New methods, persistent issues, and one solution: Gene-environment interaction studies of childhood cognitive development

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC ACS Applied Electronic Materials Pub Date : 2024-05-09 DOI:10.1016/j.intell.2024.101834
Sophie von Stumm , Allie F. Nancarrow
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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.

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新方法、老大难问题和一个解决方案:儿童认知发展的基因-环境交互作用研究
儿童在认知发展方面的差异源于遗传和环境因素的复杂相互作用。识别基因与环境在认知发展中的相互作用,是有效定位干预措施以改善儿童生活机会的关键。多基因评分的出现为精确定位基因与环境的相互作用创造了前所未有的机会。然而,统计能力--即检测到真实效应的概率--的问题仍然普遍存在,在儿童认知发展中还没有可复制的基因-环境交互作用的报道。在这篇综述文章中,我们概述了研究基因与环境相互作用的三种方法,包括双生子研究、候选基因模型和多基因评分法。然后,我们讨论了基因-环境交互作用研究中的统计能力问题,并得出结论:要开创一个可复制的基因-环境交互作用研究结果的新时代,更大的样本是关键。
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CiteScore
7.20
自引率
4.30%
发文量
567
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