African‐specific improvement of a polygenic hazard score for age at diagnosis of prostate cancer. Issue 1 (24th September 2020) - Karunamuni, Roshan A.; Huynh‐Le, Minh‐Phuong; Fan, Chun C.; Thompson, Wesley; Eeles, Rosalind A.; Kote‐Jarai, Zsofia; Muir, Kenneth; ,; Lophatananon, Artitaya; Tangen, Catherine M.; Goodman, Phyllis J.; Thompson, Ian M.; et al.
Abstract: Polygenic hazard score (PHS) models are associated with age at diagnosis of prostate cancer. Our model developed in Europeans (PHS46) showed reduced performance in men with African genetic ancestry. We used a cross‐validated search to identify single nucleotide polymorphisms (SNPs) that might improve performance in this population. Anonymized genotypic data were obtained from the PRACTICAL consortium for 6253 men with African genetic ancestry. Ten iterations of a 10‐fold cross‐validation search were conducted to select SNPs that would be included in the final PHS46+African model. The coefficients of PHS46+African were estimated in a Cox proportional hazards framework using age at diagnosis as the dependent variable and PHS46, and selected SNPs as predictors. The performance of PHS46 and PHS46+African was compared using the same cross‐validated approach. Three SNPs (rs76229939, rs74421890 and rs5013678) were selected for inclusion in PHS46+African. All three SNPs are located on chromosome 8q24. PHS46+African showed substantial improvements in all performance metrics measured, including a 75% increase in the relative hazard of those in the upper 20% compared to the bottom 20% (2.47‐4.34) and a 20% reduction in the relative hazard of those in the bottom 20% compared to the middle 40% (0.65‐0.53). In conclusion, we identified three SNPs that substantially improved the association of PHS46 with age at diagnosis of prostate cancer in men with African genetic ancestry to levels comparable to Europeans. Abstract : What's new? Polygenic models can provide personalized estimates of cancer risk. However, Africans are a population generally under‐served in genome‐wide studies. In this report, the authors used machine learning to identify three SNPs that significantly improved the performance of an established polygenic‐hazard model of prostate‐cancer risk vs age at diagnosis, specifically tailored to men of African genetic ancestry. Inclusion of these SNPs improved the performance of this novel 'PHS46+African' score by as much as 79% compared to the original model, to levels comparable with Europeans.