DataSheet_1.docx

Abstract

Although 21 pancreatic cancer susceptibility loci have been identified in individuals of European ancestry through genome-wide association studies (GWAS), much of the heritability of pancreatic cancer risk remains unidentified. A recessive genetic model could be a powerful tool for identifying additional risk variants. To discover recessively inherited pancreatic cancer risk loci, we performed a re-analysis of the largest pancreatic cancer GWAS, the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4), including 8,769 cases and 7,055 controls of European ancestry. Six single nucleotide polymorphisms (SNPs) showed associations with pancreatic cancer risk according to a recessive model of inheritance. We replicated these variants in 3,212 cases and 3,470 controls collected from the PANcreatic Disease ReseArch (PANDoRA) consortium. The results of the meta-analyses confirmed that rs4626538 (7q32.2), rs7008921 (8p23.2) and rs147904962 (17q21.31) showed specific recessive effects (p10−3), although none of the six SNPs reached the conventional threshold for genome-wide significance (p < 5×10−8). Our findings, while not conclusive, indicate the importance of considering non-additive genetic models when performing GWAS analysis. A thorough knowledge of risk factors can be used for risk stratification, which in turn can identify population subgroups at high risk who can benefit from enhanced surveillance or biomarker testing/imaging, thereby improving the chances for early detection. The SNPs associated with pancreatic cancer in this study will be a useful addiction to improve the performance of polygenic risk scores, an attractive method for risk stratification.