Eating Around the Clock: Circadian Rhythms of Eating and Metabolism.

The time of day that we eat is increasingly recognized as contributing as importantly to overall health as the amount or quality of the food we eat. The endogenous circadian clock has evolved to promote intake at optimal times when an organism is intended to be awake and active; but electric lights and abundant food allow eating around the clock with deleterious health outcomes. In this review, we highlight literature pertaining to the effects of food timing on health, beginning with animal models and then translation into human experiments. We emphasize the pitfalls and opportunities that technological advances bring in bettering understanding of eating behaviors and their association with health and disease. There is great promise for restricting the timing of food intake both in clinical interventions and in public health campaigns for improving health via nonpharmacological therapies.

Identifying an Acceptable Number of Ambulatory Blood Pressure Measurements for Accuracy of Average Blood Pressure and Nocturnal Dipping Status.

OBJECTIVE: We aimed to identify the minimum number of ABP measures to accurately determine daytime and nighttime systolic BP averages and nocturnal dipping status (i.e., relative daytime:nighttime change). METHODS: Forty-three midlife participants wore an ABP monitor for 24 hours with measurements every 20/30 minutes during the daytime/nighttime, as identified by a sleep diary. We calculated daytime/nighttime systolic BP average and dipping status from all available measurements per participant (i.e., normative data). We then calculated daytime and nighttime BP per participant based on a random selection of 8-20 and 4-10 measurements and replicated random selections 1000 times. We calculated accuracy by checking the proportion from 1000 different randomly selected samples for a particular number of measurements that systolic BP was ±5 mmHg of normative data, and dipping status remained unchanged for each participant compared to the normative value. The best fit for the regression model estimated the minimal number of measurements for an accuracy of 95% in BP averages. RESULTS: For a 95% accuracy in estimating daytime and nighttime systolic BP, 11 daytime and 8 nighttime measurements were required. The highest accuracy for dipping status was 91.6±13.4% using 20 daytime and 10 nighttime measures, while the lowest was (83.4±15.1%) using 8 daytime and 4 nighttime measures. CONCLUSION: Eleven daytime and eight nighttime measurements are likely enough to calculate average systolic BPs accurately. However, no minimum number is suggested to accurately calculate dipping status.

Pressure Building Against the Clock: The Impact of Circadian Misalignment on Blood Pressure.

PURPOSE OF REVIEW: Misalignment between the endogenous biological timing system and behavioral activities (i.e., sleep/wake, eating, activity) contributes to adverse cardiovascular health. In this review, we discuss the effects of recurring circadian misalignment on blood pressure regulation and the implications for hypertension development. Additionally, we highlight emerging therapeutic approaches designed to mitigate the negative cardiovascular consequences elicited by circadian disruption. RECENT FINDINGS: Circadian misalignment elicited by work schedules that require individuals to be awake during the biological night (i.e., shift work) alters 24-h blood pressure rhythms. Mechanistically, circadian misalignment appears to alter blood pressure via changes in autonomic nervous system balance, variations to sodium retention, dysregulation of endothelial vasodilatory responsiveness, and activation of proinflammatory mechanisms. Recurring circadian misalignment produced by a mismatch in sleep timing on free days vs. work days (i.e., social jetlag) appears to have no direct effects on prevailing blood pressure levels in healthy adults; though, circadian disruptions resulting from social jetlag may increase the risk of hypertension through enhanced sympathetic activation and/or obesity. Furthermore, social jetlag assessment may be a useful metric in shift work populations where the magnitude of circadian misalignment may be greater than in the general population. Circadian misalignment promotes unfavorable changes to 24-h blood pressure rhythms, most notably in shift working populations. While light therapy, melatonin supplementation, and the timing of drug administration may improve cardiovascular outcomes, interventions designed to target the effects of circadian misalignment on blood pressure regulation are warranted.

Chronological distribution of readings in ambulatory blood pressure monitoring exams affects the nighttime average and the magnitude of blood pressure dipping.

STUDY OBJECTIVES: Averaged nighttime blood pressure (BP) is superior to daytime BP for cardiovascular risk stratification, and the relative change between daytime/nighttime BP (dipping%) significantly predicts cardiovascular risk. Newer reports suggest that 4 measurements at night may be enough for cardiovascular risk stratification. Since BP oscillates across the night, the temporal distribution of measurements across the night may impact nighttime BP and dipping%. Therefore, we compared average nighttime BP and dipping% when using measurements in the first half (1st-half), second (2nd-half), and a combination of both (combined). METHODS: Forty-three (17 females and twenty-six males) midlife adults aged 50±10 years old wore an ambulatory BP monitor for 24 hours at home, programmed to measure BP every 20 minutes when scheduled for daytime and every 30 minutes during a self-selected 8-hour nighttime for time-in-bed. We compared the nighttime BP averages and dipping% when using either the first four measurements from the 1st-half or 2nd-half of the nighttime and combined. RESULTS: Nighttime Systolic BP was significantly different across 1st-half, 2nd-half, and combined (111±9 vs.107±11 vs. 109±9 mmHg, p<0.01), respectively, with significant pairwise differences across all categories (p<0.01 for each). Systolic BP dipping% was significantly different across 1st-half, 2nd-half, and combined (9.9±5.5 vs.13.5±6.4 vs. 11.7±5.0 %, p<0.01), respectively, with significant pairwise differences across all categories (p<0.01 for each. Diastolic BP and diastolic dipping% were similar across the three different bins. CONCLUSION: In midlife adults, systolic nighttime BP and dipping% may depend upon when BP measurements are taken during the night.

Robust stability of melatonin circadian phase, sleep metrics, and chronotype across months in young adults living in real-world settings.

Appropriate synchronization of the timing of behaviors with the circadian clock and adequate sleep are both important for almost every physiological process. The timing of the circadian clock relative to social (ie, local) clock time and the timing of sleep can vary greatly among individuals. Whether the timing of these processes is stable within an individual is not well-understood. We examined the stability of circadian-controlled melatonin timing, sleep timing, and their interaction across ~ 100 days in 15 students at a single university. At three time points ~ 35-days apart, circadian timing was determined from the dim-light melatonin onset (DLMO). Sleep behaviors (timing and duration) and chronotype (ie, mid-sleep time on free days corrected for sleep loss on school/work days) were determined via actigraphy and analyzed in ~ 1-month bins. Melatonin timing was stable, with an almost perfect relationship strength as determined via intraclass correlation coefficients ([ICC]=0.85); average DLMO timing across all participants only changed from the first month by 21 minutes in month 2 and 5 minutes in month 3. Sleep behaviors also demonstrated high stability, with ICC relationship strengths ranging from substantial to almost perfect (ICCs = 0.65-0.85). Average DLMO was significantly associated with average chronotype (r2  = 0.53, P <.01), with chronotype displaying substantial stability across months (ICC = 0.61). These findings of a robust stability in melatonin timing and sleep behaviors in young adults living in real-world settings holds promise for a better understanding of the reliability of previous cross-sectional reports and for the future individualized strategies to combat circadian-associated disease and impaired safety (ie, "chronomedicine").

A classification approach to estimating human circadian phase under circadian alignment from actigraphy and photometry data.

The time of dim light melatonin onset (DLMO) is the gold standard for circadian phase assessment in humans, but collection of samples for DLMO is time and resource-intensive. Numerous studies have attempted to estimate circadian phase from actigraphy data, but most of these studies have involved individuals on controlled and stable sleep-wake schedules, with mean errors reported between 0.5 and 1 hour. We found that such algorithms are less successful in estimating DLMO in a population of college students with more irregular schedules: Mean errors in estimating the time of DLMO are approximately 1.5-1.6 hours. We reframed the problem as a classification problem and estimated whether an individual's current phase was before or after DLMO. Using a neural network, we found high classification accuracy of about 90%, which decreased the mean error in DLMO estimation-identifying the time at which the switch in classification occurs-to approximately 1.3 hours. To test whether this classification approach was valid when activity and circadian rhythms are decoupled, we applied the same neural network to data from inpatient forced desynchrony studies in which participants are scheduled to sleep and wake at all circadian phases (rather than their habitual schedules). In participants on forced desynchrony protocols, overall classification accuracy dropped to 55%-65% with a range of 20%-80% for a given day; this accuracy was highly dependent upon the phase angle (ie, time) between DLMO and sleep onset, with the highest accuracy at phase angles associated with nighttime sleep. Circadian patterns in activity, therefore, should be included when developing and testing actigraphy-based approaches to circadian phase estimation. Our novel algorithm may be a promising approach for estimating the onset of melatonin in some conditions and could be generalized to other hormones.

Mistimed food intake and sleep alters 24-hour time-of-day patterns of the human plasma proteome.

Proteomics holds great promise for understanding human physiology, developing health biomarkers, and precision medicine. However, how much the plasma proteome varies with time of day and is regulated by the master circadian suprachiasmatic nucleus brain clock, assessed here by the melatonin rhythm, is largely unknown. Here, we assessed 24-h time-of-day patterns of human plasma proteins in six healthy men during daytime food intake and nighttime sleep in phase with the endogenous circadian clock (i.e., circadian alignment) versus daytime sleep and nighttime food intake out of phase with the endogenous circadian clock (i.e., circadian misalignment induced by simulated nightshift work). We identified 24-h time-of-day patterns in 573 of 1,129 proteins analyzed, with 30 proteins showing strong regulation by the circadian cycle. Relative to circadian alignment, the average abundance and/or 24-h time-of-day patterns of 127 proteins were altered during circadian misalignment. Altered proteins were associated with biological pathways involved in immune function, metabolism, and cancer. Of the 30 circadian-regulated proteins, the majority peaked between 1400 hours and 2100 hours, and these 30 proteins were associated with basic pathways involved in extracellular matrix organization, tyrosine kinase signaling, and signaling by receptor tyrosine-protein kinase erbB-2. Furthermore, circadian misalignment altered multiple proteins known to regulate glucose homeostasis and/or energy metabolism, with implications for altered metabolic physiology. Our findings demonstrate the circadian clock, the behavioral wake-sleep/food intake-fasting cycle, and interactions between these processes regulate 24-h time-of-day patterns of human plasma proteins and help identify mechanisms of circadian misalignment that may contribute to metabolic dysregulation.

Chronic sleep curtailment, even without extended (>16-h) wakefulness, degrades human vigilance performance.

Millions of individuals routinely remain awake for more than 18 h daily, which causes performance decrements. It is unknown if these functional impairments are the result of that extended wakefulness or from the associated shortened sleep durations. We therefore examined changes in objective reaction time performance and subjective alertness in a 32-d inpatient protocol in which participants were scheduled to wakefulness durations below 16 h while on a 20-h "day," with randomization into standard sleep:wake ratio (1:2) or chronic sleep restriction (CSR) ratio (1:3.3) conditions. This protocol allowed determination of the contribution of sleep deficiency independent of extended wakefulness, since individual episodes of wakefulness in the CSR condition were only 15.33 h in duration (less than the usual 16 h of wakefulness in a 24-h day) and sleep episodes were 4.67 h in duration each cycle. We found that chronic short sleep duration, even without extended wakefulness, doubled neurobehavioral reaction time performance and increased lapses of attention fivefold, yet did not uniformly decrease self-reported alertness. Further, these impairments in neurobehavioral performance were worsened during the circadian night and were not recovered during the circadian day, indicating that the deleterious effect from the homeostatic buildup of CSR is expressed even during the circadian promotion of daytime arousal. These findings reveal a fundamental aspect of human biology: Chronic insufficient sleep duration equivalent to 5.6 h of sleep opportunity per 24 h impairs neurobehavioral performance and self-assessment of alertness, even without extended wakefulness.

Circadian Rhythm of Vascular Function in Midlife Adults.

Objective- Adverse cardiovascular events occur more frequently in the morning than at other times of the day. Vascular endothelial function (VEF)-a robust cardiovascular risk marker-is impaired during this morning period. We recently discovered that this morning impairment in VEF is not caused by either overnight sleep or the inactivity that accompanies sleep. We determined whether the endogenous circadian system is responsible for this morning impairment in VEF. We also assessed whether the circadian system affects mechanistic biomarkers, that is, oxidative stress (malondialdehyde adducts), endothelin-1, blood pressure, and heart rate. Approach and Results- Twenty-one (11 women) middle-aged healthy participants completed a 5-day laboratory protocol in dim light where all behaviors, including sleep and activity, and all physiological measurements were evenly distributed across the 24-hour period. After baseline testing, participants underwent 10 recurring 5-hour 20-minute behavioral cycles of 2-hour 40-minute sleep opportunities and 2 hours and 40 minutes of standardized waking episodes. VEF, blood pressure, and heart rate were measured, and venous blood was sampled immediately after awakening during each wake episode. Independent of behaviors, VEF was significantly attenuated during the subjective night and across the morning ( P=0.04). Malondialdehyde adducts and endothelin-1 exhibited circadian rhythms with increases across the morning vulnerable period and peaks around noon ( P≤0.01). Both systolic ( P=0.005) and diastolic blood pressure ( P=0.04) were rhythmic with peaks in the late afternoon. Conclusions- The endogenous circadian system impairs VEF and increases malondialdehyde adducts and endothelin-1 in the morning vulnerable hours and may increase the risk of morning adverse cardiovascular events in susceptible individuals. Clinical Trial Registration- URL: http://www.clinicaltrials.gov . Unique identifier: NCT02202811.

Identifying Objective Physiological Markers and Modifiable Behaviors for Self-Reported Stress and Mental Health Status Using Wearable Sensors and Mobile Phones: Observational Study.

BACKGROUND: Wearable and mobile devices that capture multimodal data have the potential to identify risk factors for high stress and poor mental health and to provide information to improve health and well-being. OBJECTIVE: We developed new tools that provide objective physiological and behavioral measures using wearable sensors and mobile phones, together with methods that improve their data integrity. The aim of this study was to examine, using machine learning, how accurately these measures could identify conditions of self-reported high stress and poor mental health and which of the underlying modalities and measures were most accurate in identifying those conditions. METHODS: We designed and conducted the 1-month SNAPSHOT study that investigated how daily behaviors and social networks influence self-reported stress, mood, and other health or well-being-related factors. We collected over 145,000 hours of data from 201 college students (age: 18-25 years, male:female=1.8:1) at one university, all recruited within self-identified social groups. Each student filled out standardized pre- and postquestionnaires on stress and mental health; during the month, each student completed twice-daily electronic diaries (e-diaries), wore two wrist-based sensors that recorded continuous physical activity and autonomic physiology, and installed an app on their mobile phone that recorded phone usage and geolocation patterns. We developed tools to make data collection more efficient, including data-check systems for sensor and mobile phone data and an e-diary administrative module for study investigators to locate possible errors in the e-diaries and communicate with participants to correct their entries promptly, which reduced the time taken to clean e-diary data by 69%. We constructed features and applied machine learning to the multimodal data to identify factors associated with self-reported poststudy stress and mental health, including behaviors that can be possibly modified by the individual to improve these measures. RESULTS: We identified the physiological sensor, phone, mobility, and modifiable behavior features that were best predictors for stress and mental health classification. In general, wearable sensor features showed better classification performance than mobile phone or modifiable behavior features. Wearable sensor features, including skin conductance and temperature, reached 78.3% (148/189) accuracy for classifying students into high or low stress groups and 87% (41/47) accuracy for classifying high or low mental health groups. Modifiable behavior features, including number of naps, studying duration, calls, mobility patterns, and phone-screen-on time, reached 73.5% (139/189) accuracy for stress classification and 79% (37/47) accuracy for mental health classification. CONCLUSIONS: New semiautomated tools improved the efficiency of long-term ambulatory data collection from wearable and mobile devices. Applying machine learning to the resulting data revealed a set of both objective features and modifiable behavioral features that could classify self-reported high or low stress and mental health groups in a college student population better than previous studies and showed new insights into digital phenotyping.

Impact of sleep inertia on visual selective attention for rare targets and the influence of chronotype.

Sleep inertia is affected by circadian phase, with worse performance upon awakening from sleep during the biological night than biological day. Visual search/selective visual attention performance is known to be sensitive to sleep inertia and circadian phase. Individual differences exist in the circadian timing of habitual wake time, which may contribute to individual differences in sleep inertia. Because later chronotypes awaken at an earlier circadian phase, we hypothesized that later chronotypes would have worse visual search performance during sleep inertia than earlier chronotypes if awakened at habitual wake time. We analysed performance from 18 healthy participants [five females (22.1 ± 3.7 years; mean ± SD)] at ~1, 10, 20, 30, 40 and 60 min following electroencephalogram-verified awakening from an 8 h in-laboratory sleep opportunity. Cognitive throughput and reaction times of correct responses were impaired by sleep inertia and took ~10-30 min to improve after awakening. Regardless whether chronotype was defined by dim light melatonin onset or mid-sleep clock hour on free days, derived from the Munich ChronoType Questionnaire, the duration of sleep inertia for cognitive throughput and reaction times was longer for later chronotypes (n = 7) compared with earlier chronotypes (n = 7). Specifically, performance for earlier chronotypes showed significant improvement within ~10-20 min after awakening, whereas performance for later chronotypes took ~30 min or longer to show significant improvement (P < 0.05). Findings have implications for decision making immediately upon awakening from sleep, and are consistent with circadian theory suggesting that sleep inertia contributes to longer-lasting impairments in morning performance in later chronotypes.

Impact of circadian misalignment on energy metabolism during simulated nightshift work.

Eating at a time when the internal circadian clock promotes sleep is a novel risk factor for weight gain and obesity, yet little is known about mechanisms by which circadian misalignment leads to metabolic dysregulation in humans. We studied 14 adults in a 6-d inpatient simulated shiftwork protocol and quantified changes in energy expenditure, macronutrient utilization, appetitive hormones, sleep, and circadian phase during day versus nightshift work. We found that total daily energy expenditure increased by ∼4% on the transition day to the first nightshift, which consisted of an afternoon nap and extended wakefulness, whereas total daily energy expenditure decreased by ∼3% on each of the second and third nightshift days, which consisted of daytime sleep followed by afternoon and nighttime wakefulness. Contrary to expectations, energy expenditure decreased by ∼12-16% during scheduled daytime sleep opportunities despite disturbed sleep. The thermic effect of feeding also decreased in response to a late dinner on the first nightshift. Total daily fat utilization increased on the first and second nightshift days, contrary to expectations, and carbohydrate and protein utilization were reduced on the second nightshift day. Ratings of hunger were decreased during nightshift days despite decreases in 24-h levels of the satiety hormones leptin and peptide-YY. Findings suggest that reduced total daily energy expenditure during nightshift schedules and reduced energy expenditure in response to dinner represent contributing mechanisms by which humans working and eating during the biological night, when the circadian clock is promoting sleep, may increase the risk of weight gain and obesity.

Dietary fasting and time-restricted eating in Huntington's disease: therapeutic potential and underlying mechanisms.

Huntington's disease (HD) is a devastating neurodegenerative disorder caused by aggregation of the mutant huntingtin (mHTT) protein, resulting from a CAG repeat expansion in the huntingtin gene HTT. HD is characterized by a variety of debilitating symptoms including involuntary movements, cognitive impairment, and psychiatric disturbances. Despite considerable efforts, effective disease-modifying treatments for HD remain elusive, necessitating exploration of novel therapeutic approaches, including lifestyle modifications that could delay symptom onset and disease progression. Recent studies suggest that time-restricted eating (TRE), a form of intermittent fasting involving daily caloric intake within a limited time window, may hold promise in the treatment of neurodegenerative diseases, including HD. TRE has been shown to improve mitochondrial function, upregulate autophagy, reduce oxidative stress, regulate the sleep-wake cycle, and enhance cognitive function. In this review, we explore the potential therapeutic role of TRE in HD, focusing on its underlying physiological mechanisms. We discuss how TRE might enhance the clearance of mHTT, recover striatal brain-derived neurotrophic factor levels, improve mitochondrial function and stress-response pathways, and synchronize circadian rhythm activity. Understanding these mechanisms is critical for the development of targeted lifestyle interventions to mitigate HD pathology and improve patient outcomes. While the potential benefits of TRE in HD animal models are encouraging, future comprehensive clinical trials will be necessary to evaluate its safety, feasibility, and efficacy in persons with HD.

Later circadian timing and increased sleep timing variability are associated with attenuations in overnight blood pressure dipping among chronic nightshift workers.

OBJECTIVE: Determine relationships between overnight blood pressure, circadian phase, and sleep variability among dayshift and chronic nightshift nurses. METHODS: Twenty participants working dayshift (n = 10) or nightshift (n = 10) schedules participated in a 7-day cross-sectional study. Participants underwent an evening in-laboratory melatonin assessment and wore ambulatory blood pressure devices to assess 24-hour blood pressure patterns. Overnight blood pressure dipping was calculated from sleeping/waking systolic blood pressure ratio and salivary dim-light melatonin onset determined circadian phase. Sleep variability was assessed using the standard deviation of 7-day sleep onset. RESULTS: Nightshift workers had later circadian phase, greater sleep onset variability, and an attenuated overnight blood pressure dipping pattern. Later circadian phase was associated with attenuated dipping patterns and sleep onset variability was negatively correlated with blood pressure dipping magnitude in nightshift, but not dayshift workers. CONCLUSIONS: Chronic circadian disruption via higher sleep onset variability among nightshift workers may contribute to attenuated blood pressure dipping and cardiovascular risk in this population.

Obesity alters the circadian profiles of energy metabolism and glucose regulation in humans.

OBJECTIVE: Given the complex interaction among the circadian system, energy metabolism, and obesity, the authors tested whether having obesity impacts the circadian variation in energy and glucose metabolism in humans. METHODS: Participants with BMI either in the healthy weight or obesity ranges were studied in a 5-day, in-laboratory protocol that equally distributed behaviors (i.e., sleep, eating, exercise) across 24 h. Energy metabolism was measured at rest and during a standardized exercise bout and blood was sampled before and after each identical study meal to assess glucose and insulin levels. RESULTS: In those with a healthy weight, the circadian nadir of energy expenditure, during both rest and exercise, occurred when participants would normally be asleep. However, in those with obesity, this nadir appears to occur during the habitual wake period. Differences in glucose regulation also depended on the circadian phase, such that individuals with obesity appeared to have relatively greater glucose intolerance during the circadian day and produced less insulin during the circadian night. CONCLUSIONS: Obesity is associated with altered circadian energy and glucose metabolism. Understanding and addressing these associations could lead to strategies that improve body weight and metabolic health in people with obesity.

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.