Association between CLOCK 3111 T/C polymorphism with ghrelin, GLP-1, food timing, sleep and chronotype in overweight and obese Iranian adults.

BACKGROUND: Circadian Locomotor Output Cycles Kaput (CLOCK), an essential element of the positive regulatory arm in the human biological clock, is involved in metabolic regulation. The aim was to investigate the behavioral (sleep duration, food timing, dietary intake, appetite and chronobiologic characteristics) and hormonal (plasma ghrelin and Glucagon-like peptide-1 concentrations) factors that could explain the previously reported association between the CLOCK 3111 T/C SNP and obesity. METHODS: This cross-sectional study included 403 subjects, overweight and/or obesity, aged 20- 50 years from Iran. The CLOCK rs1801260 data were measured by the PCR-RFLP method. Dietary intake, food timing, sleep duration, appetite and Chrono-type were assessed using validated questionnaires. Ghrelin and GLP-1 were measured by ELIZA in plasma samples. Participants were also divided into three groups based on BMI. Logistic regression models and general linear regression models were used to assess the association between CLOCK genotype and study parameters. Univariate linear regression models were used to assess the interaction between CLOCK and VAS, Food timing, chronotype and sleep on food intakes. RESULTS: After controlling for confounding factors, there was a significant difference between genotypes for physical activity (P = 0.001), waist circumference (P˂0.05), BMI (˂0.01), weight (P = 0.001), GLP-1 (P = 0.02), ghrelin (P = 0.04), appetite (P˂0.001), chronotype (P˂0.001), sleep (P˂0.001), food timing (P˂0.001), energy (P˂0.05), carbohydrate (P˂0.05) and fat intake (P˂0.001). Our findings also show that people with the minor allele C who ate lunch after 3 PM and breakfast after 9 AM are more prone to obesity (P˂0.05). furthermore, there was significant interactions between C allele carrier group and high appetite on fat intake (Pinteraction = 0.041), eat lunch after 3 PM on energy intake (Pinteraction = 0.039) and morning type on fat intake (Pinteraction = 0.021). CONCLUSION: Sleep reduction, changes in ghrelin and GLP-1 levels, changes in eating behaviors and evening preference that characterized CLOCK 3111C can all contribute to obesity. Furthermore, the data demonstrate a clear relationship between the timing of food intake and obesity. Our results support the hypothesis that the influence of the CLOCK gene may extend to a wide range of variables related to human behaviors.

Behavioral circadian phenotypes are associated with the risk of elevated body mass index.

BACKGROUND: Metabolic dysfunction and obesity rates are on the rise. Although the central modes of circadian disruption has been studied in relation to the risk of obesity, the role of eating time has remained unclear. Here, we aimed to assess circadian behavioral phenotypes and their association with the risk of elevated body mass index (BMI). METHODS: This was a prospective cross-sectional study of individuals presenting for colorectal cancer screening colonoscopy. Participants completed demographic questionnaires, The Munich ChronoType Questionnaire (MCTQ), and Food Timing Screener (FTS). The primary outcome of the study was the association between circadian phenotypes and elevated BMI. RESULTS: A total of 488 individuals completed the survey, with a mean (SD) age of 57.5 (10.8) years. The mean body mass index (BMI) was 28.8 (6.1) kg/m2, with 72.3% of individuals met criteria for elevated BMI. Four circadian behavioral phenotypes were generated: early chronotype with regular food timing (ER) (34.7%), early chronotype with irregular food timing (EI) (11.7%), intermediate/late chronotype with regular food timing (LR) (33.9%), and intermediate/late chronotype with irregular food timing (LI) (19.7%). In a multivariable regression analysis, LI phenotype had 2.9 times higher odds of elevated BMI as compared to ER phenotype (OR 2.9, 95% CI 1.3-6.7, P = 0.01). CONCLUSION: The combination of late chronotype and irregular food timing, representative of a behavioral circadian rhythm disruption, is associated with higher rates of elevated BMI. The majority of individuals with this abnormal circadian phenotype were younger than 60 years old. This observation is especially relevant because of the ongoing rise in the obesity rates among young adults. LEVEL III: Evidence obtained from well-designed cohort or case-control analytic studies.

Sex-specific metabolic responses to 6 hours of fasting during the active phase in young mice.

KEY POINTS: Night time/active phase food restriction for 6 h impaired glucose intolerance in young male and female mice. Females displayed increased capacity for lipogenesis and triglyceride storage in response to a short daily fast. Females had lower fasting insulin levels and an increased potential for utilizing fat for energy through ß-oxidation compared to males. The need for the inclusion of both sexes, and the treatment of sex as an independent variable, is emphasized within the context of this fasting regime. ABSTRACT: There is growing interest in understanding the mechanistic significance and benefits of fasting physiology in combating obesity. Increasing the fasting phase of a normal day can promote restoration and repair mechanisms that occur during the post-absorptive period. Most studies exploring the effect of restricting food access on mitigating obesity have done so with a large bias towards the use of male mice. Here, we disentangle the roles of sex, food intake and food withdrawal in the response to a short-term daily fasting intervention, in which food was removed for 6 h in the dark/active phase of young, 8-week-old mice. We showed that the removal of food during the dark phase impaired glucose tolerance in males and females, possibly due to the circadian disruption induced by this feeding protocol. Although both sexes demonstrated similar patterns of food intake, body composition and various metabolic markers, there were clear sex differences in the magnitude and extent of these responses. While females displayed enhanced capacity for lipogenesis and triglyceride storage, they also had low fasting insulin levels and an increased potential for utilizing available energy sources such as fat for energy through ß-oxidation. Our results highlight the intrinsic biological and metabolic disparities between male and female mice, emphasizing the growing need for the inclusion of both sexes in scientific research. Furthermore, our results illustrate sex-specific metabolic pathways that regulate lipogenesis, obesity and overall metabolic health.

Impact of dosage timing on the bioavailability of oral anticancer medications: Is pre-prandial dosing equivalent to post-prandial dosing.

Many oral anticancer agents are recommended to be given either at least 1 h before or 2 h after a meal, according to the prescribing information. However, the effect of dosage timing of an oral anticancer agent with reference to food intake on anticancer treatment remains unclear. As shown by the literature survey and labeling analysis for oral anticancer drugs approved by the US Food and Drug Administration from 2010 to 2016, labeling information regarding dosage timing for several anticancer drugs appeared not be optimum, leading to suboptimal bioavailability and plasma drug concentrations. This supports a call to regularly recalibrate the labeling information for dosage timing of oral anticancer medications to minimize the risks of compromised efficacy or unintended toxicities.

Maternal Circadian Eating Time and Frequency Are Associated with Blood Glucose Concentrations during Pregnancy.

BACKGROUND: Synchronizing eating schedules to daily circadian rhythms may improve metabolic health, but its association with gestational glycemia is unknown. OBJECTIVE: This study examined the association of maternal night-fasting intervals and eating episodes with blood glucose concentrations during pregnancy. METHODS: This was a cross-sectional study within a prospective cohort in Singapore. Maternal 24-h dietary recalls, fasting glucose, and 2-h glucose concentrations were ascertained at 26-28 wk gestation for 1061 women (aged 30.7 ± 5.1 y). Night-fasting intervals were based on the longest fasting duration during the night (1900-0659). Eating episodes were defined as events that provided >50 kcal, with a time interval between eating episodes of ≥15 min. Multiple linear regressions with adjustment for confounders were conducted. RESULTS: Mean ± SD night-fasting intervals and eating episodes per day were 9.9 ± 1.6 h and 4.2 ± 1.3 times/d, respectively; fasting and 2-h glucose concentrations were 4.4 ± 0.5 and 6.6 ± 1.5 mmol/L, respectively. In adjusted models, each hourly increase in night-fasting intervals was associated with a 0.03 mmol/L decrease in fasting glucose (95% CI: -0.06, -0.01 mmol/L), whereas each additional daily eating episode was associated with a 0.15 mmol/L increase in 2-h glucose (95% CI: 0.03, 0.28 mmol/L). Conversely, night-fasting intervals and daily eating episodes were not associated with 2-h and fasting glucose, respectively. CONCLUSIONS: Increased maternal night-fasting intervals and reduced eating episodes per day were associated with decreased fasting glucose and 2-h glucose, respectively, in the late-second trimester of pregnancy. This points to potential alternative strategies to improve glycemic control in pregnant women. This study was registered at www.clinicaltrials.gov as NCT01174875.

Maternal Night-Fasting Interval during Pregnancy Is Directly Associated with Neonatal Head Circumference and Adiposity in Girls but Not Boys.

Background: Synchrony between daily feeding-fasting signals and circadian rhythms has been shown to improve metabolic health in animals and adult humans, but the potential programming effect on fetal growth is unknown.Objective: We examined the associations of the maternal night-fasting interval during pregnancy with offspring birth size and adiposity.Methods: This was a cross-sectional study of mother-offspring dyads within the Growing Up in Singapore Towards healthy Outcomes (GUSTO) cohort. For 384 mothers aged 30.8 ± 4.8 y (mean ± SD), the night-fasting interval at 26-28 wk of gestation was determined from a 3-d food diary based on the average of the fasting duration at night (1900-0659). Offspring birth weight, length, and head circumference were measured and converted to weight-for-gestational age (GA), length-for-GA, and head circumference-for-GA z scores, respectively, by using local customized percentile charts. The percentage of neonatal total body fat (TBF) was derived by using a validated prediction equation. Multivariable general linear models, stratified by child sex, were performed.Results: The mean ± SD maternal night-fasting interval was 9.9 ± 1.3 h. In infant girls, each 1-h increase in the maternal night-fasting interval was associated with a 0.22-SD (95% CI: 0.05-, 0.40-SD; P = 0.013) increase in birth head circumference-for-GA and a 0.84% (95% CI: 0.19%, 1.49%; P = 0.012) increase in TBF at birth, after adjustment for confounders. In infant boys, no associations were observed between the maternal night-fasting interval and birth size or TBF.Conclusions: An increased maternal night-fasting interval in the late second trimester of pregnancy is associated with increased birth head circumference and TBF in girls but not boys. Our findings are in accordance with previous observations that suggest that there are sex-specific responses in fetal brain growth and adiposity, and raise the possibility of the maternal night-fasting interval as an underlying influence. This trial was registered at clinicaltrials.gov as NCT01174875.

Mobile Apps for Dietary and Food Timing Assessment: Evaluation for Use in Clinical Research.

BACKGROUND: Over the last decade, health mobile apps have become an increasingly popular tool used by clinicians and researchers to track food consumption and exercise. However, many consumer apps lack the technological features for facilitating the capture of critical food timing details. OBJECTIVE: This study aimed to introduce users to 11 apps from US app stores that recorded both dietary intake and food timing to establish which one would be the most appropriate for clinical research. METHODS: To determine a viable app that recorded both dietary intake and food timing for use in a food timing-related clinical study, we evaluated the time stamp data, usability, privacy policies, the accuracy of nutrient estimates, and general features of 11 mobile apps for dietary assessment that were available on US app stores. The following apps were selected using a keyword search of related terms and reviewed: text entry apps-Cronometer, DiaryNutrition, DietDiary, FoodDiary, Macros, and MyPlate; image entry apps-FoodView and MealLogger; and text plus image entry apps-Bitesnap, myCircadianClock, and MyFitnessPal. RESULTS: Our primary goal was to identify apps that recorded food time stamps, which 8 (73%) of the 11 reviewed apps did. Of the 11 apps, only 4 (36%) allowed users to edit the time stamps. Next, we sought to evaluate the usability of the apps using the System Usability Scale across 2 days, and 82% (9/11) of the apps received favorable scores for usability. To enable use in research and clinical settings, the privacy policies of each app were systematically reviewed using common criteria, with 1 (9%) Health Insurance Portability and Accountability Act-compliant app (Cronometer). Furthermore, protected health information was collected by 9 (82%) of the 11 apps. Finally, to assess the accuracy of the nutrient estimates generated by these apps, we selected 4 sample food items and a 3-day dietary record to input into each app. The caloric and macronutrient estimates of the apps were compared with the nutrient estimates provided by a registered dietitian using the Nutrition Data System for Research database. In terms of the 3-day food record, the apps were found to consistently underestimate daily calories and macronutrients compared with the Nutrition Data System for Research output. CONCLUSIONS: Overall, we found that the Bitesnap app provided flexible dietary and food timing functionality capable of being used in research and clinical settings, whereas most other apps lacked in the necessary food timing functionality or user privacy.

Inconsistent eating time is associated with obesity: A prospective study.

Obesity is characterized by an accumulation of redundant body fat linked to metabolic dysregulation and low-grade systemic inflammation. Lifestyle choices are imperative determining factors of obesity. The contemporary lifestyle is associated with behaviors that disrupt circadian rhythms, impacting metabolic homeostasis. Our animal and human studies suggest that circadian phenotypes could be related to the risk of metabolic dysregulation and obesity. The purpose of this study is to examine the role of inconsistent eating habits on body weight in adults. Individuals who presented for colon cancer screening were enrolled. Subjects received structured questionnaires to capture 7-day eating and sleeping times in a week prospectively. Bodyweight and height were extracted from medical records, and Body Mass Index (BMI) was calculated. Inconsistent eating times were defined as an average difference of >2 hours between the largest meal on weekdays and weekends. Forty-nine of the 61 (80.3 %) individuals enrolled in the study completed the questionnaires. The mean age and standard deviation (SD) were 60.8 (7.9), and 27 (55.1 %) were male. Subjects with inconsistent eating times had a significantly higher BMI (33.8 ± 3.6 SD, n = 9) than subjects who did not (27.5 ± 6.5 SD, n = 40; p = 0.001). The highest BMI was observed in subjects who ate inconsistently and late (35.8 ± 4.6 SD). In this cross-sectional study, time of eating habits was associated with BMI. Controlled cohort studies are needed to determine the potential link between eating time and the risk of obesity in the long term.

Breakfast skipping and timing of lunch and dinner: Relationship with BMI and obesity.

OBJECTIVE: To determine whether breakfast-skipping, late-lunch, and late-dinner eating are cross-sectionally associated with higher BMI and obesity. Also, to identify obesogenic behaviors and circadian-related variables, associated with late eating. METHODS: Participants(n = 776) were part of exploratory, population-based research, with data collection in a virtual environment. They were grouped into breakfast-eaters (first meal until 10:00) and skippers (first meal after 10:00), and the population median for the lunch and dinner timing was used to stratify participants into early (lunch/dinner-time before 12:34/20:55) and late (lunch/dinner-time after 12:34/20:55) eaters. Student's t-test and chi-square test were performed to assess differences in characteristics and lifestyle traits between groups. Logistic regression models were used to assess differences in obesity between groups. Linear regression analysis was conducted to determine the association of the clock time of meals with BMI. Analyses were adjusted for potential confounders variables. RESULTS: BMI raised of 0.74 Kg/m2 for each additional hour of lunch-time [95 %CI= 0.31;1.18,P ≤ 0.001]. Breakfast-skippers [OR(95 % CI):1.84(1.02;3.31);P ≤ 0.05] and late-lunch eaters [OR(95 % CI):1.61(1.04;2.49),P ≤ 0.05] had higher odds of having obesity, compared with breakfast-eaters and early-lunch eaters, respectively. These associations were independent of age, gender, diet quality, physical activity duration, and region. No statistically significant differences were found in the comparison between early and late-dinner eaters. CONCLUSIONS: Our results suggest that skipping breakfast and eating late-lunch are associated with BMI and higher odds of having obesity. Insights into the obesogenic behaviors/characteristics related to breakfast-skipping and late-eating may be helpful for future nutritional recommendations and obesity prevention and treatment.

How Accurately Can We Recall the Timing of Food Intake? A Comparison of Food Times from Recall-Based Survey Questions and Daily Food Records.

BACKGROUND: There currently are no standard, low-cost, and validated methods to assess the timing of food intake. OBJECTIVES: The aim of this study was to validate simple, recall-based questions that can characterize food timing in free-living populations. METHODS: The concordance between recall-based survey questions and food times estimated from multiple daily food records was assessed in 249 generally healthy, free-living adults from the Shift Work, Heredity, Insulin, and Food Timing (SHIFT) Study. At baseline, participants were asked: "At what time do you first start and stop eating on weekdays/workdays and weekends/non-workdays?" and "At what time do you have your main meal on weekdays/workdays and weekends/non-workdays?" Participants were then asked to complete ≤14 d of food records noting the start time of each eating occasion. The timing of the first, last, and main (largest percentage calories) eating occasions were determined from food records. Wilcoxon matched pairs signed rank and Kendall's coefficient of concordance were used to compare differences and determine agreements between the methods for these food timing parameters, as well as for the midpoint between first and last eating occasion. RESULTS: Eating occasions on work and free days showed significant agreements between the 2 methods, except for the main eating occasion on free days. Significant agreements were generally modest and ranged from 0.16 (workdays main eating occasion) to 0.45 (workdays first eating occasion). Generally, times based on recall were later than those estimated from food records, and the differences in estimated times were smaller on workdays compared with free days, and smaller for the first compared with the last eating occasion. Main eating occasions from food records often varied between lunch and dinner times, contributing to low concordance with recalled times. CONCLUSIONS: Modest agreements were found between food times derived from simple, recall-based survey questions and food times estimated from multiple-day food records. Single administration of these questions can effectively characterize the overall timing of eating occasions within a population for chrononutrition research purposes.

Enhancing Nutrition Care Through Real-Time, Sensor-Based Capture of Eating Occasions: A Scoping Review.

As food intake patterns become less structured, different methods of dietary assessment may be required to capture frequently omitted snacks, smaller meals, and the time of day when they are consumed. Incorporating sensors that passively and objectively detect eating behavior may assist in capturing these eating occasions into dietary assessment methods. The aim of this study was to identify and collate sensor-based technologies that are feasible for dietitians to use to assist with performing dietary assessments in real-world practice settings. A scoping review was conducted using the PRISMA extension for scoping reviews (PRISMA-ScR) framework. Studies were included if they were published between January 2016 and December 2021 and evaluated the performance of sensor-based devices for identifying and recording the time of food intake. Devices from included studies were further evaluated against a set of feasibility criteria to determine whether they could potentially be used to assist dietitians in conducting dietary assessments. The feasibility criteria were, in brief, consisting of an accuracy ≥80%; tested in settings where subjects were free to choose their own foods and activities; social acceptability and comfort; a long battery life; and a relatively rapid detection of an eating episode. Fifty-four studies describing 53 unique devices and 4 device combinations worn on the wrist (n = 18), head (n = 16), neck (n = 9), and other locations (n = 14) were included. Whilst none of the devices strictly met all feasibility criteria currently, continuous refinement and testing of device software and hardware are likely given the rapidly changing nature of this emerging field. The main reasons devices failed to meet the feasibility criteria were: an insufficient or lack of reporting on battery life (91%), the use of a limited number of foods and behaviors to evaluate device performance (63%), and the device being socially unacceptable or uncomfortable to wear for long durations (46%). Until sensor-based dietary assessment tools have been designed into more inconspicuous prototypes and are able to detect most food and beverage consumption throughout the day, their use will not be feasible for dietitians in practice settings.

Psychometric Testing of a Food Timing Questionnaire and Food Timing Screener.

BACKGROUND: Circadian rhythms coordinate multiple biological processes, and time of eating is an important entrainer of peripheral circadian clocks, including those in the gastrointestinal tract and liver. Whereas time of eating can be assessed through valid and reliable tools designed to measure nutrient intake (24-h recalls), currently there is no easily administered, valid, and reliable tool designed to specifically assess both time of food intake and sleep. OBJECTIVES: The objective of this study was to test the validity and reliability of 2 questionnaires developed to measure food and sleep-wake timing, the Food Timing Questionnaire (FTQ) and Food Timing Screener (FTS), and the agreement between these 2 tools. METHODS: The content validity of these tools was assessed by an expert panel of 10 registered dietitian nutritionists. Adult volunteers (n = 61) completed both tools to assess internal consistency and test-retest reliability. Criterion-related validity was determined through the association of FTQ and FTS with 2 valid instruments, the Automated Self-Administered 24-hour recall (ASA24®) Dietary Assessment tool and the Munich Chronotype Questionnaire. Agreement between the FTQ and FTS was tested by calculating the Pearson's correlations for both food and sleep-wake timing. RESULTS: The content validity indexes for both tools were >0.80, and internal consistency and test-retest reliability coefficients were >0.50 for all meals and sleep-wake times. Correlation coefficients were >0.40 between both tools and criterion measures of food intake and sleep except for snacks. Correlations between the FTQ and FTS for all eating events and sleep were >0.60 except for snack 1. CONCLUSIONS: Both the FTQ and FTS are valid and reliable instruments for meal timing and sleep. However, further psychometric testing in a more expansive and diverse sample will improve the ability of these tools to accurately assess food timing and sleep and their impact on health outcomes.

DIet and Health From reGIstered Trials on ClinicalTrials.gov: The DIGIT Study.

Background: Clinical trial registration has become a valuable tool that can be used to track the status and nature of trials conducted on a specific topic. This approach has been applied to many areas of research, but less is known about the characteristics and trends over time of clinical trials focused on diet and health. The aim of this study was to analyze diet-related clinical trials registered on the National Institute of Health "ClinicalTrials.gov" web platform in the last 10 years, to list and describe their characteristics, and to identify possible gaps to be filled in the future research. Methods: A search was performed on the ClinicalTrials.gov database. Intervention studies registered from January 2010 to December 2020, conducted on adults, with a follow-up of ≥2 weeks, evaluating the impact of different diets on all outcomes except those assessed with scales or questionnaires were considered. Results: At the end of the selection process, a total of 1,016 registered clinical trials were identified and included in the analysis. The most investigated dietary approaches were balanced diets (n = 381 trials), followed by those based on a modification of macronutrients (n = 288) and time-restricted feeding and intermittent fasting diets (n = 140). The main measured outcomes included anthropometric parameters and body composition (57.8%), glycemic control parameters (49.7%), lipid parameters (40.1%), inflammatory markers (29.1%), and blood pressure and/or heart rate (24.5%). A growing body of studies also focused on microbiota and host metabolism (17.8%). Most studies had a duration of less than 12 weeks (~60%), and more than 90% of studies enrolled volunteers with overweight/obesity or other diseases. Regarding aging, only 21 studies focused only on older adults. Conclusion: The number of studies investigating the relationship between diet and health has increased over the years. Despite the growing interest in the topic, there are some gaps, such as the limited duration of most trials, the underrepresentation of some population groups, and the limited number of studies for some diets that, although popular in the population, lack robust scientific evidence.

Late eating is associated with cardiometabolic risk traits, obesogenic behaviors, and impaired weight loss.

BACKGROUND: There is a paucity of evidence regarding the role of food timing on cardiometabolic health and weight loss in adults. OBJECTIVES: To determine whether late eating is cross-sectionally associated with obesity and cardiometabolic risk factors at baseline; and whether late eating is associated with weight loss rate and success following a weight loss intervention protocol. Also, to identify obesogenic behaviors and weight loss barriers associated with late eating. METHODS: Participants were recruited from a weight-loss program in Spain. Upon recruitment, the midpoint of meal intake was determined by calculating the midway point between breakfast and dinner times, and dietary composition was determined from diet recall. Population median for the midpoint of meal intake was used to stratify participants into early (before 14:54) and late (after 14:54) eaters. Cardiometabolic and satiety hormonal profiles were determined from fasting blood samples collected prior to intervention. Weekly weight loss and barriers were evaluated during the ∼19-wk program. Linear and logistic regression models were used to assess differences between late and early eaters in cardiometabolic traits, satiety hormones, obesogenic behaviors, and weight loss, adjusted for age, sex, clinic site, year of recruitment, and baseline BMI. RESULTS: A total of 3362 adults [mean (SD): age: 41 (14) y; 79.2% women, BMI: 31.05 (5.58) kg/m2] were enrolled. At baseline, no differences were observed in energy intake or physical activity levels between early and late eaters (P >0.05). Late eaters had higher BMI, higher concentrations of triglycerides, and lower insulin sensitivity compared with early eaters (all P <0.05) prior to intervention. In addition, late eaters had higher concentrations of the satiety hormone leptin in the morning (P = 0.001). On average, late eaters had an average 80 g lower weekly rate of weight loss [early, 585 (667) g/wk; late, 505 (467) g/wk; P = 0.008], higher odds of having weight-loss barriers [OR (95% CI): 1.22 (1.03, 1.46); P = 0.025], and lower odds of motivation for weight loss [0.81 (0.66, 0.99); P = 0.044] compared with early eaters. CONCLUSION: Our results suggest that late eating is associated with cardiometabolic risk factors and reduced efficacy of a weight-loss intervention. Insights into the characteristics and behaviors related to late eating may be useful in the development of future interventions aimed at advancing the timing of food intake.

Sleep and circadian rhythms: pillars of health-a Keystone Symposia report.

The human circadian system consists of the master clock in the suprachiasmatic nuclei of the hypothalamus as well as in peripheral molecular clocks located in organs throughout the body. This system plays a major role in the temporal organization of biological and physiological processes, such as body temperature, blood pressure, hormone secretion, gene expression, and immune functions, which all manifest consistent diurnal patterns. Many facets of modern life, such as work schedules, travel, and social activities, can lead to sleep/wake and eating schedules that are misaligned relative to the biological clock. This misalignment can disrupt and impair physiological and psychological parameters that may ultimately put people at higher risk for chronic diseases like cancer, cardiovascular disease, and other metabolic disorders. Understanding the mechanisms that regulate sleep circadian rhythms may ultimately lead to insights on behavioral interventions that can lower the risk of these diseases. On February 25, 2021, experts in sleep, circadian rhythms, and chronobiology met virtually for the Keystone eSymposium "Sleep & Circadian Rhythms: Pillars of Health" to discuss the latest research for understanding the bidirectional relationships between sleep, circadian rhythms, and health and disease.

Interaction of alcohol with time of eating on markers of circadian dyssynchrony and colon tissue injury.

BACKGROUND: Alcohol increases the risk of developing colon cancer (CRC), in part via tissue inflammation and impaired barrier integrity. Circadian dyssynchrony (CD) is an understudied but common lifestyle associated factor that increases the risk of multi-organ tissue injury and number of malignancies including CRC. Our prior studies showed that the shift in light-dark cycle exacerbates barrier dysfunction and colonic inflammation in the setting of alcohol treatment, and increases the risk of CRC. Here we studied the interaction of alcohol with an abnormal eating pattern on markers of CD and colonic barrier integrity. METHOD: Mice were subjected to day (rest-phase = wrong-time WT) or night-time (active-phase = right-time RT) access to food in combination with access to water or 15% alcohol for total duration of 10 weeks. The food and liquid intake was measured. The locomotor activity data was recorded throughout the study, using a beam-break system. Mice were euthanized at two time points (ZT2 and ZT14). Time variation in the expression of the molecular marker of circadian clock (per2 gene) was measured in the central (hypothalamus) and intestinal (colon) tissue. Colonic protein expression of barrier markers (Occludin and Claudin-1) was studied. RESULTS: No significant differences were present in the weight gain and alcohol intake among the groups over the study period. We observed an interaction of WT eating with alcohol on behavioral markers of circadian rhythm. Compared to the RT + Water treated animals ("reference group"), combination of WT eating and alcohol consumption (WT + Alcohol) significantly changed the per2 oscillatory pattern, that was different between the colon and hypothalamus, indicative of worsening circadian dyssynchrony. This was associated with an overall impaired expression of barrier integrity markers in the colon. CONCLUSIONS: Alcohol induces circadian dyssynchrony which is worsened by abnormal food timing, associated with impaired barrier integrity in the colon. Future studies on the interaction of alcohol and food timing could provide further insights into alcohol associated CRC pathophysiology.

Abnormal Food Timing Promotes Alcohol-Associated Dysbiosis and Colon Carcinogenesis Pathways.

Background: Alcohol consumption is an established risk factor for colorectal cancer (CRC). Identifying cofactor(s) that modulate the effect of alcohol on colon inflammation and carcinogenesis could help risk stratification for CRC. Disruption of circadian rhythm by light/dark shift promotes alcohol-induced colonic inflammation and cancer. More recently, we found that abnormal food timing causes circadian rhythm disruption and promotes alcohol associated colon carcinogenesis. In this study, we examined the interaction of wrong-time feeding (WTF) and alcohol on CRC-related pathways, in relation to changes in microbial community structure. Methods: Polyposis mice (TS4Cre ×cAPC Δ468) underwent four conditions: alcohol or water and feeding during the light (wrong-time fed/WTF) or during the dark (right-time fed). Colonic cecum mucosal gene expression was analyzed by RNA-seq. Microbiota 16S ribosomal RNA sequencing analysis was used to examine colonic feces. Modeling was used to estimate the extent of the gene expression changes that could be related to the changes in the colonic microbial composition. Results: The circadian rhythm pathway was the most altered pathway by the WTF treatment, indicating that WTF is disruptive to the colonic circadian rhythm. Pathway analysis revealed interaction of WTF with alcohol in dysregulating pathways related to colon carcinogenesis. Similarly, the interaction of alcohol and WTF was detected at multiple parameters of the colonic microbiota including α and ß diversity, as well as the community structure. Our modeling revealed that almost a third of total gene alterations induced by our treatments could be related to alterations in the abundance of the microbial taxa. Conclusion: These data support the promoting effect of abnormal food timing alcohol-associated CRC-related pathways in the colon and suggest colon dysbiosis as a targetable mechanism.

Effects of Shift Work on the Eating Behavior of Police Officers on Patrol.

Recent studies indicate that the timing of food intake can significantly affect metabolism and weight management. Workers operating at atypical times of the 24-h day are at risk of disturbed feeding patterns. Given the increased risk of weight gain, obesity and metabolic syndrome in shift working populations, further research is required to understand whether their eating behavior could contribute to these increased metabolic risks. The objective of this study was to characterize the dietary patterns of police officers across different types of shifts in their natural environments. Thirty-one police officers (six women; aged 32.1 ± 5.4 years, mean ± SD) from the province of Quebec, Canada, participated in a 28- to 35-day study, comprising 9- to 12-h morning, evening, and night shifts alternating with rest days. Sleep and work patterns were recorded with actigraphy and diaries. For at least 24 h during each type of work day and rest day, participants logged nutrient intake by timestamped photographs on smartphones. Macronutrient composition and caloric content were estimated by registered dieticians using the Nutrition Data System for Research database. Data were analyzed with linear mixed effects models and circular ANOVA. More calories were consumed relative to individual metabolic requirements on rest days than both evening- and night-shift days (p = 0.001), largely sourced from increased fat (p = 0.004) and carbohydrate (trend, p = 0.064) intake. Regardless, the proportions of calories from carbohydrates, fat, and protein did not differ significantly between days. More calories were consumed during the night, between 2300 h and 0600 h, on night-shift days than any other days (p < 0.001). Caloric intake occurred significantly later for night-shift days (2308 h ± 0114 h, circular mean ± SD) than for rest days (1525 h ± 0029 h; p < 0.01) and was dispersed across a longer eating window (13.9 h ± 3.1 h vs. 11.3 h ± 1.8 h, mean ± SD). As macronutrient proportions were similar and caloric intake was lower, the finding of later meals times on night-shift days versus rest days is consistent with emerging hypotheses that implicate the biological timing of food intake-rather than its quantity or composition-as the differentiating dietary factor in shift worker health.

Heritability of the timing of food intake.

BACKGROUND & AIMS: While environmental factors are presumed to be primary drivers of food timing, preliminary evidence suggests that genetics may be an additional determinant. The aim was to explore the relative contribution of genetics and environmental factors to variation in the timing of food intake in a Spanish twin population. Because chronotype, bedtime and wake time are related to food timing, covariance with food timing was further assessed. METHODS: In this observational study, 53 pairs of adult (mean (SD) = 52 (6.03) years) female twins (28 monozygotic; 25 dizygotic) were recruited from the Murcia Twin Register. Zygosity was determined by DNA-testing. Timing of the three main meals of the day was assessed via 7-day dietary records, and the midpoint of food intake was computed by calculating the midpoint between breakfast and dinner times. Chronotype, bedtime and wake time were self-reported. Heritability of food timing and related traits were estimated by comparing monozygotic and dizygotic twin correlations and fitting genetic structural equation models to measured variables. RESULTS: We observed genetic influences for food timing, with highest heritability for the midpoint of food intake (64%) in an overweight/obese population (BMI = 26.01 ± 3.77). Genetic factors contributed to a higher degree to the timing of breakfast (56%) than the timing of lunch (38%) or dinner (n.s.). Similarly, heritability estimates were larger in related behavioral traits earlier on in the day (i.e. wake time, (55%)), than those later on in the day (i.e. bedtime, (38%)). Bivariate analyses revealed a significant genetic overlap between food timing and bedtime and chronotype (rG between 0.78 and 0.91). CONCLUSIONS: Genetic influences appear to account for a significant proportion of the variability in food timing, particularly breakfast. Thus, interventions related to food timing may be more effective when targeting afternoon/evening traits, such as lunch or dinner times. Furthermore, our data suggest shared genetic architecture underlying food timing and phenotypically related traits. CLINICAL TRIAL: NCT03059576. https://clinicaltrials.gov/ct2/show/NCT03059576.

Genome-wide association study of breakfast skipping links clock regulation with food timing.

BACKGROUND: Little is known about the contribution of genetic variation to food timing, and breakfast has been determined to exhibit the most heritable meal timing. As breakfast timing and skipping are not routinely measured in large cohort studies, alternative approaches include analyses of correlated traits. OBJECTIVES: The aim of this study was to elucidate breakfast skipping genetic variants through a proxy-phenotype genome-wide association study (GWAS) for breakfast cereal skipping, a commonly assessed correlated trait. METHODS: We leveraged the statistical power of the UK Biobank (n = 193,860) to identify genetic variants related to breakfast cereal skipping as a proxy-phenotype for breakfast skipping and applied several in silico approaches to investigate mechanistic functions and links to traits/diseases. Next, we attempted validation of our approach in smaller breakfast skipping GWAS from the TwinUK (n = 2,006) and the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium (n = 11,963). RESULTS: In the UK Biobank, we identified 6 independent GWAS variants, including those implicated for caffeine (ARID3B/CYP1A1), carbohydrate metabolism (FGF21), schizophrenia (ZNF804A), and encoding enzymes important for N6-methyladenosine RNA transmethylation (METTL4, YWHAB, and YTHDF3), which regulates the pace of the circadian clock. Expression of identified genes was enriched in the cerebellum. Genome-wide correlation analyses indicated positive correlations with anthropometric traits. Through Mendelian randomization (MR), we observed causal links between genetically determined breakfast skipping and higher body mass index, more depressive symptoms, and smoking. In bidirectional MR, we demonstrated a causal link between being an evening person and skipping breakfast, but not vice versa. We observed association of our signals in an independent breakfast skipping GWAS in another British cohort (P = 0.032), TwinUK, but not in a meta-analysis of non-British cohorts from the CHARGE consortium (P = 0.095). CONCLUSIONS: Our proxy-phenotype GWAS identified 6 genetic variants for breakfast skipping, linking clock regulation with food timing and suggesting a possible beneficial role of regular breakfast intake as part of a healthy lifestyle.