Publications by authors named "Hassan S Dashti"

60 Publications

Genetic risk for obesity and the effectiveness of the ChooseWell 365 workplace intervention to prevent weight gain and improve dietary choices.

Am J Clin Nutr 2021 Sep 28. Epub 2021 Sep 28.

Division of General Internal Medicine, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.

Background: It is unknown whether behavioral interventions to improve diet are effective in people with a genetic predisposition to obesity.

Objectives: To examine associations between BMI genetic risk and changes in weight and workplace purchases by employees participating in a randomized controlled trial of an automated behavioral workplace intervention to promote healthy food choices.

Methods: Participants were hospital employees enrolled in a 12-mo intervention followed by a 12-mo follow-up. Hospital cafeterias utilized a traffic-light labeling system (e.g., green = healthy, red = unhealthy) that was used to calculate a validated Healthy Purchasing Score (HPS; higher = healthier). A weighted genome-wide BMI genetic score was generated by summing BMI-increasing alleles.

Results: The study included 397 adults of European ancestry (mean age, 44.9 y; 80.9% female). Participants in the highest genetic quartile (Q4) had a lower HPS and higher purchases of red-labeled items relative to participants in the lowest quartile (Q1) at baseline [Q4-Q1 Beta HPS, -4.66 (95% CI, -8.01 to -1.32); red-labeled items, 4.26% (95% CI, 1.45%-7.07%)] and at the 12-mo [HPS, -3.96 (95% CI, -7.5 to -0.41); red-labeled items, 3.20% (95% CI, 0.31%-6.09%)] and 24-mo [HPS, -3.70 (95% CI, -7.40 to 0.00); red-labeled items, 3.48% (95% CI, 0.54%-6.41%)] follow-up periods. In the intervention group, increases in HPS were similar in Q4 and Q1 at 12 mo (Q4-Q1 Beta, 1.04; 95% CI, -2.42 to 4.50). At the 24-mo follow-up, the change in BMI from baseline was similar between Q4 and Q1 (0.17 kg/m2; 95% CI, -0.55 to 0.89 kg/m2) in the intervention group, but higher in Q4 than Q1 (1.20 kg/m2; 95% CI, 0.26-2.13 kg/m2) in the control group. No interaction was evident between the treatment arm and genetic score for BMI or HPS.

Conclusions: Having a high BMI genetic risk was associated with greater increases in BMI and lower quality purchases over 2 y. The 12-mo behavioral intervention improved employees' food choices, regardless of the genetic burden, and may have attenuated weight gain conferred by having the genetic risk.
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http://dx.doi.org/10.1093/ajcn/nqab303DOI Listing
September 2021

Associations of sleep duration and sleep-wake rhythm with lung parenchymal abnormalities on computed tomography: The MESA study.

J Sleep Res 2021 Sep 9:e13475. Epub 2021 Sep 9.

Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.

Impairment of the circadian rhythm promotes lung inflammation and fibrosis in pre-clinical models. We aimed to examine whether short and/or long sleep duration and other markers of sleep-wake patterns are associated with a greater burden of lung parenchymal abnormalities on computed tomography among adults. We cross-sectionally examined associations of sleep duration captured by actigraphy with interstitial lung abnormalities (n = 1111) and high attenuation areas (n = 1416) on computed tomography scan in the Multi-Ethnic Study of Atherosclerosis at Exam 5 (2010-2013). We adjusted for potential confounders in logistic and linear regression models for interstitial lung abnormalities and high attenuation area, respectively. High attenuation area models were also adjusted for study site, lung volume imaged, radiation dose and stratified by body mass index. Secondary exposures were self-reported sleep duration, sleep fragmentation index, sleep midpoint and chronotype. The mean age of those with longer sleep duration (≥ 8 hr) was 70 years and the prevalence of interstitial lung abnormalities was 14%. Increasing actigraphy-based sleep duration among participants with ≥ 8 hr of sleep was associated with a higher adjusted odds of interstitial lung abnormalities (odds ratio of 2.66 per 1-hr increment, 95% confidence interval 1.42-4.99). Longer sleep duration and higher sleep fragmentation index were associated with greater high attenuation area on computed tomography among participants with a body mass index < 25 kg m (p-value for interaction < 0.02). Self-reported sleep duration, later sleep midpoint and evening chronotype were not associated with outcomes. Actigraphy-based longer sleep duration and sleep fragmentation were associated with a greater burden of lung abnormalities on computed tomography scan.
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http://dx.doi.org/10.1111/jsr.13475DOI Listing
September 2021

Association of Employees' Meal Skipping Patterns with Workplace Food Purchases, Dietary Quality, and Cardiometabolic Risk: A Secondary Analysis from the ChooseWell 365 Trial.

J Acad Nutr Diet 2021 Aug 31. Epub 2021 Aug 31.

Division of General Internal Medicine, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts. Electronic address:

Background: Employed adults may skip meals due to time or financial constraints, challenging work schedules, or limited workplace food choices. Little is known about the relationship between employees' meal skipping patterns and workplace dietary choices and health.

Objective: To examine whether hospital employees' meal skipping patterns were associated with workplace food purchases, dietary quality, and cardiometabolic risk factors (ie, obesity, hypertension, and prediabetes/diabetes).

Design: This is a secondary cross-sectional analysis of baseline data from the ChooseWell 365 randomized controlled trial. Employees reported meal-skipping frequency in a baseline survey. The healthfulness of workplace food purchases was determined with a validated Healthy Purchasing Score (HPS) (range = 0 to 100 where higher scores = healthier purchases) calculated using sales data for participants' purchases in the 3 months before study enrollment. Dietary quality was measured with the 2015 Healthy Eating Index (range = 0 to 100 where higher score = healthier diet) from two 24-hour recalls. Cardiometabolic risk factors were ascertained from clinic measurements.

Participants/setting: Participants were 602 hospital employees who regularly visited workplace cafeterias and enrolled in ChooseWell 365, a workplace health promotion study in Boston, MA, during 2016-2018.

Main Outcome Measures: Primary outcomes were HPS, 2015 Healthy Eating Index, and cardiometabolic risk factors.

Statistical Analyses: Regression analyses examined differences in HPS, 2015 Healthy Eating Index, and cardiometabolic variables by meal skipping frequency, adjusting for demographic characteristics.

Results: Participants' mean (standard deviation) age was 43.6 (12.2) years and 478 (79%) were women. Overall, 45.8% skipped breakfast, 36.2% skipped lunch, and 24.9% skipped dinner ≥ 1 day/week. Employees who skipped breakfast ≥ 3 days/week (n = 102) had lower HPS (65.1 vs 70.4; P < 0.01) and 2015 Healthy Eating Index score (55.9 vs 62.8; P < 0.001) compared with those who never skipped. Skipping lunch ≥ 3 days/week and dinner ≥ 1 day/week were associated with significantly lower HPS compared with never skipping. Employees who worked nonstandard shifts skipped more meals than those who worked standard shifts. Meal skipping was not associated with obesity or other cardiometabolic variables.

Conclusions: Skipping meals was associated with less healthy food purchases at work, and skipping breakfast was associated with lower dietary quality. Future research to understand employees' reasons for skipping meals may inform how employers could support healthier dietary intake at work.
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http://dx.doi.org/10.1016/j.jand.2021.08.109DOI Listing
August 2021

Genetic analysis of dietary intake identifies new loci and functional links with metabolic traits.

Nat Hum Behav 2021 Aug 23. Epub 2021 Aug 23.

Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.

Dietary intake is a major contributor to the global obesity epidemic and represents a complex behavioural phenotype that is partially affected by innate biological differences. Here, we present a multivariate genome-wide association analysis of overall variation in dietary intake to account for the correlation between dietary carbohydrate, fat and protein in 282,271 participants of European ancestry from the UK Biobank (n = 191,157) and Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (n = 91,114), and identify 26 distinct genome-wide significant loci. Dietary intake signals map exclusively to specific brain regions and are enriched for genes expressed in specialized subtypes of GABAergic, dopaminergic and glutamatergic neurons. We identified two main clusters of genetic variants for overall variation in dietary intake that were differently associated with obesity and coronary artery disease. These results enhance the biological understanding of interindividual differences in dietary intake by highlighting neural mechanisms, supporting functional follow-up experiments and possibly providing new avenues for the prevention and treatment of prevalent complex metabolic diseases.
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http://dx.doi.org/10.1038/s41562-021-01182-wDOI Listing
August 2021

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

Ann N Y Acad Sci 2021 Aug 2. Epub 2021 Aug 2.

Sleep Center of Excellence, Columbia University Irving Medical Center, New York, New York.

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.
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http://dx.doi.org/10.1111/nyas.14661DOI Listing
August 2021

Sugar-Sweetened Beverage Consumption May Modify Associations Between Genetic Variants in the CHREBP (Carbohydrate Responsive Element Binding Protein) Locus and HDL-C (High-Density Lipoprotein Cholesterol) and Triglyceride Concentrations.

Circ Genom Precis Med 2021 Aug 16;14(4):e003288. Epub 2021 Jul 16.

Department of Clinical Epidemiology (R.L.G., D.O.M.-K., F.R.R., R.dM.), Leiden University Medical Center, the Netherlands.

Background: ChREBP (carbohydrate responsive element binding protein) is a transcription factor that responds to sugar consumption. Sugar-sweetened beverage (SSB) consumption and genetic variants in the locus have separately been linked to HDL-C (high-density lipoprotein cholesterol) and triglyceride concentrations. We hypothesized that SSB consumption would modify the association between genetic variants in the locus and dyslipidemia.

Methods: Data from 11 cohorts from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (N=63 599) and the UK Biobank (N=59 220) were used to quantify associations of SSB consumption, genetic variants, and their interaction on HDL-C and triglyceride concentrations using linear regression models. A total of 1606 single nucleotide polymorphisms within or near were considered. SSB consumption was estimated from validated questionnaires, and participants were grouped by their estimated intake.

Results: In a meta-analysis, rs71556729 was significantly associated with higher HDL-C concentrations only among the highest SSB consumers (β, 2.12 [95% CI, 1.16-3.07] mg/dL per allele; <0.0001), but not significantly among the lowest SSB consumers (=0.81; <0.0001). Similar results were observed for 2 additional variants (rs35709627 and rs71556736). For triglyceride, rs55673514 was positively associated with triglyceride concentrations only among the highest SSB consumers (β, 0.06 [95% CI, 0.02-0.09] ln-mg/dL per allele, =0.001) but not the lowest SSB consumers (=0.84; =0.0005).

Conclusions: Our results identified genetic variants in the locus that may protect against SSB-associated reductions in HDL-C and other variants that may exacerbate SSB-associated increases in triglyceride concentrations. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT00005133, NCT00005121, NCT00005487, and NCT00000479.
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http://dx.doi.org/10.1161/CIRCGEN.120.003288DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8373451PMC
August 2021

Genetics of Sleep and Insights into Its Relationship with Obesity.

Annu Rev Nutr 2021 Oct 8;41:223-252. Epub 2021 Jun 8.

Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, Massachusetts 02111, USA.

Considerable recent advancements in elucidating the genetic architecture of sleep traits and sleep disorders may provide insight into the relationship between sleep and obesity. Despite the involvement of the circadian clock in sleep and metabolism, few shared genes, including , were implicated in genome-wide association studies (GWASs) of sleep and obesity. Polygenic scores composed of signals from GWASs of sleep traits show largely null associations with obesity, suggesting lead variants are unique to sleep. Modest genome-wide genetic correlations are observed between many sleep traits and obesity and are largest for snoring. Notably, U-shaped positive genetic correlations with body mass index (BMI) exist for both short and long sleep durations. Findings from Mendelian randomization suggest robust causal effects of insomnia on higher BMI and, conversely, of higher BMI on snoring and daytime sleepiness. In addition, bidirectional effects between sleep duration and daytime napping with obesity may also exist. Limited gene-sleep interaction studies suggest that achieving favorable sleep, as part of a healthy lifestyle, may attenuate genetic predisposition to obesity,but whether these improvements produce clinically meaningful reductions in obesity risk remains unclear. Investigations of the genetic link between sleep and obesity for sleep disorders other than insomnia and in populations of non-European ancestry are currently limited.
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http://dx.doi.org/10.1146/annurev-nutr-082018-124258DOI Listing
October 2021

Habitual Sleep Duration, Daytime Napping, and Dietary Intake: A Mendelian Randomization Study.

Curr Dev Nutr 2021 Mar 3;5(3):nzab019. Epub 2021 Mar 3.

Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.

Background: Chronic inadequate sleep and frequent daytime napping may inflict deleterious health effects including weight gain, cardiometabolic and psychiatric diseases, and cancer. It is plausible that these relations may be partly influenced by the consumption of suboptimal diets.

Objectives: The study aimed to identify potential causal links of genetically proxied longer habitual sleep duration and more frequent daytime napping on 61 dietary variables derived from an FFQ. In addition, the study aimed to assess potential bidirectional causal links between habitual sleep duration or daytime napping and macronutrient composition.

Methods: Genetic variants robustly associated with habitual sleep duration and daytime napping from published genome-wide association analyses were used. Outcomes included 61 dietary variables estimated from FFQs in the UK Biobank (= 361,194). For bidirectional associations with macronutrient composition, genetic variants associated with percentage of energy from carbohydrate, fat, and protein were used. Two-sample Mendelian randomization (MR) effects were estimated with inverse-variance weighted (IVW) analysis.

Results: In 2-sample MR, genetically proxied longer sleep duration was associated with a 0.068 (95% CI: 0.034, 0.103) category increase in salad/raw vegetable intake [  = 0.006] per hour of sleep and with "no major dietary changes in the past 5 years" (  = 0.043). No associations were evident for daytime napping on dietary variables (all  > 0.05). In addition, there were no bidirectional associations between habitual sleep duration or daytime napping with the relative intake of carbohydrate, fat, and protein (all  > 0.05).

Conclusions: In this MR study, there was modest evidence for associations between habitual sleep duration with dietary intake and no evidence for associations between daytime napping frequency with dietary intake. These preliminary findings suggest that changes to habitual sleep duration or daytime napping frequency may have limited impact on long-term changes in dietary intake.
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http://dx.doi.org/10.1093/cdn/nzab019DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8171253PMC
March 2021

Selection into shift work is influenced by educational attainment and body mass index: a Mendelian randomization study in the UK Biobank.

Int J Epidemiol 2021 08;50(4):1229-1240

Broad Institute of MIT and Harvard, Cambridge, MA, USA.

Background: Shift work is associated with increased cardiometabolic disease risk. This observation may be partly explained by cardiometabolic risk factors having a role in the selection of individuals into or out of shift work. We performed Mendelian randomization (MR) analyses in the UK Biobank (UKB) to test this hypothesis.

Methods: We used genetic risk scores (GRS) to proxy nine cardiometabolic risk factors and diseases (including educational attainment, body mass index (BMI), smoking, and alcohol consumption), and tested associations of each GRS with self-reported frequency of current shift work among employed UKB participants of European ancestry (n = 190 573). We used summary-level MR sensitivity analyses to assess robustness of the identified effects, and we tested whether effects were mediated through sleep timing preference.

Results: Genetically instrumented liability to lower educational attainment (odds ratio (OR) per 3.6 fewer years in educational attainment = 2.40, 95% confidence interval (CI) = 2.22-2.59, P = 4.84 × 10-20) and higher body mass index (OR per 4.7 kg/m2 higher BMI = 1.30, 95% CI = 1.14-1.47, P = 5.85 × 10-5) increased odds of reporting participation in frequent shift work. Results were unchanged in sensitivity analyses allowing for different assumptions regarding horizontal pleiotropy. No selection effects were evident for the remaining exposures, nor for any exposures on selection out of shift work. Sleep timing preference did not mediate the effects of BMI and educational attainment on selection into shift work.

Conclusions: Liability to lower educational attainment and higher BMI may influence selection into shift work. This phenomenon may bias epidemiological studies of shift work that are performed in the UKB.
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http://dx.doi.org/10.1093/ije/dyab031DOI Listing
August 2021

Genetic determinants of daytime napping and effects on cardiometabolic health.

Nat Commun 2021 02 10;12(1):900. Epub 2021 Feb 10.

Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.

Daytime napping is a common, heritable behavior, but its genetic basis and causal relationship with cardiometabolic health remain unclear. Here, we perform a genome-wide association study of self-reported daytime napping in the UK Biobank (n = 452,633) and identify 123 loci of which 61 replicate in the 23andMe research cohort (n = 541,333). Findings include missense variants in established drug targets for sleep disorders (HCRTR1, HCRTR2), genes with roles in arousal (TRPC6, PNOC), and genes suggesting an obesity-hypersomnolence pathway (PNOC, PATJ). Association signals are concordant with accelerometer-measured daytime inactivity duration and 33 loci colocalize with loci for other sleep phenotypes. Cluster analysis identifies three distinct clusters of nap-promoting mechanisms with heterogeneous associations with cardiometabolic outcomes. Mendelian randomization shows potential causal links between more frequent daytime napping and higher blood pressure and waist circumference.
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http://dx.doi.org/10.1038/s41467-020-20585-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7876146PMC
February 2021

Sleep characteristics across the lifespan in 1.1 million people from the Netherlands, United Kingdom and United States: a systematic review and meta-analysis.

Nat Hum Behav 2021 01 16;5(1):113-122. Epub 2020 Nov 16.

Research Institute of Child Development and Education, University of Amsterdam, Amsterdam, the Netherlands.

We aimed to obtain reliable reference charts for sleep duration, estimate the prevalence of sleep complaints across the lifespan and identify risk indicators of poor sleep. Studies were identified through systematic literature search in Embase, Medline and Web of Science (9 August 2019) and through personal contacts. Eligible studies had to be published between 2000 and 2017 with data on sleep assessed with questionnaires including ≥100 participants from the general population. We assembled individual participant data from 200,358 people (aged 1-100 years, 55% female) from 36 studies from the Netherlands, 471,759 people (40-69 years, 55.5% female) from the United Kingdom and 409,617 people (≥18 years, 55.8% female) from the United States. One in four people slept less than age-specific recommendations, but only 5.8% slept outside of the 'acceptable' sleep duration. Among teenagers, 51.5% reported total sleep times (TST) of less than the recommended 8-10 h and 18% report daytime sleepiness. In adults (≥18 years), poor sleep quality (13.3%) and insomnia symptoms (9.6-19.4%) were more prevalent than short sleep duration (6.5% with TST < 6 h). Insomnia symptoms were most frequent in people spending ≥9 h in bed, whereas poor sleep quality was more frequent in those spending <6 h in bed. TST was similar across countries, but insomnia symptoms were 1.5-2.9 times higher in the United States. Women (≥41 years) reported sleeping shorter times or slightly less efficiently than men, whereas with actigraphy they were estimated to sleep longer and more efficiently than man. This study provides age- and sex-specific population reference charts for sleep duration and efficiency which can help guide personalized advice on sleep length and preventive practices.
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http://dx.doi.org/10.1038/s41562-020-00965-xDOI Listing
January 2021

Night shift work is associated with an increased risk of asthma.

Thorax 2021 01 16;76(1):53-60. Epub 2020 Nov 16.

Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK

Introduction: Shift work causes misalignment between internal circadian time and the external light/dark cycle and is associated with metabolic disorders and cancer. Approximately 20% of the working population in industrialised countries work permanent or rotating night shifts, exposing this large population to the risk of circadian misalignment-driven disease. Analysis of the impact of shift work on chronic inflammatory diseases is lacking. We investigated the association between shift work and asthma.

Methods: We describe the cross-sectional relationship between shift work and prevalent asthma in >280000 UK Biobank participants, making adjustments for major confounding factors (smoking history, ethnicity, socioeconomic status, physical activity, body mass index). We also investigated chronotype.

Results: Compared with day workers, 'permanent' night shift workers had a higher likelihood of moderate-severe asthma (OR 1.36 (95% CI 1.03 to 1.8)) and all asthma (OR 1.23 (95% CI 1.03 to 1.46)). Individuals doing any type of shift work had higher adjusted odds of wheeze/whistling in the chest. Shift workers who never or rarely worked on nights and people working permanent nights had a higher adjusted likelihood of having reduced lung function (FEV <80% predicted). We found an increase in the risk of moderate-severe asthma in morning chronotypes working irregular shifts, including nights (OR 1.55 (95% CI 1.06 to 2.27)).

Conclusions: The public health implications of these findings are far-reaching due to the high prevalence and co-occurrence of both asthma and shift work. Future longitudinal follow-up studies are needed to determine if modifying shift work schedules to take into account chronotype might present a public health measure to reduce the risk of developing inflammatory diseases such as asthma.
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http://dx.doi.org/10.1136/thoraxjnl-2020-215218DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7803886PMC
January 2021

Is disrupted sleep a risk factor for Alzheimer's disease? Evidence from a two-sample Mendelian randomization analysis.

Int J Epidemiol 2021 07;50(3):817-828

MRC Integrative Epidemiology Unit, at the University of Bristol, Bristol, UK.

Background: It is established that Alzheimer's disease (AD) patients experience sleep disruption. However, it remains unknown whether disruption in the quantity, quality or timing of sleep is a risk factor for the onset of AD.

Methods: We used the largest published genome-wide association studies of self-reported and accelerometer-measured sleep traits (chronotype, duration, fragmentation, insomnia, daytime napping and daytime sleepiness), and AD. Mendelian randomization (MR) was used to estimate the causal effect of self-reported and accelerometer-measured sleep parameters on AD risk.

Results: Overall, there was little evidence to support a causal effect of sleep traits on AD risk. There was some suggestive evidence that self-reported daytime napping was associated with lower AD risk [odds ratio (OR): 0.70, 95% confidence interval (CI): 0.50-0.99). Some other sleep traits (accelerometer-measured 'eveningness' and sleep duration, and self-reported daytime sleepiness) had ORs of a similar magnitude to daytime napping, but were less precisely estimated.

Conclusions: Overall, we found very limited evidence to support a causal effect of sleep traits on AD risk. Our findings provide tentative evidence that daytime napping may reduce AD risk. Given that this is the first MR study of multiple self-report and objective sleep traits on AD risk, findings should be replicated using independent samples when such data become available.
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http://dx.doi.org/10.1093/ije/dyaa183DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8271193PMC
July 2021

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

Am J Clin Nutr 2020 Oct 6. Epub 2020 Oct 6.

Department of Physiology, University of Murcia, Murcia, Spain; IMIB-Arrixaca, Murcia, Spain.

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.
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http://dx.doi.org/10.1093/ajcn/nqaa264DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7779221PMC
October 2020

Sleep health, diseases, and pain syndromes: findings from an electronic health record biobank.

Sleep 2021 03;44(3)

Mass General Brigham Personalized Medicine, Mass General Brigham, Boston, MA.

Study Objectives: Implementation of electronic health record biobanks has facilitated linkage between clinical and questionnaire data and enabled assessments of relationships between sleep health and diseases in phenome-wide association studies (PheWAS). In the Mass General Brigham Biobank, a large health system-based study, we aimed to systematically catalog associations between time in bed, sleep timing, and weekly variability with clinical phenotypes derived from ICD-9/10 codes.

Methods: Self-reported habitual bed and wake times were used to derive variables: short (<7 hours) and long (≥9 hours) time in bed, sleep midpoint, social jetlag, and sleep debt. Logistic regression and Cox proportional hazards models were used to test cross-sectional and prospective associations, respectively, adjusted for age, gender, race/ethnicity, and employment status and further adjusted for body mass index.

Results: In cross-sectional analysis (n = 34,651), sleep variable associations were most notable for circulatory system, mental disorders, and endocrine/metabolic phenotypes. We observed the strongest associations for short time in bed with obesity, for long time in bed and sleep midpoint with major depressive disorder, for social jetlag with hypercholesterolemia, and for sleep debt with acne. In prospective analysis (n = 24,065), we observed short time in bed associations with higher incidence of acute pain and later sleep midpoint and higher sleep debt and social jetlag associations with higher incidence of major depressive disorder.

Conclusions: Our analysis reinforced that sleep health is a multidimensional construct, corroborated robust known findings from traditional cohort studies, and supported the application of PheWAS as a promising tool for advancing sleep research. Considering the exploratory nature of PheWAS, careful interrogation of novel findings is imperative.
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http://dx.doi.org/10.1093/sleep/zsaa189DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7953212PMC
March 2021

Sleep Apnea and COVID-19 Mortality and Hospitalization.

Am J Respir Crit Care Med 2020 11;202(10):1462-1464

Brigham and Women's Hospital Boston, Massachusetts.

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http://dx.doi.org/10.1164/rccm.202006-2252LEDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7667903PMC
November 2020

Morning diurnal preference and food intake: a Mendelian randomization study.

Am J Clin Nutr 2020 11;112(5):1348-1357

Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.

Background: Poor dietary choices may underlie known associations between having an evening diurnal preference and cardiometabolic diseases. Assessing causal links between diurnal preference and food intake is now possible in Mendelian randomization (MR) analyses.

Objectives: We aimed to use a 2-sample MR to determine potential causal effects of genetic liability to a morning preference on food intake. We also examined potential causal effects of a morning preference on objectively captured response performances to email-administered 24-h diet recalls.

Methods: We used genetic variants associated with a morning preference from a published genome-wide association meta-analysis. Our outcomes included 61 food items with estimates from a food-frequency questionnaire in the UK Biobank (n = 361,194). For significant findings, we repeated the analysis using intake estimates from modified 24-h diet recalls in a subset of overlapping participants (n = 146,086). In addition, we examined 7 response performance outcomes, including the time and duration of responses to 24-h diet recalls (n = 123,035). MR effects were estimated using an inverse-variance weighted analysis.

Results: Genetic liability to a morning preference was associated with increased intake of 6 food items (fresh fruit, alcohol with meals, bran cereal, cereals, dried fruit, and water), decreased intake of 4 food items (beer plus cider, processed meat, other cereals [e.g., corn or frosted flakes], and full cream milk), increased temperature of hot drinks, and decreased variation in diet (PFalse Discovery Rate < 0.05). There was no evidence for an effect on coffee or tea intake. Findings for fresh fruit, beer plus cider, bran cereal, and cereal were consistent when intakes were estimated by 24-h diet recalls (P < 0.05). We also identified potential causal links between a morning preference with earlier timing and a shorter duration for completing email-administered 24-h diet recalls.

Conclusions: Our findings provide evidence for a potentially causal effect of a morning preference with the increased intake of foods known to constitute a healthy diet, suggesting possible health benefits of adopting a more morning diurnal preference.
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http://dx.doi.org/10.1093/ajcn/nqaa219DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7657324PMC
November 2020

Polygenic risk score for obesity and the quality, quantity, and timing of workplace food purchases: A secondary analysis from the ChooseWell 365 randomized trial.

PLoS Med 2020 07 21;17(7):e1003219. Epub 2020 Jul 21.

Division of General Internal Medicine, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America.

Background: The influence of genetic risk for obesity on food choice behaviors is unknown and may be in the causal pathway between genetic risk and weight gain. The aim of this study was to examine associations between genetic risk for obesity and food choice behaviors using objectively assessed workplace food purchases.

Methods And Findings: This study is a secondary analysis of baseline data collected prior to the start of the "ChooseWell 365" health-promotion intervention randomized control trial. Participants were employees of a large hospital in Boston, MA, who enrolled in the study between September 2016 and February 2018. Cafeteria sales data, collected retrospectively for 3 months prior to enrollment, were used to track the quantity (number of items per 3 months) and timing (median time of day) of purchases, and participant surveys provided self-reported behaviors, including skipping meals and preparing meals at home. A previously validated Healthy Purchasing Score was calculated using the cafeteria traffic-light labeling system (i.e., green = healthy, yellow = less healthy, red = unhealthy) to estimate the healthfulness (quality) of employees' purchases (range, 0%-100% healthy). DNA was extracted and genotyped from blood samples. A body mass index (BMI) genome-wide polygenic score (BMIGPS) was generated by summing BMI-increasing risk alleles across the genome. Additionally, 3 polygenic risk scores (PRSs) were generated with 97 BMI variants previously identified at the genome-wide significance level (P < 5 × 10-8): (1) BMI97 (97 loci), (2) BMICNS (54 loci near genes related to central nervous system [CNS]), and (3) BMInon-CNS (43 loci not related to CNS). Multivariable linear and logistic regression tested associations of genetic risk score quartiles with workplace purchases, adjusted for age, sex, seasonality, and population structure. Associations were considered significant at P < 0.05. In 397 participants, mean age was 44.9 years, and 80.9% were female. Higher genetic risk scores were associated with higher BMI. The highest quartile of BMIGPS was associated with lower Healthy Purchasing Score (-4.8 percentage points [95% CI -8.6 to -1.0]; P = 0.02), higher quantity of food purchases (14.4 more items [95% CI -0.1 to 29.0]; P = 0.03), later time of breakfast purchases (15.0 minutes later [95% CI 1.5-28.5]; P = 0.03), and lower likelihood of preparing dinner at home (Q4 odds ratio [OR] = 0.3 [95% CI 0.1-0.9]; P = 0.03) relative to the lowest BMIGPS quartile. Compared with the lowest quartile, the highest BMICNS quartile was associated with fewer items purchased (P = 0.04), and the highest BMInon-CNS quartile was associated with purchasing breakfast at a later time (P = 0.01), skipping breakfast (P = 0.03), and not preparing breakfast (P = 0.04) or lunch (P = 0.01) at home. A limitation of this study is our data come from a relatively small sample of healthy working adults of European ancestry who volunteered to enroll in a health-promotion study, which may limit generalizability.

Conclusions: In this study, genetic risk for obesity was associated with the quality, quantity, and timing of objectively measured workplace food purchases. These findings suggest that genetic risk for obesity may influence eating behaviors that contribute to weight and could be targeted in personalized workplace wellness programs in the future.

Trial Registration: Clinicaltrials.gov NCT02660086.
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http://dx.doi.org/10.1371/journal.pmed.1003219DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7373257PMC
July 2020

Quantifying Diet Intake and Its Association with Cardiometabolic Risk in the UK Airwave Health Monitoring Study: A Data-Driven Approach.

Nutrients 2020 Apr 22;12(4). Epub 2020 Apr 22.

Department of Integrative Physiology, University of Colorado Boulder, Boulder, CO 80309, USA.

We used data-driven approaches to identify independent diet exposures among 45 candidate variables, for which we then probed cross-sectional associations with cardiometabolic risk (CMR). We derived average daily caloric intake and macronutrient composition, daily meal frequencies, and irregularity of energy and macronutrient intake from 7-day food diaries in the Airwave Health Monitoring Study participants ( = 8090). We used K-means and hierarchical clustering to identify non-redundant diet exposures with representative exposures for each cluster chosen by silhouette value. We then used multi-variable adjusted logistic regression to estimate prevalence ratios (PR) and 95% confidence intervals (95%CI) for CMR (≥3 criteria: dyslipidemia, hypertension, central adiposity, inflammation and impaired glucose control) across diet exposure quartiles. We identified four clusters: i) fat intake, ii) carbohydrate intake, iii) protein intake and intake regularity, and iv) meal frequencies and energy intake. Of these clusters, higher carbohydrate intake was associated with lower likelihood of CMR (PR = 0.89, 95%CI = 0.81-0.98; = 0.02), as was higher fiber intake (PR = 0.76, 95%CI = 0.68-0.85; < 0.001). Higher meal frequency was also associated with lower likelihood of CMR (PR = 0.76, 95%CI = 0.68-0.85; < 0.001). Our results highlight a novel, data-driven approach to select non-redundant, minimally collinear, primary exposures across a host of potentially relevant exposures (including diet composition, temporal distribution, and regularity), as often encountered in nutritional epidemiology.
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http://dx.doi.org/10.3390/nu12041170DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7230946PMC
April 2020

Assessment of Type 2 Diabetes Genetic Risk Modification by Shift Work and Morningness-Eveningness Preference in the UK Biobank.

Diabetes 2020 02 22;69(2):259-266. Epub 2019 Nov 22.

Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA

Night shift work, behavioral rhythms, and the common risk single nucleotide polymorphism (SNP), rs10830963, associate with type 2 diabetes; however, whether they exert joint effects to exacerbate type 2 diabetes risk is unknown. Among employed participants of European ancestry in the UK Biobank ( = 189,488), we aimed to test the cross-sectional independent associations and joint interaction effects of these risk factors on odds of type 2 diabetes ( = 5,042 cases) and HbA levels ( = 175,156). Current shift work, definite morning or evening preference, and rs10830963 risk allele associated with type 2 diabetes and HbA levels. The effect of rs10830963 was not modified by shift work schedules. While marginal evidence of interaction between self-reported morningness-eveningness preference and rs10830963 on risk of type 2 diabetes was seen, this interaction did not persist when analysis was expanded to include all participants regardless of employment status and when accelerometer-derived sleep midpoint was used as an objective measure of morningness-eveningness preference. Our findings suggest that risk allele carriers who carry out shift work or have more extreme morningness-eveningness preference may not have enhanced risk of type 2 diabetes.
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http://dx.doi.org/10.2337/db19-0606DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6971490PMC
February 2020

The Contribution of Lipids to the Interindividual Response of Vitamin K Biomarkers to Vitamin K Supplementation.

Mol Nutr Food Res 2019 12 3;63(24):e1900399. Epub 2019 Oct 3.

Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA, 02111, USA.

Scope: A better understanding of factors contributing to interindividual variability in biomarkers of vitamin K can enhance the understanding of the equivocal role of vitamin K in cardiovascular disease. Based on the known biology of phylloquinone, the major form of vitamin K, it is hypothesized that plasma lipids contribute to the variable response of biomarkers of vitamin K metabolism to phylloquinone supplementation.

Methods And Results: The association of plasma lipids and 27 lipid-related genetic variants with the response of biomarkers of vitamin K metabolism is examined in a secondary analysis of data from a 3-year phylloquinone supplementation trial in men (n = 66) and women (n = 85). Year 3 plasma triglycerides (TG), but not total cholesterol, LDL-cholesterol, or HDL-cholesterol, are associated with the plasma phylloquinone response (men: β = 1.01, p < 0.001, R  = 0.34; women: β = 0.61, p = 0.008, R  = 0.11; sex interaction p = 0.077). Four variants and the TG-weighted genetic risk score are associated with the plasma phylloquinone response in men only. Plasma lipids are not associated with changes in biomarkers of vitamin K function (undercarboxylated osteocalcin and matrix gla protein) in either sex.

Conclusion: Plasma TG are an important determinant of the interindividual response of plasma phylloquinone to phylloquinone supplementation, but changes in biomarkers of vitamin K carboxylation are not influenced by lipids.
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http://dx.doi.org/10.1002/mnfr.201900399DOI Listing
December 2019

Sleep Duration and Myocardial Infarction.

J Am Coll Cardiol 2019 09;74(10):1304-1314

Broad Institute of MIT and Harvard, Cambridge, Massachusetts; Department of Integrative Physiology, University of Colorado at Boulder, Boulder, Colorado. Electronic address:

Background: Observational studies suggest associations between extremes of sleep duration and myocardial infarction (MI), but the causal contribution of sleep to MI and its potential to mitigate genetic predisposition to coronary disease is unclear.

Objectives: This study sought to investigate associations between sleep duration and incident MI, accounting for joint effects with other sleep traits and genetic risk of coronary artery disease, and to assess causality using Mendelian randomization (MR).

Methods: In 461,347 UK Biobank (UKB) participants free of relevant cardiovascular disease, the authors estimated multivariable adjusted hazard ratios (HR) for MI (5,128 incident cases) across habitual self-reported short (<6 h) and long (>9 h) sleep duration, and examined joint effects with sleep disturbance traits and a coronary artery disease genetic risk score. The authors conducted 2-sample MR for short (24 single nucleotide polymorphisms) and continuous (71 single nucleotide polymorphisms) sleep duration with MI (n = 43,676 cases/128,199 controls), and replicated results in UKB (n = 12,111/325,421).

Results: Compared with sleeping 6 to 9 h/night, short sleepers had a 20% higher multivariable-adjusted risk of incident MI (HR: 1.20; 95% confidence interval [CI]: 1.07 to 1.33), and long sleepers had a 34% higher risk (HR: 1.34; 95% CI: 1.13 to 1.58); associations were independent of other sleep traits. Healthy sleep duration mitigated MI risk even among individuals with high genetic liability (HR: 0.82; 95% CI: 0.68 to 0.998). MR was consistent with a causal effect of short sleep duration on MI in CARDIoGRAMplusC4D (Coronary ARtery DIsease Genome wide Replication and Meta-analysis plus Coronary Artery Disease Genetics Consortium) (HR: 1.19; 95% CI: 1.09 to 1.29) and UKB (HR: 1.21; 95% CI: 1.08 to 1.37).

Conclusions: Prospective observational and MR analyses support short sleep duration as a potentially causal risk factor for MI. Investigation of sleep extension to prevent MI may be warranted.
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http://dx.doi.org/10.1016/j.jacc.2019.07.022DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6785011PMC
September 2019

Genome-wide association analysis of self-reported daytime sleepiness identifies 42 loci that suggest biological subtypes.

Nat Commun 2019 08 13;10(1):3503. Epub 2019 Aug 13.

Institute for Molecular Medicine FIMM, HiLIFE, University of Helsinki, Helsinki, Finland.

Excessive daytime sleepiness (EDS) affects 10-20% of the population and is associated with substantial functional deficits. Here, we identify 42 loci for self-reported daytime sleepiness in GWAS of 452,071 individuals from the UK Biobank, with enrichment for genes expressed in brain tissues and in neuronal transmission pathways. We confirm the aggregate effect of a genetic risk score of 42 SNPs on daytime sleepiness in independent Scandinavian cohorts and on other sleep disorders (restless legs syndrome, insomnia) and sleep traits (duration, chronotype, accelerometer-derived sleep efficiency and daytime naps or inactivity). However, individual daytime sleepiness signals vary in their associations with objective short vs long sleep, and with markers of sleep continuity. The 42 sleepiness variants primarily cluster into two predominant composite biological subtypes - sleep propensity and sleep fragmentation. Shared genetic links are also seen with obesity, coronary heart disease, psychiatric diseases, cognitive traits and reproductive ageing.
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http://dx.doi.org/10.1038/s41467-019-11456-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6692391PMC
August 2019

Quality of dietary fat and genetic risk of type 2 diabetes: individual participant data meta-analysis.

BMJ 2019 07 25;366:l4292. Epub 2019 Jul 25.

Objective: To investigate whether the genetic burden of type 2 diabetes modifies the association between the quality of dietary fat and the incidence of type 2 diabetes.

Design: Individual participant data meta-analysis.

Data Sources: Eligible prospective cohort studies were systematically sourced from studies published between January 1970 and February 2017 through electronic searches in major medical databases (Medline, Embase, and Scopus) and discussion with investigators.

Review Methods: Data from cohort studies or multicohort consortia with available genome-wide genetic data and information about the quality of dietary fat and the incidence of type 2 diabetes in participants of European descent was sought. Prospective cohorts that had accrued five or more years of follow-up were included. The type 2 diabetes genetic risk profile was characterized by a 68-variant polygenic risk score weighted by published effect sizes. Diet was recorded by using validated cohort-specific dietary assessment tools. Outcome measures were summary adjusted hazard ratios of incident type 2 diabetes for polygenic risk score, isocaloric replacement of carbohydrate (refined starch and sugars) with types of fat, and the interaction of types of fat with polygenic risk score.

Results: Of 102 305 participants from 15 prospective cohort studies, 20 015 type 2 diabetes cases were documented after a median follow-up of 12 years (interquartile range 9.4-14.2). The hazard ratio of type 2 diabetes per increment of 10 risk alleles in the polygenic risk score was 1.64 (95% confidence interval 1.54 to 1.75, I=7.1%, τ=0.003). The increase of polyunsaturated fat and total omega 6 polyunsaturated fat intake in place of carbohydrate was associated with a lower risk of type 2 diabetes, with hazard ratios of 0.90 (0.82 to 0.98, I=18.0%, τ=0.006; per 5% of energy) and 0.99 (0.97 to 1.00, I=58.8%, τ=0.001; per increment of 1 g/d), respectively. Increasing monounsaturated fat in place of carbohydrate was associated with a higher risk of type 2 diabetes (hazard ratio 1.10, 95% confidence interval 1.01 to 1.19, I=25.9%, τ=0.006; per 5% of energy). Evidence of small study effects was detected for the overall association of polyunsaturated fat with the risk of type 2 diabetes, but not for the omega 6 polyunsaturated fat and monounsaturated fat associations. Significant interactions between dietary fat and polygenic risk score on the risk of type 2 diabetes (P>0.05 for interaction) were not observed.

Conclusions: These data indicate that genetic burden and the quality of dietary fat are each associated with the incidence of type 2 diabetes. The findings do not support tailoring recommendations on the quality of dietary fat to individual type 2 diabetes genetic risk profiles for the primary prevention of type 2 diabetes, and suggest that dietary fat is associated with the risk of type 2 diabetes across the spectrum of type 2 diabetes genetic risk.
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http://dx.doi.org/10.1136/bmj.l4292DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6652797PMC
July 2019

Factors associated with sharing e-mail information and mental health survey participation in large population cohorts.

Int J Epidemiol 2020 04;49(2):410-421

Division of Psychiatry, Royal Edinburgh Hospital, Edinburgh, UK.

Background: People who opt to participate in scientific studies tend to be healthier, wealthier and more educated than the broader population. Although selection bias does not always pose a problem for analysing the relationships between exposures and diseases or other outcomes, it can lead to biased effect size estimates. Biased estimates may weaken the utility of genetic findings because the goal is often to make inferences in a new sample (such as in polygenic risk score analysis).

Methods: We used data from UK Biobank, Generation Scotland and Partners Biobank and conducted phenotypic and genome-wide association analyses on two phenotypes that reflected mental health data availability: (i) whether participants were contactable by e-mail for follow-up; and (ii) whether participants responded to follow-up surveys of mental health.

Results: In UK Biobank, we identified nine genetic loci associated (P <5 × 10-8) with e-mail contact and 25 loci associated with mental health survey completion. Both phenotypes were positively genetically correlated with higher educational attainment and better health and negatively genetically correlated with psychological distress and schizophrenia. One single nucleotide polymorphism association replicated along with the overall direction of effect of all association results.

Conclusions: Re-contact availability and follow-up participation can act as further genetic filters for data on mental health phenotypes.
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http://dx.doi.org/10.1093/ije/dyz134DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7266553PMC
April 2020

Investigating causal relations between sleep traits and risk of breast cancer in women: mendelian randomisation study.

BMJ 2019 Jun 26;365:l2327. Epub 2019 Jun 26.

MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.

Objective: To examine whether sleep traits have a causal effect on risk of breast cancer.

Design: Mendelian randomisation study.

Setting: UK Biobank prospective cohort study and Breast Cancer Association Consortium (BCAC) case-control genome-wide association study.

Participants: 156 848 women in the multivariable regression and one sample mendelian randomisation (MR) analysis in UK Biobank (7784 with a breast cancer diagnosis) and 122 977 breast cancer cases and 105 974 controls from BCAC in the two sample MR analysis.

Exposures: Self reported chronotype (morning or evening preference), insomnia symptoms, and sleep duration in multivariable regression, and genetic variants robustly associated with these sleep traits.

Main Outcome Measure: Breast cancer diagnosis.

Results: In multivariable regression analysis using UK Biobank data on breast cancer incidence, morning preference was inversely associated with breast cancer (hazard ratio 0.95, 95% confidence interval 0.93 to 0.98 per category increase), whereas there was little evidence for an association between sleep duration and insomnia symptoms. Using 341 single nucleotide polymorphisms (SNPs) associated with chronotype, 91 SNPs associated with sleep duration, and 57 SNPs associated with insomnia symptoms, one sample MR analysis in UK Biobank provided some supportive evidence for a protective effect of morning preference on breast cancer risk (0.85, 0.70, 1.03 per category increase) but imprecise estimates for sleep duration and insomnia symptoms. Two sample MR using data from BCAC supported findings for a protective effect of morning preference (inverse variance weighted odds ratio 0.88, 95% confidence interval 0.82 to 0.93 per category increase) and adverse effect of increased sleep duration (1.19, 1.02 to 1.39 per hour increase) on breast cancer risk (both oestrogen receptor positive and oestrogen receptor negative), whereas evidence for insomnia symptoms was inconsistent. Results were largely robust to sensitivity analyses accounting for horizontal pleiotropy.

Conclusions: Findings showed consistent evidence for a protective effect of morning preference and suggestive evidence for an adverse effect of increased sleep duration on breast cancer risk.
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http://dx.doi.org/10.1136/bmj.l2327DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6592406PMC
June 2019

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

Am J Clin Nutr 2019 08;110(2):473-484

Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA.

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.
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http://dx.doi.org/10.1093/ajcn/nqz076DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6669061PMC
August 2019

Timing of Food Intake: Identifying Contributing Factors to Design Effective Interventions.

Adv Nutr 2019 07;10(4):606-620

Department of Physiology, University of Murcia, Murcia, Spain.

Observations that mistimed food intake may have adverse metabolic health effects have generated interest in personalizing food timing recommendations in interventional studies and public health strategies for the purpose of disease prevention and improving overall health. Small, controlled, and short-termed intervention studies suggest that food timing may be modified as it is presumed to be primarily regulated by choice. Identifying and evaluating social and biological factors that explain variability in food timing may determine whether changes in food timing in uncontrolled, free-living environments are sustainable in the long term, and may facilitate design of successful food timing-based interventions. Based on a comprehensive literature search, we summarize 1) cultural and environmental factors; 2) behavioral and personal preference factors; and 3) physiological factors that influence the time when people consume foods. Furthermore, we 1) highlight vulnerable populations who have been identified in experimental and epidemiological studies to be at risk of mistimed food intake and thus necessitating intervention; 2) identify currently used food timing assessment tools and their limitations; and 3) indicate other important considerations for the design of food timing interventions based on successful strategies that address timing of other lifestyle behaviors. Conclusions drawn from this overview may help design practical food timing interventions, develop feasible public health programs, and establish guidelines for effective lifestyle recommendations for prevention and treatment of adverse health outcomes attributed to mistimed food intake.
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http://dx.doi.org/10.1093/advances/nmy131DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6628856PMC
July 2019

Genetic studies of accelerometer-based sleep measures yield new insights into human sleep behaviour.

Nat Commun 2019 04 5;10(1):1585. Epub 2019 Apr 5.

Genetics of Complex Traits, College of Medicine and Health, University of Exeter, Exeter, EX2 5DW, UK.

Sleep is an essential human function but its regulation is poorly understood. Using accelerometer data from 85,670 UK Biobank participants, we perform a genome-wide association study of 8 derived sleep traits representing sleep quality, quantity and timing, and validate our findings in 5,819 individuals. We identify 47 genetic associations at P < 5 × 10, of which 20 reach a stricter threshold of P < 8 × 10. These include 26 novel associations with measures of sleep quality and 10 with nocturnal sleep duration. The majority of identified variants associate with a single sleep trait, except for variants previously associated with restless legs syndrome. For sleep duration we identify a missense variant (p.Tyr727Cys) in PDE11A as the likely causal variant. As a group, sleep quality loci are enriched for serotonin processing genes. Although accelerometer-derived measures of sleep are imperfect and may be affected by restless legs syndrome, these findings provide new biological insights into sleep compared to previous efforts based on self-report sleep measures.
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http://dx.doi.org/10.1038/s41467-019-09576-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6451011PMC
April 2019
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