{"date_created":"2020-04-30T10:39:33Z","language":[{"iso":"eng"}],"date_updated":"2021-01-12T08:14:59Z","author":[{"full_name":"Sulc, Jonathan","last_name":"Sulc","first_name":"Jonathan"},{"first_name":"Ninon","last_name":"Mounier","full_name":"Mounier, Ninon"},{"full_name":"Günther, Felix","first_name":"Felix","last_name":"Günther"},{"full_name":"Winkler, Thomas","last_name":"Winkler","first_name":"Thomas"},{"full_name":"Wood, Andrew R.","first_name":"Andrew R.","last_name":"Wood"},{"first_name":"Timothy M.","last_name":"Frayling","full_name":"Frayling, Timothy M."},{"full_name":"Heid, Iris M.","last_name":"Heid","first_name":"Iris M."},{"first_name":"Matthew Richard","id":"E5D42276-F5DA-11E9-8E24-6303E6697425","last_name":"Robinson","orcid":"0000-0001-8982-8813","full_name":"Robinson, Matthew Richard"},{"last_name":"Kutalik","first_name":"Zoltán","full_name":"Kutalik, Zoltán"}],"publication_identifier":{"issn":["2041-1723"]},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_processing_charge":"No","title":"Quantification of the overall contribution of gene-environment interaction for obesity-related traits","year":"2020","day":"20","_id":"7707","intvolume":"        11","doi":"10.1038/s41467-020-15107-0","quality_controlled":"1","publication_status":"published","type":"journal_article","article_type":"original","month":"03","publication":"Nature Communications","publisher":"Springer Nature","citation":{"chicago":"Sulc, Jonathan, Ninon Mounier, Felix Günther, Thomas Winkler, Andrew R. Wood, Timothy M. Frayling, Iris M. Heid, Matthew Richard Robinson, and Zoltán Kutalik. “Quantification of the Overall Contribution of Gene-Environment Interaction for Obesity-Related Traits.” <i>Nature Communications</i>. Springer Nature, 2020. <a href=\"https://doi.org/10.1038/s41467-020-15107-0\">https://doi.org/10.1038/s41467-020-15107-0</a>.","ama":"Sulc J, Mounier N, Günther F, et al. Quantification of the overall contribution of gene-environment interaction for obesity-related traits. <i>Nature Communications</i>. 2020;11. doi:<a href=\"https://doi.org/10.1038/s41467-020-15107-0\">10.1038/s41467-020-15107-0</a>","apa":"Sulc, J., Mounier, N., Günther, F., Winkler, T., Wood, A. R., Frayling, T. M., … Kutalik, Z. (2020). Quantification of the overall contribution of gene-environment interaction for obesity-related traits. <i>Nature Communications</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41467-020-15107-0\">https://doi.org/10.1038/s41467-020-15107-0</a>","ieee":"J. Sulc <i>et al.</i>, “Quantification of the overall contribution of gene-environment interaction for obesity-related traits,” <i>Nature Communications</i>, vol. 11. Springer Nature, 2020.","short":"J. Sulc, N. Mounier, F. Günther, T. Winkler, A.R. Wood, T.M. Frayling, I.M. Heid, M.R. Robinson, Z. Kutalik, Nature Communications 11 (2020).","ista":"Sulc J, Mounier N, Günther F, Winkler T, Wood AR, Frayling TM, Heid IM, Robinson MR, Kutalik Z. 2020. Quantification of the overall contribution of gene-environment interaction for obesity-related traits. Nature Communications. 11, 1385.","mla":"Sulc, Jonathan, et al. “Quantification of the Overall Contribution of Gene-Environment Interaction for Obesity-Related Traits.” <i>Nature Communications</i>, vol. 11, 1385, Springer Nature, 2020, doi:<a href=\"https://doi.org/10.1038/s41467-020-15107-0\">10.1038/s41467-020-15107-0</a>."},"extern":"1","volume":11,"article_number":"1385","main_file_link":[{"url":"https://doi.org/10.1038/s41467-020-15107-0","open_access":"1"}],"date_published":"2020-03-20T00:00:00Z","oa_version":"Published Version","oa":1,"status":"public","abstract":[{"text":"The growing sample size of genome-wide association studies has facilitated the discovery of gene-environment interactions (GxE). Here we propose a maximum likelihood method to estimate the contribution of GxE to continuous traits taking into account all interacting environmental variables, without the need to measure any. Extensive simulations demonstrate that our method provides unbiased interaction estimates and excellent coverage. We also offer strategies to distinguish specific GxE from general scale effects. Applying our method to 32 traits in the UK Biobank reveals that while the genetic risk score (GRS) of 376 variants explains 5.2% of body mass index (BMI) variance, GRSxE explains an additional 1.9%. Nevertheless, this interaction holds for any variable with identical correlation to BMI as the GRS, hence may not be GRS-specific. Still, we observe that the global contribution of specific GRSxE to complex traits is substantial for nine obesity-related measures (including leg impedance and trunk fat-free mass).","lang":"eng"}]}