Home > Publications database > Exploratory genome-wide interaction analysis of non-steroidal anti-inflammatory drugs and predicted gene expression on colorectal cancer risk. > print |
001 | 157054 | ||
005 | 20240229123127.0 | ||
024 | 7 | _ | |a 10.1158/1055-9965.EPI-19-1018 |2 doi |
024 | 7 | _ | |a pmid:32651213 |2 pmid |
024 | 7 | _ | |a 1055-9965 |2 ISSN |
024 | 7 | _ | |a 1538-7755 |2 ISSN |
024 | 7 | _ | |a altmetric:85654025 |2 altmetric |
037 | _ | _ | |a DKFZ-2020-01345 |
041 | _ | _ | |a eng |
082 | _ | _ | |a 610 |
100 | 1 | _ | |a Wang, Xiaoliang |b 0 |
245 | _ | _ | |a Exploratory genome-wide interaction analysis of non-steroidal anti-inflammatory drugs and predicted gene expression on colorectal cancer risk. |
260 | _ | _ | |a Philadelphia, Pa. |c 2020 |b AACR |
336 | 7 | _ | |a article |2 DRIVER |
336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1600329015_29117 |2 PUB:(DE-HGF) |
336 | 7 | _ | |a ARTICLE |2 BibTeX |
336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
500 | _ | _ | |a 2020 Sep;29(9):1800-1808 |
520 | _ | _ | |a 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. |
536 | _ | _ | |a 313 - Cancer risk factors and prevention (POF3-313) |0 G:(DE-HGF)POF3-313 |c POF3-313 |f POF III |x 0 |
588 | _ | _ | |a Dataset connected to CrossRef, PubMed, |
700 | 1 | _ | |a Su, Yu-Ru |b 1 |
700 | 1 | _ | |a Petersen, Paneen S |b 2 |
700 | 1 | _ | |a Bien, Stephanie |b 3 |
700 | 1 | _ | |a Schmit, Stephanie L |b 4 |
700 | 1 | _ | |a Drew, David A |0 0000-0002-8813-0816 |b 5 |
700 | 1 | _ | |a Albanes, Demetrius |b 6 |
700 | 1 | _ | |a Berndt, Sonja I |b 7 |
700 | 1 | _ | |a Brenner, Hermann |0 P:(DE-He78)90d5535ff896e70eed81f4a4f6f22ae2 |b 8 |u dkfz |
700 | 1 | _ | |a Campbell, Peter T |b 9 |
700 | 1 | _ | |a Casey, Graham |b 10 |
700 | 1 | _ | |a Chang-Claude, Jenny |0 P:(DE-He78)c259d6cc99edf5c7bc7ce22c7f87c253 |b 11 |u dkfz |
700 | 1 | _ | |a Gallinger, Steven |b 12 |
700 | 1 | _ | |a Gruber, Stephen B |0 0000-0001-8656-7822 |b 13 |
700 | 1 | _ | |a Haile, Robert W |0 0000-0001-6902-1836 |b 14 |
700 | 1 | _ | |a Harrison, Tabitha A |0 0000-0002-4173-7530 |b 15 |
700 | 1 | _ | |a Hoffmeister, Michael |0 P:(DE-He78)6c5d058b7552d071a7fa4c5e943fff0f |b 16 |u dkfz |
700 | 1 | _ | |a Jacobs, Eric J |b 17 |
700 | 1 | _ | |a Jenkins, Mark A |b 18 |
700 | 1 | _ | |a Joshi, Amit D |b 19 |
700 | 1 | _ | |a Li, Li |b 20 |
700 | 1 | _ | |a Lin, Yi |b 21 |
700 | 1 | _ | |a Lindor, Noralane M |b 22 |
700 | 1 | _ | |a Le Marchand, Loic |b 23 |
700 | 1 | _ | |a Martín, Vicente |0 0000-0003-0552-2804 |b 24 |
700 | 1 | _ | |a Milne, Roger L |0 0000-0001-5764-7268 |b 25 |
700 | 1 | _ | |a Maclnnis, Robert |0 0000-0002-1627-5047 |b 26 |
700 | 1 | _ | |a Moreno, Victor |0 0000-0002-2818-5487 |b 27 |
700 | 1 | _ | |a Nan, Hongmei |b 28 |
700 | 1 | _ | |a Newcomb, Polly A |b 29 |
700 | 1 | _ | |a Potter, John D |0 0000-0001-5439-1500 |b 30 |
700 | 1 | _ | |a Rennert, Gad |b 31 |
700 | 1 | _ | |a Rennert, Hedy S |0 0000-0001-5772-2977 |b 32 |
700 | 1 | _ | |a Slattery, Martha L |0 0000-0002-1655-6543 |b 33 |
700 | 1 | _ | |a Thibodeau, Stephen N |b 34 |
700 | 1 | _ | |a Weinstein, Stephanie J |0 0000-0002-3834-1535 |b 35 |
700 | 1 | _ | |a Woods, Michael O |b 36 |
700 | 1 | _ | |a Chan, Andrew T |b 37 |
700 | 1 | _ | |a White, Emily |b 38 |
700 | 1 | _ | |a Hsu, Li |b 39 |
700 | 1 | _ | |a Peters, Ulrike |b 40 |
773 | _ | _ | |a 10.1158/1055-9965.EPI-19-1018 |g p. cebp.1018.2019 - |0 PERI:(DE-600)2036781-8 |n 9 |p 1800-1808 |t Cancer epidemiology, biomarkers & prevention |v 29 |y 2020 |x 1538-7755 |
909 | C | O | |o oai:inrepo02.dkfz.de:157054 |p VDB |
910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 8 |6 P:(DE-He78)90d5535ff896e70eed81f4a4f6f22ae2 |
910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 11 |6 P:(DE-He78)c259d6cc99edf5c7bc7ce22c7f87c253 |
910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 16 |6 P:(DE-He78)6c5d058b7552d071a7fa4c5e943fff0f |
913 | 1 | _ | |a DE-HGF |l Krebsforschung |1 G:(DE-HGF)POF3-310 |0 G:(DE-HGF)POF3-313 |2 G:(DE-HGF)POF3-300 |v Cancer risk factors and prevention |x 0 |4 G:(DE-HGF)POF |3 G:(DE-HGF)POF3 |b Gesundheit |
914 | 1 | _ | |y 2020 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |d 2020-01-17 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0310 |2 StatID |b NCBI Molecular Biology Database |d 2020-01-17 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |d 2020-01-17 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1110 |2 StatID |b Current Contents - Clinical Medicine |d 2020-01-17 |
915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0110 |2 StatID |b Science Citation Index |d 2020-01-17 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |d 2020-01-17 |
915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0111 |2 StatID |b Science Citation Index Expanded |d 2020-01-17 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0160 |2 StatID |b Essential Science Indicators |d 2020-01-17 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1190 |2 StatID |b Biological Abstracts |d 2020-01-17 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1030 |2 StatID |b Current Contents - Life Sciences |d 2020-01-17 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1050 |2 StatID |b BIOSIS Previews |d 2020-01-17 |
915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b CANCER EPIDEM BIOMAR : 2018 |d 2020-01-17 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |d 2020-01-17 |
915 | _ | _ | |a IF >= 5 |0 StatID:(DE-HGF)9905 |2 StatID |b CANCER EPIDEM BIOMAR : 2018 |d 2020-01-17 |
920 | 1 | _ | |0 I:(DE-He78)C070-20160331 |k C070 |l C070 Klinische Epidemiologie und Alternf. |x 0 |
920 | 1 | _ | |0 I:(DE-He78)C020-20160331 |k C020 |l C020 Epidemiologie von Krebs |x 1 |
920 | 1 | _ | |0 I:(DE-He78)C120-20160331 |k C120 |l Präventive Onkologie |x 2 |
920 | 1 | _ | |0 I:(DE-He78)HD01-20160331 |k HD01 |l DKTK HD zentral |x 3 |
980 | _ | _ | |a journal |
980 | _ | _ | |a VDB |
980 | _ | _ | |a I:(DE-He78)C070-20160331 |
980 | _ | _ | |a I:(DE-He78)C020-20160331 |
980 | _ | _ | |a I:(DE-He78)C120-20160331 |
980 | _ | _ | |a I:(DE-He78)HD01-20160331 |
980 | _ | _ | |a UNRESTRICTED |
Library | Collection | CLSMajor | CLSMinor | Language | Author |
---|