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.

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:	English
Published:	Nature Publishing Group 2020-03-01
Series:	Nature Communications
Online Access:	https://doi.org/10.1038/s41467-020-15107-0

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spelling	doaj-d57fd22b9d4044d6822ee669df08a3852021-05-11T08:53:40ZengNature Publishing GroupNature Communications2041-17232020-03-0111111310.1038/s41467-020-15107-0Quantification of the overall contribution of gene-environment interaction for obesity-related traitsJonathan Sulc0Ninon Mounier1Felix Günther2Thomas Winkler3Andrew R. Wood4Timothy M. Frayling5Iris M. Heid6Matthew R. Robinson7Zoltán Kutalik8University Center for Primary Care and Public Health, University of LausanneUniversity Center for Primary Care and Public Health, University of LausanneDepartment of Genetic Epidemiology, University of RegensburgDepartment of Genetic Epidemiology, University of RegensburgGenetics of Complex Traits, University of Exeter Medical School, University of ExeterGenetics of Complex Traits, University of Exeter Medical School, University of ExeterDepartment of Genetic Epidemiology, University of RegensburgDepartment of Computational Biology, University of LausanneUniversity Center for Primary Care and Public Health, University of LausanneMost 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.https://doi.org/10.1038/s41467-020-15107-0
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Jonathan Sulc Ninon Mounier Felix Günther Thomas Winkler Andrew R. Wood Timothy M. Frayling Iris M. Heid Matthew R. Robinson Zoltán Kutalik
spellingShingle	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 Nature Communications
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 Publishing Group
series	Nature Communications
issn	2041-1723
publishDate	2020-03-01
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.
url	https://doi.org/10.1038/s41467-020-15107-0
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Quantification of the overall contribution of gene-environment interaction for obesity-related traits

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