Showing papers by "Susan Redline published in 2019"
Daniel Taliun1, Daniel N. Harris2, Michael D. Kessler2, Jedidiah Carlson1 +191 more•Institutions (61)
TL;DR: The nearly complete catalog of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and non-coding sequence variants to phenotypic variation as well as resources and early insights from the sequence data.
Abstract: Summary paragraph The Trans-Omics for Precision Medicine (TOPMed) program seeks to elucidate the genetic architecture and disease biology of heart, lung, blood, and sleep disorders, with the ultimate goal of improving diagnosis, treatment, and prevention. The initial phases of the program focus on whole genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here, we describe TOPMed goals and design as well as resources and early insights from the sequence data. The resources include a variant browser, a genotype imputation panel, and sharing of genomic and phenotypic data via dbGaP. In 53,581 TOPMed samples, >400 million single-nucleotide and insertion/deletion variants were detected by alignment with the reference genome. Additional novel variants are detectable through assembly of unmapped reads and customized analysis in highly variable loci. Among the >400 million variants detected, 97% have frequency
662 citations
TL;DR: The 'hypoxic burden', an easily derived signal from overnight sleep study, predicts CVD mortality across populations and suggests that not only the frequency but the depth and duration of sleep related upper airway obstructions, are important disease characterizing features.
Abstract: Aims Apnoea-hypopnoea index (AHI), the universal clinical metric of sleep apnoea severity, poorly predicts the adverse outcomes of sleep apnoea, potentially because the AHI, a frequency measure, does not adequately capture disease burden. Therefore, we sought to evaluate whether quantifying the severity of sleep apnoea by the 'hypoxic burden' would predict mortality among adults aged 40 and older. Methods and results The samples were derived from two cohort studies: The Outcomes of Sleep Disorders in Older Men (MrOS), which included 2743 men, age 76.3 ± 5.5 years; and the Sleep Heart Health Study (SHHS), which included 5111 middle-aged and older adults (52.8% women), age: 63.7 ± 10.9 years. The outcomes were all-cause and Cardiovascular disease (CVD)-related mortality. The hypoxic burden was determined by measuring the respiratory event-associated area under the desaturation curve from pre-event baseline. Cox models were used to calculate the adjusted hazard ratios for hypoxic burden. Unlike the AHI, the hypoxic burden strongly predicted CVD mortality and all-cause mortality (only in MrOS). Individuals in the MrOS study with hypoxic burden in the highest two quintiles had hazard ratios of 1.81 [95% confidence interval (CI) 1.25-2.62] and 2.73 (95% CI 1.71-4.36), respectively. Similarly, the group in the SHHS with hypoxic burden in the highest quintile had a hazard ratio of 1.96 (95% CI 1.11-3.43). Conclusion The 'hypoxic burden', an easily derived signal from overnight sleep study, predicts CVD mortality across populations. The findings suggest that not only the frequency but the depth and duration of sleep related upper airway obstructions, are important disease characterizing features.
347 citations
Broad Institute1, Harvard University2, University of Exeter3, Brigham and Women's Hospital4, Northeastern University5, University of Manchester6, University of Bristol7, University of Murcia8, University of Oxford9, Massachusetts Institute of Technology10, Aston University11, University of Freiburg12, VA Boston Healthcare System13, Erasmus University Medical Center14, Beth Israel Deaconess Medical Center15
TL;DR: Performing GWAS for self-reported habitual sleep duration in adults, supported by accelerometer-derived measures, and identifying genetic correlation with psychiatric and metabolic traits provides insights into the genetic basis for inter-individual variation in sleep duration implicating multiple biological pathways.
Abstract: Sleep is an essential state of decreased activity and alertness but molecular factors regulating sleep duration remain unknown. Through genome-wide association analysis in 446,118 adults of European ancestry from the UK Biobank, we identify 78 loci for self-reported habitual sleep duration (p < 5 × 10−8; 43 loci at p < 6 × 10−9). Replication is observed for PAX8, VRK2, and FBXL12/UBL5/PIN1 loci in the CHARGE study (n = 47,180; p < 6.3 × 10−4), and 55 signals show sign-concordant effects. The 78 loci further associate with accelerometer-derived sleep duration, daytime inactivity, sleep efficiency and number of sleep bouts in secondary analysis (n = 85,499). Loci are enriched for pathways including striatum and subpallium development, mechanosensory response, dopamine binding, synaptic neurotransmission and plasticity, among others. Genetic correlation indicates shared links with anthropometric, cognitive, metabolic, and psychiatric traits and two-sample Mendelian randomization highlights a bidirectional causal link with schizophrenia. This work provides insights into the genetic basis for inter-individual variation in sleep duration implicating multiple biological pathways.
299 citations
Broad Institute1, Harvard University2, University of Exeter3, Norwegian University of Science and Technology4, Oslo University Hospital5, Brigham and Women's Hospital6, University of Bristol7, Northeastern University8, University of Manchester9, University College London10, Massachusetts Institute of Technology11, Aston University12, University of Oxford13, Erasmus University Rotterdam14, University of Michigan15, Beth Israel Deaconess Medical Center16, University of Freiburg17, John Radcliffe Hospital18, Manchester Academic Health Science Centre19
TL;DR: Genome-wide association analyses identify 57 loci associated with insomnia symptoms and provide evidence of shared genetic architecture between insomnia and cardiometabolic, behavioral, psychiatric and reproductive traits.
Abstract: Insomnia is a common disorder linked with adverse long-term medical and psychiatric outcomes. The underlying pathophysiological processes and causal relationships of insomnia with disease are poorly understood. Here we identified 57 loci for self-reported insomnia symptoms in the UK Biobank (n = 453,379) and confirmed their effects on self-reported insomnia symptoms in the HUNT Study (n = 14,923 cases and 47,610 controls), physician-diagnosed insomnia in the Partners Biobank (n = 2,217 cases and 14,240 controls), and accelerometer-derived measures of sleep efficiency and sleep duration in the UK Biobank (n = 83,726). Our results suggest enrichment of genes involved in ubiquitin-mediated proteolysis and of genes expressed in multiple brain regions, skeletal muscle, and adrenal glands. Evidence of shared genetic factors was found between frequent insomnia symptoms and restless legs syndrome, aging, and cardiometabolic, behavioral, psychiatric, and reproductive traits. Evidence was found for a possible causal link between insomnia symptoms and coronary artery disease, depressive symptoms, and subjective well-being.
207 citations
University of Queensland1, University of Washington2, Boston University3, University of California, San Diego4, Vanderbilt University Medical Center5, University of Maryland, Baltimore6, United States Department of Veterans Affairs7, Kaiser Permanente8, Fred Hutchinson Cancer Research Center9, University of Illinois at Chicago10, University of Kentucky11, University of Texas Health Science Center at San Antonio12, Los Angeles Biomedical Research Institute13, University of Alabama at Birmingham14, Cleveland Clinic15, Harvard University16, Johns Hopkins University School of Medicine17, University of Virginia18, Brigham and Women's Hospital19, Mayo Clinic20, University of California, San Francisco21, McGill University22, Brown University23, University of North Carolina at Chapel Hill24, University of Colorado Denver25, Wenzhou Medical College26
TL;DR: The results imply that rare variants, in particular those in regions of low LD, is a major source of the still missing heritability of complex traits and disease.
Abstract: Heritability, the proportion of phenotypic variance explained by genetic factors, can be estimated from pedigree data 1, but such estimates are uninformative with respect to the underlying genetic architecture. Analyses of data from genome-wide association studies (GWAS) on unrelated individuals have shown that for human traits and disease, approximately one-third to two-thirds of heritability is captured by common SNPs 2–5. It is not known whether the remaining heritability is due to the imperfect tagging of causal variants by common SNPs, in particular if the causal variants are rare, or other reasons such as over-estimation of heritability from pedigree data. Here we show that pedigree heritability for height and body mass index (BMI) appears to be fully recovered from whole-genome sequence (WGS) data on 21,620 unrelated individuals of European ancestry. We assigned 47.1 million genetic variants to groups based upon their minor allele frequencies (MAF) and linkage disequilibrium (LD) with variants nearby, and estimated and partitioned variation accordingly. The estimated heritability was 0.79 (SE 0.09) for height and 0.40 (SE 0.09) for BMI, consistent with pedigree estimates. Low-MAF variants in low LD with neighbouring variants were enriched for heritability, to a greater extent for protein altering variants, consistent with negative selection thereon. Cumulatively variants in the MAF range of 0.0001 to 0.1 explained 0.54 (SE 0.05) and 0.51 (SE 0.11) of heritability for height and BMI, respectively. Our results imply that the still missing heritability of complex traits and disease is accounted for by rare variants, in particular those in regions of low LD.
197 citations
TL;DR: The apnea-hypopnea index does not capture the range of sleep apnea as discussed by the authors, which is a poor risk predictor for mortality, since it does not represent the full spectrum of sleep disorders.
Abstract: Rationale: Obstructive sleep apnea is a risk factor for mortality, but its diagnostic metric—the apnea–hypopnea index—is a poor risk predictor. The apnea–hypopnea index does not capture the range o...
116 citations
TL;DR: Investigating the association between irregular sleep patterns, a potential marker for circadian disruption, and metabolic abnormalities found increased variability inSleep duration and timing was associated with higher prevalence and incidence of metabolic abnormalities even after consideration of sleep duration and other lifestyle factors.
Abstract: OBJECTIVE To cross-sectionally and prospectively investigate the association between irregular sleep patterns, a potential marker for circadian disruption, and metabolic abnormalities. RESEARCH DESIGN AND METHODS In the Multi-Ethnic Study of Atherosclerosis, participants completed 7-day actigraphy at exam 5 (2010–2013) and were prospectively followed throughout exam 6 (2016 to 2017). Sleep regularity was quantified by the 7-day SD of actigraphy-assessed sleep duration and sleep onset timing. Metabolic abnormalities were defined by 1 ) the National Cholesterol Education Program Adult Treatment Panel III criteria and 2 ) a data-driven clustering of metabolic factors. RESULTS In the exam 5 cross-sectional analysis adjusted for sociodemographic and lifestyle factors ( n = 2,003), every 1-h increase in the sleep duration SD was associated with 27% (95% CI 1.10, 1.47) higher odds of metabolic syndrome, and every 1-h increase in the sleep timing SD was associated with 23% (95% CI 1.06, 1.42) higher odds. The associations remained significant, with additional adjustment for sleep-related factors including sleep duration. In the prospective analysis ( n = 970), the corresponding fully adjusted odds ratio (OR) (95% CI) was 1.27 (0.97, 1.65) for sleep duration and 1.36 (1.03, 1.80) for sleep timing. Compared with the cluster of few metabolic changes, every 1-h increase in sleep variability was associated with almost doubled odds for the cluster characterized by incidence of multiple metabolic abnormalities (OR 1.97 [95% CI 1.18, 3.30] for sleep duration and OR 2.10 [95% CI 1.25, 3.53] for sleep timing). CONCLUSIONS Increased variability in sleep duration and timing was associated with higher prevalence and incidence of metabolic abnormalities even after considering sleep duration and other lifestyle factors.
103 citations
TL;DR: Treatments could be individualized based on the underlying cause of OSA; patients could better understand which symptoms and outcomes will respond to OSA treatment, and by how much; and researchers could select populations most likely to benefit from specific treatment approaches for OSA.
Abstract: Traditionally, the presence and severity of obstructive sleep apnea (OSA) have been defined by the apnea-hypopnea index (AHI). Continuous positive airway pressure is generally first-line therapy despite low adherence, because it reliably reduces the AHI when used, and the response to other therapies is variable. However, there is growing appreciation that the underlying etiology (i.e., endotype) and clinical manifestation (i.e., phenotype) of OSA in an individual are not well described by the AHI. We define and review the important progress made in understanding and measuring physiological mechanisms (or endotypes) that help define subtypes of OSA and identify the potential use of genetics to further refine disease classification. This more detailed understanding of OSA pathogenesis should influence clinical treatment decisions as well as help inform research priorities and clinical study design. In short, treatments could be individualized on the basis of the underlying cause of OSA; patients could better understand which symptoms and outcomes will respond to OSA treatment and by how much; and researchers could select populations most likely to benefit from specific treatment approaches for OSA.
92 citations
TL;DR: In this article, the authors investigated associations of chronotype and social jet lag with adiposity and cardiometabolic risk in young adolescents, finding that greater evening preference was associated with a higher waist circumference and higher fat mass index.
Abstract: Importance Inadequate sleep duration and quality increase the risk of obesity. Sleep timing, while less studied, is important in adolescents because increasing evening preferences (chronotypes), early school start times, and irregular sleep schedules may cause circadian misalignment. Objective To investigate associations of chronotype and social jet lag with adiposity and cardiometabolic risk in young adolescents. Design, Setting, and Participants Starting in 1999, Project Viva recruited pregnant women from eastern Massachusetts. Mother-child in-person visits occurred throughout childhood. From January 23, 2012, to October 16, 2016, 804 adolescents aged 12 to 17 years completed 5 days or more of wrist actigraphy, questionnaires, and anthropometric measurements. A cross-sectional analysis using these data was conducted from April 31, 2018, to May 1, 2019. Exposures Chronotype, measured via a continuous scale with higher scores indicating greater evening preferences, and social jet lag, measured as the continuous difference in actigraphy sleep midpoint in hours from midnight on weekends vs weekdays, with higher values representing more delayed sleep timing on weekends. Main Outcomes and Measures Adiposity, measured via anthropometry and dual-energy x-ray absorptiometry. For a subset of 479 adolescents with blood samples, cardiometabolic risk scores were computed as the mean of 5 sex- and cohort-specificzscores for waist circumference, systolic blood pressure, inversely scaled high-density lipoprotein cholesterol, and log-transformed triglycerides and homeostatic model of insulin resistance. Results Among the 804 adolescents in the study, 418 were girls and 386 were boys, with a mean (SD) age of 13.2 (0.9) years. In multivariable models adjusted for age, puberty, season, and sociodemographics, associations of chronotype and social jet lag with adiposity varied by sex. For girls, greater evening preference was associated with a 0.58-cm (95% CI, 0.12-1.03 cm;P = .04 for interaction) higher waist circumference and 0.16 kg/m2(95% CI, 0.01-0.31 kg/m2;P = .03 for interaction) higher fat mass index as measured by dual-energy x-ray absorptiometry; each hour of social jet lag was associated with a 1.19-cm (95% CI, 0.04-2.35 cm;P = .21 for interaction) higher waist circumference and 0.45 kg/m2(95% CI, 0.09-0.82 kg/m2;P = .01 for interaction) higher fat mass index as measured by dual-energy x-ray absorptiometry. Associations of social jet lag and evening chronotypes persisted for many measures of adiposity after adjustment for sleep duration and other lifestyle behaviors. By contrast, no associations were observed in boys. There were no associations with the cardiometabolic risk score for either sex, although statistical power was low for this outcome. Conclusions and Relevance Evening chronotypes and social jet lag were associated with greater adiposity in adolescent girls but not adolescent boys. Interventions aimed at improving sleep schedules may be useful for obesity prevention, especially in girls.
91 citations
Brigham and Women's Hospital1, Broad Institute2, Harvard University3, University of Exeter4, Norwegian University of Science and Technology5, University of Bristol6, Oslo University Hospital7, National Institutes of Health8, Helsinki University Central Hospital9, University of Helsinki10, Northeastern University11, University of the West Indies12, University of Manchester13, University of Oxford14, Massachusetts Institute of Technology15, Aston University16, University of Freiburg17, Case Western Reserve University18, University of Michigan19, John Radcliffe Hospital20, Manchester Academic Health Science Centre21, Beth Israel Deaconess Medical Center22
TL;DR: 42 genome-wide significant loci for self-reported daytime sleepiness in GWAS of 452,071 individuals from the UK Biobank that cluster into two biological subtypes of either sleep propensity or sleep fragmentation.
Abstract: 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. A main symptom of chronic insufficient sleep is excessive daytime sleepiness. Here, Wang et al. report 42 genome-wide significant loci for self-reported daytime sleepiness in 452,071 individuals from the UK Biobank that cluster into two biological subtypes of either sleep propensity or sleep fragmentation.
90 citations
TL;DR: This study demonstrated maintenance of solriamfetol efficacy and safety over 6 weeks and common adverse events included headache, dry mouth, nausea, dizziness, and insomnia.
Tuomas O. Kilpeläinen1, Tuomas O. Kilpeläinen2, Amy R. Bentley3, Raymond Noordam4 +248 more•Institutions (84)
TL;DR: In this article, the role of physical activity interactions in the genetic contribution to blood lipid levels was investigated, showing that higher levels of physical activities enhance the HDL cholesterol-increasing effects of the CLASP1, LHX1, and SNTA1 loci and attenuate the LDL cholesterol -increasing effect of the CNTNAP2 locus.
Abstract: Many genetic loci affect circulating lipid levels, but it remains unknown whether lifestyle factors, such as physical activity, modify these genetic effects. To identify lipid loci interacting with physical activity, we performed genome-wide analyses of circulating HDL cholesterol, LDL cholesterol, and triglyceride levels in up to 120,979 individuals of European, African, Asian, Hispanic, and Brazilian ancestry, with follow-up of suggestive associations in an additional 131,012 individuals. We find four loci, in/near CLASP1, LHX1, SNTA1, and CNTNAP2, that are associated with circulating lipid levels through interaction with physical activity; higher levels of physical activity enhance the HDL cholesterol-increasing effects of the CLASP1, LHX1, and SNTA1 loci and attenuate the LDL cholesterol-increasing effect of the CNTNAP2 locus. The CLASP1, LHX1, and SNTA1 regions harbor genes linked to muscle function and lipid metabolism. Our results elucidate the role of physical activity interactions in the genetic contribution to blood lipid levels.
TL;DR: The aim of this study was to establish a longitudinal association between napping and cognitive impairment in older adults and establish a baseline level of trust in adults with a history of napping problems.
Abstract: Introduction Little is known about the longitudinal association between napping and cognitive impairment in older adults. Methods We used wrist actigraphy to measure naps in 2751 community-dwelling older men. Cognition was assessed repeatedly over 12 years, and clinically significant cognitive impairment was determined by physician diagnosis, Alzheimer's medication use or a significant cognitive decline. Results After adjustment for all covariates, men with longer napping duration had greater cognitive decline and higher risk of cognitive impairment. Men who napped for ≥120 min/day (vs. Discussion Napping might be useful as an early marker of cognitive impairment in the elderly, and its cognitive effects may differ by nighttime sleep.
TL;DR: The authors perform genome-wide gene-by-sleep interaction analysis and find 49 previously unreported lipid loci when considering short or long total sleep time, contributing to the understanding of the biological mechanisms involved in sleep-associated adverse lipid profiles.
Abstract: Both short and long sleep are associated with an adverse lipid profile, likely through different biological pathways. To elucidate the biology of sleep-associated adverse lipid profile, we conduct multi-ancestry genome-wide sleep-SNP interaction analyses on three lipid traits (HDL-c, LDL-c and triglycerides). In the total study sample (discovery + replication) of 126,926 individuals from 5 different ancestry groups, when considering either long or short total sleep time interactions in joint analyses, we identify 49 previously unreported lipid loci, and 10 additional previously unreported lipid loci in a restricted sample of European-ancestry cohorts. In addition, we identify new gene-sleep interactions for known lipid loci such as LPL and PCSK9. The previously unreported lipid loci have a modest explained variance in lipid levels: most notable, gene-short-sleep interactions explain 4.25% of the variance in triglyceride level. Collectively, these findings contribute to our understanding of the biological mechanisms involved in sleep-associated adverse lipid profiles.
TL;DR: It is suggested that untreated OSA may contribute to inadequate BP control in blacks and the association of sleep apnea with uncontrolled BP and resistant hypertension in blacks is investigated.
Abstract: Background: Blacks have a high prevalence of hypertension and uncontrolled blood pressure (BP), each of which may be partially explained by untreated sleep apnea. We investigated the association of...
TL;DR: Among African-American participants of the Jackson Heart Sleep Study, self-assessed average sleep duration underestimated objectively-measured sleep while self-ASSessed wake-bed time differences overestimated objectively-Measured sleep.
Abstract: STUDY OBJECTIVES Most epidemiological studies assess sleep duration using questionnaires. Interpreting this information requires understanding the extent to which self-reported habitual sleep reflects objectively assessed sleep duration, particularly among African Americans, who disproportionately experience poor sleep health. METHODS Among African-American participants of the Jackson Heart Sleep Study, we investigated differences in questionnaire-based self-assessed average sleep duration and self-assessed wake-bed time differences compared to actigraphy-based assessments of total sleep time (TST) and average time in bed (TIB). Linear regression models provided estimates of concordance between actigraphy-based and self-reported sleep duration. RESULTS Among 821 adults, self-assessed average sleep duration was lower than self-assessed wake-bed time differences (6.4 ± 1.4 vs. 7.5 ± 1.7 h, p < 0.0001). Mean actigraphy-based TST was 6.6 ± 1.2 h, and actigraphy-based average TIB was 7.6 ± 1.2 h. Self-assessed average sleep duration and actigraphy-based TST were moderately correlated (r = 0.28, p < 0.0001). Self-assessed average sleep duration underestimated actigraphy-based TST by -30.7 min (95% confidence intervals [CI]: -36.5 to -24.9). In contrast, self-assessed wake-bed time differences overestimated actigraphy-based TST by 45.1 min (95% CI: 38.6-51.5). In subgroup analyses, self-assessed average sleep duration underestimated actigraphy-based measures most strongly among participants with insomnia symptoms. CONCLUSIONS Among African Americans, self-assessed average sleep duration underestimated objectively measured sleep while self-assessed wake-bed time differences overestimated objectively measured sleep. Sleep measurement property differences should be considered when investigating disparities in sleep and evaluating their associations with health outcomes.
TL;DR: Moderate-to-more severe OSA is associated with a less healthy dietary profile that is partially explained by reduced N3 sleep, suggesting the opportunity to target sleep quality in interventions aimed at improving cardio-metabolic risk factors in patients with OSA.
Abstract: Rationale
Although short sleep duration has been linked to unhealthy dietary patterns, little is known about the association of obstructive sleep apnea (OSA), a disorder characterized by sleep fragmentation and diet.
TL;DR: In this article, the authors applied machine learning to establish the predictive ability of a multidimensional self-reported sleep domain for all-cause and cardiovascular mortality in older adults relative to other established risk factors and to identify which sleep characteristics are most predictive.
Abstract: BACKGROUND Sleep characteristics related to duration, timing, continuity, and sleepiness are associated with mortality in older adults, but rarely considered in health recommendations. We applied machine learning to: (i) establish the predictive ability of a multidimensional self-reported sleep domain for all-cause and cardiovascular mortality in older adults relative to other established risk factors and (ii) to identify which sleep characteristics are most predictive. METHODS The analytic sample includes N = 8,668 older adults (54% female) aged 65-99 years with self-reported sleep characterization and longitudinal follow-up (≤15.5 years), aggregated from three epidemiological cohorts. We used variable importance (VIMP) metrics from a random survival forest to rank the predictive abilities of 47 measures and domains to which they belong. VIMPs > 0 indicate predictive variables/domains. RESULTS Multidimensional sleep was a significant predictor of all-cause (VIMP [99.9% confidence interval {CI}] = 0.94 [0.60, 1.29]) and cardiovascular (1.98 [1.31, 2.64]) mortality. For all-cause mortality, it ranked below that of the sociodemographic (3.94 [3.02, 4.87]), physical health (3.79 [3.01, 4.57]), and medication (1.33 [0.94, 1.73]) domains but above that of the health behaviors domain (0.22 [0.06, 0.38]). The domains were ranked similarly for cardiovascular mortality. The most predictive individual sleep characteristics across outcomes were time in bed, hours spent napping, and wake-up time. CONCLUSION Multidimensional sleep is an important predictor of mortality that should be considered among other more routinely used predictors. Future research should develop tools for measuring multidimensional sleep-especially those incorporating time in bed, napping, and timing-and test mechanistic pathways through which these characteristics relate to mortality.
TL;DR: Season was associated with large changes in sleep timing, and smaller changes in other sleep and PA measurements, and future health behavioral interventions may benefit by targeting “season-specific” interventions.
Abstract: Background: Understanding variation in physical activity (PA) and sleep is necessary to develop novel intervention strategies targeting adolescents' health behaviors. We examined the extent to which PA and sleep vary by aspects of the physical environment. Participants: We performed a cross-sectional analysis of 669 adolescents in the Project Viva cohort. Methods: We estimated total PA, sleep duration, sleep efficiency, and sleep midpoint timing from wrist accelerometers. We used multivariable linear regression models and generalized estimated equations to assess associations of PA and sleep with season and daily weather conditions obtained from the National Oceanic and Atmospheric Administration archive. Results: Mean age was 12.9 (SD 0.6) years; 51% were female and 68% were white. Mean sleep duration was 466 (SD 42) min per night and total PA was 1,652 (SD 431) counts per min per day. Sleep midpoint time was 41 (95% CI: 27 to 54) min later in summer, 28 (95% CI: -41 to -14) min earlier in spring, and 29 (95% CI: -43 to -15) min earlier in autumn compared to winter. Higher temperature and longer day length both were associated with small reductions of nightly sleep duration. Adolescents were less physically active during winter and on rainy and short sunlight days. There was an inverse U-shaped relationship between PA and mean temperature. Conclusions: Season was associated with large changes in sleep timing, and smaller changes in other sleep and PA measurements. Given the importance of sleep and circadian alignment, future health behavioral interventions may benefit by targeting "season-specific" interventions.
01 Jan 2019
TL;DR: It is found that physical activity modifies the effects of four genetic loci on HDL or LDL cholesterol, and higher levels of physical activity enhance the HDL cholesterol-increasing effects of the CLASP1, LHX1, and SNTA1 loci and attenuate the LDL cholesterol- Increasing effect of the CNTNAP2 locus.
Abstract: Many genetic loci affect circulating lipid levels, but it remains unknown whether lifestyle factors, such as physical activity, modify these genetic effects. To identify lipid loci interacting with physical activity, we performed genome-wide analyses of circulating HDL cholesterol, LDL cholesterol, and triglyceride levels in up to 120,979 individuals of European, African, Asian, Hispanic, and Brazilian ancestry, with follow-up of suggestive associations in an additional 131,012 individuals. We find four loci, in/near CLASP1, LHX1, SNTA1, and CNTNAP2, that are associated with circulating lipid levels through interaction with physical activity; higher levels of physical activity enhance the HDL cholesterol-increasing effects of the CLASP1, LHX1, and SNTA1 loci and attenuate the LDL cholesterol-increasing effect of the CNTNAP2 locus. The CLASP1, LHX1, and SNTA1 regions harbor genes linked to muscle function and lipid metabolism. Our results elucidate the role of physical activity interactions in the genetic contribution to blood lipid levels.GWAS have identified more than 500 genetic loci associated with blood lipid levels. Here, the authors report a genome-wide analysis of interactions between genetic markers and physical activity, and find that physical activity modifies the effects of four genetic loci on HDL or LDL cholesterol.
Harvard University1, Broad Institute2, Case Western Reserve University3, University of Washington4, University of Texas Health Science Center at Houston5, Vanderbilt University6, California Pacific Medical Center7, University of California, Los Angeles8, Baylor College of Medicine9, University of Mississippi10, University of California, San Francisco11, University of California, San Diego12, University of Miami13, Veterans Health Administration14, Northwestern University15, Yeshiva University16, Icahn School of Medicine at Mount Sinai17, United States Department of Veterans Affairs18, University of Pittsburgh19, Johns Hopkins University20, University of North Carolina at Chapel Hill21
TL;DR: Novel associations with variants in the iron/heme metabolism pathway suggest a role for iron in influencing respiratory traits underlying OSA in this first admixture mapping study of OSA.
Abstract: Obstructive sleep apnea (OSA) is a common disorder associated with increased risk of cardiovascular disease and mortality. Its prevalence and severity vary across ancestral background. Although OSA traits are heritable, few genetic associations have been identified. To identify genetic regions associated with OSA and improve statistical power, we applied admixture mapping on three primary OSA traits [the apnea hypopnea index (AHI), overnight average oxyhemoglobin saturation (SaO2) and percentage time SaO2 < 90%] and a secondary trait (respiratory event duration) in a Hispanic/Latino American population study of 11 575 individuals with significant variation in ancestral background. Linear mixed models were performed using previously inferred African, European and Amerindian local genetic ancestry markers. Global African ancestry was associated with a lower AHI, higher SaO2 and shorter event duration. Admixture mapping analysis of the primary OSA traits identified local African ancestry at the chromosomal region 2q37 as genome-wide significantly associated with AHI (P < 5.7 × 10-5), and European and Amerindian ancestries at 18q21 suggestively associated with both AHI and percentage time SaO2 < 90% (P < 10-3). Follow-up joint ancestry-SNP association analyses identified novel variants in ferrochelatase (FECH), significantly associated with AHI and percentage time SaO2 < 90% after adjusting for multiple tests (P < 8 × 10-6). These signals contributed to the admixture mapping associations and were replicated in independent cohorts. In this first admixture mapping study of OSA, novel associations with variants in the iron/heme metabolism pathway suggest a role for iron in influencing respiratory traits underlying OSA.
TL;DR: By validating the PRS for sleep duration and identifying cross-phenotype associations, this work lays the groundwork for future investigations on the intersection between sleep, genetics, clinical measures, and diseases using large EMR datasets.
Abstract: STUDY OBJECTIVES We aimed to detect cross-sectional phenotype and polygenic risk score (PRS) associations between sleep duration and prevalent diseases using the Partners Biobank, a hospital-based cohort study linking electronic medical records (EMR) with genetic information. METHODS Disease prevalence was determined from EMR, and sleep duration was self-reported. A PRS for sleep duration was derived using 78 previously associated SNPs from genome-wide association studies (GWAS) for self-reported sleep duration. We tested for associations between (1) self-reported sleep duration and 22 prevalent diseases (n = 30 251), (2) the PRS and self-reported sleep duration (n = 6903), and (3) the PRS and the 22 prevalent diseases (n = 16 033). For observed PRS-disease associations, we tested causality using two-sample Mendelian randomization (MR). RESULTS In the age-, sex-, and race-adjusted model, U-shaped associations were observed for sleep duration and asthma, depression, hypertension, insomnia, obesity, obstructive sleep apnea, and type 2 diabetes, where both short and long sleepers had higher odds for these diseases than normal sleepers (p < 2.27 × 10-3). Next, we confirmed associations between the PRS and longer sleep duration (0.65 ± 0.19 SD minutes per effect allele; p = 7.32 × 10-04). The PRS collectively explained 1.4% of the phenotypic variance in sleep duration. After adjusting for age, sex, genotyping array, and principal components of ancestry, we observed that the PRS was also associated with congestive heart failure (CHF; p = 0.015), obesity (p = 0.019), hypertension (p = 0.039), restless legs syndrome (RLS; p = 0.041), and insomnia (p = 0.049). Associations were maintained following additional adjustment for obesity status, except for hypertension and insomnia. For all diseases, except RLS, carrying a higher genetic burden of the 78 sleep duration-increasing alleles (i.e. higher sleep duration PRS) associated with lower odds for prevalent disease. In MR, we estimated causal associations between genetically defined longer sleep duration with decreased risk of CHF (inverse variance weighted [IVW] OR per minute of sleep [95% CI] = 0.978 [0.961-0.996]; p = 0.019) and hypertension (IVW OR [95% CI] = 0.993 [0.986-1.000]; p = 0.049), and increased risk of RLS (IVW OR [95% CI] = 1.018 [1.000-1.036]; p = 0.045). CONCLUSIONS By validating the PRS for sleep duration and identifying cross-phenotype associations, we lay the groundwork for future investigations on the intersection between sleep, genetics, clinical measures, and diseases using large EMR datasets.
TL;DR: The results suggest that weekly sleep duration variation, possibly leading to circadian misalignment, may be associated with cardiovascular risk in older women.
Abstract: STUDY OBJECTIVES Short sleep duration is associated with increased cardiovascular disease (CVD) risk. However, it is uncertain whether sleep debt, a measure of sleep deficiency during the week compared to the weekend, confers increased cardiovascular risk. Because sleep disturbances increase with age particularly in women, we examined the relationship between sleep debt and ideal cardiovascular health (ICH) in older women. METHODS Sleep debt is defined as the difference between self-reported total weekday and weekend sleep hours of at least 2 hours among women without apparent CVD and cancer participating in the Women's Health Stress Study follow-up cohort of female health professionals (N = 22 082). The ICH consisted of seven health factors and behaviors as defined by the American Heart Association Strategic 2020 goals including body mass index, smoking, physical activity, diet, blood pressure, total cholesterol, and glucose. RESULTS Mean age was 72.1 ± 6.0 years. Compared to women with no sleep debt, women with sleep debt were more likely to be obese and have hypertension (pall < .05). Linear regression models adjusted for age and race/ethnicity revealed that sleep debt was significantly associated with poorer ICH (B = -0.13 [95% CI = -0.18 to -0.08]). The relationship was attenuated but remained significant after adjustment for education, income, depression/anxiety, cumulative stress, and snoring. CONCLUSION Sleep debt was associated with poorer ICH, despite taking into account socioeconomic status and psychosocial factors. These results suggest that weekly sleep duration variation, possibly leading to circadian misalignment, may be associated with cardiovascular risk in older women.
TL;DR: Differences in lipid metabolites may be an important pathogenic pathway linking poor habitual sleep quality and CHD risk after adjusting for age, race/ethnicity, body mass index (BMI) and smoking.
Abstract: BACKGROUND Epidemiologic studies suggest a strong link between poor habitual sleep quality and increased cardiovascular disease risk. However, the underlying mechanisms are not entirely clear. Metabolomic profiling may elucidate systemic differences associated with sleep quality that influence cardiometabolic health. METHODS We explored cross-sectional associations between sleep quality and plasma metabolites in a nested case-control study of coronary heart disease (CHD) in the Women's Health Initiative (WHI; n = 1956) and attempted to replicate the results in an independent sample from the Nurses' Health Study II (NHSII; n = 209). A sleep-quality score (SQS) was derived from self-reported sleep problems asked in both populations. Plasma metabolomics were assayed using LC-MS with 347 known metabolites. General linear regression was used to identify individual metabolites associated with continuous SQS (false-discovery rate <0.05). Using least absolute shrinkage and selection operator (LASSO) algorithms, a metabolite score was created from replicated metabolites and evaluated with CHD risk in the WHI. RESULTS After adjusting for age, race/ethnicity, body mass index (BMI) and smoking, we identified 69 metabolites associated with SQS in the WHI (59 were lipids). Of these, 16 were replicated in NHSII (15 were lipids), including 6 triglycerides (TAGs), 4 phosphatidylethanolamines (PEs), 3 phosphatidylcholines (PCs), 1 diglyceride (DAG), 1 lysophosphatidylcholine and N6-acetyl-L-lysine (a product of histone acetylation). These metabolites were consistently higher among women with poorer sleep quality. The LASSO selection resulted in a nine-metabolite score (TAGs 45: 1, 48: 1, 50: 4; DAG 32: 1; PEs 36: 4, 38: 5; PCs 30: 1, 40: 6; N6-acetyl-L-lysine), which was positively associated with CHD risk (odds ratio per SD increase in the score: 1.16; 95% confidence interval: 1.05, 1.28; p = 0.0003) in the WHI after adjustment for matching factors and conventional CHD risk factors. CONCLUSIONS Differences in lipid metabolites may be an important pathogenic pathway linking poor habitual sleep quality and CHD risk.
Yun Ju Sung1, Lisa de las Fuentes1, Thomas W. Winkler2, Daniel I. Chasman3 +314 more•Institutions (101)
TL;DR: A genome-wide gene-smoking interaction study of mean arterial pressure (MAP) and pulse pressure (PP) in 129 913 individuals in stage 1 and follow-up analysis in 480 178 additional individuals in stages 2 identified 136 loci significantly associated with MAP and/or PP and identified nine new signals near known loci.
Abstract: Elevated blood pressure (BP), a leading cause of global morbidity and mortality, is influenced by both genetic and lifestyle factors. Cigarette smoking is one such lifestyle factor. Across five ancestries, we performed a genome-wide gene-smoking interaction study of mean arterial pressure (MAP) and pulse pressure (PP) in 129 913 individuals in stage 1 and follow-up analysis in 480 178 additional individuals in stage 2. We report here 136 loci significantly associated with MAP and/or PP. Of these, 61 were previously published through main-effect analysis of BP traits, 37 were recently reported by us for systolic BP and/or diastolic BP through gene-smoking interaction analysis and 38 were newly identified (P < 5 × 10-8, false discovery rate < 0.05). We also identified nine new signals near known loci. Of the 136 loci, 8 showed significant interaction with smoking status. They include CSMD1 previously reported for insulin resistance and BP in the spontaneously hypertensive rats. Many of the 38 new loci show biologic plausibility for a role in BP regulation. SLC26A7 encodes a chloride/bicarbonate exchanger expressed in the renal outer medullary collecting duct. AVPR1A is widely expressed, including in vascular smooth muscle cells, kidney, myocardium and brain. FHAD1 is a long non-coding RNA overexpressed in heart failure. TMEM51 was associated with contractile function in cardiomyocytes. CASP9 plays a central role in cardiomyocyte apoptosis. Identified only in African ancestry were 30 novel loci. Our findings highlight the value of multi-ancestry investigations, particularly in studies of interaction with lifestyle factors, where genomic and lifestyle differences may contribute to novel findings.
TL;DR: Results from this study suggest facilitating the linkage between participant-generated mediating factors and strategies for better-designed interventions include making the negative impact of sleep on health more explicit, and improving youth awareness about sleep hygiene.
Harvard University1, Broad Institute2, University of Texas Health Science Center at Houston3, University of Washington4, University of California, San Diego5, Yeshiva University6, Vanderbilt University7, University of North Carolina at Chapel Hill8, California Pacific Medical Center9, Baylor College of Medicine10, University of Chicago11, United States Department of Veterans Affairs12, Sir Charles Gairdner Hospital13, Columbia University14, University of Mississippi15, Flinders University16, University of Pittsburgh17, Johns Hopkins University18, University of Miami19, Northwestern University20, Icahn School of Medicine at Mount Sinai21, University of California, Los Angeles22, Veterans Health Administration23, University of California, San Francisco24, University of Adelaide25, Case Western Reserve University26
TL;DR: The replicated associations with HK1 and IL18R1 suggest that variants in inflammatory pathways, such as the biologically-plausible NLRP3 inflammasome, may contribute to nocturnal hypoxemia.
Abstract: Sleep disordered breathing (SDB)-related overnight hypoxemia is associated with cardiometabolic disease and other comorbidities. Understanding the genetic bases for variations in nocturnal hypoxemia may help understand mechanisms influencing oxygenation and SDB-related mortality. We conducted genome-wide association tests across 10 cohorts and 4 populations to identify genetic variants associated with three correlated measures of overnight oxyhemoglobin saturation: average and minimum oxyhemoglobin saturation during sleep and the percent of sleep with oxyhemoglobin saturation under 90%. The discovery sample consisted of 8,326 individuals. Variants with p < 1 × 10−6 were analyzed in a replication group of 14,410 individuals. We identified 3 significantly associated regions, including 2 regions in multi-ethnic analyses (2q12, 10q22). SNPs in the 2q12 region associated with minimum SpO2 (rs78136548 p = 2.70 × 10−10). SNPs at 10q22 were associated with all three traits including average SpO2 (rs72805692 p = 4.58 × 10−8). SNPs in both regions were associated in over 20,000 individuals and are supported by prior associations or functional evidence. Four additional significant regions were detected in secondary sex-stratified and combined discovery and replication analyses, including a region overlapping Reelin, a known marker of respiratory complex neurons.These are the first genome-wide significant findings reported for oxyhemoglobin saturation during sleep, a phenotype of high clinical interest. Our replicated associations with HK1 and IL18R1 suggest that variants in inflammatory pathways, such as the biologically-plausible NLRP3 inflammasome, may contribute to nocturnal hypoxemia.
TL;DR: Timing of zeitgebers was associated with sleep and rest-activity patterns, including bedtimes, L5 and M10 midpoint, and there was a significant interaction between morning chronotype and first eating episode with rest- activity patterns, with firsteating episode associating with timing of activities only in non-morning type adults.
Abstract: Zeitgebers such as light, eating and physical activity provide input to the circadian clock. Chronic circadian misalignment is associated with significant adverse health effects. An improved unders...
TL;DR: Findings suggest that sleep apnea and sleep fragmentation are associated with accelerated biological aging.
Abstract: Study objectives Sleep disturbances and sleep apnea are associated with increased vulnerability to age-related disease, altering molecular pathways affecting biological aging. Telomere length captures one component of biological aging. We evaluated whether objectively assessed sleep and sleep apnea relate to leukocyte telomere length (LTL) in the Multi-Ethnic Study of Atherosclerosis (MESA). Methods Men and women aged 44-84 years (n = 672) from the MESA Stress and MESA Sleep studies underwent polysomnography and 7 day actigraphy (at Exam 5) and assessment of LTL (at baseline [Exam 1] and about 10 years later [Exam 5]). Results General linear models adjusting for age, sex, race/ethnicity, BMI, physical activity, and smoking found that severe obstructive sleep apnea (OSA; apnea-hypopnea index > 30) was cross-sectionally associated with shorter LTL (p = 0.007). Modest associations of shorter LTL with less rapid eye movement sleep, more stage 1 sleep, wake after sleep onset >30 min, and long sleep duration were found, but these effects were diminished after adjusting for lifestyle and OSA. Exploratory analyses found that higher arousal index at Exam 5 was associated with greater LTL decline over the prior 10 years (p = 0.004). Conclusions OSA was associated with shorter LTL. Individuals with high-arousal frequency had greater leukocyte telomere attrition over the prior decade. These findings suggest that sleep apnea and sleep fragmentation are associated with accelerated biological aging.