MP28-10 GENETIC RISK SCORE-BASED MODELS CAN DISCRIMINATE THE RISK FOR DEVELOPING BENIGN PROSTATIC HYPERPLASIA AND PROSTATE CANCER

Abstract

You have accessJournal of UrologyBenign Prostatic Hyperplasia: Epidemiology & Evaluation (MP28)1 Sep 2021MP28-10 GENETIC RISK SCORE-BASED MODELS CAN DISCRIMINATE THE RISK FOR DEVELOPING BENIGN PROSTATIC HYPERPLASIA AND PROSTATE CANCER Alexander Glaser, Zhuqing Shi, Jun Wei, Brian Helfand, and Jianfeng Xu Alexander GlaserAlexander Glaser More articles by this author , Zhuqing ShiZhuqing Shi More articles by this author , Jun WeiJun Wei More articles by this author , Brian HelfandBrian Helfand More articles by this author , and Jianfeng XuJianfeng Xu More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002025.10AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Middle age men, especially those with modestly increased PSA levels, are at increased risk for diagnosis of prostate cancer (PCa) and/or benign prostatic hyperplasia (BPH). Both of these disease states are highly heritable and their underlying genetics can be largely explained by polygenic risk scores. However, the ability for the genetic risk scores (GRS) to distinguish these two disease states is unknown. METHODS: Data from the UK Biobank (UKB) was split into a training set (4,927 PCa diagnoses, 98,543 controls; 11,840 BPH diagnoses, 91,630 controls) and testing set (3,345 PCa diagnoses, 65,635 controls; 7.779 BPH diagnoses, 61,181 controls). Genetic risk scores for PCa and BPH were calculated as previously described. Multivariate analysis was performed to develop and validate factors associated with diagnosis of PCa and BPH including age, body mass index (BMI), testosterone (T), prostatitis, and diabetes mellitus type 2 (DM2). RESULTS: In multivariable analysis, PCa GRS was significantly associated with PCa risk, independent of other known predictors (Table; C-statistic 0.76 in both datasets). Similarly, BPH GRS was significantly associated with the risk of BPH, independent of other known predictors (Table; C-statistic 0.74 in both datasets). Using a combination of these two genetic models can better predict and discriminate the risk for PCa and BPH (Figure). For example, 4% and 22% men were diagnosed with PCa and BPH, respectively in men with low probability for PCa (<0.2) and high probability for BPH (≥0.8). In comparison, 10.1% and 13.9% men were diagnosed with PCa and BPH, respectively in men with high probability for PCa (≥0.2) and low probability for BPH (<0.8). CONCLUSIONS: In a large population-based prospective study, a multivariate model including genetic risk score has high discriminative ability to determine the subsequent risk of developing BPH and/or PCa. Incorporation of GRS holds potential to help clarify decisions around men with elevated PSA values. Further exploration of the genetic overlap of these disease states is warranted. Source of Funding: None © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 206Issue Supplement 3September 2021Page: e484-e485 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.MetricsAuthor Information Alexander Glaser More articles by this author Zhuqing Shi More articles by this author Jun Wei More articles by this author Brian Helfand More articles by this author Jianfeng Xu More articles by this author Expand All Advertisement Loading ...