Incorporating polygenic risk scores and social determinants of health across populations: Considerations and best practices in research.

Abstract

There is a growing interest in evaluating the intersection of genetic and environmental factors, particularly social determinants of health (SDoH). As both the distributions and associations of genetic and SDoH-related risk vary across populations, a thorough understanding of the interplay of these factors (genetics and SDoH across populations) is necessary for the appropriate design and interpretation of studies examining their combined impact on health outcomes. In this review, we review population descriptors, including self-reported social constructs and genetically defined constructs, highlighting the different concepts they may capture and when it may be appropriate to use them. We discuss the challenges of applying polygenic risk scores (PRSs) to populations distinct in their genetic architecture or social context from the cohort in which they were developed. We provide an overview of conceptual SDoH frameworks and measures at the individual and area levels, discussing how these measures are defined, assessed, utilized, and interpreted in health research. For evaluating SDoH and PRS jointly, we outline analytic considerations, including calculating main-effect estimates, conducting gene-environment interaction studies, testing for mediation, and incorporating these factors into clinical prediction algorithms. When examining across populations, we highlight opportunities and challenges of data harmonization across existing cohorts and biobanks and ethical considerations necessary before embarking on or reporting work in this field. In all cases, we highlight the criticality of basing scientific questions upon well-considered conceptual frameworks arising from prior established relationships between risk factors and disease.