Environment-by-PGS Interaction: Combining the classical twin design and Polygenic Scores to test for Genotype x Environment Interaction

Susanne Bruins, Jouke-Jan Hottenga, Michael C. Neale, René Pool, Dorret Boomsma and Conor V. Dolan
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Susanne Bruins: Vrije Universiteit

No 7a4v8, OSF Preprints from Center for Open Science

Abstract: Genotype - environment (GxE) interaction occurs when genetic effects on an outcome (phenotype) are moderated by an environment, or when environmental effects on a phenotype are moderated by genes. Our aim is to present an overview of GxE interaction models, and to propose a test of GxE interaction, which includes observed genetic variables (polygenic scores: PGSs) which account for part of the additive genetic variance of the phenotype of interest. We introduce this environment-by-PGS interaction model and the results of a simulation study to address statistical power and parameter recovery. Next, we apply the model to empirical data on anxiety and negative affect in children. The power to detect environment-by-PGS interaction depends on the contributions of genes and environment to the phenotype, and on the strength of the PGS, i.e., the proportion of heritability captured by the PGS. We discuss the results of the simulation and the empirical study and consider under which conditions the environment-by-PGS model might yield biased or false positive results.

Date: 2022-09-15
New Economics Papers: this item is included in nep-env
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Persistent link: https://EconPapers.repec.org/RePEc:osf:osfxxx:7a4v8

DOI: 10.31219/osf.io/7a4v8

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