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    Additional SNPs improve risk stratification of a polygenic hazard score for prostate cancer

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    Authors
    Karunamuni, R. A.
    Huynh-Le, M. P.
    Fan, C. C.
    Thompson, W.
    Eeles, R. A.
    Kote-Jarai, Z.
    Muir, K.
    Lophatananon, A.
    Schleutker, J.
    Pashayan, N.
    Batra, J.
    Grönberg, H.
    Walsh, E. I.
    Turner, E. L.
    Lane, A.
    Martin, R. M.
    Neal, D. E.
    Donovan, J. L.
    Hamdy, F. C.
    Nordestgaard, B. G.
    Tangen, C. M.
    MacInnis, R. J.
    Wolk, A.
    Albanes, D.
    Haiman, C. A.
    Travis, R. C.
    Stanford, J. L.
    Mucci, L. A.
    West, Catharine M L
    Nielsen, S. F.
    Kibel, A. S.
    Wiklund, F.
    Cussenot, O.
    Berndt, S. I.
    Koutros, S.
    Sørensen, K. D.
    Cybulski, C.
    Grindedal, E. M.
    Park, J. Y.
    Ingles, S. A.
    Maier, C.
    Hamilton, R. J.
    Rosenstein, B. S.
    Vega, A.
    Kogevinas, M.
    Penney, K. L.
    Teixeira, M. R.
    Brenner, H.
    John, E. M.
    Kaneva, R.
    Logothetis, C. J.
    Neuhausen, S. L.
    Razack, A.
    Newcomb, L. F.
    Gamulin, M.
    Usmani, N.
    Claessens, F.
    Gago-Dominguez, M.
    Townsend, P. A.
    Roobol, M. J.
    Zheng, W.
    Mills, I. G.
    Andreassen, O. A.
    Dale, A. M.
    Seibert, T. M.
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    Affiliation
    Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA, USA.
    Issue Date
    2021
    
    Metadata
    Show full item record
    Abstract
    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.
    Citation
    Karunamuni RA, Huynh-Le MP, Fan CC, Thompson W, Eeles RA, Kote-Jarai Z, et al. Additional SNPs improve risk stratification of a polygenic hazard score for prostate cancer. Prostate Cancer Prostatic Dis. 2021.
    Journal
    Prostate Cancer and Prostatic Diseases
    URI
    http://hdl.handle.net/10541/623725
    DOI
    10.1038/s41391-020-00311-2
    PubMed ID
    33420416
    Additional Links
    https://dx.doi.org/10.1038/s41391-020-00311-2
    Type
    Article
    Language
    en
    ae974a485f413a2113503eed53cd6c53
    10.1038/s41391-020-00311-2
    Scopus Count
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