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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4681468 | PMC |
| http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0144792 | PLOS |
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Department of Epidemiology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA.
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.
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