Journal Article

Pathway analysis of genome-wide association study data highlights pancreatic development genes as susceptibility factors for pancreatic cancer

Donghui Li, Eric J. Duell, Kai Yu, Harvey A. Risch, Sara H. Olson, Charles Kooperberg, Brian M. Wolpin, Li Jiao, Xiaoqun Dong, Bill Wheeler, Alan A. Arslan, H. Bas Bueno-de-Mesquita, Charles S. Fuchs, Steven Gallinger, Myron Gross, Patricia Hartge, Robert N. Hoover, Elizabeth A. Holly, Eric J. Jacobs, Alison P. Klein, Andrea LaCroix, Margaret T. Mandelson, Gloria Petersen, Wei Zheng, Ilir Agalliu, Demetrius Albanes, Marie-Christine Boutron-Ruault, Paige M. Bracci, Julie E. Buring, Federico Canzian, Kenneth Chang, Stephen J. Chanock, Michelle Cotterchio, J.Michael Gaziano, Edward L. Giovannucci, Michael Goggins, Göran Hallmans, Susan E. Hankinson, Judith A. Hoffman Bolton, David J. Hunter, Amy Hutchinson, Kevin B. Jacobs, Mazda Jenab, Kay-Tee Khaw, Peter Kraft, Vittorio Krogh, Robert C. Kurtz, Robert R. McWilliams, Julie B. Mendelsohn, Alpa V. Patel, Kari G. Rabe, Elio Riboli, Xiao-Ou Shu, Anne Tjønneland, Geoffrey S. Tobias, Dimitrios Trichopoulos, Jarmo Virtamo, Kala Visvanathan, Joanne Watters, Herbert Yu, Anne Zeleniuch-Jacquotte, Laufey Amundadottir and Rachael Z. Stolzenberg-Solomon

in Carcinogenesis

Volume 33, issue 7, pages 1384-1390
Published in print July 2012 | ISSN: 0143-3334
Published online April 2012 | e-ISSN: 1460-2180 | DOI: http://dx.doi.org/10.1093/carcin/bgs151
Pathway analysis of genome-wide association study data highlights pancreatic development genes as susceptibility factors for pancreatic cancer

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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.

Journal Article.  5377 words. 

Subjects: Clinical Cytogenetics and Molecular Genetics

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