Genome-wide gene-diabetes and gene-obesity interaction scan in 8,255 cases and 11,900 controls from PanScan and PanC4 consortia Journal Article
| Authors: | Tang, H.; Jiang, L.; Stolzenberg-Solomon, R. Z.; Arslan, A. A.; Freeman, L. E. B.; Bracci, P. M.; Brennan, P.; Canzian, F.; Du, M.; Gallinger, S.; Giles, G. G.; Goodman, P. J.; Kooperberg, C.; Le Marchand, L.; Neale, R. E.; Shu, X. O.; Visvanathan, K.; White, E.; Zheng, W.; Albanes, D.; Andreotti, G.; Babic, A.; Bamlet, W. R.; Berndt, S. I.; Blackford, A.; Bueno-de-Mesquita, B.; Buring, J. E.; Campa, D.; Chanock, S. J.; Childs, E.; Duell, E. J.; Fuchs, C.; Gaziano, J. M.; Goggins, M.; Hartge, P.; Hassam, M. H.; Holly, E. A.; Hoover, R. N.; Hung, R. J.; Kurtz, R. C.; Lee, I. M.; Malats, N.; Milne, R. L.; Ng, K.; Oberg, A. L.; Orlow, I.; Peters, U.; Porta, M.; Rabe, K. G.; Rothman, N.; Scelo, G.; Sesso, H. D.; Silverman, D. T.; Thompson, I. M. Jr; Tjønneland, A.; Trichopoulou, A.; Wactawski-Wende, J.; Wentzensen, N.; Wilkens, L. R.; Yu, H.; Zeleniuch-Jacquotte, A.; Amundadottir, L. T.; Jacobs, E. J.; Petersen, G. M.; Wolpin, B. M.; Risch, H. A.; Chatterjee, N.; Klein, A. P.; Li, D.; Kraft, P.; Wei, P. |
| Article Title: | Genome-wide gene-diabetes and gene-obesity interaction scan in 8,255 cases and 11,900 controls from PanScan and PanC4 consortia |
| 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 < 1.25 106) was observed in the meta-analysis (PGxE 1⁄4 1.2 106, PJoint 1⁄4 4.2 107). 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. © 2020 American Association for Cancer Research. |
| Journal Title: | Cancer Epidemiology Biomarkers and Prevention |
| Volume: | 29 |
| Issue: | 9 |
| ISSN: | 1055-9965 |
| Publisher: | American Association for Cancer Research |
| Date Published: | 2020-09-01 |
| Start Page: | 1784 |
| End Page: | 1791 |
| Language: | English |
| DOI: | 10.1158/1055-9965.Epi-20-0275 |
| PUBMED: | 32546605 |
| PROVIDER: | scopus |
| PMCID: | PMC7483330 |
| DOI/URL: | |
| Notes: | Article -- Export Date: 1 March 2021 -- Source: Scopus |
Altmetric
Citation Impact
BMJ Impact Analytics
Related MSK Work