Genome-wide investigation of gene-environment interactions in colorectal cancer.

Authors:
Sabine Siegert, Jochen Hampe, Clemens Schafmayer, Witigo von Schönfels, Jan-Hendrik Egberts, Asta Försti, Bowang Chen, Jesús Lascorz, Kari Hemminki, Andre Franke, Michael Nothnagel, Ute Nöthlings, Michael Krawczak
Year of publication:
2013
Volume:
132
Issue:
2
Issn:
0340-6717
Journal title abbreviated:
HUM GENET
Journal title long:
Human genetics
Impact factor:
5.138
Abstract: 
Colorectal cancer (CRC), one of the most frequent neoplasias worldwide, has both genetic and environmental causes. As yet, however, gene-environment (G × E) interactions in CRC have been studied mostly for a small number of candidate genes only. Therefore, we investigated the possible interaction, in CRC etiology, between single-nucleotide polymorphisms (SNPs) on the one hand, and overweight, smoking and alcohol consumption on the other, at a genome-wide level. To this end, we adopted a two-tiered approach comprising a case-only screening stage I (314 cases) and a case-control validation stage II (259 cases, 1,002 controls). Interactions with the smallest p value in stage I were verified in stage II using multiple logistic regression analysis adjusted for sex and age. In addition, we specifically studied known CRC-associated SNPs for possible G × E interactions. Upon adjustment for sex and age, and after allowing for multiple testing, however, only a single SNP (rs1944511) was found to be involved in a statistically significant interaction, namely with overweight (multiplicity-corrected p = 0.042 in stage II). Several other G × E interactions were nominally significant but failed correction for multiple testing, including a previously reported interaction between rs9929218 and alcohol consumption that also emerged in our candidate SNP study (nominal p = 0.008). Notably, none of the interactions identified in our genome-wide analysis was with a previously reported CRC-associated SNP. Our study therefore highlights the potential of an "agnostic" genome-wide approach to G × E analysis.