Genes–Environment Interactions in Obesity- and Diabetes-Associated Pancreatic Cancer: A GWAS Data Analysis

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 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 employing the likelihood ratio test (LRT) 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 was 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 SNPs 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 Gene-environment interaction analysis may provide new insights into the genetic susceptibility and molecular mechanisms of obesity- and diabetes-related pancreatic cancer.

Pancreatic Cancer: Current Status and Challenges

“…However, whether the association between diabetes and obesity is linked to a further enhanced risk of PanCA development is not yet clear as different studies have had conflicting results [26, 27]. A number of studies have also demonstrated the association between obesity and pancreatic inflammation [24–28]. Interestingly, all known risk factors for PanCA can contribute to or cause inflammation of the pancreas (pancreatitis) [16, 30].…”

Pathway and Network Approaches for Identification of Cancer Signature Markers from Omics Data

“…Machine learning methods have been used for the biomarker discovery from high-throughput omics data, inferring causal relations between mutations and diseases [21] , interactions between genes and proteins [86][87][88] and relations between environmental features and cancer [89] as well as pathway and network modeling. There are two kinds of basic machine learning techniques, one is unsupervised machine learning such as hierarchical clustering, self-organizing mapping (SOM) etc.…”

Genetics of Diabetic Retinopathy

“…Large-scale consortia have been successful in other diseases, including AMD and T2D. [29, 32, 42–45] We are hopeful that when these same strategies are employed in GWAS for DR, we will begin to uncover the genetic underpinnings of this disease.…”