Home > Publications database > Identification of potential mediators of the relationship between body mass index and colorectal cancer: a Mendelian randomization analysis. > print |
001 | 290093 | ||
005 | 20240510175950.0 | ||
024 | 7 | _ | |a 10.1093/ije/dyae067 |2 doi |
024 | 7 | _ | |a pmid:38725300 |2 pmid |
024 | 7 | _ | |a 0300-5771 |2 ISSN |
024 | 7 | _ | |a 1464-3685 |2 ISSN |
037 | _ | _ | |a DKFZ-2024-00992 |
041 | _ | _ | |a English |
082 | _ | _ | |a 610 |
100 | 1 | _ | |a Bouras, Emmanouil |0 0000-0003-1489-5506 |b 0 |
245 | _ | _ | |a Identification of potential mediators of the relationship between body mass index and colorectal cancer: a Mendelian randomization analysis. |
260 | _ | _ | |a Oxford |c 2024 |b Oxford Univ. Press |
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 1715345298_25993 |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 |
520 | _ | _ | |a Colorectal cancer (CRC) is the third-most-common cancer worldwide and its rates are increasing. Elevated body mass index (BMI) is an established risk factor for CRC, although the molecular mechanisms behind this association remain unclear. Using the Mendelian randomization (MR) framework, we aimed to investigate the mediating effects of putative biomarkers and other CRC risk factors in the association between BMI and CRC.We selected as mediators biomarkers of established cancer-related mechanisms and other CRC risk factors for which a plausible association with obesity exists, such as inflammatory biomarkers, glucose homeostasis traits, lipids, adipokines, insulin-like growth factor 1 (IGF1), sex hormones, 25-hydroxy-vitamin D, smoking, physical activity (PA) and alcohol consumption. We used inverse-variance weighted MR in the main univariable analyses and performed sensitivity analyses (weighted-median, MR-Egger, Contamination Mixture). We used multivariable MR for the mediation analyses.Genetically predicted BMI was positively associated with CRC risk [odds ratio per SD (5 kg/m2) = 1.17, 95% CI: 1.08-1.24, P-value = 1.4 × 10-5] and robustly associated with nearly all potential mediators. Genetically predicted IGF1, fasting insulin, low-density lipoprotein cholesterol, smoking, PA and alcohol were associated with CRC risk. Evidence for attenuation was found for IGF1 [explained 7% (95% CI: 2-13%) of the association], smoking (31%, 4-57%) and PA (7%, 2-11%). There was little evidence for pleiotropy, although smoking was bidirectionally associated with BMI and instruments were weak for PA.The effect of BMI on CRC risk is possibly partly mediated through plasma IGF1, whereas the attenuation of the BMI-CRC association by smoking and PA may reflect confounding and shared underlying mechanisms rather than mediation. |
536 | _ | _ | |a 313 - Krebsrisikofaktoren und Prävention (POF4-313) |0 G:(DE-HGF)POF4-313 |c POF4-313 |f POF IV |x 0 |
588 | _ | _ | |a Dataset connected to CrossRef, PubMed, , Journals: inrepo02.dkfz.de |
650 | _ | 7 | |a BMI |2 Other |
650 | _ | 7 | |a Body mass index |2 Other |
650 | _ | 7 | |a CRC |2 Other |
650 | _ | 7 | |a Mendelian randomization |2 Other |
650 | _ | 7 | |a colorectal cancer |2 Other |
650 | _ | 7 | |a mediation analysis |2 Other |
650 | _ | 7 | |a obesity |2 Other |
650 | _ | 7 | |a Insulin-Like Growth Factor I |0 67763-96-6 |2 NLM Chemicals |
650 | _ | 2 | |a Humans |2 MeSH |
650 | _ | 2 | |a Colorectal Neoplasms: genetics |2 MeSH |
650 | _ | 2 | |a Colorectal Neoplasms: epidemiology |2 MeSH |
650 | _ | 2 | |a Mendelian Randomization Analysis |2 MeSH |
650 | _ | 2 | |a Body Mass Index |2 MeSH |
650 | _ | 2 | |a Risk Factors |2 MeSH |
650 | _ | 2 | |a Obesity: genetics |2 MeSH |
650 | _ | 2 | |a Obesity: epidemiology |2 MeSH |
650 | _ | 2 | |a Insulin-Like Growth Factor I: metabolism |2 MeSH |
650 | _ | 2 | |a Alcohol Drinking: epidemiology |2 MeSH |
700 | 1 | _ | |a Gill, Dipender |0 0000-0001-7312-7078 |b 1 |
700 | 1 | _ | |a Zuber, Verena |0 0000-0001-9827-1877 |b 2 |
700 | 1 | _ | |a Murphy, Neil |0 0000-0003-3347-8249 |b 3 |
700 | 1 | _ | |a Dimou, Niki |b 4 |
700 | 1 | _ | |a Aleksandrova, Krasimira |0 0000-0002-1275-1827 |b 5 |
700 | 1 | _ | |a Lewis, Sarah J |b 6 |
700 | 1 | _ | |a Martin, Richard M |b 7 |
700 | 1 | _ | |a Yarmolinsky, James |b 8 |
700 | 1 | _ | |a Albanes, Demetrius |b 9 |
700 | 1 | _ | |a Brenner, Hermann |0 P:(DE-He78)90d5535ff896e70eed81f4a4f6f22ae2 |b 10 |u dkfz |
700 | 1 | _ | |a Castellví-Bel, Sergi |b 11 |
700 | 1 | _ | |a Chan, Andrew T |b 12 |
700 | 1 | _ | |a Cheng, Iona |0 0000-0003-4132-2893 |b 13 |
700 | 1 | _ | |a Gruber, Stephen |b 14 |
700 | 1 | _ | |a Van Guelpen, Bethany |0 0000-0002-9692-101X |b 15 |
700 | 1 | _ | |a Li, Christopher I |b 16 |
700 | 1 | _ | |a Le Marchand, Loic |b 17 |
700 | 1 | _ | |a Newcomb, Polly A |b 18 |
700 | 1 | _ | |a Ogino, Shuji |b 19 |
700 | 1 | _ | |a Pellatt, Andrew |b 20 |
700 | 1 | _ | |a Schmit, Stephanie L |b 21 |
700 | 1 | _ | |a Wolk, Alicja |0 0000-0001-7387-6845 |b 22 |
700 | 1 | _ | |a Wu, Anna H |b 23 |
700 | 1 | _ | |a Peters, Ulrike |b 24 |
700 | 1 | _ | |a Gunter, Marc J |b 25 |
700 | 1 | _ | |a Tsilidis, Konstantinos K |b 26 |
773 | _ | _ | |a 10.1093/ije/dyae067 |g Vol. 53, no. 3, p. dyae067 |0 PERI:(DE-600)1494592-7 |n 3 |p dyae067 |t International journal of epidemiology |v 53 |y 2024 |x 0300-5771 |
909 | C | O | |o oai:inrepo02.dkfz.de:290093 |p VDB |
910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 10 |6 P:(DE-He78)90d5535ff896e70eed81f4a4f6f22ae2 |
913 | 1 | _ | |a DE-HGF |b Gesundheit |l Krebsforschung |1 G:(DE-HGF)POF4-310 |0 G:(DE-HGF)POF4-313 |3 G:(DE-HGF)POF4 |2 G:(DE-HGF)POF4-300 |4 G:(DE-HGF)POF |v Krebsrisikofaktoren und Prävention |x 0 |
914 | 1 | _ | |y 2024 |
915 | _ | _ | |a Nationallizenz |0 StatID:(DE-HGF)0420 |2 StatID |d 2023-10-21 |w ger |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |d 2023-10-21 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0320 |2 StatID |b PubMed Central |d 2023-10-21 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |d 2023-10-21 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1050 |2 StatID |b BIOSIS Previews |d 2023-10-21 |
915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0113 |2 StatID |b Science Citation Index Expanded |d 2023-10-21 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |d 2023-10-21 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1030 |2 StatID |b Current Contents - Life Sciences |d 2023-10-21 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1190 |2 StatID |b Biological Abstracts |d 2023-10-21 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0160 |2 StatID |b Essential Science Indicators |d 2023-10-21 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1110 |2 StatID |b Current Contents - Clinical Medicine |d 2023-10-21 |
915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b INT J EPIDEMIOL : 2022 |d 2023-10-21 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |d 2023-10-21 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0600 |2 StatID |b Ebsco Academic Search |d 2023-10-21 |
915 | _ | _ | |a Peer Review |0 StatID:(DE-HGF)0030 |2 StatID |b ASC |d 2023-10-21 |
915 | _ | _ | |a IF >= 5 |0 StatID:(DE-HGF)9905 |2 StatID |b INT J EPIDEMIOL : 2022 |d 2023-10-21 |
920 | 1 | _ | |0 I:(DE-He78)C070-20160331 |k C070 |l C070 Klinische Epidemiologie und Alternf. |x 0 |
920 | 1 | _ | |0 I:(DE-He78)C120-20160331 |k C120 |l Präventive Onkologie |x 1 |
920 | 1 | _ | |0 I:(DE-He78)HD01-20160331 |k HD01 |l DKTK HD zentral |x 2 |
980 | _ | _ | |a journal |
980 | _ | _ | |a VDB |
980 | _ | _ | |a I:(DE-He78)C070-20160331 |
980 | _ | _ | |a I:(DE-He78)C120-20160331 |
980 | _ | _ | |a I:(DE-He78)HD01-20160331 |
980 | _ | _ | |a UNRESTRICTED |
Library | Collection | CLSMajor | CLSMinor | Language | Author |
---|