The Rare Variant rs35356162 in UHRF1BP1 Increases Bladder Cancer Risk in Han Chinese Population

Academic Article

Abstract

  • Background: Seventeen loci have been found to be associated with bladder cancer risk by genome-wide association studies (GWAS) in European population. However, little is known about contribution of low-frequency and rare variants to bladder cancer susceptibility, especially in Eastern population. Methods: We performed a three-stage case-control study including 3,399 bladder cancer patients and 4,647 controls to identify low-frequency and rare variants associated with bladder cancer risk in Han Chinese. We examined exome-array data in 1,019 bladder cancer patients and 1,008 controls in discovery stage. Two replication stages were included to validate variants identified. Bonferroni adjustment was performed to define statistical significance. Logistic regression was conducted to evaluate single marker association with bladder cancer risk. We used SKAT-O method to perform gene level-based analysis. We also conduct additional experiments to explore the underlying mechanism of filtered gene(s). Results: We identified a novel rare coding variant (rs35356162 in UHRF1BP1: G > T, OR = 4.332, P = 3.62E-07 < 7.93E-07, Bonferroni cutoff) that increased bladder cancer risk in Han Chinese. Gene-level analysis showed a significant association of UHRF1BP1 (P = 4.47E-03) with bladder cancer risk. Experiments indicated down-regulation of UHRF1BP1 promoted migration and invasion through epithelial-mesenchymal transition in bladder cancer cell lines. Conclusion: The rare variant of UHRF1BP1, rs35356162, increases bladder cancer risk in Han Chinese and UHRF1BP1 might act as a tumor suppressor in bladder cancer development and progression. Summary: Little is known about potential contribution of low-frequency and rare variants to bladder cancer susceptibility. We performed a three-stage case-control study and identified a new rare variant, rs35356162 in UHRF1BP1, which increased bladder cancer risk in Han Chinese.
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    Author List

  • Wu J; Wang M; Chen H; Xu J; Zhang G; Gu C; Ding Q; Wei Q; Zhu Y; Ye D
  • Volume

  • 10