Instability of high polygenic risk classification and mitigation by integrative scoring.

Polygenic risk scores (PRS) continue to improve with novel methods and expanding genome-wide association studies. Healthcare and commercial laboratories are increasingly deploying PRS reports to patients, but it is unknown how the classification of high polygenic risk changes across individual PRS. Here, we assess the association and classification performance of cataloged PRS for three complex traits. We chronologically order all trait-related publications (Pub _n ) and identify the single PRS Best(Pub _n ) for each Pub _n that has the strongest association with the target outcome. While each Best(Pub _n ) demonstrates generally consistent population-level strengths of associations, the classification of individuals in the top 10% of each Best(Pub _n ) distribution varies widely. Using the PRSmix framework, which integrates information across several PRS to improve prediction, we generate corresponding ChronoAdd(Pub _n ) scores for each Pub _n that combine all polygenic scores from all publications up to and including Pub _n . When compared with Best(Pub _n ), ChronoAdd(Pub _n ) scores demonstrate more consistent high-risk classification amongst themselves. This integrative scoring approach provides stable and reliable classification of high-risk individuals and is an adaptable framework into which new scores can be incorporated as they are introduced, integrating easily with current PRS implementation strategies.
Competing Interests: Competing interests: A.C.F. reports being a co-founder of Goodpath, serving as scientific advisor to MyOme and HeartFlow, and receiving a research grant from Foresite Labs. J.W.S. is a member of the Scientific Advisory Board of Sensorium Therapeutics (with options), has received grant support from Biogen, Inc., and is PI of a collaborative study of the genetics of depression and bipolar disorder sponsored by 23andMe for which 23andMe provides analysis time as in-kind support but no payments. P.N. reports research grants from Allelica, Amgen, Apple, Boston Scientific, Genentech / Roche, and Novartis, personal fees from Allelica, Apple, AstraZeneca, Blackstone Life Sciences, Creative Education Concepts, CRISPR Therapeutics, Eli Lilly & Co, Esperion Therapeutics, Foresite Labs, Genentech / Roche, GV, HeartFlow, Magnet Biomedicine, Merck, Novartis, TenSixteen Bio, and Tourmaline Bio, equity in Bolt, Candela, Mercury, MyOme, Parameter Health, Preciseli, and TenSixteen Bio, and spousal employment at Vertex Pharmaceuticals, all unrelated to the present work. The remaining authors declare no competing interests.
(© 2025. The Author(s).)