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American Association for Cancer Research, Cancer Epidemiology, Biomarkers & Prevention, 1(23), p. 98-106, 2014

DOI: 10.1158/1055-9965.epi-13-0437-t

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Genes-environment interactions in obesity- and diabetes-associated pancreatic cancer: A GWAS data analysis

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Abstract Background: Obesity and diabetes are potentially alterable risk factors for pancreatic cancer. Genetic factors that modify the associations of obesity and diabetes with pancreatic cancer have previously not been examined at the genome-wide level. Methods: Using genome-wide association studies (GWAS) genotype and risk factor data from the Pancreatic Cancer Case Control Consortium, we conducted a discovery study of 2,028 cases and 2,109 controls to examine gene–obesity and gene–diabetes interactions in relation to pancreatic cancer risk by using the likelihood-ratio test nested in logistic regression models and Ingenuity Pathway Analysis (IPA). Results: After adjusting for multiple comparisons, a significant interaction of the chemokine signaling pathway with obesity (P = 3.29 × 10−6) and a near significant interaction of calcium signaling pathway with diabetes (P = 1.57 × 10−4) in modifying the risk of pancreatic cancer were observed. These findings were supported by results from IPA analysis of the top genes with nominal interactions. The major contributing genes to the two top pathways include GNGT2, RELA, TIAM1, and GNAS. None of the individual genes or single-nucleotide polymorphism (SNP) except one SNP remained significant after adjusting for multiple testing. Notably, SNP rs10818684 of the PTGS1 gene showed an interaction with diabetes (P = 7.91 × 10−7) at a false discovery rate of 6%. Conclusions: Genetic variations in inflammatory response and insulin resistance may affect the risk of obesity- and diabetes-related pancreatic cancer. These observations should be replicated in additional large datasets. Impact: A gene–environment interaction analysis may provide new insights into the genetic susceptibility and molecular mechanisms of obesity- and diabetes-related pancreatic cancer. Cancer Epidemiol Biomarkers Prev; 23(1); 98–106. ©2013 AACR.