Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, we conducted genome-wide association meta-analyses of waist and hip circumference-related traits in up to 224,459 individuals. We identified 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (WHRadjBMI) and an additional 19 loci newly associated with related waist and hip circumference measures (P<5×10−8). Twenty of the 49 WHRadjBMI loci showed significant sexual dimorphism, 19 of which displayed a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation, and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms.

Over the past 50 years, the incidence of heart failure has declined among women but not among men, whereas survival after the onset of heart failure has improved in both sexes. Factors contributing to these trends need further clarification.

Background-Visceral adipose tissue (VAT) compartments may confer increased metabolic risk. The incremental utility of measuring both visceral and subcutaneous abdominal adipose tissue (SAT) in association with metabolic risk factors and underlying heritability has not been well described in a population-based setting. Methods and Results-Participants (nϭ3001) were drawn from the Framingham Heart Study (48% women; mean age, 50 years), were free of clinical cardiovascular disease, and underwent multidetector computed tomography assessment of SAT and VAT volumes between 2002 and. Metabolic risk factors were examined in relation to increments of SAT and VAT after multivariable adjustment. Heritability was calculated using variance-components analysis. Among both women and men, SAT and VAT were significantly associated with blood pressure, fasting plasma glucose, triglycerides, and high-density lipoprotein cholesterol and with increased odds of hypertension, impaired fasting glucose, diabetes mellitus, and metabolic syndrome (P range Ͻ0.01). In women, relations between VAT and risk factors were consistently stronger than in men. However, VAT was more strongly correlated with most metabolic risk factors than was SAT. For example, among women and men, both SAT and VAT were associated with increased odds of metabolic syndrome. In women, the odds ratio (OR) of metabolic syndrome per 1-standard deviation increase in VAT (OR, 4.7) was stronger than that for SAT (OR, 3.0; P for difference between SAT and VAT Ͻ0.0001); similar differences were noted for men (OR for VAT, 4.2; OR for SAT, 2.5). Furthermore, VAT but not SAT contributed significantly to risk factor variation after adjustment for body mass index and waist circumference (P Յ0.01). Among overweight and obese individuals, the prevalence of hypertension, impaired fasting glucose, and metabolic syndrome increased linearly and significantly across increasing VAT quartiles. Heritability values for SAT and VAT were 57% and 36%, respectively. Conclusions-Although both SAT and VAT are correlated with metabolic risk factors, VAT remains more strongly associated with an adverse metabolic risk profile even after accounting for standard anthropometric indexes. Our findings are consistent with the hypothesized role of visceral fat as a unique, pathogenic fat depot. Measurement of VAT may provide a more complete understanding of metabolic risk associated with variation in fat distribution. (Circulation.

Background-Atrial fibrillation (AF) and congestive heart failure (CHF) frequently occur together, but there is limited information regarding their temporal relations and the combined influence of these conditions on mortality. Methods and Results-We studied participants in the Framingham Study with new-onset AF or CHF. Multivariable Cox proportional hazards models with time-dependent variables were used to evaluate whether mortality after AF or CHF was affected by the occurrence and timing of the other condition. Hazard ratios (HRs) were adjusted for time period and cardiovascular risk factors. During the study period, 1470 participants developed AF, CHF, or both. Among 382 individuals with both conditions, 38% had AF first, 41% had CHF first, and 21% had both diagnosed on the same day. The incidence of CHF among AF subjects was 33 per 1000 person-years, and the incidence of AF among CHF subjects was 54 per 1000 person-years. In AF subjects, the subsequent development of CHF was associated with increased mortality (men: HR 2.7; 95% CI, 1.9 to 3.7; women: HR 3.1; 95% CI, 2.2 to 4.2). Similarly, in CHF subjects, later development of AF was associated with increased mortality (men: HR 1.6; 95% CI, 1.2 to 2.1; women: HR 2.7, 95% CI, 2.0 to 3.6). Preexisting CHF adversely affected survival in individuals with AF, but preexisting AF was not associated with adverse survival in those with CHF. Conclusions-Individuals with AF or CHF who subsequently develop the other condition have a poor prognosis.Additional studies addressing the pathogenesis, prevention, and optimal management of the joint occurrence of AF and

BackgroundDNA methylation levels change with age. Recent studies have identified biomarkers of chronological age based on DNA methylation levels. It is not yet known whether DNA methylation age captures aspects of biological age.ResultsHere we test whether differences between people’s chronological ages and estimated ages, DNA methylation age, predict all-cause mortality in later life. The difference between DNA methylation age and chronological age (Δage) was calculated in four longitudinal cohorts of older people. Meta-analysis of proportional hazards models from the four cohorts was used to determine the association between Δage and mortality. A 5-year higher Δage is associated with a 21% higher mortality risk, adjusting for age and sex. After further adjustments for childhood IQ, education, social class, hypertension, diabetes, cardiovascular disease, and APOE e4 status, there is a 16% increased mortality risk for those with a 5-year higher Δage. A pedigree-based heritability analysis of Δage was conducted in a separate cohort. The heritability of Δage was 0.43.ConclusionsDNA methylation-derived measures of accelerated aging are heritable traits that predict mortality independently of health status, lifestyle factors, and known genetic factors.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-015-0584-6) contains supplementary material, which is available to authorized users.

Estimates of biological age based on DNA methylation patterns, often referred to as “epigenetic age”, “DNAm age”, have been shown to be robust biomarkers of age in humans. We previously demonstrated that independent of chronological age, epigenetic age assessed in blood predicted all-cause mortality in four human cohorts. Here, we expanded our original observation to 13 different cohorts for a total sample size of 13,089 individuals, including three racial/ethnic groups. In addition, we examined whether incorporating information on blood cell composition into the epigenetic age metrics improves their predictive power for mortality. All considered measures of epigenetic age acceleration were predictive of mortality (p≤8.2×10−9), independent of chronological age, even after adjusting for additional risk factors (p<5.4×10−4), and within the racial/ethnic groups that we examined (non-Hispanic whites, Hispanics, African Americans). Epigenetic age estimates that incorporated information on blood cell composition led to the smallest p-values for time to death (p=7.5×10−43). Overall, this study a) strengthens the evidence that epigenetic age predicts all-cause mortality above and beyond chronological age and traditional risk factors, and b) demonstrates that epigenetic age estimates that incorporate information on blood cell counts lead to highly significant associations with all-cause mortality.

Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n=321,223) and offspring birth weight (n=230,069 mothers), we identified 190 independent association signals (129 novel). We used structural equation modelling to decompose the contributions of direct fetal and indirect maternal genetic effects, and then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of those alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight-blood pressure association is attributable to genetic effects, and not to intrauterine programming.

Summary paragraphThe 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 <1% and 46% are singletons. These rare variants provide insights into mutational processes and recent human evolutionary history. 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. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and extends the reach of nearly all genome-wide association studies to include variants down to ~0.01% in frequency.