Phenotypic vulnerability of energy balance responses to sleep loss in healthy adults.
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ABSTRACT:
SUBMITTER: Spaeth AM
PROVIDER: S-EPMC4597338 | biostudies-other | 2015 Oct
REPOSITORIES: biostudies-other
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Project description:We objectively measured body composition, energy expenditure, caloric intake, and sleep in a large, diverse sample of healthy men and women and determined how energy balance and diet associated with sleep physiology. Healthy adults (n = 50; 21-50 years) participated in an in-laboratory study involving two baseline sleep nights (BL1-2, 10 hours time-in-bed/night, 2200-0800 hours). Polysomnography was recorded on BL2. Demographic information, body composition, and energy expenditure measurements were collected at study admittance and on BL1. Daily food/drink intake was recorded both before (on BL1) and after (on BL2) the sleep measurement. Partial Pearson's correlations assessed the relationship between energy balance and sleep physiology variables. At baseline, greater fat-free mass associated with lower total sleep time (r = -0.52, p = .030), lower sleep efficiency (r = -0.53, p = .004), and greater wake after sleep onset (r = 0.55, p = .002). Higher body fat percentage (r = 0.39, p = .038) and being overweight (Body Mass Index [BMI] 25-30; p = .026) associated with more rapid eye movement (REM) sleep. Higher protein intake (r's = 0.46-0.52; p's < .001-.002) and lower carbohydrate intake (r's = -0.31 to -0.34; p's = .027-.046) on BL1 and BL2 associated with more REM sleep. Greater fiber consumption on BL1 and BL2 associated with more slow-wave sleep (SWS; r's = 0.33-0.35; p's = .02-.03). More SWS related to increased carbohydrate intake the following day (BL2, r = 0.32, p = .037). Body composition and diet were related to baseline sleep characteristics, including SWS and REM sleep duration and sleep maintenance. Future studies should further evaluate the influence of energy balance measures on sleep physiology, since dietary interventions may be useful in treating insufficient sleep, poor sleep quality, excessive sleepiness or other sleep disorders.
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Project description: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.
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Project description:PurposeTo assess the acute effect of pre-sleep protein supplementation combined with resistance exercise on energy metabolism (including 24-h total energy expenditure (TEE), sleep energy expenditure (SEE), basal energy expenditure (BEE), glycolipid oxidation, and appetite of sedentary adults.MethodsA total of thirty-one sedentary participants completed this randomized, double-blind, crossover study. Participants completed the following 24-h experimental conditions in random order in the Human Calorimeter chamber: (1) 40-g protein supplementation with dinner before a nighttime resistance exercise, and followed by pre-sleep placebo intake (PRO-PLA); (2) placebo intake with dinner before a nighttime resistance exercise, and followed by pre-sleep 40-g protein supplementation (PLA-PRO); and (3) placebo supplementation both with dinner and pre-sleep combined with a nighttime resistance exercise (PLA). Subjective appetite score before breakfast the next day was evaluated using the visual analog scale.ResultsThe SEE values were significantly higher by a mean of 21.7 kcal and 33.3 kcal in PRO-PLA (318.3 ± 44.3 kcal) and PLA-PRO (329.9 ± 45.2 kcal), respectively, than in PLA (296.6 ± 46.6 kcal). In addition, the SEE values for PLA-PRO was also significantly higher by 11.6 kcal than that for PRO-PLA. Further, the fullness the next morning was significantly higher by 30.8% in PLA-PRO (43.9 ± 23.5 mm) than in PLA (33.5 ± 26.6 mm). These effects remained after adjustment for 24-h energy intake.ConclusionPre-sleep protein supplementation combined with resistance exercise can significantly increase the SEE and fullness in the next morning, indicating a possible strategy to improve sleep energy metabolism in the sedentary population.
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Project description:BackgroundThe capacity of an individual to respond to changes in food intake so that postprandial metabolic perturbations are resolved, and metabolism returns to its pre-prandial state, is called phenotypic flexibility. This ability may be a more important indicator of current health status than metabolic markers in a fasting state.AimIn this parallel randomized controlled trial study, an energy-restricted healthy diet and 2 dietary challenges were used to assess the effect of weight loss on phenotypic flexibility.MethodsSeventy-two volunteers with overweight and obesity underwent a 12-wk dietary intervention. The participants were randomized to a weight loss group (WLG) with 20% less energy intake or a weight-maintenance group (WMG). At weeks 1 and 12, participants were assessed for body composition by MRI. Concurrently, markers of metabolism and insulin sensitivity were obtained from the analysis of plasma metabolome during 2 different dietary challenges-an oral glucose tolerance test (OGTT) and a mixed-meal tolerance test.ResultsIntended weight loss was achieved in the WLG (-5.6 kg, P < 0.0001) and induced a significant reduction in total and regional adipose tissue as well as ectopic fat in the liver. Amino acid-based markers of insulin action and resistance such as leucine and glutamate were reduced in the postprandial phase of the OGTT in the WLG by 11.5% and 28%, respectively, after body weight reduction. Weight loss correlated with the magnitude of changes in metabolic responses to dietary challenges. Large interindividual variation in metabolic responses to weight loss was observed.ConclusionApplication of dietary challenges increased sensitivity to detect metabolic response to weight loss intervention. Large interindividual variation was observed across a wide range of measurements allowing the identification of distinct responses to the weight loss intervention and mechanistic insight into the metabolic response to weight loss.
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Project description:ObjectivesTo investigate the objective sleep influencers behind older adult responses to subjective sleep measures, in this case, the Pittsburgh Sleep Quality Index (PSQI). Based on previous literature, we hypothesized that SE would be associated with PSQI reported sleep disruption. Furthermore, because SOL increases progressively with age and it tends to be easily remembered by the patients, we also expected it to be one of the main predictors of the perceived sleep quality in the elderly.MethodsWe studied 32 cognitively healthy community-dwelling older adults (age 74 ± 0.3 years) who completed an at-home sleep assessment (Zeo, Inc.) and the PSQI. Linear mixed models were used to analyze the association of the objective sleep parameters (measured by the Zeo) with the PSQI total score and sub-scores, adjusting for age, gender, years of education and likelihood of sleep apnea.ResultsObjective sleep parameters did not show any association with the PSQI total score. We found that objective measures of Wake after sleep onset (WASO, % and min) were positively associated with the PSQI sleep disturbance component, while SE and Total Sleep Time (TST) were negatively associated with PSQI sleep disturbance. Lastly, objective SE was positively associated with PSQI SE.ConclusionsOur findings showed that WASO, SE and TST, are associated with PSQI sleep disturbance, where the greater WASO, overall lower SE and less TST, were associated with increased subjective report of sleep disturbance. As expected, subjective (PSQI) and objective measures of SE were related. However, PSQI total score did not relate to any of the objective measures. These results suggest that by focusing on the PSQI total score we may miss the insight this easily administered self-report tool can provide. If interpreted in the right way, the PSQI can provide further insight into cognitively healthy older adults that have the likelihood of objective sleep disturbance.
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Project description:ObjectiveTo determine associations among objectively-measured nocturnal sleep time, bedtime and obesogenic behaviors, including dietary intake, timing of intake, and physical activity, in a diverse sample of school-aged children who presented for behavioral treatment to enhance sleep duration.MethodsEighty-seven children (8-11 y, 66.7% female, zBMI: 0.86 ± 1.0) who self-reported sleeping <9.5 h/night were studied for one week using wrist actigraphy to estimate sleep; hip-worn accelerometers to measure physical activity; and 24 h dietary recalls to capture dietary intake and meal timing. Pearson and Spearman's rho correlations and linear regressions controlling for age, gender and race were used for statistical analyses.Results and conclusionMean bedtime was 10:31 PM (±58.2 min) and mean nocturnal sleep time was 7.7 h (±37.5 min). Although later bedtime was associated with shorter sleep time (r = -0.61, p < 0.001), the two variables were differentially related to obesity risk factors. Later bedtime, but not sleep time, correlated with greater daily fat intake, later first meal of the day, and greater after-dinner intake (all p < 0.05). Nocturnal sleep time, but not bedtime, correlated with zBMI (p = 0.04). Both sleep time and later bedtime were associated with a later last meal of the day (all p < 0.05). Findings remained consistent after controlling for demographic factors. In short-sleeping school-aged children, bedtime may be more predictive of dietary obesity risk factors whereas sleep duration may be more predictive of zBMI. Results suggest that health providers should consider both bedtime and sleep duration for reducing obesity risk in children.Clinical trialEnhancing Sleep Duration: Effects on Children's Eating and Activity Behaviors, NCT03186508, https://clinicaltrials.gov/ct2/show/NCT03186508.
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Project description:ObjectiveFree-living adaptive responses to short-term overfeeding (OF) were explored as predictors of longitudinal weight change in adults classified as having obesity resistance (OR) or obesity proneness (OP) based on self-identification and personal/family weight history.MethodsAdults identified as OP (n?=?21; BMI: 23.8?±?2.5 kg/m2 ) and OR (n?=?20; BMI: 20.2?±?2.1 kg/m2 ) completed 3 days of eucaloric feeding (EU; 100% of energy needs) and 3 days of OF (140% of energy needs). Following each condition, adaptive responses in physical activity (PA), total daily energy expenditure, ad libitum energy intake, and energy balance were objectively measured for 3 days in a free-living environment. Body mass and composition were measured annually by using dual-energy x-ray absorptiometry for 5 years. Adaptive responses to OF were correlated with 5-year changes in body mass and composition.ResultsIncreases in sedentary time correlated with longitudinally measured changes in fat mass (r?=?0.34, P?=?0.04) in the cohort taken as a whole. Those with OP reduced their levels of PA following OF, whereas those with OR maintained or increased their PA. No other variables were found to correlate with weight gain.ConclusionsFailure to decrease sedentary behavior following short-term OF is one mechanism that may be contributing to fat mass gain.
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Project description:Although recent studies have shown that human genomes contain hundreds of loci that exhibit signatures of positive selection, variants that are associated with adaptation in energy-balance regulation remain elusive. We reasoned that the difficulty in identifying such variants could be due to heterogeneity in selection pressure and that an integrative approach that incorporated experiment-based evidence and population genetics-based statistical judgments would be needed to reveal important metabolic modifiers in humans.To identify common metabolic modifiers that underlie phenotypic variation in diabetes-associated or obesity-associated traits in humans, or both, we screened 207 candidate loci for regulatory single nucleotide polymorphisms (SNPs) that exhibited evidence of gene-environmental interactions.Three SNPs (rs3895874, rs3848460, and rs937301) at the 5' gene region of human GIP were identified as prime metabolic-modifier candidates at the enteroinsular axis. Functional studies have shown that GIP promoter reporters carrying derived alleles of these three SNPs (haplotype GIP(-1920A)) have significantly lower transcriptional activities than those with ancestral alleles at corresponding positions (haplotype GIP(-1920G)). Consistently, studies of pregnant women who have undergone a screening test for gestational diabetes have shown that patients with a homozygous GIP(-1920A/A) genotype have significantly lower serum concentrations of glucose-dependent insulinotropic polypeptide (GIP) than those carrying an ancestral GIP(-1920G) haplotype. After controlling for a GIPR variation, we showed that serum glucose concentrations of patients carrying GIP(-1920A/A) homozygotes are significantly higher than that of those carrying an ancestral GIP(-1920G) haplotype (odds ratio 3.53).Our proof-of-concept study indicates that common regulatory GIP variants impart a difference in GIP and glucose metabolism. The study also provides a rare example that identified the common variant-common phenotypic variation pattern based on evidence of moderate gene-environmental interactions.
| S-EPMC3046833 | biostudies-literature
Project description:Study objectivesExcessive daytime sleepiness commonly affects obese people, even in those without sleep apnea, yet its causes remain uncertain. We sought to determine whether acute dietary changes could induce or rescue wake impairments independent of body weight.DesignWe implemented a novel feeding paradigm that generates two groups of mice with equal body weight but opposing energetic balance. Two subsets of mice consuming either regular chow (RC) or high-fat diet (HFD) for 8 w were switched to the opposite diet for 1 w. Sleep recordings were conducted at Week 0 (baseline), Week 8 (pre-diet switch), and Week 9 (post-diet switch) for all groups. Sleep homeostasis was measured at Week 8 and Week 9.ParticipantsYoung adult, male C57BL/6J mice.Measurements and resultsDifferences in total wake, nonrapid eye movement (NREM), and rapid eye movement (REM) time were quantified, in addition to changes in bout fragmentation/consolidation. At Week 9, the two diet switch groups had similar body weight. However, animals switched to HFD (and thus gaining weight) had decreased wake time, increased NREM sleep time, and worsened sleep/wake fragmentation compared to mice switched to RC (which were in weight loss). These effects were driven by significant sleep/wake changes induced by acute dietary manipulations (Week 8 → Week 9). Sleep homeostasis, as measured by delta power increase following sleep deprivation, was unaffected by our feeding paradigm.ConclusionsAcute dietary manipulations are sufficient to alter sleep and wakefulness independent of body weight and without effects on sleep homeostasis.
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Project description:Study objectivesInsufficient sleep is believed to promote positive energy balance (EB) and weight gain. Increasing weekend sleep duration to "recover" from weekday sleep loss is common, yet little is known regarding how weekend recovery sleep influences EB. We conducted a randomized controlled trial to assess how: (1) 2 days and 8 days of insufficient sleep and (2) ad libitum weekend recovery sleep impact EB (energy intake [EI] - energy expenditure [EE]).MethodsFollowing ten baseline days with 9 h per night sleep opportunities, participants completed one of three 10-day experimental protocols with ad libitum EI: control (9 h sleep opportunities; n = 8; 23 ± 5 years [mean ± SD]); sleep restriction (SR; 5 h sleep opportunities; n = 14; 25 ± 5 years); sleep restriction with weekend recovery sleep (SR + WR; 5 days insufficient sleep, 2 days ad libitum weekend recovery sleep, 3 days recurrent insufficient sleep; n = 14; 27 ± 4 years).ResultsTwenty-four hour EB increased (p < 0.001; main effect) by an average of 797.7 ± 96.7 (±SEM) kcal during the 10-day experimental protocol versus baseline with no significant differences between groups. Percent change from baseline in 24 h-EE was higher (p < 0.05) on day 2 of insufficient sleep (SR and SR + WR groups; 10 ± 1%) versus adequate sleep (control group; 4 ± 3%).ConclusionsIn this between-group study, the effects of adequate sleep and insufficient sleep, with or without or weekend recovery sleep, on 24 h-EB were similar. Examining EB and body weight changes using within-subject cross-over designs and "free-living" conditions outside the laboratory (e.g. sleep extension) are needed to advance our understanding of the links between insufficient sleep, weekend recovery sleep and weight-gain.
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