The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study
Winkler, Thomas W; Justice, Anne E; Graff, Mariaelisa; Barata, Llilda; Feitosa, Mary F.; Chu, Su; Czajkowski, Jacek; Esko, Tõnu; Fall, Tove; Kilpeläinen, Tuomas O.; Lu, Yingchang; Mägi, Reedik; Mihailov, Evelin; Pers, Tune H.; Rüeger, Sina; Teumer, Alexander; Ehret, Georg B.; Ferreira, Teresa; Heard-Costa, Nancy L.; Karjalainen, Juha; Lagou, Vasiliki; Mahajan, Anubha; Neinast, Michael D.; Prokopenko, Inga; Simino, Jeannette; Teslovich, Tanya M.; Jansen, Rick; Westra, Harm-Jan; White, Charles C.; Absher, Devin; Ahluwalia, Tarunveer S.; Ahmad, Shafqat; Albrecht, Eva; Alves, Alexessander Couto; Bragg-Gresham, Jennifer L.; de Craen, Anton J. M.; Bis, Joshua C.; Bonnefond, Amélie; Boucher, Gabrielle; Cadby, Gemma; Cheng, Yu-Ching; Chiang, Charleston W. K.; Delgado, Graciela; Demirkan, Ayse; Dueker, Nicole; Eklund, Niina; Eiriksdottir, Gudny; Holmen, Oddgeir; Wilsgaard, Tom; Hveem, Kristian; Njølstad, Inger
Journal article, Peer reviewed
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Original versionPLoS Genetics 2015, 11(10) 10.1371/journal.pgen.1005378
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.