{"title":"New methods, persistent issues, and one solution: Gene-environment interaction studies of childhood cognitive development","authors":"Sophie von Stumm , Allie F. Nancarrow","doi":"10.1016/j.intell.2024.101834","DOIUrl":null,"url":null,"abstract":"<div><p>Children's differences in cognitive development stem from the complex interplay of genetic and environmental factors. Identifying gene-environment interactions in cognitive development is key for effectively targeting interventions that improve children's life chances. The advent of polygenic scores, which aggregate DNA variants to index a person's genetic propensities for phenotypic development, has created unprecedented opportunities for pinpointing gene-environment interactions. Yet, the issue of statistical power – the probability of detecting a true effect – prevails, and no replicable gene-environment interactions in child cognitive development have been reported. In this review article, we recapitulate three approaches to studying gene-environment interactions, including twin studies, candidate gene models, and polygenic score methods. We then discuss the issue of statistical power in gene-environment interaction research and conclude that larger samples are key to ushering a new era of replicable gene-environment interaction findings.</p></div>","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S016028962400028X/pdfft?md5=cd9adebcc50ca60cf1f5082cffb111b9&pid=1-s2.0-S016028962400028X-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Electronic Materials","FirstCategoryId":"102","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S016028962400028X","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Children's differences in cognitive development stem from the complex interplay of genetic and environmental factors. Identifying gene-environment interactions in cognitive development is key for effectively targeting interventions that improve children's life chances. The advent of polygenic scores, which aggregate DNA variants to index a person's genetic propensities for phenotypic development, has created unprecedented opportunities for pinpointing gene-environment interactions. Yet, the issue of statistical power – the probability of detecting a true effect – prevails, and no replicable gene-environment interactions in child cognitive development have been reported. In this review article, we recapitulate three approaches to studying gene-environment interactions, including twin studies, candidate gene models, and polygenic score methods. We then discuss the issue of statistical power in gene-environment interaction research and conclude that larger samples are key to ushering a new era of replicable gene-environment interaction findings.