- Li, Donghui;
- Duell, Eric J;
- Yu, Kai;
- Risch, Harvey A;
- Olson, Sara H;
- Kooperberg, Charles;
- Wolpin, Brian M;
- Jiao, Li;
- Dong, Xiaoqun;
- Wheeler, Bill;
- Arslan, Alan A;
- Bueno-de-Mesquita, H Bas;
- Fuchs, Charles S;
- Gallinger, Steven;
- Gross, Myron;
- Hartge, Patricia;
- Hoover, Robert N;
- Holly, Elizabeth A;
- Jacobs, Eric J;
- Klein, Alison P;
- LaCroix, Andrea;
- Mandelson, Margaret T;
- Petersen, Gloria;
- Zheng, Wei;
- Agalliu, Ilir;
- Albanes, Demetrius;
- Boutron-Ruault, Marie-Christine;
- Bracci, Paige M;
- Buring, Julie E;
- Canzian, Federico;
- Chang, Kenneth;
- Chanock, Stephen J;
- Cotterchio, Michelle;
- Gaziano, J Michael;
- Giovannucci, Edward L;
- Goggins, Michael;
- Hallmans, Göran;
- Hankinson, Susan E;
- Hoffman Bolton, Judith A;
- Hunter, David J;
- Hutchinson, Amy;
- Jacobs, Kevin B;
- Jenab, Mazda;
- Khaw, Kay-Tee;
- Kraft, Peter;
- Krogh, Vittorio;
- Kurtz, Robert C;
- McWilliams, Robert R;
- Mendelsohn, Julie B;
- Patel, Alpa V;
- Rabe, Kari G;
- Riboli, Elio;
- Shu, Xiao-Ou;
- Tjønneland, Anne;
- Tobias, Geoffrey S;
- Trichopoulos, Dimitrios;
- Virtamo, Jarmo;
- Visvanathan, Kala;
- Watters, Joanne;
- Yu, Herbert;
- Zeleniuch-Jacquotte, Anne;
- Amundadottir, Laufey;
- Stolzenberg-Solomon, Rachael Z
Four loci have been associated with pancreatic cancer through genome-wide association studies (GWAS). Pathway-based analysis of GWAS data is a complementary approach to identify groups of genes or biological pathways enriched with disease-associated single-nucleotide polymorphisms (SNPs) whose individual effect sizes may be too small to be detected by standard single-locus methods. We used the adaptive rank truncated product method in a pathway-based analysis of GWAS data from 3851 pancreatic cancer cases and 3934 control participants pooled from 12 cohort studies and 8 case-control studies (PanScan). We compiled 23 biological pathways hypothesized to be relevant to pancreatic cancer and observed a nominal association between pancreatic cancer and five pathways (P < 0.05), i.e. pancreatic development, Helicobacter pylori lacto/neolacto, hedgehog, Th1/Th2 immune response and apoptosis (P = 2.0 × 10(-6), 1.6 × 10(-5), 0.0019, 0.019 and 0.023, respectively). After excluding previously identified genes from the original GWAS in three pathways (NR5A2, ABO and SHH), the pancreatic development pathway remained significant (P = 8.3 × 10(-5)), whereas the others did not. The most significant genes (P < 0.01) in the five pathways were NR5A2, HNF1A, HNF4G and PDX1 for pancreatic development; ABO for H.pylori lacto/neolacto; SHH for hedgehog; TGFBR2 and CCL18 for Th1/Th2 immune response and MAPK8 and BCL2L11 for apoptosis. Our results provide a link between inherited variation in genes important for pancreatic development and cancer and show that pathway-based approaches to analysis of GWAS data can yield important insights into the collective role of genetic risk variants in cancer.