Abstract:SUMMARYThe objective of the study was to determine whether ADORA2A or PER3 polymorphisms contribute to individual responsivity to sleep restriction. Nineteen healthy adults (ages 18-39, 11 males, 8 females) underwent sleep restriction (SR) which consisted of seven nights of 3 h time in bed (TIB) (04:00-07:00). SR was preceded by seven in-laboratory nights of 10 h TIB (21:00-07:00) and followed by three nights of 8 h TIB (23:00-07:00). Volunteers underwent psychomotor vigilance, objective alertness, and subject… Show more
“…More recently, we found that this polymorphism related to individual differences in sleep homeostatic responses, but not to performance responses to chronic partial sleep loss [45]. By contrast, two very recent studies [14,20] reported that PER3 is related to individual differences in neurobehavioral responses to sleep restriction. It remains uncertain whether differences in important methodological details— including the need for much larger replicate subject samples—underlie the discrepancies relative to PER3 as a marker for neurobehavioral vulnerability to sleep loss.…”
Section: Phenotypic Differential Vulnerability To Sleep Lossmentioning
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.
“…More recently, we found that this polymorphism related to individual differences in sleep homeostatic responses, but not to performance responses to chronic partial sleep loss [45]. By contrast, two very recent studies [14,20] reported that PER3 is related to individual differences in neurobehavioral responses to sleep restriction. It remains uncertain whether differences in important methodological details— including the need for much larger replicate subject samples—underlie the discrepancies relative to PER3 as a marker for neurobehavioral vulnerability to sleep loss.…”
Section: Phenotypic Differential Vulnerability To Sleep Lossmentioning
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.
“…143,144 We showed that this polymorphism related to individual differences in sleep homeostatic responses, but not cognitive performance responses to chronic sleep restriction. 148 By contrast, two recent studies, 167,184 which used different sleep-restriction paradigms than that of Goel et al , 148 claimed that the PER3 VNTR polymorphism was related to individual differences in neurobehavioral responses to chronic sleep restriction. Notably, one of these 184 failed to include subjects from the critical PER3 5/5 putatively vulnerable genotype, and thus its findings must be interpreted cautiously and replicated in the appropriately inclusive genotypes.…”
Section: Sleep Deprivation and Performancementioning
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.
“…Moreover, AKT1, a Ginsenoside Rb1 related gene, was related to diabetes. Furthermore, some related genes of other compounds of ginseng collected from the TCM-Mesh such as ADA, ADK, ADORA2A and GCG were reported to be associated with the sleep disorder 63, 64 and diabetes 65–68 .Figure 4The pharmacology network generated for ginseng. The innermost circle represents the compounds collected from the ginseng, the circle in the middle represented the related genes of compounds from ginseng, the outermost layer represented the diseases that were related to the genes.…”
With the advancement of systems biology research, we have already seen great progress in pharmacology studies, especially in network pharmacology. Network pharmacology has been proven to be effective for establishing the “compounds-proteins/genes-diseases” network, and revealing the regulation principles of small molecules in a high-throughput manner, thus would be very effective for the analysis of drug combinations, especially for TCM preparations. In this work, we have proposed the TCM-Mesh system, which records TCM-related information collected from various resources and could serve for network pharmacology analysis for TCM preparations in a high-throughput manner (http://mesh.tcm.microbioinformatics.org/). Currently, the database contains 6,235 herbs, 383,840 compounds, 14,298 genes, 6,204 diseases, 144,723 gene-disease associations, 3,440,231 pairs of gene interactions, 163,221 side effect records and 71 toxic records, and web-based software construct a network between herbs and treated diseases, which will help to understand the underlying mechanisms for TCM preparations at molecular levels. We have used 1,293 FDA-approved drugs, as well as compounds from an herbal material Panax ginseng and a patented drug Liuwei Dihuang Wan (LDW) for evaluating our database. By comparison of different databases, as well as checking against literature, we have demonstrated the completeness, effectiveness, and accuracy of our database.
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