PLoS Genetics (Apr 2014)

Genome-wide diet-gene interaction analyses for risk of colorectal cancer.

  • Jane C Figueiredo,
  • Li Hsu,
  • Carolyn M Hutter,
  • Yi Lin,
  • Peter T Campbell,
  • John A Baron,
  • Sonja I Berndt,
  • Shuo Jiao,
  • Graham Casey,
  • Barbara Fortini,
  • Andrew T Chan,
  • Michelle Cotterchio,
  • Mathieu Lemire,
  • Steven Gallinger,
  • Tabitha A Harrison,
  • Loic Le Marchand,
  • Polly A Newcomb,
  • Martha L Slattery,
  • Bette J Caan,
  • Christopher S Carlson,
  • Brent W Zanke,
  • Stephanie A Rosse,
  • Hermann Brenner,
  • Edward L Giovannucci,
  • Kana Wu,
  • Jenny Chang-Claude,
  • Stephen J Chanock,
  • Keith R Curtis,
  • David Duggan,
  • Jian Gong,
  • Robert W Haile,
  • Richard B Hayes,
  • Michael Hoffmeister,
  • John L Hopper,
  • Mark A Jenkins,
  • Laurence N Kolonel,
  • Conghui Qu,
  • Anja Rudolph,
  • Robert E Schoen,
  • Fredrick R Schumacher,
  • Daniela Seminara,
  • Deanna L Stelling,
  • Stephen N Thibodeau,
  • Mark Thornquist,
  • Greg S Warnick,
  • Brian E Henderson,
  • Cornelia M Ulrich,
  • W James Gauderman,
  • John D Potter,
  • Emily White,
  • Ulrike Peters,
  • CCFR,
  • GECCO

DOI
https://doi.org/10.1371/journal.pgen.1004228
Journal volume & issue
Vol. 10, no. 4
p. e1004228

Abstract

Read online

Dietary factors, including meat, fruits, vegetables and fiber, are associated with colorectal cancer; however, there is limited information as to whether these dietary factors interact with genetic variants to modify risk of colorectal cancer. We tested interactions between these dietary factors and approximately 2.7 million genetic variants for colorectal cancer risk among 9,287 cases and 9,117 controls from ten studies. We used logistic regression to investigate multiplicative gene-diet interactions, as well as our recently developed Cocktail method that involves a screening step based on marginal associations and gene-diet correlations and a testing step for multiplicative interactions, while correcting for multiple testing using weighted hypothesis testing. Per quartile increment in the intake of red and processed meat were associated with statistically significant increased risks of colorectal cancer and vegetable, fruit and fiber intake with lower risks. From the case-control analysis, we detected a significant interaction between rs4143094 (10p14/near GATA3) and processed meat consumption (OR = 1.17; p = 8.7E-09), which was consistently observed across studies (p heterogeneity = 0.78). The risk of colorectal cancer associated with processed meat was increased among individuals with the rs4143094-TG and -TT genotypes (OR = 1.20 and OR = 1.39, respectively) and null among those with the GG genotype (OR = 1.03). Our results identify a novel gene-diet interaction with processed meat for colorectal cancer, highlighting that diet may modify the effect of genetic variants on disease risk, which may have important implications for prevention.