Abstract
Background: We recently developed a multi-ancestry polygenic risk score (PRS) that effectively stratifies prostate cancer risk across populations. In this study, we validated the performance of the PRS in the multi-ancestry Million Veteran Program (MVP) and additional independent studies. Methods: Within each ancestry population, the association of PRS with prostate cancer risk was evaluated separately in each case-control study and then combined in a fixed-effects inverse51 variance-weighted meta-analysis. We further assessed the effect modification by age and estimated the age-specific absolute risk of prostate cancer for each ancestry population. Results: The PRS was evaluated in 31,925 cases and 490,507 controls, including men from European (22,049 cases, 414,249 controls), African (8,794 cases, 55,657 controls), and Hispanic (1,082 cases, 20,601 controls) populations. Comparing men in the top decile (90-100% of the PRS) to the average 40-60% PRS category, the prostate cancer odds ratio (OR) was 3.8-fold in European ancestry men (95% CI=3.62-3.96), 2.8-fold in African ancestry men (95% CI=2.59-3.03), and 3.2-fold in Hispanic men (95% CI=2.64-3.92). The PRS did not discriminate risk of aggressive versus non-aggressive prostate cancer. However, the OR diminished with advancing age (European ancestry men in the top decile: ≤55 years, OR=7.11; 55-60 years, OR=4.26; >70 years, OR=2.79). Men in the top PRS decile reached 5% absolute prostate cancer risk ~10 years younger than men in the 40-60% PRS category. Conclusions: Our findings validate the multi-ancestry PRS as an effective prostate cancer risk stratification tool across populations. A clinical study of PRS is warranted to determine if the PRS could be used for risk-stratified screening and early detection.
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CITATION STYLE
Chena, F., Darst, B. F., Madduri, R. K., Rodriguez, A. A., Sheng, X., Rentsch, C. T., … Haiman, C. A. (2022). Validation of a Multi-ancestry Polygenic Risk Score and Age-Specific Risks of Prostate Cancer: A Meta-analysis Within Diverse Populations. ELife, 11. https://doi.org/10.7554/elife.78304
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