Gene-lifestyle interactions in the genomics of human complex traits

The role and biological significance of gene-environment interactions in human traits and diseases remain poorly understood. To address these questions, the CHARGE Gene-Lifestyle Interactions Working Group conducted series of genome-wide interaction studies (GWIS) involving up to 610,475 individuals...

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Veröffentlicht in:European journal of human genetics : EJHG 2022-06, Vol.30 (6), p.730-739
Hauptverfasser: Laville, Vincent, Majarian, Timothy, Sung, Yun J, Schwander, Karen, Feitosa, Mary F, Chasman, Daniel I, Bentley, Amy R, Rotimi, Charles N, Cupples, L Adrienne, de Vries, Paul S, Brown, Michael R, Morrison, Alanna C, Kraja, Aldi T, Province, Mike, Gu, C Charles, Gauderman, W James, Rao, D C, Manning, Alisa K, Aschard, Hugues
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container_issue 6
container_start_page 730
container_title European journal of human genetics : EJHG
container_volume 30
creator Laville, Vincent
Majarian, Timothy
Sung, Yun J
Schwander, Karen
Feitosa, Mary F
Chasman, Daniel I
Bentley, Amy R
Rotimi, Charles N
Cupples, L Adrienne
de Vries, Paul S
Brown, Michael R
Morrison, Alanna C
Kraja, Aldi T
Province, Mike
Gu, C Charles
Gauderman, W James
Rao, D C
Manning, Alisa K
Aschard, Hugues
description The role and biological significance of gene-environment interactions in human traits and diseases remain poorly understood. To address these questions, the CHARGE Gene-Lifestyle Interactions Working Group conducted series of genome-wide interaction studies (GWIS) involving up to 610,475 individuals across four ancestries for three lipids and four blood pressure traits, while accounting for interaction effects with drinking and smoking exposures. Here we used GWIS summary statistics from these studies to decipher potential differences in genetic associations and G×E interactions across phenotype-exposure-ancestry combinations, and to derive insights on the potential mechanistic underlying G×E through in-silico functional analyses. Our analyses show first that interaction effects likely contribute to the commonly reported ancestry-specific genetic effect in complex traits, and second, that some phenotype-exposures pairs are more likely to benefit from a greater detection power when accounting for interactions. It also highlighted modest correlation between marginal and interaction effects, providing material for future methodological development and biological discussions. We also estimated contributions to phenotypic variance, including in particular the genetic heritability conditional on the exposure, and heritability partitioned across a range of functional annotations and cell types. In these analyses, we found multiple instances of potential heterogeneity of functional partitions between exposed and unexposed individuals, providing new evidence for likely exposure-specific genetic pathways. Finally, along this work, we identified potential biases in methods used to jointly meta-analyze genetic and interaction effects. We performed simulations to characterize these limitations and to provide the community with guidelines for future G×E studies.
doi_str_mv 10.1038/s41431-022-01045-6
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source MEDLINE; SpringerLink Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central
subjects Alcohol
Blood pressure
Consortia
Epidemiology
Epistasis, Genetic
Gene-Environment Interaction
Genetics
Genome-Wide Association Study
Genomes
Genomics
Genotype & phenotype
Health care
Heritability
High density lipoprotein
Human genetics
Humans
Life Sciences
Life Style
Lifestyles
Lipids
Multifactorial Inheritance
Phenotype
Phenotypes
Phenotypic variations
Preventive medicine
Public health
Quantitative Methods
Smoking
Working groups
title Gene-lifestyle interactions in the genomics of human complex traits
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