通过环境分层和基因-环境相互作用,完善酒精滥用的遗传影响范围。

IF 3 Q2 SUBSTANCE ABUSE
Jeanne E. Savage, Christiaan A. de Leeuw, Josefin Werme, Spit for Science Working Group, Danielle M. Dick, Danielle Posthuma, Sophie van der Sluis
{"title":"通过环境分层和基因-环境相互作用,完善酒精滥用的遗传影响范围。","authors":"Jeanne E. Savage,&nbsp;Christiaan A. de Leeuw,&nbsp;Josefin Werme,&nbsp;Spit for Science Working Group,&nbsp;Danielle M. Dick,&nbsp;Danielle Posthuma,&nbsp;Sophie van der Sluis","doi":"10.1111/acer.15425","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>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.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>We carried out GWEIS for four AM phenotypes in the large UK Biobank sample (<i>N</i> = 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.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>GWEIS models showed few genetic variants with significant interaction effects across gene–environment pairs. Enrichment analyses identified moderation by SES of the genes <i>NOXA1</i>, <i>DLGAP1</i>, and <i>UBE2L3</i> on drinking quantity and the gene <i>IFIT1B</i> on drinking frequency. Except for <i>DLGAP1</i>, these genes have not previously been linked to AM. The most robust results (GWEIS interaction <i>p</i> = 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.</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>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.</p>\n </section>\n </div>","PeriodicalId":72145,"journal":{"name":"Alcohol (Hanover, York County, Pa.)","volume":"48 10","pages":"1853-1865"},"PeriodicalIF":3.0000,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/acer.15425","citationCount":"0","resultStr":"{\"title\":\"Refining the scope of genetic influences on alcohol misuse through environmental stratification and gene–environment interaction\",\"authors\":\"Jeanne E. Savage,&nbsp;Christiaan A. de Leeuw,&nbsp;Josefin Werme,&nbsp;Spit for Science Working Group,&nbsp;Danielle M. Dick,&nbsp;Danielle Posthuma,&nbsp;Sophie van der Sluis\",\"doi\":\"10.1111/acer.15425\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Background</h3>\\n \\n <p>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.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>We carried out GWEIS for four AM phenotypes in the large UK Biobank sample (<i>N</i> = 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.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>GWEIS models showed few genetic variants with significant interaction effects across gene–environment pairs. Enrichment analyses identified moderation by SES of the genes <i>NOXA1</i>, <i>DLGAP1</i>, and <i>UBE2L3</i> on drinking quantity and the gene <i>IFIT1B</i> on drinking frequency. Except for <i>DLGAP1</i>, these genes have not previously been linked to AM. The most robust results (GWEIS interaction <i>p</i> = 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.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusions</h3>\\n \\n <p>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.</p>\\n </section>\\n </div>\",\"PeriodicalId\":72145,\"journal\":{\"name\":\"Alcohol (Hanover, York County, Pa.)\",\"volume\":\"48 10\",\"pages\":\"1853-1865\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2024-08-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1111/acer.15425\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Alcohol (Hanover, York County, Pa.)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/acer.15425\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"SUBSTANCE ABUSE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Alcohol (Hanover, York County, Pa.)","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/acer.15425","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"SUBSTANCE ABUSE","Score":null,"Total":0}
引用次数: 0

摘要

背景:基因-环境相互作用(G×E)可能是形成酒精滥用(AM)个体差异的重要影响因素,但分子遗传学研究尚未对其进行广泛研究。在本研究中,我们采用了一系列全基因组范围的基因-环境相互作用(GWEIS)和硅标注方法,旨在提高对酒精滥用的基因鉴定和生物学理解:我们在英国生物库(UK Biobank)大样本(N = 360,314)中对四种急性髓系白血病表型进行了全基因组-环境相互作用(GWEIS)研究,将创伤暴露和社会经济地位(SES)作为遗传效应的调节因子。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、基因和基因组富集以及多基因评分分析来解释 GWEIS 的结果:结果:GWEIS 模型显示,在基因-环境配对中具有显著交互效应的基因变异很少。富集分析发现,NOXA1、DLGAP1 和 UBE2L3 基因以及 IFIT1B 基因对饮酒量和饮酒频率的影响受 SES 的调节。除 DLGAP1 外,这些基因以前从未与 AM 联系在一起。最稳健的结果(GWEIS交互作用 p = 4.59e-09)是,社会经济地位调节了与免疫相关基因有关的变异对有餐饮酒与无餐饮酒模式的影响:我们的研究结果凸显了 SES 对 AM 遗传影响的调节作用背后的几个基因和免疫系统功能的潜在机制。尽管 GWEIS 似乎是比分层 GWAS 更受青睐的方法,但即使在大样本中,在分子水平上建立 G × E 效应模型仍然是一项挑战。要了解这些影响,需要大量的努力和更深入的表型测量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Refining the scope of genetic influences on alcohol misuse through environmental stratification and gene–environment interaction

Refining the scope of genetic influences on alcohol misuse through environmental stratification and gene–environment interaction

Refining the scope of genetic influences on alcohol misuse through environmental stratification and gene–environment interaction

Background

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.

Methods

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.

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.

Conclusions

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.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
5.40
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信