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A new Approach to Identify Gene-Environment Interactions and Reveal New Biological Insight in Complex traits

There is a long-standing debate about the magnitude of the contribution of gene-environment interactions to phenotypic variations of complex traits owing to the low statistical power and few reported interactions to date. To address this issue, the CHARGE Gene-Lifestyle Interactions Working Group ha...

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Autores principales: Zhu, Xiaofeng, Yang, Yihe, Lorincz-Comi, Noah, Li, Gen, Bentley, Amy, de Vries, Paul S, Brown, Michael, Morrison, Alanna C, Rotimi, Charles, James Gauderman, W., Rao, DC, Aschard, Hugues
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Journal Experts 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10602131/
https://www.ncbi.nlm.nih.gov/pubmed/37886448
http://dx.doi.org/10.21203/rs.3.rs-3338723/v1
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author Zhu, Xiaofeng
Yang, Yihe
Lorincz-Comi, Noah
Li, Gen
Bentley, Amy
de Vries, Paul S
Brown, Michael
Morrison, Alanna C
Rotimi, Charles
James Gauderman, W.
Rao, DC
Aschard, Hugues
author_facet Zhu, Xiaofeng
Yang, Yihe
Lorincz-Comi, Noah
Li, Gen
Bentley, Amy
de Vries, Paul S
Brown, Michael
Morrison, Alanna C
Rotimi, Charles
James Gauderman, W.
Rao, DC
Aschard, Hugues
author_sort Zhu, Xiaofeng
collection PubMed
description There is a long-standing debate about the magnitude of the contribution of gene-environment interactions to phenotypic variations of complex traits owing to the low statistical power and few reported interactions to date. To address this issue, the CHARGE Gene-Lifestyle Interactions Working Group has been spearheading efforts to investigate [Formula: see text] in large and diverse samples through meta-analysis. Here, we present a powerful new approach to screen for interactions across the genome, an approach that shares substantial similarity to the Mendelian randomization framework. We identified and confirmed 5 loci (6 independent signals) interacting with either cigarette smoking or alcohol consumption for serum lipids, and empirically demonstrated that interaction and mediation are the major contributors to genetic effect size heterogeneity across populations. The estimated lower bound of the interaction and environmentally mediated contribution ranges from 1.76% to 14.05% of SNP heritability of serum lipids in Cross-Population data. Our study improves the understanding of the genetic architecture and environmental contributions to complex traits.
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spelling pubmed-106021312023-10-27 A new Approach to Identify Gene-Environment Interactions and Reveal New Biological Insight in Complex traits Zhu, Xiaofeng Yang, Yihe Lorincz-Comi, Noah Li, Gen Bentley, Amy de Vries, Paul S Brown, Michael Morrison, Alanna C Rotimi, Charles James Gauderman, W. Rao, DC Aschard, Hugues Res Sq Article There is a long-standing debate about the magnitude of the contribution of gene-environment interactions to phenotypic variations of complex traits owing to the low statistical power and few reported interactions to date. To address this issue, the CHARGE Gene-Lifestyle Interactions Working Group has been spearheading efforts to investigate [Formula: see text] in large and diverse samples through meta-analysis. Here, we present a powerful new approach to screen for interactions across the genome, an approach that shares substantial similarity to the Mendelian randomization framework. We identified and confirmed 5 loci (6 independent signals) interacting with either cigarette smoking or alcohol consumption for serum lipids, and empirically demonstrated that interaction and mediation are the major contributors to genetic effect size heterogeneity across populations. The estimated lower bound of the interaction and environmentally mediated contribution ranges from 1.76% to 14.05% of SNP heritability of serum lipids in Cross-Population data. Our study improves the understanding of the genetic architecture and environmental contributions to complex traits. American Journal Experts 2023-10-05 /pmc/articles/PMC10602131/ /pubmed/37886448 http://dx.doi.org/10.21203/rs.3.rs-3338723/v1 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.
spellingShingle Article
Zhu, Xiaofeng
Yang, Yihe
Lorincz-Comi, Noah
Li, Gen
Bentley, Amy
de Vries, Paul S
Brown, Michael
Morrison, Alanna C
Rotimi, Charles
James Gauderman, W.
Rao, DC
Aschard, Hugues
A new Approach to Identify Gene-Environment Interactions and Reveal New Biological Insight in Complex traits
title A new Approach to Identify Gene-Environment Interactions and Reveal New Biological Insight in Complex traits
title_full A new Approach to Identify Gene-Environment Interactions and Reveal New Biological Insight in Complex traits
title_fullStr A new Approach to Identify Gene-Environment Interactions and Reveal New Biological Insight in Complex traits
title_full_unstemmed A new Approach to Identify Gene-Environment Interactions and Reveal New Biological Insight in Complex traits
title_short A new Approach to Identify Gene-Environment Interactions and Reveal New Biological Insight in Complex traits
title_sort new approach to identify gene-environment interactions and reveal new biological insight in complex traits
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10602131/
https://www.ncbi.nlm.nih.gov/pubmed/37886448
http://dx.doi.org/10.21203/rs.3.rs-3338723/v1
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