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. 2020 Oct 13;10(1):17075.
doi: 10.1038/s41598-020-74172-z.

Prostate cancer risk prediction using a polygenic risk score

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Free PMC article

Prostate cancer risk prediction using a polygenic risk score

Csilla Sipeky et al. Sci Rep. .
Free PMC article

Abstract

Hereditary factors have a strong influence on prostate cancer (PC) risk and poorer outcomes, thus stratification by genetic factors addresses a critical need for targeted PC screening and risk-adapted follow-up. In this Finnish population-based retrospective study 2283 clinically diagnosed and 455 screen-detected patients from the Finnish Randomised Study of Screening for Prostate Cancer (FinRSPC), 2400 healthy individuals have been involved. Individual genetic risk through establishment of a polygenic risk score based on 55 PC risk SNPs identified through the Finnish subset of the Collaborative Oncological Gene-Environment Study was assessed. Men with PC had significantly higher median polygenic risk score compared to the controls (6.59 vs. 3.83, P < 0.0001). The polygenic risk score above the control median was a significant predictor of PC (OR 2.13, 95% CI 1.90-2.39). The polygenic risk score predicted the risk of PC with an AUC of 0.618 (95% CI 0.60-0.63). Men in the highest polygenic risk score quartile were 2.8-fold (95% CI 2.4-3.30) more likely to develop PC compared with men in the lowest quartile. In the FinRSPC cohort, a significantly higher percentage of men had a PSA level of ≥ 4 ng/mL in polygenic risk score quartile four compared to quartile one (18.7% vs 8.3%, P < 0.00001). Adding the PRS to a PSA-only model contributed additional information in predicting PC in the FinRSPC model. Results strongly suggest that use of the polygenic risk score would facilitate the identification of men at increased risk for PC.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Flow diagram presenting the steps of participant's enrollment to the study (a) and selection of SNPs for polygenic risk score (b) QC, quality control; FDR, false discovery rate, corrected by Benjamini–Hochberg method.

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