Prevention trials provide a unique opportunity for researchers to explore gene-environment interplay, particularly within the context of differential susceptibility (Bakermans-Kranenburg & van IJzendoorn, 2015). The randomization of participants to trial arms allows for careful evaluation of the role of genetics as well as the role of the environment. This is specifically relevant because of the careful manner in which the environment is controlled, thus limiting potential gene-environment correlation. Further, these trials generally provide rich phenotypic information for more careful modelling. There are some limitations, the largest being the limited sample sizes. Researchers can improve the power associated with these statistical tests by limiting the number of genetic regions explored through use of Post-GWAS candidate selection, polygenic scoring or pathway analysis. Previous work has explored differential susceptibility utilizing meta-analytic methods, and demonstrated the remarkable increase in power for detecting GxE in intervention trials (Bakermans-Kranenburg & Van IJzendoorn, 2015).
