Evaluating approaches for constructing polygenic risk scores for prostate cancer in men of African and European ancestry

NC-LA PCaP Investigators, Canary PASS Investigators

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Genome-wide polygenic risk scores (GW-PRSs) have been reported to have better predictive ability than PRSs based on genome-wide significance thresholds across numerous traits. We compared the predictive ability of several GW-PRS approaches to a recently developed PRS of 269 established prostate cancer-risk variants from multi-ancestry GWASs and fine-mapping studies (PRS269). GW-PRS models were trained with a large and diverse prostate cancer GWAS of 107,247 cases and 127,006 controls that we previously used to develop the multi-ancestry PRS269. Resulting models were independently tested in 1,586 cases and 1,047 controls of African ancestry from the California Uganda Study and 8,046 cases and 191,825 controls of European ancestry from the UK Biobank and further validated in 13,643 cases and 210,214 controls of European ancestry and 6,353 cases and 53,362 controls of African ancestry from the Million Veteran Program. In the testing data, the best performing GW-PRS approach had AUCs of 0.656 (95% CI = 0.635–0.677) in African and 0.844 (95% CI = 0.840–0.848) in European ancestry men and corresponding prostate cancer ORs of 1.83 (95% CI = 1.67–2.00) and 2.19 (95% CI = 2.14–2.25), respectively, for each SD unit increase in the GW-PRS. Compared to the GW-PRS, in African and European ancestry men, the PRS269 had larger or similar AUCs (AUC = 0.679, 95% CI = 0.659–0.700 and AUC = 0.845, 95% CI = 0.841–0.849, respectively) and comparable prostate cancer ORs (OR = 2.05, 95% CI = 1.87–2.26 and OR = 2.21, 95% CI = 2.16–2.26, respectively). Findings were similar in the validation studies. This investigation suggests that current GW-PRS approaches may not improve the ability to predict prostate cancer risk compared to the PRS269 developed from multi-ancestry GWASs and fine-mapping.

Original languageEnglish
Pages (from-to)1200-1206
Number of pages7
JournalAmerican Journal of Human Genetics
Volume110
Issue number7
DOIs
StatePublished - 6 Jul 2023

Keywords

  • African ancestry
  • genetics
  • genome-wide polygenic risk score
  • health disparities
  • polygenic risk score
  • prostate cancer
  • risk modeling

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