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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...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Journal Experts
2023
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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. |
format | Online Article Text |
id | pubmed-10602131 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Journal Experts |
record_format | MEDLINE/PubMed |
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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