Integration of polygenic and gut metagenomic risk prediction for common diseases

: Liu Yang, Ritchie Scott C., Teo Shu Mei, Ruuskanen Matti O., Kambur Oleg, Zhu Qiyun, Sanders Jon, Vázquez-Baeza Yoshiki, Verspoor Karin, Jousilahti Pekka, Lahti Leo, Niiranen Teemu, Salomaa Veikko, Havulinna Aki S., Knight Rob, Méric Guillaume, Inouye Michael

Publisher: Nature

: 2024

: Nature Aging

: Nature aging

: Nat Aging

: 2662-8465

DOI: https://doi.org/10.1038/s43587-024-00590-7

: https://www.nature.com/articles/s43587-024-00590-7

: https://research.utu.fi/converis/portal/detail/Publication/387452832

Multiomics has shown promise in noninvasive risk profiling and early detection of various common diseases. In the present study, in a prospective population-based cohort with ~18 years of e-health record follow-up, we investigated the incremental and combined value of genomic and gut metagenomic risk assessment compared with conventional risk factors for predicting incident coronary artery disease (CAD), type 2 diabetes (T2D), Alzheimer disease and prostate cancer. We found that polygenic risk scores (PRSs) improved prediction over conventional risk factors for all diseases. Gut microbiome scores improved predictive capacity over baseline age for CAD, T2D and prostate cancer. Integrated risk models of PRSs, gut microbiome scores and conventional risk factors achieved the highest predictive performance for all diseases studied compared with models based on conventional risk factors alone. The present study demonstrates that integrated PRSs and gut metagenomic risk models improve the predictive value over conventional risk factors for common chronic diseases.

s43587-024-00590-7.pdf