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Brennan, Paul

0000-0002-0518-8714

Mayo Clinic

Centre international de recherche sur le cancer

Citations 11

Genome-Wide Gene–Diabetes and Gene–Obesity Interaction Scan in 8,255 Cases and 11,900 Controls from PanScan and PanC4 Consortia
Tang, Hongwei, Jiang, Lai , Arslan, Alan A. , Bracci, Paige M. , Brennan, Paul , Canzian, Federico , Du, Mengmeng , Gallinger, Steven , Goodman, Phyllis J. , Visvanathan, Kala , Andreotti, Gabriella , Babić, Ana , Berndt, Sonja I. , Bueno‐de‐Mesquita, Bas , Buring, Julie E. , Campa, Daniele , Childs, Erica J., Fuchs, Charles S. , Gaziano, J. Michael , Hartge, Patricia, Hassam, Manal H., Holly, Elizabeth A. , Hoover, Robert N. , Hung, Rayjean J. , Kurtz, Robert C. , Lee, I-Min, Ng, Kimmie , Oberg, Ann L. , Peters, Ulrike , Porta, Miquel , Rabe, Kari G. , Rothman, Nathaniel , Scélo, Ghislaine , Sesso, Howard D. , Thompson, Ian M. , Tjønneland, Anne , Trichopoulou, Antonia , Wactawski‐Wende, Jean , Wentzensen, Nicolas , Zeleniuch‐Jacquotte, Anne , Jacobs, Eric J. , Petersen, Gloria M. , Wolpin, Brian M. , Chatterjee, Nilanjan , Li, Donghui , Arslan, Alan A , Brennan, Paul , Canzian, Federico , Bamlet, William R , Blackford, Amanda , Duell, Eric J , Hung, Rayjean J , Malats, Nuria , Milne, Roger L , Oberg, Ann L , Orlow, Irene , Sesso, Howard D , Tjønneland, Anne , Wactawski-Wende, Jean , Yu, Herbert , Amundadottir, Laufey , Klein, Alison P , Li, Donghui , Chaffee, Kari G. , Visvanathan, Kala , Porta, Miquel , Thompson, Ian M , Zeleniuch-Jacquotte, Anne , Stolzenberg‐Solomon, Rachael Z. , Freeman, Laura E. Beane , Giles, Graham G. , Kooperberg, Charles , Marchand, Loı̈c Le , Neale, Rachel Ε. , Shu, Xiao‐Ou , White, Emily , Zheng, Wei , Albanes, Demetrius , Bamlet, William R. , Chanock, Stephen Jacob , Duell, Eric J. , Goggins, Michael , Malats, Núria , Milne, Roger L. , Orlow, Irene , Rothman, Nathaniel , Silverman, Debra T. , Wilkens, Lynne R. , Yu, Kai , Ámundadóttir, Laufey T. , Risch, Harvey A. , Klein, Alison P. , Kraft, Peter , Wei, Peng

Cancer Epidemiology, Biomarkers & Prevention | June 16, 2020 | Volume: 29 | Issue: 9 | Pages: 1784-1791

10.1158/1055-9965.epi-20-0275 Get It

Abstract Background: Obesity and diabetes are major modifiable risk factors for pancreatic cancer. Interactions between genetic variants and diabetes/obesity have not previously been comprehensively investigated in pancreatic cancer at the genome-wide level. Methods: We conducted a gene–environment interaction (GxE) analysis including 8,255 cases and 11,900 controls from four pancreatic cancer genome-wide association study (GWAS) datasets (Pancreatic Cancer Cohort Consortium I–III and Pancreatic Cancer Case Control Consortium). Obesity (body mass index ≥30 kg/m2) and diabetes (duration ≥3 years) were the environmental variables of interest. Approximately 870,000 SNPs (minor allele frequency ≥0.005, genotyped in at least one dataset) were analyzed. Case–control (CC), case-only (CO), and joint-effect test methods were used for SNP-level GxE analysis. As a complementary approach, gene-based GxE analysis was also performed. Age, sex, study site, and principal components accounting for population substructure were included as covariates. Meta-analysis was applied to combine individual GWAS summary statistics. Results: No genome-wide significant interactions (departures from a log-additive odds model) with diabetes or obesity were detected at the SNP level by the CC or CO approaches. The joint-effect test detected numerous genome-wide significant GxE signals in the GWAS main effects top hit regions, but the significance diminished after adjusting for the GWAS top hits. In the gene-based analysis, a significant interaction of diabetes with variants in the FAM63A (family with sequence similarity 63 member A) gene (significance threshold P < 1.25 × 10−6) was observed in the meta-analysis (PGxE = 1.2 ×10−6, PJoint = 4.2 ×10−7). Conclusions: This analysis did not find significant GxE interactions at the SNP level but found one significant interaction with diabetes at the gene level. A larger sample size might unveil additional genetic factors via GxE scans. Impact: This study may contribute to discovering the mechanism of diabetes-associated pancreatic cancer.