Pervasive interactions between exposures and polygenic risk can inform more effective clinical and behavioral interventions.

Authors

Sini Nagpal, Greg Gibson

Published in

Nature genetics. Jul 13, 2026. Epub Jul 13, 2026.

Abstract

The generalizability of polygenic scores (PGS) remains a major hurdle in the pursuit of equitable genomic medicine. Differences in disease prevalence across groups, potentially including social strata, influence the relationship between PGS and risk. Here we quantified the magnitude of PGS-by-context (PGS×C) interactions for seven human diseases and pairs of 75 contexts in the UK Biobank (n = 408,801). Across 24,198 PGS×C models, 746 (3.1%) had significant interactions by two criteria, up to fourfold more than expected by chance, improving predictive accuracy. The predominant mechanism for PGS×C is the amplification of genetic effects in adverse contexts, such as low polyunsaturated fatty acids or social determinants of ill health. We introduce the notion of the proportion needed to benefit as a metric that quantifies the expected effectiveness of interventions as a function of polygenic risk. Our results highlight the need for more comprehensive sampling across groups experiencing adverse exposures.

PMID:
42443528
Bibliographic data and abstract were imported from PubMed on 14 Jul 2026.

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