Additional SNPs improve risk stratification of a polygenic hazard score for prostate cancer.
Karunamuni RA., Huynh-Le M-P., Fan CC., Thompson W., Eeles RA., Kote-Jarai Z., Muir K., Lophatananon A., UKGPCS collaborators None., Schleutker J., Pashayan N., Batra J., APCB BioResource (Australian Prostate Cancer BioResource) None., Grönberg H., Walsh EI., Turner EL., Lane A., Martin RM., Neal DE., Donovan JL., Hamdy FC., Nordestgaard BG., Tangen CM., MacInnis RJ., Wolk A., Albanes D., Haiman CA., Travis RC., Stanford JL., Mucci LA., West CML., Nielsen SF., Kibel AS., Wiklund F., Cussenot O., Berndt SI., Koutros S., Sørensen KD., Cybulski C., Grindedal EM., Park JY., Ingles SA., Maier C., Hamilton RJ., Rosenstein BS., Vega A., IMPACT Study Steering Committee and Collaborators None., Kogevinas M., Penney KL., Teixeira MR., Brenner H., John EM., Kaneva R., Logothetis CJ., Neuhausen SL., Razack A., Newcomb LF., Canary PASS Investigators None., Gamulin M., Usmani N., Claessens F., Gago-Dominguez M., Townsend PA., Roobol MJ., Zheng W., Profile Study Steering Committee None., Mills IG., Andreassen OA., Dale AM., Seibert TM., PRACTICAL Consortium None.
BACKGROUND: Polygenic hazard scores (PHS) can identify individuals with increased risk of prostate cancer. We estimated the benefit of additional SNPs on performance of a previously validated PHS (PHS46). MATERIALS AND METHOD: 180 SNPs, shown to be previously associated with prostate cancer, were used to develop a PHS model in men with European ancestry. A machine-learning approach, LASSO-regularized Cox regression, was used to select SNPs and to estimate their coefficients in the training set (75,596 men). Performance of the resulting model was evaluated in the testing/validation set (6,411 men) with two metrics: (1) hazard ratios (HRs) and (2) positive predictive value (PPV) of prostate-specific antigen (PSA) testing. HRs were estimated between individuals with PHS in the top 5% to those in the middle 40% (HR95/50), top 20% to bottom 20% (HR80/20), and bottom 20% to middle 40% (HR20/50). PPV was calculated for the top 20% (PPV80) and top 5% (PPV95) of PHS as the fraction of individuals with elevated PSA that were diagnosed with clinically significant prostate cancer on biopsy. RESULTS: 166 SNPs had non-zero coefficients in the Cox model (PHS166). All HR metrics showed significant improvements for PHS166 compared to PHS46: HR95/50 increased from 3.72 to 5.09, HR80/20 increased from 6.12 to 9.45, and HR20/50 decreased from 0.41 to 0.34. By contrast, no significant differences were observed in PPV of PSA testing for clinically significant prostate cancer. CONCLUSIONS: Incorporating 120 additional SNPs (PHS166 vs PHS46) significantly improved HRs for prostate cancer, while PPV of PSA testing remained the same.