MP44-18 IDENTIFYING CANDIDATE GENE DEFECTS WITH COPY NUMBER VARIATION UNDERLYING VESICOURETERAL REFLUX

Abstract

You have accessJournal of UrologyPediatrics: Urinary Tract Infection & Vesicoureteral Relux1 Apr 2014MP44-18 IDENTIFYING CANDIDATE GENE DEFECTS WITH COPY NUMBER VARIATION UNDERLYING VESICOURETERAL REFLUX Abhishek Seth, In-Seon Choi, James C. Sander, Meade Haller, Chester J. Koh, David R. Roth, Carolina J. Jorgez, and Dolores J. Lamb Abhishek SethAbhishek Seth More articles by this author , In-Seon ChoiIn-Seon Choi More articles by this author , James C. SanderJames C. Sander More articles by this author , Meade HallerMeade Haller More articles by this author , Chester J. KohChester J. Koh More articles by this author , David R. RothDavid R. Roth More articles by this author , Carolina J. JorgezCarolina J. Jorgez More articles by this author , and Dolores J. LambDolores J. Lamb More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2014.02.1393AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail Introduction and Objectives Vesicoureteric reflux (VUR) affects approximately 1-2% of children in western countries and is a significant risk factor for clinical pyelonephritis and renal scarring. A genetic basis for VUR has been inferred through genetic linkage analysis studies, yet few candidate genes have been identified. The purpose of this study is to identify novel gene defects with copy number variation (CNV) in pediatric patients with VUR. We hypothesized that we can use genome-wide comparative genomic hybridization microarray (aCGH) analysis to identify microdeletions and microduplications in autosomal regions underlying VUR. Methods Genomic DNA from 35 pediatric patients with VUR and 5 control patients was analyzed by aCGH using 720K NimbleGen arrays (Roche). This data was then analyzed using Nexus Copy Number software (BioDiscovery). Quantitative PCR was performed using CNV-taqman assays to validate putative regions of duplication or deletion that were distinct from CNVs found throughout the genome. Results Five candidate genes with microduplications were identified. These genes included MAP1LC3C (1q43), COL23A1 (5q35.3), CLK4 (5q35.3), KDM4C (9p24.1), KIAA1217 (10p12.2). In contrast, KCNG4 (16q24.1) was the sole gene identified with a microdeletion. All 6 of these genes were validated using qPCR. Defects in COL23A1, CLK4, KDM4C, KIAA1217 and KCNG4 were found to be maternally inherited. Defect in MAP1LC3C was found to be de novo. All deletions and duplications were outside areas of known CNVs and were not present in healthy, disease-free controls. Incidence of known defects in these candidate genes is very low and ranges from 0.03 to 0.19% as extracted from the DECIPHER database. Also, we found multiple other patients (2-6) in the DECIPHER database with defects in these candidate genes that also had GU tract anomalies, including but not limited to VUR, strengthening the association between these gene defects and VUR. Conclusions We have used aCGH analysis to identify possible novel gene defects that may be responsible for VUR. Recapitulation of VUR in transgenic mice models with defects in these candidate genes will prove causation beyond association. © 2014FiguresReferencesRelatedDetails Volume 191Issue 4SApril 2014Page: e449 Advertisement Copyright & Permissions© 2014MetricsAuthor Information Abhishek Seth More articles by this author In-Seon Choi More articles by this author James C. Sander More articles by this author Meade Haller More articles by this author Chester J. Koh More articles by this author David R. Roth More articles by this author Carolina J. Jorgez More articles by this author Dolores J. Lamb More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...