Genome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age- and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of European descent) with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT) Consortium. Each study tested the association of up to ~2.8M SNPs with BMI and WHRadjBMI in four strata (men ≤50y, men >50y, women ≤50y, women >50y) and summary statistics were combined in stratum-specific meta-analyses. We then screened for variants that showed age-specific effects (G x AGE), sex-specific effects (G x SEX) or age-specific effects that differed between men and women (G x AGE x SEX). For BMI, we identified 15 loci (11 previously established for main effects, four novel) that showed significant (FDR<5%) age-specific effects, of which 11 had larger effects in younger (<50y) than in older adults (≥50y). No sex-dependent effects were identified for BMI. For WHRadjBMI, we identified 44 loci (27 previously established for main effects, 17 novel) with sex-specific effects, of which 28 showed larger effects in women than in men, five showed larger effects in men than in women, and 11 showed opposite effects between sexes. No age-dependent effects were identified for WHRadjBMI. This is the first genome-wide interaction meta-analysis to report convincing evidence of age-dependent genetic effects on BMI. In addition, we confirm the sex-specificity of genetic effects on WHRadjBMI. These results may provide further insights into the biology that underlies weight change with age or the sexually dimorphism of body shape.

SummaryLarge-scale collections of induced pluripotent stem cells (iPSCs) could serve as powerful model systems for examining how genetic variation affects biology and disease. Here we describe the iPSCORE resource: a collection of systematically derived and characterized iPSC lines from 222 ethnically diverse individuals that allows for both familial and association-based genetic studies. iPSCORE lines are pluripotent with high genomic integrity (no or low numbers of somatic copy-number variants) as determined using high-throughput RNA-sequencing and genotyping arrays, respectively. Using iPSCs from a family of individuals, we show that iPSC-derived cardiomyocytes demonstrate gene expression patterns that cluster by genetic background, and can be used to examine variants associated with physiological and disease phenotypes. The iPSCORE collection contains representative individuals for risk and non-risk alleles for 95% of SNPs associated with human phenotypes through genome-wide association studies. Our study demonstrates the utility of iPSCORE for examining how genetic variants influence molecular and physiological traits in iPSCs and derived cell lines.

Elevated resting heart rate is associated with greater risk of cardiovascular disease and mortality. In a 2-stage meta-analysis of genome-wide association studies in up to 181,171 individuals, we identified 14 new loci associated with heart rate and confirmed associations with all 7 previously established loci. Experimental downregulation of gene expression in Drosophila melanogaster and Danio rerio identified 20 genes at 11 loci that are relevant for heart rate regulation and highlight a role for genes involved in signal transmission, embryonic cardiac development and the pathophysiology of dilated cardiomyopathy, congenital heart failure and/or sudden cardiac death. In addition, genetic susceptibility to increased heart rate is associated with altered cardiac conduction and reduced risk of sick sinus syndrome, and both heart rate–increasing and heart rate–decreasing variants associate with risk of atrial fibrillation. Our findings provide fresh insights into the mechanisms regulating heart rate and identify new therapeutic targets.

Summary In this study, we used whole genome sequencing and gene expression profiling of 215 human induced pluripotent stem cell (iPSC) lines from different donors to identify genetic variants associated with RNA expression for 5,746 genes. We were able to predict causal variants for these expression quantitative trait loci (eQTLs) that disrupt transcription factor binding and validated a subset of them experimentally. We also identified copy number variant (CNV) eQTLs, including some that appear to affect gene expression by altering the copy number of intergenic regulatory regions. In addition, we were able to identify effects on gene expression of rare genic CNVs and regulatory single nucleotide variants, and found that reactivation of gene expression on the X chromosome depends on gene chromosomal position. Our work highlights the value of iPSCs for genetic association analyses and provides a unique resource for investigating the genetic regulation of gene expression in pluripotent cells.

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While genetic variation at chromatin loops is relevant for human disease, the relationships between contact propensity (the probability that loci at loops physically interact), genetics, and gene regulation are unclear. We quantitatively interrogate these relationships by comparing Hi-C and molecular phenotype data across cell types and haplotypes. While chromatin loops consistently form across different cell types, they have subtle quantitative differences in contact frequency that are associated with larger changes in gene expression and H3K27ac. For the vast majority of loci with quantitative differences in contact frequency across haplotypes, the changes in magnitude are smaller than those across cell types; however, the proportional relationships between contact propensity, gene expression, and H3K27ac are consistent. These findings suggest that subtle changes in contact propensity have a biologically meaningful role in gene regulation and could be a mechanism by which regulatory genetic variants in loop anchors mediate effects on expression.

Abstract-Essential hypertension is a multifactorial disorder and is the main risk factor for renal and cardiovascular complications. The research on the genetics of hypertension has been frustrated by the small predictive value of the discovered genetic variants. The HYPERGENES Project investigated associations between genetic variants and essential hypertension pursuing a 2-stage study by recruiting cases and controls from extensively characterized cohorts recruited over many years ). A meta-analysis, using other in silico/de novo genotyping data for a total of 21 714 subjects, resulted in an overall odds ratio of 1.34 (95% CI: 1.25-1.44; Pϭ1.032 ⅐ 10 Ϫ14). The quantitative analysis on a population-based sample revealed an effect size of 1.91 (95% CI: 0.16 -3.66) for systolic and 1.40 (95% CI: 0.25-2.55) for diastolic blood pressure. We identified in silico a potential binding site for ETS transcription factors directly next to rs3918226, suggesting a potential modulation of endothelial NO synthase expression. Biological evidence links endothelial NO synthase with hypertension, because it is a critical mediator of cardiovascular homeostasis and blood pressure control via vascular tone regulation. This finding supports the hypothesis that there may be a causal genetic variation at this locus. (Hypertension. 2012;59:248-255.) • Online Data Supplement Key Words: genetic epidemiology Ⅲ risk factors Ⅲ genetics association studies Ⅲ NO Ⅲ essential hypertension E ssential hypertension (EH) is a clinical condition affecting a large proportion (25% to 30%) of the adult population and is a major risk factor for cardiovascular and renal diseases. 1,2 It is a complex trait influenced by multiple susceptibility genes, environmental, and lifestyle factors and their interactions. 3 In the last years, huge efforts have been performed in recruiting and genotyping tens of thousands of individuals and meta-analyzing dozens of cross-sectional, population-based studies. In spite of this, the research on the genetics of EH has been frustrated by the small predictive value of the discovered genetic variants and by the fact that these variants explain a small proportion of the phenotypic variation. 4 -13 EH is a late-onset disease and, therefore, the small discovered effect sizes could in part be because of the effect of misclassification, sample selection bias, and inappropriate phenotyping of cases and controls. 9,14,15 The selection of cases and controls may have important effects on the results, because misclassification bias can lead to loss of power. For common traits, such as EH, this bias can be remedied by defining more stringent selection criteria, by recruiting hypernormal controls and adopting a more stringent case definition. 14,15 The HYPERGENES Project pursued a 2-stage study to investigate novel genetic determinants of EH. Cases and controls were recruited from extensively characterized cohorts over many years in different European regions using standardized clinical ascertainment. Particular care was devoted to c...

To understand the mutational burden of human induced pluripotent stem cells (iPSCs), we sequenced genomes of 18 fibroblast-derived iPSC lines and identified different classes of somatic mutations based on structure, origin, and frequency. Copy-number alterations affected 295 kb in each sample and strongly impacted gene expression. UV-damage mutations were present in ∼45% of the iPSCs and accounted for most of the observed heterogeneity in mutation rates across lines. Subclonal mutations (not present in all iPSCs within a line) composed 10% of point mutations and, compared with clonal variants, showed an enrichment in active promoters and increased association with altered gene expression. Our study shows that, by combining WGS, transcriptome, and epigenome data, we can understand the mutational burden of each iPSC line on an individual basis and suggests that this information could be used to prioritize iPSC lines for models of specific human diseases and/or transplantation therapy.