PD15-06 GENETIC RISK SCORE DIFFERENTIATES INHERITED RISK AMONG RELATIVES OF PATIENTS WITH HEREDITARY PROSTATE CANCER

Abstract

You have accessJournal of UrologyProstate Cancer: Detection & Screening IV1 Apr 2016PD15-06 GENETIC RISK SCORE DIFFERENTIATES INHERITED RISK AMONG RELATIVES OF PATIENTS WITH HEREDITARY PROSTATE CANCER Brian T. Helfand, Vignesh T. Packiam, Haitao Chen, S. Lilly Zheng, Carly A. Conran, Charles B. Brendler, William B. Isaacs, and Jianfeng Xu Brian T. HelfandBrian T. Helfand More articles by this author , Vignesh T. PackiamVignesh T. Packiam More articles by this author , Haitao ChenHaitao Chen More articles by this author , S. Lilly ZhengS. Lilly Zheng More articles by this author , Carly A. ConranCarly A. Conran More articles by this author , Charles B. BrendlerCharles B. Brendler More articles by this author , William B. IsaacsWilliam B. Isaacs More articles by this author , and Jianfeng XuJianfeng Xu More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2016.02.1132AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Clinical guidelines for prostate cancer (PCa) recommend targeted screening for men with a family history of the disease. However, family history assigns equivalent risk to relatives based upon the degree of relationship to affected family members. Recent genetic studies have identified single nucleotide polymorphisms (SNPs) that can be used to calculate a genetic risk score (GRS) to determine PCa risk. We examined whether GRS can stratify PCa risk among high-risk hereditary PCa families. METHODS Family members of patients with hereditary PCa were recruited and genotyped for 17 PCa risk-associated SNPs. A GRS was calculated for each family member using weighted odds ratios (ORs) and allele frequencies for each SNP obtained from previously published meta-analyses. A GRS of 1.0 indicates an average risk of developing PCa in the general population, while a GRS greater or less than 1.0 indicates increased or decreased disease risk, respectively. The generalized estimating equation (GEE) model was used to account for the relatedness of men within each family. Univariate and multivariate analyses were performed to compare the distribution of GRSs amongst affected and unaffected family members of similar and different degrees of relation. RESULTS Data was available for 789 family members of probands, of which 552 had PCa and 237 did not. There was a wide range of GRSs among family members with the same degree of relationship to a proband. The interquartile range (IQR) for GRSs among first-degree relatives ranged from 0.76 to 1.84. The median GRS was significantly higher among first-degree relatives compared to second- and third-degree relatives (GRS 1.20 vs. 1.09 vs. 1.00, p<0.001). GRSs among affected first- and second-degree relatives were significantly higher than unaffected relatives (p=0.04 and p=0.01, respectively). On univariate analysis, degree of family relationship (OR 1.85, p<0.001) and GRS (OR 1.52, p<0.001) were both independent predictors of PCa. Multivariate analysis controlling for degree of relationship demonstrated that GRS was a significant and independent predictor of PCa (OR 1.52, 95% CI: 1.15-2.01). CONCLUSIONS GRS can augment family history in differentiating inherited PCa risk among relatives of PCa patients. While prospective validation studies are required, this information can help provide guidance for these relatives in determining initiation and frequency of PCa testing. © 2016FiguresReferencesRelatedDetails Volume 195Issue 4SApril 2016Page: e391 Advertisement Copyright & Permissions© 2016MetricsAuthor Information Brian T. Helfand More articles by this author Vignesh T. Packiam More articles by this author Haitao Chen More articles by this author S. Lilly Zheng More articles by this author Carly A. Conran More articles by this author Charles B. Brendler More articles by this author William B. Isaacs More articles by this author Jianfeng Xu More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...