Exploratory genome-wide interaction analysis of nonsteroidal anti-inflammatory drugs and predicted gene expression on colorectal cancer risk

Xiaoliang Wang, Yu Ru Su, Paneen S. Petersen, Stephanie Bien, Stephanie L. Schmit, David A. Drew, Demetrius Albanes, Sonja I. Berndt, Hermann Brenner, Peter T. Campbell, Graham Casey, Jenny Chang-Claude, Steven J. Gallinger, Stephen B. Gruber, Robert W. Haile, Tabitha A. Harrison, Michael Hoffmeister, Eric J. Jacobs, Mark A. Jenkins, Amit D. JoshiLi Li, Yi Lin, Noralane M. Lindor, Loc Le Marchand, Vicente Martin, Roger Milne, Robert Maclnnis, Victor Moreno, Hongmei Nan, Polly A. Newcomb, John D. Potter, Gad Rennert, Hedy Rennert, Martha L. Slattery, Steve N. Thibodeau, Stephanie J. Weinstein, Michael O. Woods, Andrew T. Chan, Emily White, Li Hsu, Ulrike Peters

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Background: Regular use of nonsteroidal anti-inflammatory drugs (NSAID) is associated with lower risk of colorectal cancer. Genome-wide interaction analysis on single variants (G × E) has identified several SNPs that may interact with NSAIDs to confer colorectal cancer risk, but variations in gene expression levels may also modify the effect of NSAID use. Therefore, we tested interactions between NSAID use and predicted gene expression levels in relation to colorectal cancer risk. Methods: Genetically predicted gene expressions were tested for interaction with NSAID use on colorectal cancer risk among 19,258 colorectal cancer cases and 18,597 controls from 21 observational studies. A Mixed Score Test for Interactions (MiSTi) approach was used to jointly assess G × E effects which are modeled via fixed interaction effects of the weighted burden within each gene set (burden) and residual G × E effects (variance). A false discovery rate (FDR) at 0.2 was applied to correct for multiple testing. Results: Among the 4,840 genes tested, genetically predicted expression levels of four genes modified the effect of any NSAID use on colorectal cancer risk, including DPP10 (PG×E ¼ 1.96 × 10-4), KRT16 (PG×E ¼ 2.3 × 10-4), CD14 (PG×E ¼ 9.38 × 10-4), and CYP27A1 (PG×E ¼ 1.44 × 10-3). There was a significant interaction between expression level of RP11-89N17 and regular use of aspirin only on colorectal cancer risk (PG×E ¼ 3.23 × 10-5). No interactions were observed between predicted gene expression and nonaspirin NSAID use at FDR < 0.2. Conclusions: By incorporating functional information, we discovered several novel genes that interacted with NSAID use. Impact: These findings provide preliminary support that could help understand the chemopreventive mechanisms of NSAIDs on colorectal cancer.

Original languageEnglish (US)
Pages (from-to)1800-1808
Number of pages9
JournalCancer Epidemiology Biomarkers and Prevention
Volume29
Issue number9
DOIs
StatePublished - Sep 2020
Externally publishedYes

ASJC Scopus subject areas

  • Epidemiology
  • Oncology

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