Highlights d Blood cell traits differ by ancestry and are subject to selective pressure d We assessed 15 blood cell traits in 746,667 participants from 5 global populations d We identified more than 5,500 associations, including 100 associations not found in Europeans d These analyses improved risk prediction and identified potential causal variants

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.

Epidemiological studies of obesity, Type-2 diabetes (T2D), cardiovascular diseases and several common cancers have revealed an increased risk in Native Hawaiians compared to European- or Asian-Americans living in the Hawaiian islands. However, there remains a gap in our understanding of the genetic factors that affect the health of Native Hawaiians. To fill this gap, we studied the genetic risk factors at both the chromosomal and sub-chromosomal scales using genome-wide SNP array data on ~4,000 Native Hawaiians from the Multiethnic Cohort. We estimated the genomic proportion of Native Hawaiian ancestry (“global ancestry,” which we presumed to be Polynesian in origin), as well as this ancestral component along each chromosome (“local ancestry”) and tested their respective association with binary and quantitative cardiometabolic traits. After attempting to adjust for non-genetic covariates evaluated through questionnaires, we found that per 10% increase in global Polynesian genetic ancestry, there is a respective 8.6%, and 11.0% increase in the odds of being diabetic (P = 1.65×10−4) and having heart failure (P = 2.18×10−4), as well as a 0.059 s.d. increase in BMI (P = 1.04×10−10). When testing the association of local Polynesian ancestry with risk of disease or biomarkers, we identified a chr6 region associated with T2D. This association was driven by an uniquely prevalent variant in Polynesian ancestry individuals. However, we could not replicate this finding in an independent Polynesian cohort from Samoa due to the small sample size of the replication cohort. In conclusion, we showed that Polynesian ancestry, which likely capture both genetic and lifestyle risk factors, is associated with an increased risk of obesity, Type-2 diabetes, and heart failure, and that larger cohorts of Polynesian ancestry individuals will be needed to replicate the putative association on chr6 with T2D.

No abstract

Background - To assess the genetic architecture of hypertrophic cardiomyopathy (HCM) in patients of predominantly Chinese ancestry. Methods - We sequenced HCM disease genes in Singaporean patients (n=224) and Singaporean controls (n=3,634), compared findings with additional populations and Caucasian HCM cohorts (n=6,179) and performed in vitro functional studies. Results - Singaporean HCM patients had significantly fewer confidently interpreted HCM disease variants (Pathogenic (P)/Likely Pathogenic (LP):18%, p<0.0001) but an excess of variants of unknown significance (exVUS: 24%, p<0.0001), as compared to Caucasians (P/LP: 31%, exVUS: 7%). Two missense variants in thin filament encoding genes were commonly seen in Singaporean HCM ( TNNI3 :p.R79C, disease allele frequency (AF)=0.018; TNNT2 :p.R286H, disease AF=0.022) and are enriched in Singaporean HCM when compared with Asian controls ( TNNI3 :p.R79C, Singaporean controls AF=0.0055, p=0.0057, gnomAD-East Asian (gnomAD-EA) AF=0.0062, p=0.0086; TNNT2 :p.R286H, Singaporean controls AF=0.0017, p<0.0001, gnomAD-EA AF=0.0009, p<0.0001). Both these variants have conflicting annotations in ClinVar and are of low penetrance ( TNNI3 :p.R79C, 0.7%; TNNT2 :p.R286H, 2.7%) but are predicted to be deleterious by computational tools. In population controls, TNNI3 :p.R79C carriers had significantly thicker left ventricular walls compared to non-carriers while its etiological fraction is limited (0.70, 95% CI: 0.35-0.86) and thus TNNI3 :p.R79C is considered a VUS. Mutant TNNT2 :p.R286H iPSC-CMs show hypercontractility, increased metabolic requirements and cellular hypertrophy and the etiological fraction (0.93, 95% CI: 0.83-0.97) support the likely pathogenicity of TNNT2 :p.R286H. Conclusions - As compared to Caucasians, Chinese HCM patients commonly have low penetrance risk alleles in TNNT2 or TNNI3 but exhibit few clinically actionable HCM variants overall. This highlights the need for greater study of HCM genetics in non-Caucasian populations.