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Genome-Wide Gene-Diabetes and Gene-Obesity Interaction Scan in 8,255 Cases and 11,900 Controls from PanScan and PanC4 Consortia

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

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

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/m(2)) 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 covari- ates. 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 jointeffect test detected numerous genome-wide significant GxE signals in the GWAS main effects top hit regions, but the significance diminished after adjusting for theGWAStop 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 x 10(-6)) was observed in the meta-analysis (P-GxE = 1.2 x 10(-6), P-Joint = 4.2 x 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.

OriginalsprogEngelsk
TidsskriftCancer Epidemiology, Biomarkers & Prevention
Vol/bind29
Udgave nummer9
Sider (fra-til)1784-1791
Antal sider8
ISSN1055-9965
DOI
StatusUdgivet - 2020

ID: 248848206