Circadian misalignment, as experienced during shiftwork, impairs glucose metabolism and body weight regulation, yet the underlying biochemical mechanisms remain incompletely understood. Characterizing how circadian misalignment alters circulating metabolites provides a promising avenue to help identify these mechanisms. Although data from metabolomics studies have identified circulating metabolites with daily rhythms, it is not comprehensively known which rhythms shift during circadian misalignment and whether such shifts relate to metabolic impairment. We conducted 24-hour (h) metabolomic profiling every 4 h in 14 healthy adults (8 women) aged 26.4 ± 1.2 years (mean ± SD), undergoing a 6-day simulated night-shiftwork protocol. 24-h modeling analyses identified metabolite rhythms influenced by circadian versus behavioral cycles (sleep, food intake) and quantified internal circadian misalignment using acrophase shifts. Metabolic outcomes included glucose homeostasis (test meals) and energy expenditure (EE; whole-room calorimetry). Night-shiftwork produced widespread alterations in metabolite rhythms, with significant internal misalignment in multiple metabolites across pathways including pyrimidine metabolism, bile acid-microbiome signaling, and lipid metabolism. During misalignment, glucose and insulin area under the curve increased (p < 0.05) and EE decreased (p < 0.05). Internal misalignment of uridine and glycoursodeoxycholic acid was associated (p < 0.05) with impaired glucose tolerance, while their circulating concentrations were associated with decreased EE. Misalignment of uridine and glycoursodeoxycholic acid suggests dysregulated pyrimidine and bile acid-microbiome pathways as potential mechanisms linking circadian misalignment to cardiometabolic disease risk.

Study Objectives:We examined the impact of a sleep extension intervention on multiple dimensions of sleep in adults with habitual short sleep duration. Methods:Thirty healthy participants (14 women; aged 23.1 ± 4.5 years; BMI 22.3 ± 2.2 kg/m2 [mean ± SD]) with <6.5 h sleep/night completed a 2-week baseline assessment followed by a 4-week sleep extension intervention (2 h/night increased time in bed). Wrist actigraphy, at-home electroencephalography (EEG; DREEM headband), Insomnia Severity Index (ISI), Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale (ESS), and daily quality/satisfaction and alertness Likert-scales quantified sleep. Results:Baseline total sleep time (TST) was 5.5 ± 0.7 h. During sleep extension, actigraphy time in bed and TST increased (p < .001) by 60.8 ± 46.7 and 46.6 ± 41.1 minutes, respectively, sleep onset shifted earlier (p < .001) by 51.9 ± 64.5 minutes, with regularity similar to baseline. EEG showed increases (all p < .05) in TST (61.8 ± 75.6 minutes), Stage N1 (5.09 ± 6.51 minutes), Stage N2 (39.54 ± 41.78 minutes), rapid eye movement sleep (13.58 ± 28.86 minutes), and wakefulness after sleep onset (4.86 ± 8.03 minutes), with a nonsignificant decrease (p = .07) in sleep efficiency (-1.38 ± 4.15%). Subjective alertness, ISI, PSQI, and ESS each improved (all p < .05) during sleep extension. Conclusion:Our findings help establish efficacy of sleep extension as an experimental intervention the sleep field can leverage across diverse contexts to study potential health benefits of increasing free-living TST. During sleep extension, the largest effects were observed for improved TST and ESS. Alternatively, some sleep dimensions including sleep regularity remained unchanged, highlighting a potential need for developing multi-component interventions that can improve more dimensions of sleep as both short and irregular sleep are linked with adverse health outcomes. Clinical Trials:Biomarkers of Increased Free Living Sleep Time. URL: https://clinicaltrials.gov/study/NCT04214184. ClinicalTRIALS.gov ID: NCT04214184.

Topic Importance As awareness of sleep’s role in health grows, consumer sleep technologies (CSTs) have gained wide use among both researchers and the public. These devices offer continuous, noninvasive sleep tracking in real-world environments. However, understanding their accuracy compared with that of polysomnography (PSG), the gold standard in sleep measurement, remains limited, particularly in free-living settings and clinical populations. Assessing CST performance and usability in these contexts is essential for guiding future adoption. Review Findings This review identified 29 studies evaluating CSTs in ambulatory settings. CSTs showed moderate accuracy in estimating total sleep time and time in bed but lower precision for sleep efficiency, wake after sleep onset, and stage classification. Rapid eye movement and deep sleep estimates were particularly unreliable. Multi-sensor devices modestly improved basic sleep-wake detection, and contactless devices offered lower user burden but limited portability. Few studies included clinical populations such as individuals with insomnia, depression, or older adults. Only a small number explored CSTs in intervention delivery, and integration into clinical care remains minimal. Summary CSTs may support general sleep monitoring under real-world conditions, especially for duration and circadian timing. However, accuracy remains limited for sleep staging and fragmentation, and most devices have not been validated in diverse or clinical populations. Ongoing improvements in device design, signal integration, and algorithm transparency are needed to enhance CST reliability and clinical relevance.

Although protein supplementation is a common sports nutrition strategy, there is little research on its effects in adolescent athletes. Our objective was to assess the effects of whey protein supplementation on athletic performance and body composition in adolescent soccer players over a 10-week competitive soccer season. Adolescent athletes (n = 22; 59% female, age: 15.6 ± 0.2 [mean ± SEM] years; BMI percentile: 55.9 ± 6.2%) were randomized to consume either whey protein (PRO; n = 10; 20 g protein) or an isocaloric placebo (CON; n = 12) twice daily. Outcome measures included: estimated V̇O2max (1.5 mile run), sprint time (30 yard dash), muscle strength and endurance (quadricep isometric leg extension; maximum voluntary contraction and repetitions to fatigue, respectively), and body composition (fat mass and fat-free mass). Assessments were conducted at baseline and postintervention. V̇O2max improved in both groups (p < 0.001), with greater (p = 0.04) increases in the PRO versus CON group. Sprint time improved in both groups (p = 0.03), with no significant differences between groups. Muscle strength was similar across the study for both groups. Muscular endurance declined in the PRO group compared to CON (p = 0.01). Fat-free mass increased in both groups (p = 0.02), whereas fat mass was unchanged. Our results indicate that whey protein supplementation during the competitive season in adolescent athletes improved V̇O2max compared to control. However, whey protein did not lead to improvements in sprint performance, musculoskeletal fitness, and body composition compared to control. clinicaltrials.gov (NCT05589129).

The circadian system maintains optimal biological functions at the appropriate time of day, and the disruption of this organization can contribute to the pathogenesis of cardiometabolic disorders. The timing of eating is a prominent external time cue that influences the circadian system. “Chrononutrition” is an emerging dimension of nutrition and active area of research that examines how timing‐related aspects of eating and nutrition impact circadian rhythms, biological processes, and disease pathogenesis. There is evidence to support chrononutrition as a form of chronotherapy, such that optimizing the timing of eating may serve as an actionable strategy to improve cardiometabolic health. This report summarizes key information from the National Heart, Lung, and Blood Institute's virtual workshop entitled “Chrononutrition: Elucidating the Role of Circadian Biology and Meal Timing in Cardiometabolic Health,” which convened on May 2 to 3, 2023, to review current literature and identify critical knowledge gaps and research opportunities. The speakers presented evidence highlighting the impact on cardiometabolic health of earlier and shorter eating windows and more consistent day‐to‐day eating patterns. The multidimensionality of chrononutrition was a common theme, as it encompasses multiple facets of eating along with the timing of other behaviors including sleep and physical activity. Advancing the emerging field of chrononutrition will require: (1) standardization of terminology and metrics; (2) scalable and precise tools for real‐world settings; (3) consideration of individual differences that may act as effect modifiers; and (4) deeper understanding of social, behavioral, and cultural influences. Ultimately, there is great potential for circadian‐based dietary interventions to improve cardiometabolic health.

Despite significant public health efforts to counter the obesity epidemic, approximately 50% of US adults will have obesity by 2030. The cornerstone of obesity treatment is a behavioral intervention promoting negative energy balance via a reduced-calorie diet and increased physical activity. Behavioral treatment also requires additional support to promote adherence to these recommended lifestyle changes. More recently, sleep has been recognized as an important component of body weight regulation due to its effects on physiological and behavioral determinants of energy balance. Therefore, sleep may represent a modifiable behavior to target during the behavioral treatment of obesity. This review summarizes existing clinical evidence on the influence of sleep on energy balance and body weight regulation in adults. The results of controlled laboratory studies as well as pragmatic clinical trials are reviewed. In addition, we identify existing gaps and future areas of research that are necessary to understand the role of sleep in behavioral treatments for obesity.

The human blood proteome has been found to vary with time-of-day and in response to circadian misalignment (daytime sleep, nighttime wakefulness). Efforts to develop blood-based biomarkers for Alzheimer’s disease have largely ignored such factors. We identified plasma candidate biomarkers for Alzheimer’s disease by a literature review of current proteomic studies and examined if the biomarkers were influenced by time-of-day and/or circadian misalignment during an in-laboratory study. A systematic literature review using keywords including but not limited to, “Alzheimer’s”, “mild cognitive impairment”, “proteomics” and “plasma biomarker” was performed to find relevant studies. Biomarkers were chosen based upon their presence in three or more studies or cohorts. Identified proteins were analyzed using the SomaLogic Inc platform in six healthy men aged 26.2±5.6y (mean±SD) that completed a 6 day in-laboratory simulated night-shift protocol. We compared proteins analyzed every four hours during baseline circadian alignment and circadian misalignment conditions with mixed model ANOVA. From the literature review, we identified 28 proteins that appeared in three or more studies or cohorts. Of the 28 proteins, 14% varied with time-of-day (main effects of time-of-day, p< 0.05; angiopoietin-2, apolipoprotein B, insulin-like growth factor-binding protein 2, myoglobin), and 17% were influenced by circadian misalignment (main effect of study day, p< 0.05; beta-2-microglobulin, insulin-like growth factor-binding protein 2, immunoglobulin M, brain natriuretic peptide, vascular cell adhesion molecule-1). Furthermore, 17% showed study day by time-of-day interactions (p< 0.05; alpha-1-antitrypsin, apolipoprotein E, beta-2-microglobulin, myoglobin, pancreatic polypeptide) such that the time-of-day variation of these proteins depended on whether the participants were circadian aligned or misaligned. The current findings suggest that the time-of-day modulates concentrations of some protein biomarkers of Alzheimer’s disease, and that circadian misalignment also impacts such biomarkers. These findings have implications for the further development of plasma biomarkers for Alzheimer’s disease, Alzheimer’s disease risk, the potential implementation of such biomarkers, as well as precision medicine efforts. NIH Grants DK092624, HL132150, DK111161, TR001082, DK048520 and R25 NS 125603. McNair Scholars Program.

The objective of this study was to explore whether the time of day (AM vs. PM) resistance exercise is performed influences glucose and insulin concentrations, body composition, and muscular strength in adults with prediabetes. A secondary data analysis was conducted using data from the "Resist Diabetes" study, a phase II exercise intervention. Participants (age: 59.9 ± 5.4 yr; BMI: 33 ± 3.7 kg/m2) with prediabetes and overweight or obesity were categorized into AM (n = 73) or PM (n = 80) exercisers based on when they completed all of their supervised exercise sessions during a 12-wk, 2×/wk resistance exercise intervention. Blood glucose and insulin derived from oral glucose tolerance tests, body composition, and muscular strength were assessed pre- and post resistance exercise training. Inverse propensity score weighting approach was used to estimate the efficacy of AM versus PM exercise on the change of clinical responses. Paired samples t test was used to compare pre-/post-outcomes within AM and PM groups. No differences between AM and PM exercisers were detected in the change in glucose or insulin area under the curve (AUC), body composition, or muscular strength. When exploring within-group changes, PM exercisers reduced glucose AUC (change: -800.6 mg/dL·120 min; P = 0.01), whereas no significant change was detected for AM exercisers (change: -426.9 mg/dL·120 min; P = 0.26). Only AM exercisers increased fat-free mass (change: 0.6 kg; P = 0.001). The time of day resistance exercise is performed may have some impact on glucose concentrations and body composition response. Future randomized clinical trials are needed to understand how exercise timing influences cardiometabolic outcomes in at-risk adults.NEW & NOTEWORTHY In this secondary analysis, there was no difference between AM and PM exercisers in blood glucose, insulin, body composition, or muscular strength following 12 wk of supervised exercise. However, examining within-group changes, glucose area under the curve (AUC) was significantly reduced in PM exercisers, but not in AM exercisers.

Insufficient sleep and circadian misalignment dysregulate glucose homeostasis. Interventions are needed for when insufficient sleep and circadian misalignment cannot be avoided (e.g., military operations, emergency responders, shift work). Prebiotics, defined as a substrate that is selectively utilized by host microorganisms conferring a health benefit, have been shown to beneficially affect glucose metabolism in non-human preclinical models and in humans. Here, we examined in a pilot study the effects of a combined Polydextrose (PDX) and Galacto-oligosaccharide (GOS) prebiotic supplement on 24-hour glucose levels during combined sleep restriction and circadian misalignment. 5 healthy adults (aged 25.4±3.5, 2 females) completed a 39-day randomized, double-blind, placebo-controlled, cross-over study comparing a prebiotic–7.5g/day each of GOS [Frieslad Campina] and PDX [Dupont Nutrition & Biosciences] or placebo (maltodextrin [Grain Processing Corporation]) sachets dissolved in water with breakfast. Participants consumed 14 days of prebiotic or placebo at home while maintaining regular mealtimes and ~8h habitual sleep each night. Participants then completed an ~4-day in-laboratory study of combined sleep restriction and circadian misalignment with 3h sleep opportunities; the first at night and the second and third during the daytime. Prebiotic and placebo conditions continued in-laboratory. Timing and composition of food intake was identical during the in-laboratory segment for each condition and designed to maintain energy balance. Glucose levels were monitored every 15 min for ~60h using a continuous glucose monitor (FreeStyle Libre Pro [Abbott]). Participants had a 3-day washout period prior to repeating the protocol with the second condition. Mixed model ANOVA with condition and time as fixed factors were performed. Mean 24-hour glucose level over the ~60h of recording was significantly lower during prebiotic versus placebo treatment (p< 0.00001; Small effect size, Hedges’ g bias corrected). Preliminary findings from this pilot study suggest that a combination of prebiotic fibers taken prior to and during insufficient sleep and circadian misalignment may have some benefits for glucose metabolism. Office of Naval Research MURI N00014-15-1-2809, NIH CTSA Grant Ul1-TR002535, NIH T32-HL149646, and Undergraduate Research Opportunities Grant University of Colorado Boulder.

Overeating and insufficient sleep have been reported to increase total daily carbohydrate utilization. Here we evaluated substrate utilization over 24h and specifically during nighttime hours under insufficient sleep conditions. Thirty-six healthy participants (18 women/18 men) aged 25.5±4.7y (mean±SD), with normal body mass index (BMI) 22.4±1.7kg/m2 completed a 13-16 day in-laboratory study. Participants were randomly assigned to one of three groups with different sleep opportunities simulating two work weeks (WW1 and WW2) and one weekend between them. After three baseline (BL) laboratory days of 9h sleep opportunity per night, participants in the control group (n=8) were scheduled to 10 days of 9h sleep opportunity; the sleep restriction (SR) group (n=14) were scheduled to 10 days of 5h sleep opportunity, and the weekend recovery (WR) group (n=14) were scheduled to five days of 5h sleep opportunity (WW1) followed by two days of ad libitum weekend recovery sleep, followed by three days of 5h sleep opportunity (WW2). Participants were provided an energy balanced diet for three days prior to laboratory admission and continued for the three BL days. Food intake was ad libitum during WW1 and WW2. Whole room indirect calorimetry assessed hourly substrate utilization on days 3 (BL), 5 (WW1) and 11 (WW2). Respiratory quotient (RQ), fat and carbohydrate utilization were assessed by oxygen consumption and carbon dioxide production. Differences in RQ and substrate utilization throughout the 24h were analyzed within groups across BL, WW1 and WW2. Sleep restriction significantly (p< 0.05) increased carbohydrate utilization, especially during the 4h prior to bedtime, during WW1 (SR: 0.28g.min-1±0.02 and WR: 0.31g.min-1±0.02) and WW2 (SR: 0.30g.min-1±0.02 and WR: 0.31g.min-1±0.02)compared to baseline (SR: 0.15 g.min-1±0.02 and WR: 0.14g.min-1±0.02) for SR and WR groups. Additionally, the 24h RQ and 24h carbohydrate utilization were higher for the WR group in WW2 compared to BL (p< 0.05). Insufficient sleep under conditions of ad libitum food intake appears to increase nighttime carbohydrate utilization prior to bedtime. These findings contribute to our understanding of how insufficient sleep alters energy metabolism in humans. NIH HL109706, DK111161, TR001082, DK048520, and Sleep Research Society Foundation grant 011-JP-16.

Taxa level associations of the human gut microbiota have been reported in relation to sleep health; however, which taxa are associated with good sleep has yet to be determined. Many study methodologies rely on self-reported sleep metrics, 16S rRNA gene-amplicon sequencing or statistical methodologies not designed for gut microbiome assessments, which have limitations. We examined the association between sleep measures assessed by actigraphy followed by one night of in-laboratory polysomnography (PSG) and whole genome sequencing (WGS) gut microbiome taxa. Fifteen healthy participants aged 26±4.0(SD) were instructed to maintain a consistent 8h sleep schedule for fourteen days at home. Wrist actigraphy and time stamped call-ins were assessed for adherence. Following fourteen days of monitoring, participants underwent 8h overnight in-laboratory PSG. Fecal microbiome samples were collected at PSG visit. WGS at the operational genomic unit (OGU) were then referenced against Web of Life 2 for taxonomic assignment. Differential abundance testing (ANCOM-BC) was performed to detect the OGUs associated with individuals with high (≥85%) or low (< 85%) sleep efficiency (SE) assessed via actigraphy. Following, linear regression associations between SE, sleep onset latency (SOL) and wake after sleep onset (WASO) from PSG were tested against these differentially abundant OGUs to determine: 1) whether these associations were maintained with PSG SE and; 2) whether these taxa were associated with SOL or WASO. ANCOM-BC determined Bifidobacterium breve and Bifidobacterium saguini species were increased in the high SE wrist actigraphy group (log fold change 2.2, q=0.002 and log fold change 2.0, q=0.006, respectively). Linear regression indicated increased breve and saguini were associated with higher PSG SE (β=0.0003, p=0.03, R²=0.18 and β=0.0013, p=0.02, R²=0.46, respectively). Further investigation into PSG SOL and WASO indicated that the higher SE was due to these strains being associated with decreased WASO, specifically (β=–0.09, p=0.04, R²=0.38 and β=–0.58, p=0.04, R²=0.40, respectively). We find that higher SE, specifically by decreased WASO, is associated with higher levels of two Bifidobacterium species, breve and saguini. Bifidobacterium, commonly found in probiotics, may improve subjective sleep quality. Therefore, Bifidobacterium breve and saguini may be specific targets for improving human sleep. ONR N00014-15-1-2809, NIH-T32-HL149646, NIH/NCATS Colorado CTSA-UL1TR002535.

The duration between dim-light melatonin onset and offset represents the biological night, which tracks environmental darkness (i.e., scotoperiod). In humans, melatonin duration is longer after one week of exposure to natural winter (~9.33h light:14.67h dark) versus natural summer (~14.67h light:9.33h dark) light-dark cycles. Melatonin duration is also longer after one month of exposure to 14h versus habitual ~8h sleep opportunities; as well as in people who habitually sleep longer than 9h versus shorter than 6h. Our current aim was to determine whether a shorter difference in scotoperiod, 8h versus 9h sleep opportunities, impacts the duration of the biological night. Archival data from 76 healthy adult participants (aged 26.1±6.8[Mean±SD]; 44 females) from five research protocols were examined. Depending on the study protocol, participants maintained consistent 8h (n=40) or 9h (n=36) sleep schedules for one or two weeks at home, verified with wrist-actigraphy and bed/waketime call-ins. 24-hour plasma or salivary melatonin samples were then collected in the laboratory under dim-light conditions during wakefulness (< 10 lux max; ~1.9 lux, ~0.6 Watts/m2 in the angle of gaze) and darkness (0 lux) during sleep. Melatonin duration was calculated as the time between dim light melatonin onset (DLMO25%) and dim light melatonin offset (DLMOff25%). Melatonin duration was significantly longer in the 9h (11.1h±2.3) versus 8h (10.2h±1.2) (Mean±SD) sleep opportunity condition (p< 0.05). The current findings demonstrate that as little as one hour difference in scotoperiod is associated with an ~0.9h difference in the duration of the biological night, suggesting that melatonin duration tracks even relatively minor changes in environmental light-dark exposure. These findings have important implications for circadian and sleep research, including understanding how the environment contributes to differences in biological night. In future studies, it will be important to determine the impact of the duration of the biological night on human physiology and behavior. NIH HL085705, NIH HL109706, HL149646, DK111161, DK048520, TR000154, UL1TR002535 and TR001082; Sleep Research Society Foundation grant 011-JP-16; CurAegis Technologies Inc. (formerly Torvec, Inc); Office of Naval Research MURI N00014-15-1-2809; and Howard Hughes Medical Institute in collaboration with the Biological Sciences Initiative and Undergraduate Research Opportunities Grant University of Colorado Boulder