Gene × Physical Activity Interactions in Obesity: Combined Analysis of 111,421 Individuals of European Ancestry

Shafqat Ahmad,
Gull Rukh,
Tibor V. Varga,
Ashfaq Ali,
Azra Kurbasic,
Dmitry Shungin,
Ulrika Ericson,
Robert W. Koivula,
Audrey Y. Chu,
Lynda M. Rose,
Andrea Ganna,
Qibin Qi,
Alena Stančáková,
[ ... ],
Paul W. Franks mail
, [ view all ]

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Abstract

Numerous obesity loci have been identified using genome-wide association studies. A UK study indicated that physical activity may attenuate the cumulative effect of 12 of these loci, but replication studies are lacking. Therefore, we tested whether the aggregate effect of these loci is diminished in adults of European ancestry reporting high levels of physical activity. Twelve obesity-susceptibility loci were genotyped or imputed in 111,421 participants. A genetic risk score (GRS) was calculated by summing the BMI-associated alleles of each genetic variant. Physical activity was assessed using self-administered questionnaires. Multiplicative interactions between the GRS and physical activity on BMI were tested in linear and logistic regression models in each cohort, with adjustment for age, age², sex, study center (for multicenter studies), and the marginal terms for physical activity and the GRS. These results were combined using meta-analysis weighted by cohort sample size. The meta-analysis yielded a statistically significant GRS × physical activity interaction effect estimate (P_interaction = 0.015). However, a statistically significant interaction effect was only apparent in North American cohorts (n = 39,810, P_interaction = 0.014 vs. n = 71,611, P_interaction = 0.275 for Europeans). In secondary analyses, both the FTO rs1121980 (P_interaction = 0.003) and the SEC16B rs10913469 (P_interaction = 0.025) variants showed evidence of SNP × physical activity interactions. This meta-analysis of 111,421 individuals provides further support for an interaction between physical activity and a GRS in obesity disposition, although these findings hinge on the inclusion of cohorts from North America, indicating that these results are either population-specific or non-causal.

Author Summary

We undertook analyses in 111,421 adults of European descent to examine whether physical activity diminishes the genetic risk of obesity predisposed by 12 single nucleotide polymorphisms, as previously reported in a study of 20,000 UK adults (Li et al, PLoS Med. 2010). Although the study by Li et al is widely cited, the original report has not been replicated to our knowledge. Therefore, we sought to confirm or refute the original study's findings in a combined analysis of 111,421 adults. Our analyses yielded a statistically significant interaction effect (P_interaction = 0.015), confirming the original study's results; we also identified an interaction between the FTO locus and physical activity (P_interaction = 0.003), verifying previous analyses (Kilpelainen et al, PLoS Med., 2010), and we detected a novel interaction between the SEC16B locus and physical activity (P_interaction = 0.025). We also examined the power constraints of interaction analyses, thereby demonstrating that sources of within- and between-study heterogeneity and the manner in which data are treated can inhibit the detection of interaction effects in meta-analyses that combine many cohorts with varying characteristics. This suggests that combining many small studies that have measured environmental exposures differently may be relatively inefficient for the detection of gene × environment interactions.

Citation: Ahmad S, Rukh G, Varga TV, Ali A, Kurbasic A, et al. (2013) Gene × Physical Activity Interactions in Obesity: Combined Analysis of 111,421 Individuals of European Ancestry. PLoS Genet 9(7): e1003607. doi:10.1371/journal.pgen.1003607
Editor: David B. Allison, University of Alabama at Birmingham, United States of America
Received: December 26, 2012; Accepted: May 18, 2013; Published: July 25, 2013
Copyright: © 2013 Ahmad et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: Some of the work leading to this publication benefited from support from the Innovative Medicines Initiative Joint Undertaking under grant agreement n°115317 (DIRECT), resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007–2013) and EFPIA companies' in kind contribution. The current study was funded by Novo Nordisk, the Swedish Research Council, Påhlssons Foundation, the Swedish Heart-Lung Foundation, and the Skåne Regional Health Authority (all to PWF). The Fenland Study is funded by the Wellcome Trust and the Medical Research Council (MC_U106179471). The present part of the HEALTH2006 study was funded by The Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention and Care (LuCamp, www.lucamp.org). The Novo Nordisk Foundation Center for Basic Metabolic Research is an independent Research Center at the University of Copenhagen partially funded by an unrestricted donation from the Novo Nordisk Foundation (www.metabol.ku.dk). The present part of the Inter99 study was funded by The Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention and Care (LuCamp, www.lucamp.org). The Novo Nordisk Foundation Center for Basic Metabolic Research is an independent Research Center at the University of Copenhagen partially funded by an unrestricted donation from the Novo Nordisk Foundation (www.metabol.ku.dk). InterAct study was supported by funding from the European Union (Integrated Project LSHM-CT-2006-037197 in the Framework Programme 6 of the European Community) and the Medical Research Council, UK. The MDC study was supported by research grants from Swedish Research Council, the Swedish Heart-Lung Foundation, Strategic Research grant to EXODIAB, Linneus grant to Lund University Diabetes Centre (LUDC), The Albert Påhlsson Foundation, The Novo Nordisk Foundation, The Swedish Diabetes Foundation and an equipment grant from The Knut and Alice Wallenberg Foundation. METSIM study: This work has been supported by the Academy of Finland, the Finnish Diabetes Research Foundation, the Finnish Cardiovascular Research Foundation, EVO grant from the Kuopio University Hospital (5263), NIH grants DK093757, DK072193 and DK062370. The NHS study was supported by grants DK091718, HL071981, HL073168, CA87969, CA49449, CA055075, HL34594, HL088521, U01HG004399, DK080140, 5P30DK46200, U54CA155626, DK58845, U01HG004728-02, EY015473, DK70756, CA134958, and DK46200 from the National Institutes of Health, with additional support for genotyping from Merck Research Laboratories, North Wales, PA. The Swedish Twin Registry is supported by the Ministry for Higher Education, the Swedish Research Council, and GenomEUtwin; the US National Institutes of Health; and the Swedish Foundation for Strategic Research. EI and AG were supported by the Swedish Heart-Lung Foundation (grant no. 20120197) and Swedish Research Council (VR; grant no. 2012-1397) when working on this paper. The WGHS is supported by HL043851 and HL080467 from the National Heart, Lung, and Blood Institute and CA047988 from the National Cancer Institute, the Donald W. Reynolds Foundation and the Fondation Leducq, with collaborative scientific support and funding for genotyping provided by Amgen. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.