, light treatment, crew selection and training, Traditional Chinese Medicine and so on. Furthermore, we discussed and oriented the prospect of researches on sleep in space.

Interindividual variability in neurobehavioral response to sleep loss: A comprehensive review

Stable trait-like responding is well established for neurobehavioral performance measures across repeated exposures to total sleep deprivation and partial chronic sleep restriction. These observed phenotypes are task-dependent, suggesting that there are distinct cognitive profiles of responding with differential vulnerability to sleep loss within the same individual. Numerous factors have been investigated as potential markers of phenotypic vulnerability to the effects of sleep loss but none fully account for this phenomenon. Observed interindividual differences in performance during extended wakefulness may be driven by underlying deficits in the wake-promoting system resulting in greater performance instability due to failure to counteract increased homeostatic pressure. Further work would benefit from a systems approach to the study of interindividual vulnerability in which behavioral, neurobiological, and genetic data are integrated in a larger framework delineating the relationships between genes, proteins, neurobiology, and behavior.

Catechol-O-methyltransferase (COMT) genotype affects cognitive control during total sleep deprivation

Adaptive decision making is profoundly impaired by total sleep deprivation (TSD). This suggests that TSD impacts fronto-striatal pathways involved in cognitive control, where dopamine is a key neuromodulator. In the prefrontal cortex (PFC), dopamine is catabolized by the enzyme catechol-O-methyltransferase (COMT). A functional polymorphism (Val158Met) influences COMT's enzymatic activity, resulting in markedly different levels of prefrontal dopamine. We investigated the effect of this polymorphism on adaptive decision making during TSD. Sixty-six healthy young adults participated in one of two in-laboratory studies. After a baseline day, subjects were randomized to either a TSD group (n = 32) with 38 h or 62 h of extended wakefulness or a well-rested control group (n = 34) with 10 h nighttime sleep opportunities. Subjects performed a go/no-go reversal learning (GNGr) task at well-rested baseline and again during TSD or equivalent control. During the task, subjects were required to learn stimulus-response relationships from accuracy feedback. The stimulus-response relationships were reversed halfway through the task, which required subjects to learn the new stimulus-response relationships from accuracy feedback. Performance on the GNGr task was quantified by discriminability (d') between go and no-go stimuli before and after the stimulus-response reversal. GNGr performance did not differ between COMT genotypes when subjects were well-rested. However, TSD exposed a significant vulnerability to adaptive decision making impairment in subjects with the Val allele. Our results indicate that sleep deprivation degrades cognitive control through a fronto-striatal, dopaminergic mechanism.

Healthy Adults Display Long-Term Trait-Like Neurobehavioral Resilience and Vulnerability to Sleep Loss

Sleep loss produces well-characterized cognitive deficits, although there are large individual differences, with marked vulnerability or resilience among individuals. Such differences are stable with repeated exposures to acute total sleep deprivation (TSD) within a short-time interval (weeks). Whether such stability occurs with chronic sleep restriction (SR) and whether it endures across months to years in TSD, indicating a true trait, remains unknown. In 23 healthy adults, neurobehavioral vulnerability to TSD exposures, separated by 27–2,091 days (mean: 444 days; median: 210 days), showed trait-like stability in performance and subjective measures (82–95% across measures). Similarly, in 24 healthy adults, neurobehavioral vulnerability to SR exposures, separated by 78–3,058 days (mean: 935 days; median: 741 days), also showed stability (72–92% across measures). Cognitive performance outcomes and subjective ratings showed consistency across objective measures, and consistency across subjective measures, but not between objective and subjective domains. We demonstrate for the first time the stability of phenotypic neurobehavioral responses in the same individuals to SR and to TSD over long-time intervals. Across multiple measures, prior sleep loss responses are strong predictors of individual responses to subsequent sleep loss exposures chronically or intermittently, across months and years, thus validating the need for biomarkers and predictors.

Human and rat gut microbiome composition is maintained following sleep restriction

Insufficient sleep increasingly characterizes modern society, contributing to a host of serious medical problems. Loss of sleep is associated with metabolic diseases such as obesity and diabetes, cardiovascular disorders, and neurological and cognitive impairments. Shifts in gut microbiome composition have also been associated with the same pathologies; therefore, we hypothesized that sleep restriction may perturb the gut microbiome to contribute to a disease state. In this study, we examined the fecal microbiome by using a cross-species approach in both rat and human studies of sleep restriction. We used DNA from hypervariable regions (V1-V2) of 16S bacteria rRNA to define operational taxonomic units (OTUs) of the microbiome. Although the OTU richness of the microbiome is decreased by sleep restriction in rats, major microbial populations are not altered. Only a single OTU, TM7-3a, was found to increase with sleep restriction of rats. In the human microbiome, we find no overt changes in the richness or composition induced by sleep restriction. Together, these results suggest that the microbiome is largely resistant to changes during sleep restriction.

Human and rat gut microbiome composition is maintained following sleep restriction

Insufficient sleep increasingly characterizes modern society, contributing to a host of serious medical problems. Loss of sleep is associated with metabolic diseases such as obesity and diabetes, cardiovascular disorders, and neurological and cognitive impairments. Shifts in gut microbiome composition have also been associated with the same pathologies; therefore, we hypothesized that sleep restriction may perturb the gut microbiome to contribute to a disease state. In this study, we examined the fecal microbiome by using a cross-species approach in both rat and human studies of sleep restriction. We used DNA from hypervariable regions (V1-V2) of 16S bacteria rRNA to define operational taxonomic units (OTUs) of the microbiome. Although the OTU richness of the microbiome is decreased by sleep restriction in rats, major microbial populations are not altered. Only a single OTU, TM7-3a, was found to increase with sleep restriction of rats. In the human microbiome, we find no overt changes in the richness or composition induced by sleep restriction. Together, these results suggest that the microbiome is largely resistant to changes during sleep restriction.

Common variants in DRD2 are associated with sleep duration: the CARe consortium

Sleep duration is implicated in the etiologies of chronic diseases and premature mortality. However, the genetic basis for sleep duration is poorly defined. We sought to identify novel genetic components influencing sleep duration in a multi-ethnic sample. Meta-analyses were conducted of genetic associations with self-reported, habitual sleep duration from seven Candidate Gene Association Resource (CARe) cohorts of over 25 000 individuals of African, Asian, European and Hispanic American ancestry. All individuals were genotyped for ∼50 000 SNPs from 2000 candidate heart, lung, blood and sleep genes. African-Americans had additional genome-wide genotypes. Four cohorts provided replication. A SNP (rs17601612) in the dopamine D2 receptor gene (DRD2) was significantly associated with sleep duration (P = 9.8 × 10(-7)). Conditional analysis identified a second DRD2 signal with opposite effects on sleep duration. In exploratory analysis, suggestive association was observed for rs17601612 with polysomnographically determined sleep latency (P = 0.002). The lead DRD2 signal was recently identified in a schizophrenia GWAS, and a genetic risk score of 11 additional schizophrenia GWAS loci genotyped on the IBC array was also associated with longer sleep duration (P = 0.03). These findings support a role for DRD2 in influencing sleep duration. Our work motivates future pharmocogenetics research on alerting agents such as caffeine and modafinil that interact with the dopaminergic pathway and further investigation of genetic overlap between sleep and neuro-psychiatric traits.

Effects of partial sleep deprivation on slow waves during non-rapid eye movement sleep: A high density EEG investigation

OBJECTIVE

Changes in slow waves during non-rapid eye movement (NREM) sleep in response to acute total sleep deprivation are well-established measures of sleep homeostasis. This investigation utilized high-density electroencephalography (hdEEG) to examine topographic changes in slow waves during repeated partial sleep deprivation.

METHODS

Twenty-four participants underwent a 6-day sleep restriction protocol. Spectral and period-amplitude analyses of sleep hdEEG data were used to examine changes in slow wave energy, count, amplitude, and slope relative to baseline.

RESULTS

Changes in slow wave energy were dependent on the quantity of NREM sleep utilized for analysis, with widespread increases during sleep restriction and recovery when comparing data from the first portion of the sleep period, but restricted to recovery sleep if the entire sleep episode was considered. Period-amplitude analysis was less dependent on the quantity of NREM sleep utilized, and demonstrated topographic changes in the count, amplitude, and distribution of slow waves, with frontal increases in slow wave amplitude, numbers of high-amplitude waves, and amplitude/slopes of low amplitude waves resulting from partial sleep deprivation.

CONCLUSIONS

Topographic changes in slow waves occur across the course of partial sleep restriction and recovery.

SIGNIFICANCE

These results demonstrate a homeostatic response to partial sleep loss in humans.

African Genetic Ancestry is Associated with Sleep Depth in Older African Americans

STUDY OBJECTIVES

The mechanisms that underlie differences in sleep characteristics between European Americans (EA) and African Americans (AA) are not fully known. Although social and psychological processes that differ by race are possible mediators, the substantial heritability of sleep characteristics also suggests genetic underpinnings of race differences. We hypothesized that racial differences in sleep phenotypes would show an association with objectively measured individual genetic ancestry in AAs.

DESIGN

Cross sectional.

SETTING

Community-based study.

PARTICIPANTS

Seventy AA adults (mean age 59.5 ± 6.7 y; 62% female) and 101 EAs (mean age 60.5 ± 7 y, 39% female).

MEASUREMENTS AND RESULTS

Multivariate tests were used to compare the Pittsburgh Sleep Quality Index (PSQI) and in-home polysomnographic measures of sleep duration, sleep efficiency, apnea-hypopnea index (AHI), and indices of sleep depth including percent visually scored slow wave sleep (SWS) and delta EEG power of EAs and AAs. Sleep duration, efficiency, and sleep depth differed significantly by race. Individual % African ancestry (%AF) was measured in AA subjects using a panel of 1698 ancestry informative genetic markers and ranged from 10% to 88% (mean 67%). Hierarchical linear regression showed that higher %AF was associated with lower percent SWS in AAs (β (standard error) = -4.6 (1.5); P = 0.002), and explained 11% of the variation in SWS after covariate adjustment. A similar association was observed for delta power. No association was observed for sleep duration and efficiency.

CONCLUSION

African genetic ancestry is associated with indices of sleep depth in African Americans. Such an association suggests that part of the racial differences in slow-wave sleep may have genetic underpinnings.

Natural history of excessive daytime sleepiness: role of obesity, weight loss, depression, and sleep propensity

STUDY OBJECTIVES

Excessive daytime sleepiness (EDS) is highly prevalent in the general population and is associated with occupational and public safety hazards. However, no study has examined the clinical and polysomnographic (PSG) predictors of the natural history of EDS.

DESIGN

Representative longitudinal study.

SETTING

Sleep laboratory.

PARTICIPANTS

From a random, general population sample of 1,741 individuals of the Penn State Adult Cohort, 1,395 were followed up after 7.5 years.

MEASUREMENTS AND RESULTS

Full medical evaluation and 1-night PSG at baseline and standardized telephone interview at follow-up. The incidence of EDS was 8.2%, while its persistence and remission were 38% and 62%, respectively. Obesity and weight gain were associated with the incidence and persistence of EDS, while weight loss was associated with its remission. Significant interactions between depression and PSG parameters on incident EDS showed that, in depressed individuals, incident EDS was associated with sleep disturbances, while in non-depressed individuals, incident EDS was associated with increased physiologic sleep propensity. Diabetes, allergy/ asthma, anemia, and sleep complaints also predicted the natural history of EDS.

CONCLUSIONS

Obesity, a disorder of epidemic proportions, is a major risk factor for the incidence and chronicity of EDS, while weight loss is associated with its remission. Interestingly, objective sleep disturbances predict incident EDS in depressed individuals, whereas physiologic sleep propensity predicts incident EDS in those without depression. Weight management and treatment of depression and sleep disorders should be part of our public health policies.

Genetic dissection of sleep homeostasis

Sleep is a complex behavior both in its manifestation and regulation, that is common to almost all animal species studied thus far. Sleep is not a unitary behavior and has many different aspects, each of which is tightly regulated and influenced by both genetic and environmental factors. Despite its essential role for performance, health, and well-being, genetic mechanisms underlying this complex behavior remain poorly understood. One important aspect of sleep concerns its homeostatic regulation, which ensures that levels of sleep need are kept within a range still allowing optimal functioning during wakefulness. Uncovering the genetic pathways underlying the homeostatic aspect of sleep is of particular importance because it could lead to insights concerning sleep's still elusive function and is therefore a main focus of current sleep research. In this chapter, we first give a definition of sleep homeostasis and describe the molecular genetics techniques that are used to examine it. We then provide a conceptual discussion on the problem of assessing a sleep homeostatic phenotype in various animal models. We finally highlight some of the studies with a focus on clock genes and adenosine signaling molecules.

Cognitive workload and sleep restriction interact to influence sleep homeostatic responses

STUDY OBJECTIVES

Determine the effects of high versus moderate workload on sleep physiology and neurobehavioral measures, during sleep restriction (SR) and no sleep restriction (NSR) conditions.

DESIGN

Ten-night experiment involving cognitive workload and SR manipulations.

SETTING

Controlled laboratory environment.

PARTICIPANTS

Sixty-three healthy adults (mean ± standard deviation: 33.2 ± 8.7 y; 29 females), age 22-50 y.

INTERVENTIONS

Following three baseline 8 h time in bed (TIB) nights, subjects were randomized to one of four conditions: high cognitive workload (HW) + SR; moderate cognitive workload (MW) + SR; HW + NSR; or MW + NSR. SR entailed 5 consecutive nights at 4 h TIB; NSR entailed 5 consecutive nights at 8 h TIB. Subjects received three workload test sessions/day consisting of 15-min preworkload assessments, followed by a 60-min (MW) or 120-min (HW) workload manipulation comprised of visually based cognitive tasks, and concluding with 15-min of postworkload assessments. Experimental nights were followed by two 8-h TIB recovery sleep nights. Polysomnography was collected on baseline night 3, experimental nights 1, 4, and 5, and recovery night 1 using three channels (central, frontal, occipital [C3, Fz, O2]).

MEASUREMENTS AND RESULTS

High workload, regardless of sleep duration, increased subjective fatigue and sleepiness (all P < 0.05). In contrast, sleep restriction produced cumulative increases in Psychomotor Vigilance Test (PVT) lapses, fatigue, and sleepiness and decreases in PVT response speed and Maintenance of Wakefulness Test (MWT) sleep onset latencies (all P < 0.05). High workload produced longer sleep onset latencies (P < 0.05, d = 0.63) and less wake after sleep onset (P < 0.05, d = 0.64) than moderate workload. Slow-wave energy-the putative marker of sleep homeostasis-was higher at O2 than C3 only in the HW + SR condition (P < 0.05).

CONCLUSIONS

High cognitive workload delayed sleep onset, but it also promoted sleep homeostatic responses by increasing subjective fatigue and sleepiness, and producing a global sleep homeostatic response by reducing wake after sleep onset. When combined with sleep restriction, high workload increased local (occipital) sleep homeostasis, suggesting a use-dependent sleep response to visual work. We conclude that sleep restriction and cognitive workload interact to influence sleep homeostasis.

Cumulative neurobehavioral and physiological effects of chronic caffeine intake: individual differences and implications for the use of caffeinated energy products

The use of caffeine-containing energy products has increased worldwide in recent years. All of the top-selling energy drinks contain caffeine, which is likely to be the primary psychoactive ingredient in these products. Research shows that caffeine-containing energy products can improve cognitive and physical performance. Presumably, individuals consume caffeine-containing energy products to counteract feelings of low energy in situations causing tiredness, fatigue, and/or reduced alertness. This review discusses the scientific evidence for sleep loss, circadian phase, sleep inertia, and the time-on-task effect as causes of low energy and summarizes research assessing the efficacy of caffeine to counteract decreased alertness and increased fatigue in such situations. The results of a placebo-controlled experiment in healthy adults who had 3 nights of total sleep deprivation (with or without 2-hour naps every 12 hours) are presented to illustrate the physiological and neurobehavioral effects of sustained low-dose caffeine. Individual differences, including genetic factors, in the response to caffeine and to sleep loss are discussed. The review concludes with future directions for research on this important and evolving topic.

Sleepiness and Safety: Where Biology Needs Technology

Maintaining human alertness and behavioral capability under conditions of sleep loss and circadian misalignment requires fatigue management technologies due to: (1) dynamic nonlinear modulation of performance capability by the interaction of sleep homeostatic drive and circadian regulation; (2) large differences among people in neurobehavioral vulnerability to sleep loss; (3) error in subjective estimates of fatigue on performance; and (4) to inform people of the need for recovery sleep. Two promising areas of technology have emerged for managing fatigue risk in safety-sensitive occupations. The first involves preventing fatigue by optimizing work schedules using biomathematical models of performance changes associated with sleep homeostatic and circadian dynamics. Increasingly these mathematical models account for individual differences to achieve a more accurate estimate of the timing and magnitude of fatigue effects on individuals. The second area involves technologies for detecting transient fatigue from drowsiness. The Psychomotor Vigilance Test (PVT), which has been extensively validated to be sensitive to deficits in attention from sleep loss and circadian misalignment, is an example in this category. Two shorter-duration versions of the PVT recently have been developed for evaluating whether operators have sufficient behavioral alertness prior to or during work. Another example is online tracking the percent of slow eyelid closures (PERCLOS), which has been shown to reflect momentary fluctuations of vigilance. Technologies for predicting and detecting sleepiness/fatigue have the potential to predict and prevent operator errors and accidents in safety-sensitive occupations, as well as physiological and mental diseases due to inadequate sleep and circadian misalignment.

Sleepiness and Safety: Where Biology Needs Technology

Maintaining human alertness and behavioral capability under conditions of sleep loss and circadian misalignment requires fatigue management technologies due to: (1) dynamic nonlinear modulation of performance capability by the interaction of sleep homeostatic drive and circadian regulation; (2) large differences among people in neurobehavioral vulnerability to sleep loss; (3) error in subjective estimates of fatigue on performance; and (4) to inform people of the need for recovery sleep. Two promising areas of technology have emerged for managing fatigue risk in safety-sensitive occupations. The first involves preventing fatigue by optimizing work schedules using biomathematical models of performance changes associated with sleep homeostatic and circadian dynamics. Increasingly these mathematical models account for individual differences to achieve a more accurate estimate of the timing and magnitude of fatigue effects on individuals. The second area involves technologies for detecting transient fatigue from drowsiness. The Psychomotor Vigilance Test (PVT), which has been extensively validated to be sensitive to deficits in attention from sleep loss and circadian misalignment, is an example in this category. Two shorter-duration versions of the PVT recently have been developed for evaluating whether operators have sufficient behavioral alertness prior to or during work. Another example is online tracking the percent of slow eyelid closures (PERCLOS), which has been shown to reflect momentary fluctuations of vigilance. Technologies for predicting and detecting sleepiness/fatigue have the potential to predict and prevent operator errors and accidents in safety-sensitive occupations, as well as physiological and mental diseases due to inadequate sleep and circadian misalignment.

Sustained attention performance during sleep deprivation associates with instability in behavior and physiologic measures at baseline

STUDY OBJECTIVES

To identify baseline behavioral and physiologic markers that associate with individual differences in sustained attention during sleep deprivation.

DESIGN

In a retrospective study, ocular, electrocardiogram, and electroencephalogram (EEG) measures were compared in subjects who were characterized as resilient (n = 15) or vulnerable (n = 15) to the effects of total sleep deprivation on sustained attention.

SETTING

Chronobiology and Sleep Laboratory, Duke-NUS Graduate Medical School Singapore.

PARTICIPANTS

Healthy volunteers aged 22-32 years from the general population.

INTERVENTIONS

Subjects were kept awake for at least 26 hours under constant environmental conditions. Every 2 hours, sustained attention was assessed using a 10-minute psychomotor vigilance task (PVT).

MEASUREMENTS AND RESULTS

During baseline sleep and recovery sleep, EEG slow wave activity was similar in resilient versus vulnerable subjects, suggesting that individual differences in vulnerability to sleep loss were not related to differences in homeostatic sleep regulation. Rather, irrespective of time elapsed since wake, subjects who were vulnerable to sleep deprivation exhibited slower and more variable PVT response times, lower and more variable heart rate, and higher and more variable EEG spectral power in the theta frequency band (6.0-7.5 Hz).

CONCLUSIONS

Performance decrements in sustained attention during sleep deprivation associate with instability in behavioral and physiologic measures at baseline. Small individual differences in sustained attention that are present at baseline are amplified during prolonged wakefulness, thus contributing to large between-subjects differences in performance and sleepiness.

Sleep deprivation and neurobehavioral dynamics

Lifestyles involving sleep deprivation are common, despite mounting evidence that both acute total sleep deprivation and chronically restricted sleep degrade neurobehavioral functions associated with arousal, attention, memory and state stability. Current research suggests dynamic differences in the way the central nervous system responds to acute versus chronic sleep restriction, which is reflected in new models of sleep-wake regulation. Chronic sleep restriction likely induces long-term neuromodulatory changes in brain physiology that could explain why recovery from it may require more time than from acute sleep loss. High intraclass correlations in neurobehavioral responses to sleep loss suggest that these trait-like differences are phenotypic and may include genetic components. Sleep deprivation induces changes in brain metabolism and neural activation that involve distributed networks and connectivity.

Disrupted directed connectivity along the cingulate cortex determines vigilance after sleep deprivation

The cingulate cortex is regarded as the backbone of structural and functional connectivity of the brain. While its functional connectivity has been intensively studied, little is known about its effective connectivity, its modulation by behavioral states, and its involvement in cognitive performance. Given the previously reported effects on cingulate functional connectivity, we investigated how eye-closure and sleep deprivation changed cingulate effective connectivity, estimated from resting-state high-density electroencephalography (EEG) using a novel method to calculate Granger Causality directly in source space. Effective connectivity along the cingulate cortex was dominant in the forward direction. Eyes-open connectivity in the forward direction was greater compared to eyes-closed, in well-rested participants. The difference between eyes-open and eyes-closed connectivity was attenuated and no longer significant after sleep deprivation. Individual variability in the forward connectivity after sleep deprivation predicted subsequent task performance, such that those subjects who showed a greater increase in forward connectivity between the eyes-open and the eyes-closed periods also performed better on a sustained attention task. Effective connectivity in the opposite, backward, direction was not affected by whether the eyes were open or closed or by sleep deprivation. These findings indicate that the effective connectivity from posterior to anterior cingulate regions is enhanced when a well-rested subject has his eyes open compared to when they are closed. Sleep deprivation impairs this directed information flow, proportional to its deleterious effect on vigilance. Therefore, sleep may play a role in the maintenance of waking effective connectivity.

Sleep loss as risk factor for neurologic disorders: a review

Sleep loss refers to sleep of shorter duration than the average baseline need of seven to eight hours per night. Sleep loss and sleep deprivation have severe effects on human health. In this article, we review the main aspects of sleep loss, taking into account its effects on the central nervous system. The neurocognitive and behavioral effects of sleep loss are well known. However, there is an increasing amount of research pointing to sleep deprivation as a risk factor for neurologic diseases, namely stroke, multiple sclerosis, Alzheimer's disease, headache, epilepsy, pain, and somnambulism. Conversely, sleep loss has been reported to be a potential protective factor against Parkinson's disease. The pathophysiology involved in this relationship is multiple, comprising immune, neuroendocrine, autonomic, and vascular mechanisms. It is extremely important to identify the individuals at risk, since recognition and adequate treatment of their sleep problems may reduce the risk of certain neurologic disorders.

Circadian rhythms, sleep deprivation, and human performance

Much of the current science on, and mathematical modeling of, dynamic changes in human performance within and between days is dominated by the two-process model of sleep-wake regulation, which posits a neurobiological drive for sleep that varies homeostatically (increasing as a saturating exponential during wakefulness and decreasing in a like manner during sleep), and a circadian process that neurobiologically modulates both the homeostatic drive for sleep and waking alertness and performance. Endogenous circadian rhythms in neurobehavioral functions, including physiological alertness and cognitive performance, have been demonstrated using special laboratory protocols that reveal the interaction of the biological clock with the sleep homeostatic drive. Individual differences in circadian rhythms and genetic and other components underlying such differences also influence waking neurobehavioral functions. Both acute total sleep deprivation and chronic sleep restriction increase homeostatic sleep drive and degrade waking neurobehavioral functions as reflected in sleepiness, attention, cognitive speed, and memory. Recent evidence indicating a high degree of stability in neurobehavioral responses to sleep loss suggests that these trait-like individual differences are phenotypic and likely involve genetic components, including circadian genes. Recent experiments have revealed both sleep homeostatic and circadian effects on brain metabolism and neural activation. Investigation of the neural and genetic mechanisms underlying the dynamically complex interaction between sleep homeostasis and circadian systems is beginning. A key goal of this work is to identify biomarkers that accurately predict human performance in situations in which the circadian and sleep homeostatic systems are perturbed.

Predicting Risk in Space: Genetic Markers for Differential Vulnerability to Sleep Restriction

Several laboratories have found large, highly reliable individual differences in the magnitude of cognitive performance, fatigue and sleepiness, and sleep homeostatic vulnerability to acute total sleep deprivation and to chronic sleep restriction in healthy adults. Such individual differences in neurobehavioral performance are also observed in space flight as a result of sleep loss. The reasons for these stable phenotypic differential vulnerabilities are unknown: such differences are not yet accounted for by demographic factors, IQ or sleep need, and moreover, psychometric scales do not predict those individuals cognitively vulnerable to sleep loss. The stable, trait-like (phenotypic) inter-individual differences observed in response to sleep loss-with intraclass correlation coefficients accounting for 58%-92% of the variance in neurobehavioral measures- point to an underlying genetic component. To this end, we utilized multi-day highly controlled laboratory studies to investigate the role of various common candidate gene variants-each independently-in relation to cumulative neurobehavioral and sleep homeostatic responses to sleep restriction. These data suggest that common genetic variations (polymorphisms) involved in sleep-wake, circadian, and cognitive regulation may serve as markers for prediction of inter-individual differences in sleep homeostatic and neurobehavioral vulnerability to sleep restriction in healthy adults. Identification of genetic predictors of differential vulnerability to sleep restriction-as determined from candidate gene studies-will help identify astronauts most in need of fatigue countermeasures in space flight and inform medical standards for obtaining adequate sleep in space. This review summarizes individual differences in neurobehavioral vulnerability to sleep deprivation and ongoing genetic efforts to identify markers of such differences.