Validation of a prostate cancer polygenic risk score

Abstract

Background: Genome-wide association studies have identified over 100 single-nucleotide polymorphisms (SNPs) associated with prostate cancer (PrCa), and polygenic risk scores (PRS) based on their combined genotypes have been developed for risk stratification. We aimed to assess the contribution of PRS to PrCa risk in a large multisite study.

Methods: The sample included 1972 PrCa cases and 1919 unaffected controls. Next-generation sequencing was used to assess pathogenic variants in 14 PrCa-susceptibility genes and 72 validated PrCa-associated SNPs. We constructed a population-standardized PRS and tested its association with PrCa using logistic regression adjusted for age and family history of PrCa.

Results: The mean age of PrCa cases at diagnosis and age of controls at testing/last clinic visit was 59.5 ± 7.2 and 57.2 ± 13.0 years, respectively. Among 1740 cases with pathology data, 57.4% had Gleason score ≤ 6, while 42.6% had Gleason score ≥ 8. In addition, 39.6% cases and 20.1% controls had a family history of PrCa. The PRS was significantly higher in cases than controls (mean ± SD: 1.42 ± 1.11 vs 1.02 ± 0.76; P < .0001). Compared with men in the 1st quartile of age-adjusted PRS, those in the 2nd, 3rd, and 4th quartile were 1.58 (95% confidence interval [CI]: 1.31-1.90), 2.36 (95% CI: 1.96-2.84), and 3.98 (95% CI: 3.29-4.82) times as likely to have PrCa (all P < .0001). Adjustment for family history yielded similar results. PRS predictive performance was consistent with prior literature (area under the receiver operating curve = 0.64; 95% CI: 0.62-0.66).

Conclusions: These data suggest that a 72-SNP PRS is predictive of PrCa, supporting its potential use in clinical risk assessment.

Keywords: polygenic; prostate cancer.

Figure 1

Distribution of the sum of risk alleles across 72 single‐nucleotide polymorphisms, for cases (red) compared with controls (blue). Probability density on the y axis represents the proportion of cases and controls, respectively, with a given risk allele count (x axis). The mean ± standard deviation risk allele count in cases vs controls: 64.7 ± 5.4 vs 62.2 ± 5.3; P < .0001 [Color figure can be viewed at wileyonlinelibrary.com]

Figure 2

AUROC for the accuracy of the PRS in distinguishing between prostate cancer cases and controls (AUROC = 0.64, 95% CI: 0.62‐0.66). AUROC, area under the receiver operating curve; CI, confidence interval; PRS, polygenic risk scores

Figure 3

Cumulative lifetime (absolute) risk for prostate cancer by percentiles of PRS, stratified by family history (yes/no). PrCa, prostate cancer; PRS, polygenic risk scores [Color figure can be viewed at wileyonlinelibrary.com]