Savage Jeanne E, de Leeuw Christiaan A, Werme Josefin, Dick Danielle M, Posthuma Danielle, van der Sluis Sophie
Department of Complex Trait Genetics, Centre for Neurogenomics and Cognitive Research, VU University, Amsterdam, The Netherlands.
Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers Addiction Research Center, Rutgers University, Piscataway, New Jersey, USA.
Alcohol Clin Exp Res (Hoboken). 2024 Oct;48(10):1853-1865. doi: 10.1111/acer.15425. Epub 2024 Aug 28.
Gene-environment interaction (G × E) is likely an important influence shaping individual differences in alcohol misuse (AM), yet it has not been extensively studied in molecular genetic research. In this study, we use a series of genome-wide gene-environment interaction (GWEIS) and in silico annotation methods with the aim of improving gene identification and biological understanding of AM.
We carried out GWEIS for four AM phenotypes in the large UK Biobank sample (N = 360,314), with trauma exposure and socioeconomic status (SES) as moderators of the genetic effects. Exploratory analyses compared stratified genome-wide association (GWAS) and GWEIS modeling approaches. We applied functional annotation, gene- and gene-set enrichment, and polygenic score analyses to interpret the GWEIS results.
GWEIS models showed few genetic variants with significant interaction effects across gene-environment pairs. Enrichment analyses identified moderation by SES of the genes NOXA1, DLGAP1, and UBE2L3 on drinking quantity and the gene IFIT1B on drinking frequency. Except for DLGAP1, these genes have not previously been linked to AM. The most robust results (GWEIS interaction p = 4.59e-09) were seen for SES moderating the effects of variants linked to immune-related genes on a pattern of drinking with versus without meals.
Our results highlight several genes and a potential mechanism of immune system functioning behind the moderating effect of SES on the genetic influences on AM. Although GWEIS seems to be a preferred approach over stratified GWAS, modeling G × E effects at the molecular level remains a challenge even in large samples. Understanding these effects will require substantial effort and more in-depth phenotypic measurement.
基因-环境相互作用(G×E)可能是影响酒精滥用(AM)个体差异的一个重要因素,但在分子遗传学研究中尚未得到广泛研究。在本研究中,我们使用了一系列全基因组基因-环境相互作用(GWEIS)和计算机注释方法,旨在改善对AM的基因识别和生物学理解。
我们在大型英国生物银行样本(N = 360,314)中对四种AM表型进行了GWEIS分析,将创伤暴露和社会经济地位(SES)作为基因效应的调节因素。探索性分析比较了分层全基因组关联(GWAS)和GWEIS建模方法。我们应用功能注释、基因和基因集富集以及多基因评分分析来解释GWEIS结果。
GWEIS模型显示,跨基因-环境对具有显著相互作用效应的遗传变异很少。富集分析确定,SES对饮酒量相关基因NOXA1、DLGAP1和UBE2L3以及饮酒频率相关基因IFIT1B具有调节作用。除DLGAP1外,这些基因以前尚未与AM相关联。在SES调节与免疫相关基因的变异对就餐与不就餐时饮酒模式的影响方面,观察到了最显著的结果(GWEIS相互作用p = 4.59e-09)。
我们的结果突出了几个基因以及SES对AM遗传影响的调节作用背后的免疫系统功能潜在机制。尽管GWEIS似乎比分层GWAS更具优势,但即使在大样本中,在分子水平上模拟G×E效应仍然是一个挑战。理解这些效应需要付出巨大努力并进行更深入的表型测量。