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

TY - JOUR

T1 - New methods, persistent issues, and one solution

T2 - Gene-environment interaction studies of childhood cognitive development

AU - von Stumm, Sophie

AU - Nancarrow, Allie F.

N1 - © 2024 The Authors

PY - 2024/7/1

Y1 - 2024/7/1

N2 - 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.

AB - 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.

KW - Cognitive development

KW - Effect size

KW - Gene-environment interaction

KW - Sample size

KW - Statistical power

UR - http://www.scopus.com/inward/record.url?scp=85192736033&partnerID=8YFLogxK

U2 - 10.1016/j.intell.2024.101834

DO - 10.1016/j.intell.2024.101834

M3 - Review article

AN - SCOPUS:85192736033

SN - 0160-2896

VL - 105

JO - Intelligence

JF - Intelligence

M1 - 101834

ER -