How Well do Polygenic Risk Scores Identify Men at High Risk for Prostate Cancer? Systematic Review and Meta-Analysis
Aino Siltari, Ragnar Lönnerbro, Karl H. Pang, Кирилл Ширанов, Alex Asiimwe, Susan Evans‐Axelsson, Billy Franks, Amit Kiran, Teemu J. Murtola, Jack A. Schalken, Carl Steinbeißer, Anders Bjartell, Anssi Auvinen, James N’Dow, Emma Jane Smith, Ray W. Shepherd, María J. Ribal, Nicolas Mottet, Lisa Moris, M. Lardas, P-P. Willemse, Giorgio Gandaglia, Riccardo Campi, Rossella Nicoletti, Mauro Gacci, Alberto Briganti, M.M. Ratti, Eugenia Alleva, Luca Leardini, E.S. Sisca, R. Bangma, Monique J. Roobol, Sebastiaan Remmers, Derya Tilki, Tapio Visakorpi, Kirsi Talala, Teuvo L.J. Tammela, Mieke Van Hemelrijck, Kristijan Bayer, Stéphane Lejeune, Stephanie Byrne, L. Fialho, P. Palaiologou B. De Meulder, C. Auffray, Ayman Hijazy, Shaun Power, Nazanin Zounemat Kermani, Kees van Bochove, Maria Kalafati, M. Moinat, Erica A. Voss, Denis Horgan, Louise Fullwood, Marc Holtorf, Doron Lancet, Gregory Bernstein, Islam Omar, Steven MacLennan, Steven MacLennan, S. Tripathee, M. Wirth, Michael Froehner, Baruch Brenner, Angelika Borkowetz, Christian Thomas, Friedemann Horn, K. Reiche, M. Kreux, Andreas Josefsson, D. Gasi Tandefekt, Jonas Hugosson, Henkjan Huisman, Jack A. Schalken, T. Hofmacher, Peter Lindgren, Emelie Andersson, Adam Fridhammar, J. Zong, J-E. Butler-Ransohoff, R. Herrera, Matthias Maass, P. Torremante, M Voss, Zsuzsanna Devecseri, Thomas A. Abbott, Chad Dau, Kishore Papineni, Robert Snijder, Maarten Lambrecht, R. Wolfinger, S. Rogiers, A. Servan, Luca Antoni, K. Pacoe, P. A. Robinson, Bertrand Jaton, Daniel Bakkard, H. Turunen, O. Kilkku, P. Pohjanjousi
Abstract
ObjectivesGenome-wide association studies have revealed over 200 genetic susceptibility loci for prostate cancer (PCa). By combining them, polygenic risk scores (PRS) can be generated to predict risk of PCa. We summarize the published evidence and conduct meta-analyses of PRS as a predictor of PCa risk in Caucasian men.Patients and methodsData were extracted from 59 studies, with 16 studies including 17 separate analyses used in the main meta-analysis with a total of 20,786 cases and 69,106 controls identified through a systematic search of ten databases. Random effects meta-analysis was used to obtain pooled estimates of area under the receiver-operating characteristic curve (AUC). Meta-regression was used to assess the impact of number of single-nucleotide polymorphisms (SNPs) incorporated in PRS on AUC. Heterogeneity is expressed as I2 scores. Publication bias was evaluated using funnel plots and Egger tests.ResultsThe ability of PRS to identify men with PCa was modest (pooled AUC 0.63, 95% CI 0.62-0.64) with moderate consistency (I2 64%). Combining PRS with clinical variables increased the pooled AUC to 0.74 (0.68-0.81). Meta-regression showed only negligible increase in AUC for adding incremental SNPs. Despite moderate heterogeneity, publication bias was not evident.ConclusionTypically, PRS accuracy is comparable to PSA or family history with a pooled AUC value 0.63 indicating mediocre performance for PRS alone.