ABSTRACT
[This corrects the article DOI: 10.1371/journal.pgen.1006528.].
ABSTRACT
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 genome-wide 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 discovery.
Subject(s)
Adiposity/genetics , Alpha-Ketoglutarate-Dependent Dioxygenase FTO/genetics , Exercise , Obesity/genetics , Adiposity/physiology , Body Mass Index , Epigenomics , Female , Genetic Predisposition to Disease , Genome-Wide Association Study , Genotype , Humans , Male , Obesity/physiopathology , Waist Circumference , Waist-Hip RatioABSTRACT
[This corrects the article DOI: 10.1371/journal.pgen.1005378.].
ABSTRACT
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.
Subject(s)
Body Mass Index , Body Size/genetics , Genetic Predisposition to Disease , Genome-Wide Association Study , Adult , Age Factors , Aged , Chromosome Mapping , Female , Humans , Male , Middle Aged , Polymorphism, Single Nucleotide , Sex Characteristics , Waist-Hip Ratio , White PeopleABSTRACT
The accumulation of excess fat in the liver (hepatic steatosis) in the absence of heavy alcohol consumption causes nonalcoholic fatty liver disease (NAFLD), which has become a global epidemic. Identifying metabolic risk factors that interact with the genetic risk of NAFLD is important for reducing disease burden. We tested whether serum glucose, insulin, insulin resistance, triglyceride (TG), low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, body mass index (BMI), and waist-to-hip ratio adjusted for BMI interact with genetic variants in or near the patatin-like phospholipase domain containing 3 (PNPLA3) gene, the glucokinase regulatory protein (GCKR) gene, the neurocan/transmembrane 6 superfamily member 2 (NCAN/TM6SF2) gene, and the lysophospholipase-like 1 (LYPLAL1) gene to exacerbate hepatic steatosis, estimated by liver attenuation. We performed association analyses in 10 population-based cohorts separately and then meta-analyzed results in up to 14,751 individuals (11,870 of European ancestry and 2,881 of African ancestry). We found that PNPLA3-rs738409 significantly interacted with insulin, insulin resistance, BMI, glucose, and TG to increase hepatic steatosis in nondiabetic individuals carrying the G allele. Additionally, GCKR-rs780094 significantly interacted with insulin, insulin resistance, and TG. Conditional analyses using the two largest European ancestry cohorts in the study showed that insulin levels accounted for most of the interaction of PNPLA3-rs738409 with BMI, glucose, and TG in nondiabetic individuals. Insulin, PNPLA3-rs738409, and their interaction accounted for at least 8% of the variance in hepatic steatosis in these two cohorts. Conclusion: Insulin resistance, either directly or through the resultant elevated insulin levels, more than other metabolic traits, appears to amplify the PNPLA3-rs738409-G genetic risk for hepatic steatosis. Improving insulin resistance in nondiabetic individuals carrying PNPLA3-rs738409-G may preferentially decrease hepatic steatosis.
ABSTRACT
Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution.
Subject(s)
Genetic Predisposition to Disease/genetics , Genome-Wide Association Study/methods , Obesity/genetics , Quantitative Trait Loci/genetics , Smoking/genetics , Adiposity/genetics , Adult , Body Fat Distribution , Body Mass Index , Epistasis, Genetic , Humans , Phenotype , Polymorphism, Single Nucleotide , Waist Circumference/genetics , Waist-Hip RatioABSTRACT
Genetic technologies are being implemented in areas that extend beyond the field of medicine to address social and legal problems. An emerging example is the implementation of genetic testing in the family petitioning process in immigration policy. This use of genetic testing offers the potential benefits of reducing immigration fraud and making the process more efficient and accessible for immigrants, especially those without documentation. However, little is known about the positive or negative impacts of such testing on immigrant families and their communities. This study collected empirical data through family interviews to understand the experiences and attitudes of individuals who have taken a DNA test to prove a family relationship for immigration purposes. Based on study results, we present a set of recommendations to improve the processes with which DNA testing is applied to immigration cases. We argue that DNA testing might serve as a useful tool for families who lack documentary evidence of a family relationship. However, testing might also reveal sensitive information, such as misattributed parentage, that can damage relationships and cause serious harm to beneficiaries, especially children. Petitioners should be provided with adequate information to form an understanding of the DNA test and its implementation as well as the positive and negative consequences from using it, in order to carefully assess whether DNA testing will help their case. We recommend that additional protections be put in place to safeguard children from the potential impacts of misattributed parentage or disclosure of hidden social adoptions. This research provides empirical evidence to inform policy related to the use of genetic testing in immigration.