Genome-wide association studies (GWAS) have detected several susceptibility variants for urinary bladder cancer, but how gene regulation affects disease development remains unclear. To extend GWAS findings, we conducted a transcriptome-wide association study (TWAS) using PrediXcan to predict gene expression levels in whole blood using genome-wide genotype data for 6180 bladder cancer cases and 5699 controls included in the database of Genotypes and Phenotypes (dbGaP). Logistic regression was used to estimate adjusted gene-level odds ratios (OR) per 1-standard deviation higher expression with 95% confidence intervals (CI) for bladder cancer risk. We further assessed associations for individual single-nucleotide polymorphisms (SNPs) used to predict expression levels and proximal loci for genes identified in gene-level analyses with false-discovery rate (FDR) correction. TWAS identified four genes for which expression levels were associated with bladder cancer risk: SLC39A3 (OR = 0.91, CI = 0.87-0.95, FDR = 0.015), ZNF737 (OR = 0.91, CI = 0.88-0.95, FDR = 0.016), FAM53A (OR = 1.09, CI = 1.05-1.14, FDR = 0.022), and PPP1R2 (OR = 1.09, CI = 1.05-1.13, FDR = 0.049). Findings from this TWAS enhance our understanding of how genetically-regulated gene expression affects bladder cancer development and point to potential prevention and treatment targets.
Scientific reports. 2025 Jan 09*** epublish ***
Siting Li, Jiang Gui, Margaret R Karagas, Michael N Passarelli
Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Hanover, NH, USA., Department of Epidemiology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA., Department of Epidemiology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA. .