The sociogenomics of human phenotypes: How social and biological factors jointly shape individual behaviors and outcomes related to socioeconomic attainment and demographic outcomes.

Genetics has been increasingly integrated into research on sociological topics such as fertility, well-being, risk-taking, and longevity (Mills and Tropf, 2020). While the existing literature has established heritability of a set of sociopsychological, behavioral, and health outcomes, estimates from different cohorts or study designs —e.g., twin and family studies, GWAS, and SNP heritability — differ substantially. Missing/hidden heritability prompts discussion on the optimal methodological approach. We seek to understand how the use of family designs impacts the validity of genetic effect estimates. Specifically, we will compare the performance of classic and family-based GWAS and their downstream polygenic scores (PGSs) in predicting a rich set of sociopsychological, behavioral, and health outcomes. Additionally, we will explore to what extent family-based GWAS results yield increased portability to diverse and admixed ancestries.

Another important area is gene-environment interactions (G×E). G×E research has employed diverse approaches (Miao et al., 2022), such as differential heritability/variance, genetic correlation, and mean/variance PGS (Johnson et al., 2022) analyses. Despite this, limitations remain; many (early) G×E studies fail to properly control for potential confounders (Keller, 2014). Moreover, which G×E mechanisms — e.g., outcome moderation (i.e., Domingue et al. 2020) vs. variability moderation —underlie the effects is poorly understood. In addition, little is known about the extent which to social changes serve to modify associations between genetic ancestry and self-identified/reviewer classified race. We aim to employ recent methodological advances to the multiple research gaps described above.
We will examine a rich set of variables, including SES, early-life experiences, physical development, mental health, medical conditions, and mortality. This work will be collaborative with Professor Sam Trejo, also of Princeton University (Sociology).

This project aims to increase understanding of how genetic and socioenvironmental factors interactively affect social, behavioral, and health outcomes, with an eye towards gaps in the research literature. For one thing, existing efforts at quantifying the genetic effects on individual behaviors/outcomes have come to sometimes substantially different estimates. For another, many existing G×E studies have been improperly designed to answer their intended research question, and few of them have specifically examined which GxE mechanisms explain the observed patterns.

This project can help us better understand the biosocial underpinnings of a rich set of individual outcomes and inform policies aimed at reducing social/health disparities. Our research improves the development of tools that identify individuals for early intervention, suggests how the DNA characteristics of a population may influence the effectiveness of health policies, and facilitate evidence-based policymaking that considers not only socioenvironmental factors but also their interactions with one’s gene’s.