TY  - JOUR
AU  - Wang, Xiaoliang
AU  - Su, Yu-Ru
AU  - Petersen, Paneen S
AU  - Bien, Stephanie
AU  - Schmit, Stephanie L
AU  - Drew, David A
AU  - Albanes, Demetrius
AU  - Berndt, Sonja I
AU  - Brenner, Hermann
AU  - Campbell, Peter T
AU  - Casey, Graham
AU  - Chang-Claude, Jenny
AU  - Gallinger, Steven
AU  - Gruber, Stephen B
AU  - Haile, Robert W
AU  - Harrison, Tabitha A
AU  - Hoffmeister, Michael
AU  - Jacobs, Eric J
AU  - Jenkins, Mark A
AU  - Joshi, Amit D
AU  - Li, Li
AU  - Lin, Yi
AU  - Lindor, Noralane M
AU  - Le Marchand, Loic
AU  - Martín, Vicente
AU  - Milne, Roger L
AU  - Maclnnis, Robert
AU  - Moreno, Victor
AU  - Nan, Hongmei
AU  - Newcomb, Polly A
AU  - Potter, John D
AU  - Rennert, Gad
AU  - Rennert, Hedy S
AU  - Slattery, Martha L
AU  - Thibodeau, Stephen N
AU  - Weinstein, Stephanie J
AU  - Woods, Michael O
AU  - Chan, Andrew T
AU  - White, Emily
AU  - Hsu, Li
AU  - Peters, Ulrike
TI  - Exploratory genome-wide interaction analysis of non-steroidal anti-inflammatory drugs and predicted gene expression on colorectal cancer risk.
JO  - Cancer epidemiology, biomarkers & prevention
VL  - 29
IS  - 9
SN  - 1538-7755
CY  - Philadelphia, Pa.
PB  - AACR
M1  - DKFZ-2020-01345
SP  - 1800-1808
PY  - 2020
N1  - 2020 Sep;29(9):1800-1808
AB  - Regular use of non-steroidal anti-inflammatory drugs (NSAIDs) is associated with lower risk of colorectal cancer (CRC). Genome-wide interaction analysis on single variants (G×E) has identified several SNPs that may interact with NSAIDs to confer CRC 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 CRC risk.Genetically predicted gene expressions were tested for interaction with NSAID use on CRC risk among 19,258 CRC 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 sets (burden) and residual G×E effects (variance). A false discovery rate (FDR) at 0.2 was applied to correct for multiple testing.Among the 4,840 genes tested, genetically predicted expression levels of four genes modified the effect of any NSAID use on CRC risk, including DPP10 (P-G×E=1.96×10-4), KRT16 (P-G×E=2.3×10-4), CD14 (P-G×E=9.38×10-4), and CYP27A1 (P-G×E=1.44×10-3). There was a significant interaction between expression level of RP11-89N17 and regular use of aspirin only on CRC risk (P-G×E=3.23×10-5). No interactions were observed between predicted gene expression and non-aspirin NSAID use at FDR<0.2.By incorporating functional information, we discovered several novel genes that interacted with NSAID use.These findings provide preliminary support that could help understand the chemopreventive mechanisms of NSAIDs on CRC.
LB  - PUB:(DE-HGF)16
C6  - pmid:32651213
DO  - DOI:10.1158/1055-9965.EPI-19-1018
UR  - https://inrepo02.dkfz.de/record/157054
ER  -