Quantification of the overall contribution of gene-environment interaction for obesity-related traits

Most gene-by-environment interaction methods rely on the availability of the interacting environment. Here, the authors propose a robust maximum likelihood method for estimating the overall statistical interaction between a genetic risk score for a continuous outcome and all environmental variables.

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Bibliographic Details
Main Authors:	Jonathan Sulc, Ninon Mounier, Felix Günther, Thomas Winkler, Andrew R. Wood, Timothy M. Frayling, Iris M. Heid, Matthew R. Robinson, Zoltán Kutalik
Format:	article
Language:	EN
Published:	Nature Portfolio 2020
Subjects:	Science Q
Online Access:	https://doaj.org/article/d57fd22b9d4044d6822ee669df08a385
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id	oai:doaj.org-article:d57fd22b9d4044d6822ee669df08a385
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spelling	oai:doaj.org-article:d57fd22b9d4044d6822ee669df08a3852021-12-02T14:40:52ZQuantification of the overall contribution of gene-environment interaction for obesity-related traits10.1038/s41467-020-15107-02041-1723https://doaj.org/article/d57fd22b9d4044d6822ee669df08a3852020-03-01T00:00:00Zhttps://doi.org/10.1038/s41467-020-15107-0https://doaj.org/toc/2041-1723Most gene-by-environment interaction methods rely on the availability of the interacting environment. Here, the authors propose a robust maximum likelihood method for estimating the overall statistical interaction between a genetic risk score for a continuous outcome and all environmental variables.Jonathan SulcNinon MounierFelix GüntherThomas WinklerAndrew R. WoodTimothy M. FraylingIris M. HeidMatthew R. RobinsonZoltán KutalikNature PortfolioarticleScienceQENNature Communications, Vol 11, Iss 1, Pp 1-13 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Jonathan Sulc Ninon Mounier Felix Günther Thomas Winkler Andrew R. Wood Timothy M. Frayling Iris M. Heid Matthew R. Robinson Zoltán Kutalik Quantification of the overall contribution of gene-environment interaction for obesity-related traits
description	Most gene-by-environment interaction methods rely on the availability of the interacting environment. Here, the authors propose a robust maximum likelihood method for estimating the overall statistical interaction between a genetic risk score for a continuous outcome and all environmental variables.
format	article
author	Jonathan Sulc Ninon Mounier Felix Günther Thomas Winkler Andrew R. Wood Timothy M. Frayling Iris M. Heid Matthew R. Robinson Zoltán Kutalik
author_facet	Jonathan Sulc Ninon Mounier Felix Günther Thomas Winkler Andrew R. Wood Timothy M. Frayling Iris M. Heid Matthew R. Robinson Zoltán Kutalik
author_sort	Jonathan Sulc
title	Quantification of the overall contribution of gene-environment interaction for obesity-related traits
title_short	Quantification of the overall contribution of gene-environment interaction for obesity-related traits
title_full	Quantification of the overall contribution of gene-environment interaction for obesity-related traits
title_fullStr	Quantification of the overall contribution of gene-environment interaction for obesity-related traits
title_full_unstemmed	Quantification of the overall contribution of gene-environment interaction for obesity-related traits
title_sort	quantification of the overall contribution of gene-environment interaction for obesity-related traits
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/d57fd22b9d4044d6822ee669df08a385
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Quantification of the overall contribution of gene-environment interaction for obesity-related traits

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