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PGS Browser: a public platform for personalized polygenic score interpretation

Kolosov, N.; Reeve, M. P.; Parolo, P. D. B.; Kurki, M. I.; FinnGen, ; Llorens, V.; Sipila, T. P.; Herman, A.; Molotkov, I.; Aavikko, M.; Ripatti, S.; Palotie, A.; Daly, M. J.; Artomov, M.

2025-07-05 genetic and genomic medicine
10.1101/2025.07.03.25330851 medRxiv
Show abstract

Identifying individuals at elevated risk before disease onset is a cornerstone of personalized prevention, and polygenic scores (PGSs) have proven to be nstrumental in this regard. In this study, we systematically benchmarked 3,168 PGS models from the PGS Catalog in 473,681 FinnGen participants, revealing top-performing scores across major ancestry groups and highlighting traits where non-target PGSs significantly improve prediction. We conducted 10,531 phenome-wide association studies, uncovering 439,070 significant associations between PGSs and 4,739 clinical endpoints. To support individual score interpretation, we provide public access to ancestry-adjusted reference PGS distributions derived from the large-scale FinnGen cohort, alongside elastic-net Cox models for predicting time-to-event for 22 major disorders All data and predictive tools are accessible via the PGS Browser (pgs.nchigm.org), an interactive web-based platform for PGS analysis and interpretation. We envision that this esource will greatly advance both research and translational applications of polygenic scores.

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