Identity-by-descent captures Shared Environmental Factors at Biobank Scale

Abstract

Genealogical ties leave traces beyond shared genetic material: relatives tend to share environmental exposures and cultural practices that persist across generations. Using genomic and electronic health record data from 13,143 individuals in the Biorepository for Integrative Genomics, we applied a hierarchical community detection algorithm to group individuals into four major communities and 17 subcommunities based on the proportion of their genome shared identical by descent (IBD). This approach captured a fine-scale demographic structure beyond traditional ancestry classifications. By integrating neighborhood-level geographic data with census-derived environmental metrics, we revealed unequal exposure to environmental stressors between subcommunities, which correlated with differential rates of health conditions, including elevated respiratory condition prevalence in subcommunities under greater pollution burden. Through an interventional mediation analysis we found that excess risk at the subcommunity-level substantially exceeded what measured environmental factors alone could explain. thus showing the contribution of unmeasured shared exposures that IBD-based grouping captures. Subcommunity-level disparities persisted in sensitivity analyses adjusting for self-reported race, indicating that IBD-based clustering captures health-relevant information beyond demographic categories commonly used as proxies for social determinants of health. We implemented an open-source dashboard for interactive exploration of IBD-defined communities, disease prevalence, and environmental exposures. Together, we demonstrate that IBD-based clustering jointly captures genetic and environmental determinants of health, offering a scalable framework for precision health and population genetics that translates biobank data into actionable insights.