Abstract 2214: Genome-wide gene-diabetes and gene-obesity interaction scan in the pancreatic cancer case control consortium

Introduction Pancreatic cancer is a highly lethal malignancy due to late diagnosis and aggressiveness of the tumor. Characterization of high-risk populations for monitoring, intervention and early detection remains challenging. Obesity and diabetes are potentially modifiable contributors to pancreatic cancer. Genetic factors modifying the risk of obesity- and diabetes-induced pancreatic cancer have previously not been fully investigated at the genome-wide level. Hypothesis There are potential genetic factors modifying the associations between obesity/diabetes and pancreatic cancer. Methods Integrating genotype with risk factor data from a GWAS for the Pancreatic Cancer Case Control Consortium, we performed a genome-wide gene-environment interaction (G x E) scan for 457,688 SNPs in a discovery study of 2,028 cases and 2,109 controls using state-of-the-art methods including case-only (CO), case-control (CC), Empirical Hierarchical Bayes (EHB), Empirical-Bayes test (EB) and three 2-step approaches (DG2, EG2, DGEG2). Results We detected a genome-wide significant (P -7 ) interaction of diabetes with rs13061928 (in CNTN4) in CO (P = 8.8 x 10 -8 ), which was independent of diabetes in control group (P = 0.08). The minor allele was in a synergism with diabetes on the cancer risk: diabetics carrying GA/AA genotype had a 3.39-fold (95% CI: 2.47-4.65) increased disease risk compared with non-diabetics carrying GG genotype. Consistently, the SNP-diabetes interaction had a high ranking statistic in EHB (No.1) and high p-value ranks for EG2 and DGEG2 methods (No.1, P= 5.44 x 10 -5 ). Conclusions These observations, once validated/confirmed, may help define at-risk subpopulation and initiate targeted intervention and prevention of pancreatic cancer. Genome-wide G x E analysis requires larger sample size than genetic main effects scan; combining the CO method with alternative methods may be the optimal scheme for genome-wide G x E analysis. Citation Format: Hongwei Tang, Eric J. Duell, Harvey A. Risch Risch, Sara H. Olson, H. Bas Bueno-de-Mesquita, Steven Gallinger, Elizabeth A. Holly, Gloria M. Petersen, Paige M. Bracci, Robert R. McWilliams, Mazda Jenab, Elio Riboli, Anne Tjonneland, Marie Christine Boutron-Ruault, Rudolf Kaaks, Dimitrios Trichopoulos, Salvatore Panico, Malin Sund, Petra H. M Peeters, Kay-Tee Khaw, Christopher I Amos, Donghui Li, Peng Wei. Genome-wide gene-diabetes and gene-obesity interaction scan in the pancreatic cancer case control consortium. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2214. doi:10.1158/1538-7445.AM2014-2214