Diurnal variation in anxiety and activity is influenced by chronotype and probable anxiety-related disorder status.

Anxiety symptoms vary moment-to-moment within a day. One factor that may influence these variations is chronotype. Evening chronotypes prefer to engage in activities (e.g., sleep, physical and social activity) later in the day, and evening chronotype is implicated in psychopathology, including anxiety-related disorders. However, it is unknown whether chronotype influences diurnal variation in anxiety symptoms and whether these effects are amplified in individuals with a probable anxiety-related disorder. We examined the diurnal variation in anxiety symptoms and daily activities in morning and evening chronotypes with and without probable generalized anxiety disorder (GAD) or obsessive-compulsive disorder (OCD) in a community sample of adults (N = 410). Evening chronotypes reported higher anxiety symptoms, particularly in the evening hours, and lower engagement in daily activities, predominantly in the morning hours. Evening chronotypes with probable GAD or OCD reported worse anxiety symptoms in the evening. Our findings indicate that anxiety symptoms and engagement in daily activities fluctuate considerably across the day, and these patterns differ depending on chronotype. Evening chronotypes have more anxiety symptoms in the evening, despite preferring this time of day. Personalized treatment approaches that consider chronotype and target certain times of day may be efficient in alleviating peaks in anxiety symptoms.

Chronotype and Affective Response to Sleep Restriction and Subsequent Sleep Deprivation.

Prior research indicates that sleep restriction, sleep deprivation, and circadian misalignment diminish positive affect, whereas effects on negative affect are inconsistent. One potential factor that may influence an individual's affective response to sleep restriction, sleep deprivation, and circadian misalignment is chronotype. Later chronotypes generally report higher negative affect and lower positive affect under typical sleep conditions; however, there is mixed evidence for an influence of chronotype on affective responses to sleep restriction and sleep deprivation. The present study examined the effect of chronotype on positive and negative affect during sleep restriction and subsequent total sleep deprivation. Sixteen healthy adults (Mage = 28.2 years, SDage = 11.6 years) were classified as earlier or later chronotypes using multiple chronotype definitions: morningness-eveningness (MEQ), mid-sleep on free days corrected (MSFsc), habitual mid-sleep timing, dim light melatonin onset (DLMO), and phase relationship between DLMO and bedtime. Participants completed a 10-day protocol with one night of sleep restriction and subsequent 28 h total sleep deprivation. Affect was assessed hourly during scheduled wakefulness with the Positive and Negative Affect Schedule (PANAS). Data were analyzed with mixed-model analyses of variance (ANOVAs). During sleep restriction and subsequent sleep deprivation, positive affect decreased and negative affect increased. Across all chronotype measures, relatively later chronotypes demonstrated vulnerability to increased negative affect during sleep loss. The influence of chronotype on positive affect during sleep loss varied by chronotype measure. These findings suggest later chronotypes are more vulnerable to affective impairments during sleep loss and circadian misalignment, even when late chronotype is not extreme.

Distribution of dim light melatonin offset (DLMOff) and phase relationship to waketime in healthy adults and associations with chronotype.

OBJECTIVES: Dim light melatonin onset, or the rise in melatonin levels representing the beginning of the biological night, is the gold standard indicator of circadian phase. Considerably less is known about dim light melatonin offset, or the decrease in melatonin to low daytime levels representing the end of the biological night. In the context of insufficient sleep, morning circadian misalignment, or energy intake after waketime but before dim light melatonin offset, is linked to impaired insulin sensitivity, suggesting the need to characterize dim light melatonin offset and identify risk for morning circadian misalignment. METHODS: We examined the distributions of dim light melatonin offset clock hour and the phase relationship between dim light melatonin offset and waketime, and associations between dim light melatonin offset, phase relationship, and chronotype in healthy adults (N = 62) who completed baseline protocols measuring components of the circadian melatonin rhythm and chronotype. RESULTS: 74.4% demonstrated dim light melatonin offset after waketime, indicating most healthy adults wake up before the end of biological night. Later chronotype (morningness-eveningness, mid-sleep on free days corrected, and average mid-sleep) was associated with later dim light melatonin offset clock hour. Later chronotype was also associated with a larger, positive phase relationship between dim light melatonin offset and waketime, except for morningness-eveningness. CONCLUSIONS: These findings suggest morning circadian misalignment risk among healthy adults, which would not be detected if only dim light melatonin onset were assessed. Chronotype measured by sleep timing may better predict this risk in healthy adults keeping a consistent sleep schedule than morningness-eveningness preferences. Additional research is needed to develop circadian biomarkers to predict dim light melatonin offset and evaluate appropriate dim light melatonin offset timing to promote health.

Influence of circadian phase and extended wakefulness on glucose levels during forced desynchrony.

OBJECTIVES: Circadian misalignment and sleep deprivation often occur in tandem, and both negatively impact glucose homeostasis and metabolic health. The present study employed a forced desynchrony protocol to examine the influence of extended wakefulness and circadian misalignment on hourly glucose levels. METHODS: Nine healthy adults (4F/5M; 26 ± 4years) completed a 31-day in-laboratory protocol. After three 24 hour baseline days with 8 hours scheduled sleep opportunities, participants were scheduled to 14 consecutive 42.85 hour sleep-wake cycles, with 28.57 hours extended wakefulness and 14.28 hours sleep opportunities each cycle. Blood was sampled hourly across the forced desynchrony and over 600 plasma samples per participant were analyzed for glucose levels. RESULTS: Both hours into the 42.85 hours forced desynchrony day and circadian phase modulated glucose levels (p < .0001). Glucose peaked after each meal during scheduled wakefulness and decreased during scheduled sleep/fasting. Glucose levels were, on average, lowest during the biological daytime and rose throughout the biological night, peaking in the biological morning. When analyzed separately for scheduled sleep vs. wakefulness, the peak timing of the circadian rhythm in glucose was later during sleep (p < .05). Glucose area under the curve levels increased rapidly from the beginning of the forced desynchrony protocol and were highest on the second forced desynchrony day (p < .01), returning towards forced desynchrony day 1 levels thereafter. CONCLUSIONS: These findings have important implications for understanding factors contributing to altered glucose metabolism during sleep loss and circadian misalignment, and for potential physiological adaptation of metabolism in healthy adults, who are increasingly exposed to such conditions in our society.

Multivariate genome-wide association study of sleep health demonstrates unity and diversity.

There has been a recent push to focus sleep research less on disordered sleep and more on the dimensional sleep health. Sleep health incorporates several dimensions of sleep: chronotype, efficiency, daytime alertness, duration, regularity, and satisfaction with sleep. A previous study demonstrated sleep health domains correlate only moderately with each other at the genomic level (|rGs| = 0.11-0.51) and show unique relationships with psychiatric domains (controlling for shared variances, duration, alertness, and non-insomnia independently related to a factor for internalizing psychopathology). Of the domains assessed, circadian preference was the least genetically correlated with all other facets of sleep health. This pattern is important because it suggests sleep health should be considered a multifaceted construct rather than a unitary construct. Prior genome-wide association studies (GWASs) have vastly increased our knowledge of the biological underpinnings of specific sleep traits but have only focused on univariate analyses. We present the first multivariate GWAS of sleep and circadian health (multivariate circadian preference, efficiency, and alertness factors, and three single-indicator factors of insomnia, duration, and regularity) using genomic structural equation modeling. We replicated loci found in prior sleep GWASs, but also discovered "novel" loci for each factor and found little evidence for genomic heterogeneity. While we saw overlapping genomic enrichment in subcortical brain regions and shared associations with external traits, much of the genetic architecture (loci, mapped genes, and enriched pathways) was diverse among sleep domains. These results confirm sleep health as a family of correlated but genetically distinct domains, which has important health implications.

Insufficient sleep and weekend recovery sleep: classification by a metabolomics-based machine learning ensemble.

Although weekend recovery sleep is common, the physiological responses to weekend recovery sleep are not fully elucidated. Identifying molecular biomarkers that represent adequate versus insufficient sleep could help advance our understanding of weekend recovery sleep. Here, we identified potential molecular biomarkers of insufficient sleep and defined the impact of weekend recovery sleep on these biomarkers using metabolomics in a randomized controlled trial. Healthy adults (n = 34) were randomized into three groups: control (CON: 9-h sleep opportunities); sleep restriction (SR: 5-h sleep opportunities); or weekend recovery (WR: simulated workweek of 5-h sleep opportunities followed by ad libitum weekend recovery sleep and then 2 days with 5-h sleep opportunities). Blood for metabolomics was collected on the simulated Monday immediately following the weekend. Nine machine learning models, including a machine learning ensemble, were built to classify samples from SR versus CON. Notably, SR showed decreased glycerophospholipids and sphingolipids versus CON. The machine learning ensemble showed the highest G-mean performance and classified 50% of the WR samples as insufficient sleep. Our findings show insufficient sleep and recovery sleep influence the plasma metabolome and suggest more than one weekend of recovery sleep may be necessary for the identified biomarkers to return to healthy adequate sleep levels.

Not simply a matter of parents-Infants' sleep-wake patterns are associated with their regularity of eating.

In adults there are indications that regular eating patterns are related to better sleep quality. During early development, sleep and eating habits experience major maturational transitions. Further, the bacterial landscape of the gut microbiota undergoes a rapid increase in complexity. Yet little is known about the association between sleep, eating patterns and the gut microbiota. We first hypothesized that higher eating regularity is associated with more mature sleep patterns, and second, that this association is mediated by the maturational status of the gut microbiota. To test this hypothesis, we performed a longitudinal study in 162 infants to assess actigraphy, diaries of sleep and eating times, and stool microbiota composition at ages 3, 6 and 12 months. To comprehensively capture infants' habitual sleep-wake patterns, 5 sleep composites that characterize infants' sleep habits across multiple days in their home environment were computed. To assess timing of eating habits, we developed an Eating Regularity Index (ERI). Gut microbial composition was assessed by 16S rRNA gene amplicon sequencing, and its maturation was assessed based on alpha diversity, bacterial maturation index, and enterotype. First, our results demonstrate that increased eating regularity (higher ERI) in infants is associated with less time spent awake during the night (sleep fragmentation) and more regular sleep patterns. Second, the associations of ERI with sleep evolve with age. Third, the link between infant sleep and ERI remains significant when controlling for parents' subjectively rated importance of structuring their infant's eating and sleeping times. Finally, the gut microbial maturational markers did not account for the link between infant's sleep patterns and ERI. Thus, infants who eat more regularly have more mature sleep patterns, which is independent of the maturational status of their gut microbiota. Interventions targeting infant eating rhythm thus constitute a simple, ready-to-use anchor to improve sleep quality.

Mechanisms and physiological function of daily haemoglobin oxidation rhythms in red blood cells.

Cellular circadian rhythms confer temporal organisation upon physiology that is fundamental to human health. Rhythms are present in red blood cells (RBCs), the most abundant cell type in the body, but their physiological function is poorly understood. Here, we present a novel biochemical assay for haemoglobin (Hb) oxidation status which relies on a redox-sensitive covalent haem-Hb linkage that forms during SDS-mediated cell lysis. Formation of this linkage is lowest when ferrous Hb is oxidised, in the form of ferric metHb. Daily haemoglobin oxidation rhythms are observed in mouse and human RBCs cultured in vitro, or taken from humans in vivo, and are unaffected by mutations that affect circadian rhythms in nucleated cells. These rhythms correlate with daily rhythms in core body temperature, with temperature lowest when metHb levels are highest. Raising metHb levels with dietary sodium nitrite can further decrease daytime core body temperature in mice via nitric oxide (NO) signalling. These results extend our molecular understanding of RBC circadian rhythms and suggest they contribute to the regulation of body temperature.

Sleep Health at the Genomic Level: Six Distinct Factors and Their Relationships With Psychopathology.

Background: Poor sleep is associated with many negative health outcomes, including multiple dimensions of psychopathology. In the past decade, sleep researchers have advocated for focusing on the concept of sleep health as a modifiable health behavior to mitigate or prevent these outcomes. Sleep health dimensions often include sleep efficiency, duration, satisfaction, regularity, timing, and daytime alertness. However, there is no consensus on how to best operationalize sleep health at the phenotypic and genetic levels. In some studies, specific sleep health domains were examined individually, while in others, sleep health domains were examined together (e.g., with an aggregate sleep health score). Methods: Here, we compared alternative sleep health factor models using genomic structural equation modeling on summary statistics from previously published genome-wide association studies of self-reported and actigraphic sleep measures with effective sample sizes up to 452,633. Results: Our best-fitting sleep health model had 6 correlated genetic factors pertaining to 6 sleep health domains: circadian preference, efficiency, alertness, duration, noninsomnia, and regularity. All sleep health factors were significantly correlated (|rgs| = 0.11-0.51), except for the circadian preference factor with duration and noninsomnia. Better sleep health was generally significantly associated with lower genetic liability for psychopathology (|rgs| = 0.05-0.48), yet the 6 sleep health factors showed divergent patterns of associations with different psychopathology factors, especially when controlling for covariance among the sleep health factors. Conclusions: These results provide evidence for genetic separability of sleep health constructs and their differentiation with respect to associations with mental health.

COVID-19 stay-at-home restrictions increase the alignment in sleep and light exposure between school days and weekends in university students.

Younger adults have a biological disposition to sleep and wake at later times that conflict with early morning obligations like work and school; this conflict leads to inadequate sleep duration and a difference in sleep timing between school days and weekends. The COVID-19 pandemic forced universities and workplaces to shut down in person attendance and implement remote learning and meetings that decreased/removed commute times and gave students more flexibility with their sleep timing. To determine the impact of remote learning on the daily sleep-wake cycle we conducted a natural experiment using wrist actimetry monitors to compare activity patterns and light exposure in three cohorts of students: pre-shutdown in-person learning (2019), during-shutdown remote learning (2020), and post-shutdown in-person learning (2021). Our results show that during-shutdown the difference between school day and weekend sleep onset, duration, and midsleep timing was diminished. For instance, midsleep during school days pre-shutdown occurred 50 min later on weekends (5:14 ±â€…12 min) than school days (4:24 ±â€…14 min) but it did not differ under COVID restrictions. Additionally, we found that while the interindividual variance in sleep parameters increased under COVID restrictions the intraindividual variance did not change, indicating that the schedule flexibility did not cause more irregular sleep patterns. In line with our sleep timing results, school day vs. weekend differences in the timing of light exposure present pre- and post-shutdown were absent under COVID restrictions. Our results provide further evidence that increased freedom in class scheduling allows university students to better and consistently align sleep behavior between school days and weekends.

Meal timing variability of rotating shift workers throughout a complete shift cycle and its effect on daily energy and macronutrient intake: a field study.

PURPOSE: To evaluate the meal timing variability of rotating shift workers throughout a complete shift schedule and its effect on daily energy and macronutrient intake. METHODS: Thirty male shift-workers from a mining company were evaluated in a complete rotation shift cycle over 240 consecutive hours (10 days; two days of morning shifts, two days of evening shifts, 24 h free, two days of night shifts and three days off). Food intake related variables [meal timing, energy (kcal) and macronutrient intake (%)] were assessed by 24 h recall by a trained nutritionist. Mixed models were used to analyze the variation in meal timing and energy and macronutrient intake throughout the shift cycle, as well as the interaction between shift and time ranges (00:00-03:59, 04:00-07:59, 08:00-11:59, 12:00-15:59, 16:00-19:59, 20:00-23:59). RESULTS: The first meal of the day was earlier on night shifts [D6 (3:44 ± 0:33) and D7 (5:52 ± 0:42)] compared to the other shifts (p < 0.001), except for D4 (evening shift; 5:51 ± 0:47) versus D7 (p = 0.999). Night shifts also showed a shorter night fasting (D5-D6, 9.3 h; D6-D7, 9.6 h) than most other nights (p < 0.05), except for the fasting between D1-D2 (11.3 h) and D3-D4 (11.2 h) (p > 0.05). There was no difference in 24 h energy intake throughout the shift cycle (p = 0.065). The analysis of interaction between shift and time ranges showed that night shift (D6) presented a higher intake of energy (441.5 ± 48.4 kcal), percentage of energy (D6: 17.8 ± 1.8%), fat (17.6 ± 2.0%), carbohydrate (17.0 ± 1.7%) and protein (16.4 ± 1.8%) between 00:00 and 03:59 compared with the other shift days (p < 0.05). CONCLUSION: Night shifts seem to contribute to a longer eating window than other shifts. Moreover, there is a higher energy and macronutrients intake during night shifts, which reduces the night fast period and could have implications for metabolic dysregulation.

Evidence of circalunar rhythmicity in young children's evening melatonin levels.

In adults, recent evidence demonstrates that sleep and circadian physiology change across lunar phases, including findings that endogenous melatonin levels are lower near the full moon compared to the new moon. Here, we extend these results to early childhood by examining circalunar fluctuations in children's evening melatonin levels. We analysed extant data on young children's circadian rhythms (n = 46, aged 3.0-5.9 years, 59% female). After following a strict sleep schedule for 5-7 days, children completed an in-home, dim-light circadian assessment (<10 lux). Salivary melatonin was assessed at regular 20- to 30-min intervals until 1 h past each child's scheduled bedtime. Melatonin levels varied significantly across lunar phases, such that melatonin was lower in participants assessed near the full moon as compared to near the new moon. Significant differences were observed at 50 min (meanfull  = 2.5 pg/ml; meannew  = 5.4 pg/ml) and 10 min (meanfull  = 7.3 pg/ml; meannew  = 15.8 pg/ml) before children's scheduled bedtime, as well as at 20 min (meanfull  = 15.5 pg/ml; meannew  = 26.1 pg/ml) and 50 min (meanfull  = 19.9 pg/ml; meannew  = 34.3 pg/ml) after bedtime. To our knowledge, these are the first data demonstrating that melatonin secretion, a process regulated by the human circadian system, is sensitive to changes in lunar phase at an early age. Future research is needed to understand the mechanisms underlying this association (e.g., an endogenous circalunar rhythm) and its potential influence on children's sleep and circadian health.

Daytime light exposure is a strong predictor of seasonal variation in sleep and circadian timing of university students.

In the absence of electric light, sleep for humans typically starts soon after dusk and at higher latitudes daily sleep timing changes seasonally as photoperiod changes. However, access to electric light shields humans from natural photoperiod changes, and whether seasonal changes in sleep occur despite this isolation from the natural light-dark cycle remains a matter of controversy. We measured sleep timing in over 500 university students living in the city of Seattle, WA (47.6°N) throughout the four seasons; we show that even when students are following a school schedule, sleep timing is delayed during the fall and winter. For instance, during the winter school days, students fell asleep 35 min later and woke up 27 min later (under daylight-savings time) than students during the summer school days, a change that is an hour larger relative to solar midnight. Furthermore, chronotype defined by mid-sleep on free days corrected for oversleep (MSFc), an indirect estimate of circadian phase, was more than 30 min later in the winter compared with the summer. Analysis of the effect of light exposure showed that the number of hours of light exposure to at least 50 lux during the daytime was a stronger predictor of MSFc than the exposure time to this illuminance after dusk. Specifically, MSFc was advanced by 30 min for each additional hour of light exposure during daytime and delayed by only 15 min for each additional hour of postdusk exposure to light. Additionally, the time of the day of exposure to high light intensities was more predictive of MSFc when daytime exposure was considered than when exposure for the full 24-h day was considered. Our results show that although sleep time is highly synchronized to social time, a delayed timing of sleep is evident during the winter months. They also suggest that daily exposure to daylight is key to prevent this delayed phase of the circadian clock and thus circadian disruption that is typically exacerbated in high-latitude winters.

Influence of fasting during the night shift on next day eating behavior, hunger, and glucose and insulin levels: a randomized, three-condition, crossover trial.

AIMS: To investigate the influence of fasting during the night shift on eating behavior, hunger, glucose and insulin levels the following day. METHODS: Study with 10 male police officers who have been working at night. Participants were tested under three different conditions separated by at least 6 days of washout in a randomized, crossover design: "Night Shift Fasting" (NSF)-two nights of fasting during the night shift; "Night Shift Eating" (NSE)-two nights with the consumption of a standardized meal during the night shift (678 ± 42 kcal consumed at ~ 0200 h); and "Nighttime Sleep" (NS)-two nights of sleep. The morning after, blood glucose and insulin and hunger ratings were assessed, and food intake was assessed with an ad libitum test meal. Food intake was also assessed throughout the remainder of the day using a food record. Generalized Estimating Equations were used to analyze the effect of experimental condition. RESULTS: Food intake during the test meal, especially of proteins and fats, was higher after fasting during the night shift compared to the other conditions (p < 0.05), whereas desire to eat scores were lower after the NSF compared to NSE condition (p = 0.043). Hunger levels were lower after the NSF compared to the NS condition (p = 0.012). Insulin and HOMA-IR were also lower in the morning after NSF (p < 0.001). CONCLUSION: Fasting during the night shift leads to not only a higher intake of energy and macronutrients both in the early morning after work and throughout the next day, but also lower insulin levels and HOMA-IR in the morning. REGISTRATION NUMBER OF CLINICAL TRIAL: NCT03800732. Initial release: 01/09/2019. Last release: 02/23/2022.

Evening Light Intensity and Phase Delay of the Circadian Clock in Early Childhood.

Late sleep timing is prevalent in early childhood and a risk factor for poor behavioral and health outcomes. Sleep timing is influenced by the phase of the circadian clock, with later circadian timing linked to delayed sleep onset in young children. Light is the strongest zeitgeber of circadian timing and, in adults, evening light produces circadian phase delay in an intensity-dependent manner. The intensity-dependent circadian phase-shifting response to evening light in children, however, is currently unknown. In the present study, 33 healthy, good-sleeping children aged 3.0 to 4.9 years (M = 4.14 years, 39% male) completed a 10-day between-subjects protocol. Following 7 days of a stable sleep schedule, an in-home dim-light circadian assessment was performed. Children remained in dim-light across 3 days (55 h), with salivary melatonin collected in regular intervals throughout each evening. Phase-shifting effects of light exposure were determined via changes in the timing of the dim-light melatonin onset (DLMO) prior to (Day 8) and following (Day 10) a light exposure stimulus. On Day 9, children were exposed to a 1 h light stimulus in the hour before their habitual bedtime. Each child was randomly assigned to one intensity between 5 and 5000 lux (4.5-3276 melanopic EDI). Across light intensities, children showed significant circadian phase delays, with an average phase delay of 56.1 min (SD = 33.6 min), and large inter-individual variability. No relationship between light intensity and magnitude of the phase shift was observed. However, a greater percentage of melatonin suppression during the light exposure was associated with a greater phase delay (r = -0.73, p < 0.01). These findings demonstrate that some young children may be highly sensitive to light exposure in the hour before bedtime and suggest that the home lighting environment and its impact on circadian timing should be considered a possible contributor to behavioral sleep difficulties.

Desynchronizing the sleep---wake cycle from circadian timing to assess their separate contributions to physiology and behaviour and to estimate intrinsic circadian period.

Circadian clocks drive cyclic variations in many aspects of physiology, but some daily variations are evoked by periodic changes in the environment or sleep-wake state and associated behaviors, such as changes in posture, light levels, fasting or eating, rest or activity and social interactions; thus, it is often important to quantify the relative contributions of these factors. Yet, circadian rhythms and these evoked effects cannot be separated under typical 24-h day conditions, because circadian phase and the length of time awake or asleep co-vary. Nathaniel Kleitman's forced desynchrony (FD) protocol was designed to assess endogenous circadian rhythmicity and to separate circadian from evoked components of daily rhythms in multiple parameters. Under FD protocol conditions, light intensity is kept low to minimize its impact on the circadian pacemaker, and participants have sleep-wake state and associated behaviors scheduled to an imposed non-24-h cycle. The period of this imposed cycle, Τ, is chosen so that the circadian pacemaker cannot entrain to it and therefore continues to oscillate at its intrinsic period (τ, ~24.15 h), ensuring circadian components are separated from evoked components of daily rhythms. Here we provide detailed instructions and troubleshooting techniques on how to design, implement and analyze the data from an FD protocol. We provide two procedures: one with general guidance for designing an FD study and another with more precise instructions for replicating one of our previous FD studies. We discuss estimating circadian parameters and quantifying the separate contributions of circadian rhythmicity and the sleep-wake cycle, including statistical analysis procedures and an R package for conducting the non-orthogonal spectral analysis method that enables an accurate estimation of period, amplitude and phase.

The role of insufficient sleep and circadian misalignment in obesity.

Traditional risk factors for obesity and the metabolic syndrome, such as excess energy intake and lack of physical activity, cannot fully explain the high prevalence of these conditions. Insufficient sleep and circadian misalignment predispose individuals to poor metabolic health and promote weight gain and have received increased research attention in the past 10 years. Insufficient sleep is defined as sleeping less than recommended for health benefits, whereas circadian misalignment is defined as wakefulness and food intake occurring when the internal circadian system is promoting sleep. This Review discusses the impact of insufficient sleep and circadian misalignment in humans on appetite hormones (focusing on ghrelin, leptin and peptide-YY), energy expenditure, food intake and choice, and risk of obesity. Some potential strategies to reduce the adverse effects of sleep disruption on metabolic health are provided and future research priorities are highlighted. Millions of individuals worldwide do not obtain sufficient sleep for healthy metabolic functions. Furthermore, modern working patterns, lifestyles and technologies are often not conducive to adequate sleep at times when the internal physiological clock is promoting it (for example, late-night screen time, shift work and nocturnal social activities). Efforts are needed to highlight the importance of optimal sleep and circadian health in the maintenance of metabolic health and body weight regulation.

Sleep duration, plasma metabolites, and obesity and diabetes: a metabolome-wide association study in US women.

Short and long sleep duration are associated with adverse metabolic outcomes, such as obesity and diabetes. We evaluated cross-sectional differences in metabolite levels between women with self-reported habitual short (<7 h), medium (7-8 h), and long (≥9 h) sleep duration to delineate potential underlying biological mechanisms. In total, 210 metabolites were measured via liquid chromatography-mass spectrometry in 9207 women from the Nurses' Health Study (NHS; N = 5027), the NHSII (N = 2368), and the Women's Health Initiative (WHI; N = 2287). Twenty metabolites were consistently (i.e. praw < .05 in ≥2 cohorts) and/or strongly (pFDR < .05 in at least one cohort) associated with short sleep duration after multi-variable adjustment. Specifically, levels of two lysophosphatidylethanolamines, four lysophosphatidylcholines, hydroxyproline and phenylacetylglutamine were higher compared to medium sleep duration, while levels of one diacylglycerol and eleven triacylglycerols (TAGs; all with ≥3 double bonds) were lower. Moreover, enrichment analysis assessing associations of metabolites with short sleep based on biological categories demonstrated significantly increased acylcarnitine levels for short sleep. A metabolite score for short sleep duration based on 12 LASSO-regression selected metabolites was not significantly associated with prevalent and incident obesity and diabetes. Associations of single metabolites with long sleep duration were less robust. However, enrichment analysis demonstrated significant enrichment scores for four lipid classes, all of which (most markedly TAGs) were of opposite sign than the scores for short sleep. Habitual short sleep exhibits a signature on the human plasma metabolome which is different from medium and long sleep. However, we could not detect a direct link of this signature with obesity and diabetes risk.

A Naturalistic Actigraphic Assessment of Changes in Adolescent Sleep, Light Exposure, and Activity Before and During COVID-19.

The majority of high school-aged adolescents obtain less than the recommended amount of sleep per night, in part because of imposed early school start times. Utilizing a naturalistic design, the present study evaluated changes in objective measurements of sleep, light, and physical activity before (baseline) and during the first wave of the COVID-19 pandemic (during COVID-19) in a group of US adolescents. Sixteen adolescents (aged 15.9 ± 1.2 years, 68.8% female) wore an actigraphy monitor for 7 consecutive days during an in-person week of school before the pandemic (October 2018-February 2020) and again during the pandemic when instruction was performed virtually (May 2020). Delayed weekday sleep onset times of 1.66 ± 1.33 h (p < 0.001) and increased sleep duration of 1 ± 0.87 h (p < 0.001) were observed during COVID-19 compared with baseline. Average lux was significantly higher during COVID-19 compared with baseline (p < 0.001). Weekday physical activity parameters were not altered during COVID-19 compared with baseline, except for a delay in the midpoint of the least active 5 h (p value = 0.044). This analysis provides insight into how introducing flexibility into the traditional school schedule might influence sleep in adolescents.