Genome-wide physical activity interactions in adiposity : a meta-analysis of 200 452 adults

Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genomewide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discover

The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study

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 \u3e50y, women ≤50y, women \u3e50y) 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\u3c5%) age-specific effects, of which 11 had larger effects in younger (\u3c50y) 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

Shared genetic risk between anorexia nervosa and cardiovascular disease events: Evidence from genome‐wide association studies

OBJECTIVE: Cardiovascular complications occur in up to 80% of patients with anorexia nervosa (AN), yet the underlying mechanisms warrant further investigation. We assessed the genetic correlation (rg ) between AN and cardiovascular disease (CVD) events to inform whether elevated cardiovascular risk among individuals with AN is due to shared genetic effects. METHOD: We used genome-wide association study summary statistics for AN (N = 72,517), AN with binge eating (N = 12,630), AN without binge eating (N = 12,516), and six CVD events (N = 390,142 to 977,323). We calculated the rg s via linkage disequilibrium score regression and corrected for multiple testing using false discovery rate. RESULTS: Significant rg s emerged between AN with heart failure (rg  = -0.11, SE = 0.05, q = .04) and myocardial infarction (rg  = -0.10, SE = 0.03, q = .01). AN with binge eating had a significant rg with myocardial infarction (rg  = -0.15, SE = 0.06, q = .02). No significant rg emerged between AN without binge eating and any CVD event. DISCUSSION: Some loci affect the liability to AN and CVD in opposite directions and the shared genetic effects may not be consistent across all CVD events. Our results provide further evidence suggesting that the elevated cardiovascular risk in AN may not be due to shared genetic underpinnings, but more likely a downstream consequence of the disease

A Powerful Statistical Framework for Generalization Testing in GWAS, with Application to the HCHS/SOL

In GWAS, “generalization” is the replication of genotype-phenotype association in a population with different ancestry than the population in which it was first identified. The standard for reporting findings from a GWAS requires a two-stage design, in which discovered associations are replicated in an independent follow-up study. Current practices for declaring generalizations rely on testing associations while controlling the Family Wise Error Rate (FWER) in the discovery study, then separately controlling error measures in the follow-up study. While this approach limits false generalizations, we show that it does not guarantee control over the FWER or False Discovery Rate (FDR) of the generalization null hypotheses. In addition, it fails to leverage the two-stage design to increase power for detecting generalized associations. We develop a formal statistical framework for quantifying the evidence of generalization that accounts for the (in)consistency between the directions of associations in the discovery and follow-up studies. We develop the directional generalization FWER (FWERg) and FDR (FDRg) controlling r-values, which are used to declare associations as generalized. This framework extends to generalization testing when applied to a published list of SNP-trait associations. We show that our framework accommodates various SNP selection rules for generalization testing based on p-values in the discovery study, and still control FWERg or FDRg. A key finding is that it is often beneficial to use a more lenient p-value threshold then the genome-wide significance threshold. For instance, in a GWAS of Total Cholesterol (TC) in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), when testing all SNPs with p-values\u3c 5 × 10−8 (15 genomic regions) for generalization in a large GWAS of whites, we generalized SNPs from 15 regions. But when testing all SNPs with p-values\u3c 6.6×10−5 (89 regions), we generalized SNPs from 27 regions

Ancestral diversity improves discovery and fine-mapping of genetic loci for anthropometric traits-The Hispanic/Latino Anthropometry Consortium

Hispanic/Latinos have been underrepresented in genome-wide association studies (GWAS) for anthropometric traits despite their notable anthropometric variability, ancestry proportions, and high burden of growth stunting and overweight/obesity. To address this knowledge gap, we analyzed densely imputed genetic data in a sample of Hispanic/Latino adults to identify and fine-map genetic variants associated with body mass index (BMI), height, and BMI-adjusted waist-to-hip ratio (WHRadjBMI). We conducted a GWAS of 18 studies/consortia as part of the Hispanic/Latino Anthropometry (HISLA) Consortium (stage 1, n = 59,771) and generalized our findings in 9 additional studies (stage 2, n = 10,538). We conducted a trans-ancestral GWAS with summary statistics from HISLA stage 1 and existing consortia of European and African ancestries. In our HISLA stage 1 + 2 analyses, we discovered one BMI locus, as well as two BMI signals and another height signal each within established anthropometric loci. In our trans-ancestral meta-analysis, we discovered three BMI loci, one height locus, and one WHRadjBMI locus. We also identified 3 secondary signals for BMI, 28 for height, and 2 for WHRadjBMI in established loci. We show that 336 known BMI, 1,177 known height, and 143 known WHRadjBMI (combined) SNPs demonstrated suggestive transferability (nominal significance and effect estimate directional consistency) in Hispanic/Latino adults. Of these, 36 BMI, 124 height, and 11 WHRadjBMI SNPs were significant after trait-specific Bonferroni correction. Trans-ancestral meta-analysis of the three ancestries showed a small-to-moderate impact of uncorrected population stratification on the resulting effect size estimates. Our findings demonstrate that future studies may also benefit from leveraging diverse ancestries and differences in linkage disequilibrium patterns to discover novel loci and additional signals with less residual population stratification

Genetic Epidemiology of Body Mass Index and Body Mass Change From Adolescence to Young Adulthood

The complex interplay between genes and environment affecting body mass gain over lifecycle periods of risk is not well understood. We use longitudinal sibling cohort data to examine the role of shared household environment, additive genetic, and shared genetic effects on Body Mass Index (BMI) and BMI change. In the National Longitudinal Study of Adolescent Health, siblings and twin pairs sharing households for ≥10 years as adolescents (N=5524; mean=16.5±1.7 years) were followed into young adulthood (N = 4368; mean=22.4±1.8 years). Using a variance component approach, we quantified genetic and household effects on BMI in siblings and non-siblings sharing household environments over time. Adjusting for race, age, sex, and age by sex interaction, we detected a heritability of 0.43±0.05 for BMI change. Significant household effects were noted during the young adulthood time period only (0.11±0.06). We find evidence for shared genetic effects between BMI and BMI change during adolescence [Genetic Correlation (ρG)=0.61±0.03] and young adulthood (ρG=0.23±0.06). Our findings support a complex etiology of BMI and BMI change

Sex-influenced association of nonalcoholic fatty liver disease with coronary heart disease

This study investigated whether nonalcoholic fatty liver disease (NAFLD) predicts prevalent coronary heart disease (CHD)

Characterization of the contribution of shared environmental and genetic factors to metabolic syndrome methylation heritability and familial correlations

Abstract Background Transgenerational epigenetic inheritance has been posited as a possible contributor to the observed heritability of metabolic syndrome (MetS). Yet the extent to which estimates of epigenetic inheritance for DNA methylation sites are inflated by environmental and genetic covariance within families is still unclear. We applied current methods to quantify the environmental and genetic contributors to the observed heritability and familial correlations of four previously associated MetS methylation sites at three genes (CPT1A, SOCS3 and ABCG1) using real data made available through the GAW20. Results Our findings support the role of both shared environment and genetic variation in explaining the heritability of MetS and the four MetS cytosine-phosphate-guanine (CpG) sites, although the resulting heritability estimates were indistinguishable from one another. Familial correlations by type of relative pair generally followed our expectation based on relatedness, but in the case of sister and parent pairs we observed nonsignificant trends toward greater correlation than expected, as would be consistent with the role of shared environmental factors in the inflation of our estimated correlations. Conclusions Our work provides an interesting and flexible statistical framework for testing models of epigenetic inheritance in the context of human family studies. Future work should endeavor to replicate our findings and advance these methods to more robustly describe epigenetic inheritance patterns in human populations

Sex and race differences in the prevalence of fatty liver disease as measured by computed tomography liver attenuation in European American and African American participants of the NHLBI family heart study

Liver attenuation (LA) (Hounsfield Units, HU) by computed tomography (CT) is a validated quantitative measure inversely related to liver fat burden. We examined race-and sex- differences on the distribution of LA (one of the first stages of fatty liver disease) and the predictors of these mean differences in European American (EA) and African American (AA) participants of the Family Heart Study. A total of 1242 (1064 EA, 178 AA) and 1477 (1150 EA, 327 AA) men and women, respectively, underwent CT examination from which LA and abdominal adipose volume were measured. LA (adjusted for phantom and field center) was the dependent variable in linear mixed models (to control for family relatedness) that tested for mean differences by race and by sex. Independent explanatory variables included age, body mass index, visceral adipose tissue volume, subcutaneous adipose tissue volume, alcohol consumption, TG, HDL-C, and insulin resistance. Mean LA varied significantly by sex, [(men) 57.76 ±10.03 HU and (women) 60.03 ±10.91 HU, p=0.0002], but not by race. Higher LA was associated with older age, while higher values of VAT, triglycerides, and insulin resistance were associated with lower LA in men and women. In contrast, alcohol consumption and BMI were associated with lower LA only among men. In analyses stratified by race LA was associated with alcohol consumption, VAT, and insulin resistance in both EA and AA and with age, BMI, and HDL-C in EA participants only. Our study findings confirm that there are important sex differences and race by sex interaction effects on the distribution of liver attenuation, the prevalence of FLD, and on the influence of metabolic risk factors on LA and FLD

Assessing efficiency of fine-mapping obesity-associated variants through leveraging ancestry architecture and functional annotation using PAGE and UKBB cohorts.

Inadequate representation of non-European ancestry populations in genome-wide association studies (GWAS) has limited opportunities to isolate functional variants. Fine-mapping in multi-ancestry populations should improve the efficiency of prioritizing variants for functional interrogation. To evaluate this hypothesis, we leveraged ancestry architecture to perform comparative GWAS and fine-mapping of obesity-related phenotypes in European ancestry populations from the UK Biobank (UKBB) and multi-ancestry samples from the Population Architecture for Genetic Epidemiology (PAGE) consortium with comparable sample sizes. In the investigated regions with genome-wide significant associations for obesity-related traits, fine-mapping in our ancestrally diverse sample led to 95% and 99% credible sets (CS) with fewer variants than in the European ancestry sample. Lead fine-mapped variants in PAGE regions had higher average coding scores, and higher average posterior probabilities for causality compared to UKBB. Importantly, 99% CS in PAGE loci contained strong expression quantitative trait loci (eQTLs) in adipose tissues or harbored more variants in tighter linkage disequilibrium (LD) with eQTLs. Leveraging ancestrally diverse populations with heterogeneous ancestry architectures, coupled with functional annotation, increased fine-mapping efficiency and performance, and reduced the set of candidate variants for consideration for future functional studies. Significant overlap in genetic causal variants across populations suggests generalizability of genetic mechanisms underpinning obesity-related traits across populations