Pathway analysis of genome-wide association study data highlights pancreatic development genes as susceptibility factors for pancreatic cancer
View/ Open
26815 bgs151.pdf (156.6Kb)
Access Status
Full text of the requested work is not available in DASH at this time ("dark deposit"). For more information on dark deposits, see our FAQ.Author
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.
Bolton, Judith Hoffman
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.
Published Version
https://doi.org/10.1093/carcin/bgs151Metadata
Show full item recordCitation
Li, Donghui, Eric J. Duell, Kai Yu, Harvey A. Risch, Sara H. Olson, Charles Kooperberg, Brian M. Wolpin, et al. 2012. “Pathway Analysis of Genome-Wide Association Study Data Highlights Pancreatic Development Genes as Susceptibility Factors for Pancreatic Cancer.” Carcinogenesis 33 (7): 1384–90. https://doi.org/10.1093/carcin/bgs151.Abstract
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 x 10(-6), 1.6 x 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 x 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.Citable link to this page
http://nrs.harvard.edu/urn-3:HUL.InstRepos:41392169
Collections
- SPH Scholarly Articles [6344]
Contact administrator regarding this item (to report mistakes or request changes)