Predicting Risk in Space: Genetic Markers for Differential Vulnerability to Sleep Restriction.
ABSTRACT 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.
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ABSTRACT: 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.Progress in molecular biology and translational science 01/2013; 119:155-90. · 3.11 Impact Factor
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ABSTRACT: Maintaining human alertness and behavioral capability under conditions of sleep loss and circadian misalignment requires fatigue management technologies due to: (i) dynamic nonlinear modulation of performance capability by the interaction of sleep homeostatic drive and circadian regulation; (ii) large differences among people in neurobehavioral vulnerability to sleep loss; (iii) error in subjective estimates of fatigue on performance; and (iv) 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.Sleep and Biological Rhythms 04/2014; 12(2). · 1.05 Impact Factor
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ABSTRACT: 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.Current opinion in neurobiology 03/2013; · 7.21 Impact Factor