Five supplementary tables and one supplementary figure. Supplementary Table 1. Performance of gene expression prediction models built. Supplementary Table 2. Twenty-five lambda pairs and the corresponding prediction performance in the tuning set for prediction models of the 13 associated genes. Supplementary Table 3. Associations of age, sex, top principle components, and assessed pancreatic cancer risk variants with pancreatic cancer risk in conditional analyses of 13 associated genes. Supplementary Table 4. The functions of RCCD1, and CFDP1 and their reported links with human cancers. Supplementary Table 5. Associations of genes identified in Zhong et al. with pancreatic cancer risk in the present study. Supplementary Figure 1. The flowchart of quality control and prediction model training in the reference dataset.
Funding
University of Hawaii Cancer Center
NCI
National Human Genome Research Institute
NIH
Harbin Medical University Cancer Hospital
Department of Education of Fujian Province
American Society of Clinical Oncology Conquer Cancer Foundation
Howard Hughes Medical Institute
Lustgarten Foundation
Pancreatic Cancer Research and Promises for Purple
Mayo Clinic Biospecimen Resource for Pancreas Research
Ontario Pancreas Cancer Study (OPCS)
Center for Inherited Disease Research (CIDR)
National Eye Institute
Find out more...ARTICLE ABSTRACT
Pancreatic cancer is among the most well-characterized cancer types, yet a large proportion of the heritability of pancreatic cancer risk remains unclear. Here, we performed a large transcriptome-wide association study to systematically investigate associations between genetically predicted gene expression in normal pancreas tissue and pancreatic cancer risk. Using data from 305 subjects of mostly European descent in the Genotype-Tissue Expression Project, we built comprehensive genetic models to predict normal pancreas tissue gene expression, modifying the UTMOST (unified test for molecular signatures). These prediction models were applied to the genetic data of 8,275 pancreatic cancer cases and 6,723 controls of European ancestry. Thirteen genes showed an association of genetically predicted expression with pancreatic cancer risk at an FDR ≤ 0.05, including seven previously reported genes (INHBA, SMC2, ABO, PDX1, RCCD1, CFDP1, and PGAP3) and six novel genes not yet reported for pancreatic cancer risk [6q27: SFT2D1 OR (95% confidence interval (CI), 1.54 (1.25–1.89); 13q12.13: MTMR6 OR (95% CI), 0.78 (0.70–0.88); 14q24.3: ACOT2 OR (95% CI), 1.35 (1.17–1.56); 17q12: STARD3 OR (95% CI), 6.49 (2.96–14.27); 17q21.1: GSDMB OR (95% CI), 1.94 (1.45–2.58); and 20p13: ADAM33 OR (95% CI): 1.41 (1.20–1.66)]. The associations for 10 of these genes (SFT2D1, MTMR6, ACOT2, STARD3, GSDMB, ADAM33, SMC2, RCCD1, CFDP1, and PGAP3) remained statistically significant even after adjusting for risk SNPs identified in previous genome-wide association study. Collectively, this analysis identified novel candidate susceptibility genes for pancreatic cancer that warrant further investigation.
A transcriptome-wide association analysis identified seven previously reported and six novel candidate susceptibility genes for pancreatic cancer risk.
