Emerging research on gene-by-environment interactions (GxE) has shown that gene expression is amplified or reduced in the presence of particular environments. Conversely, the effects of environments on individuals are influenced by the presence or absence of specific genetic susceptibilities. Given these findings, the integration of genetic data into large-scale multidisciplinary social surveys holds the potential to revolutionize our understanding of how social and biological forces interact to shape social and health inequalities over the life course.
Dalton Conley and Lauren Schmitz point out, however, that many studies claiming to have discovered GxE interactions have methodological flaws, and that significant methodological hurdles remain in research that uses observational data to explore GxE effects in population-based samples. They will carry out a project that avoids these methodological weaknesses in testing for GxE interactions in cognitive and health outcomes. They will use new methods that provide clean identification of G, E, and thus GxE effects in genome-wide observational data. They will incorporate validated genetic risk scores (GRS) that have been identified in molecular genetics research into analyses with quasi-experimental designs to overcome omitted variables and selection problems in estimates of causal relationships. The project will combine genotype data with exogenous environmental shocks to estimate GxE interactions on a range of health, behavioral and developmental outcomes.