ArticlemedRxiv : the preprint server for health sciences2025
Pathway-specific polygenic scores substantially increase the discovery of gene-adiposity interactions impacting liver biomarkers.
Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Polygenic scores (PGS) have been leveraged to detect gene-environment interactions across many complex traits and environmental variables. While PGS×E regression is potentially more powerful than single-variant genome-wide interaction studies (GWIS) due to the aggregation of genetic effects and reduced multiple testing burden, standard PGS reflect many different biological mechanisms, limiting interpretation and potentially diluting pathway-specific interaction signals. Previous work has uncovered significant genome-wide PGS×BMI signal for liver function, but there is an opportunity for additional and more interpretable discoveries. Here, we leverage pathway-specific polygenic scores (pPGS) to discover novel mechanism-specific gene-adiposity interactions. We tested for adiposity interactions impacting three liver-related biomarkers (ALT, AST and GGT) using (1) a standard, genome-wide PGS, (2) an array of pPGS containing variant subsets derived from KEGG pathways, and (3) a GWIS. For ALT, we identified 49 significant pPGS×BMI interactions at a Bonferroni corrected
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