You have accessJournal of UrologyStone Disease: Basic Research & Pathophysiology I (PD04)1 Apr 2020PD04-08 POLYGENIC RISK SCORE ASSOCIATES WITH URINARY TRACT STONE DIAGNOSIS IN MULTIETHNIC COHORT Ishan Paranjpe, Anna Zampini*, Ross O'Hagan, Manish Paranjpe, Kumardeep Chaudhary, Arjun Kapoor, Suraj Jaladanki, John Pfail, Lili Chan, John Cijiang He, Steven Coca, Mantu Gupta, and Girish Nadkarni Ishan ParanjpeIshan Paranjpe More articles by this author , Anna Zampini*Anna Zampini* More articles by this author , Ross O'HaganRoss O'Hagan More articles by this author , Manish ParanjpeManish Paranjpe More articles by this author , Kumardeep ChaudharyKumardeep Chaudhary More articles by this author , Arjun KapoorArjun Kapoor More articles by this author , Suraj JaladankiSuraj Jaladanki More articles by this author , John PfailJohn Pfail More articles by this author , Lili ChanLili Chan More articles by this author , John Cijiang HeJohn Cijiang He More articles by this author , Steven CocaSteven Coca More articles by this author , Mantu GuptaMantu Gupta More articles by this author , and Girish NadkarniGirish Nadkarni More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000000824.08AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Urinary tract stones have high heritability indicating a strong genetic component. However, genome wide association studies (GWAS) have uncovered only a few genome wide significant single nucleotide polymorphisms (SNPs). Polygenic scores sum the cumulative effect of many SNPs and shed light on underlying genetic architecture. METHODS: Using LDPred adjusted GWAS summary statistics from the UK Biobank (n=361,141), we generated a polygenic risk score (PRS) for urinary tract stone diagnosis which was ascertained using diagnostic codes. We then associated the PRS with stone diagnosis in a biobanked cohort using imputed genotyping data (BioMe Biobank, n=28,877) in a logistic regression model adjusted for ten genetic principal components (PCs), sex, age, body mass index (BMI), and history of gout, hypertension, and type 2 diabetes. Analyses were performed separately in racial groups and a meta-analysis was performed using the inverse-weighting method. A low risk cohort was defined as individuals with BMI <25 and no history of gout, hypertension, or type 2 diabetes. RESULTS: In our cohort (1,071 cases, 27,828 controls), for every standard deviation (SD) increase in PRS, we observed an increment in adjusted odds ratio (OR) of 1.2 (95% confidence interval 1.13-1.26; p<0.001). Individuals in the top PRS decile had adjusted OR of 2.6 (95% confidence interval 1.9 –3.6; p<0.001) for diagnosis compared to the lowest decile. Upon stratifying by clinical risk factors, we observed an increment in adjusted OR of 1.3 (95% confidence interval 1.12 – 1.58; p = 0.001) in the low-risk and 1.2 (95% confidence interval 1.1 – 1.2; p = 1.1 x 10-6) in the high-risk group for every SD increment in PRS. CONCLUSIONS: This study shows that a genome wide polygenic score is associated with urinary tract stones overall and in the absence of known clinical risk factors and provides insight into the complex genetic architecture of stones. This score may allow for early stratification of urinary tract stone risk in individuals without a history of stone formation or other clinical risk factors. Source of Funding: NA © 2020 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 203Issue Supplement 4April 2020Page: e81-e81 Advertisement Copyright & Permissions© 2020 by American Urological Association Education and Research, Inc.MetricsAuthor Information Ishan Paranjpe More articles by this author Anna Zampini* More articles by this author Ross O'Hagan More articles by this author Manish Paranjpe More articles by this author Kumardeep Chaudhary More articles by this author Arjun Kapoor More articles by this author Suraj Jaladanki More articles by this author John Pfail More articles by this author Lili Chan More articles by this author John Cijiang He More articles by this author Steven Coca More articles by this author Mantu Gupta More articles by this author Girish Nadkarni More articles by this author Expand All Advertisement PDF downloadLoading ...