guest ::
| Home > Publications database > The genetic interplay between body mass index, breast size and breast cancer risk: a Mendelian randomization analysis. > print |
| Home > Publications database > The genetic interplay between body mass index, breast size and breast cancer risk: a Mendelian randomization analysis. > print |
| 001 | 144148 | ||
| 005 | 20240229112618.0 | ||
| 024 | 7 | _ | |a 10.1093/ije/dyz124 |2 doi |
| 024 | 7 | _ | |a pmid:31243447 |2 pmid |
| 024 | 7 | _ | |a 0300-5771 |2 ISSN |
| 024 | 7 | _ | |a 1464-3685 |2 ISSN |
| 024 | 7 | _ | |a altmetric:62807029 |2 altmetric |
| 037 | _ | _ | |a DKFZ-2019-01697 |
| 041 | _ | _ | |a eng |
| 082 | _ | _ | |a 610 |
| 100 | 1 | _ | |a Ooi, Brandon Nick Sern |b 0 |
| 245 | _ | _ | |a The genetic interplay between body mass index, breast size and breast cancer risk: a Mendelian randomization analysis. |
| 260 | _ | _ | |a Oxford |c 2019 |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 1573738354_28187 |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 Evidence linking breast size to breast cancer risk has been inconsistent, and its interpretation is often hampered by confounding factors such as body mass index (BMI). Here, we used linkage disequilibrium score regression and two-sample Mendelian randomization (MR) to examine the genetic associations between BMI, breast size and breast cancer risk.Summary-level genotype data from 23andMe, Inc (breast size, n = 33 790), the Breast Cancer Association Consortium (breast cancer risk, n = 228 951) and the Genetic Investigation of ANthropometric Traits (BMI, n = 183 507) were used for our analyses. In assessing causal relationships, four complementary MR techniques [inverse variance weighted (IVW), weighted median, weighted mode and MR-Egger regression] were used to test the robustness of the results.The genetic correlation (rg) estimated between BMI and breast size was high (rg = 0.50, P = 3.89x10-43). All MR methods provided consistent evidence that higher genetically predicted BMI was associated with larger breast size [odds ratio (ORIVW): 2.06 (1.80-2.35), P = 1.38x10-26] and lower overall breast cancer risk [ORIVW: 0.81 (0.74-0.89), P = 9.44x10-6]. No evidence of a relationship between genetically predicted breast size and breast cancer risk was found except when using the weighted median and weighted mode methods, and only with oestrogen receptor (ER)-negative risk. There was no evidence of reverse causality in any of the analyses conducted (P > 0.050).Our findings indicate a potential positive causal association between BMI and breast size and a potential negative causal association between BMI and breast cancer risk. We found no clear evidence for a direct relationship between breast size and breast cancer risk. |
| 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 Loh, Huiwen |b 1 |
| 700 | 1 | _ | |a Ho, Peh Joo |b 2 |
| 700 | 1 | _ | |a Milne, Roger L |b 3 |
| 700 | 1 | _ | |a Giles, Graham |b 4 |
| 700 | 1 | _ | |a Gao, Chi |b 5 |
| 700 | 1 | _ | |a Kraft, Peter |b 6 |
| 700 | 1 | _ | |a John, Esther M |b 7 |
| 700 | 1 | _ | |a Swerdlow, Anthony |b 8 |
| 700 | 1 | _ | |a Brenner, Hermann |0 P:(DE-He78)90d5535ff896e70eed81f4a4f6f22ae2 |b 9 |u dkfz |
| 700 | 1 | _ | |a Wu, Anna H |b 10 |
| 700 | 1 | _ | |a Haiman, Christopher |b 11 |
| 700 | 1 | _ | |a Evans, D Gareth |b 12 |
| 700 | 1 | _ | |a Zheng, Wei |b 13 |
| 700 | 1 | _ | |a Fasching, Peter A |b 14 |
| 700 | 1 | _ | |a Castelao, Jose Esteban |b 15 |
| 700 | 1 | _ | |a Kwong, Ava |b 16 |
| 700 | 1 | _ | |a Shen, Xia |b 17 |
| 700 | 1 | _ | |a Czene, Kamila |b 18 |
| 700 | 1 | _ | |a Hall, Per |b 19 |
| 700 | 1 | _ | |a Dunning, Alison |b 20 |
| 700 | 1 | _ | |a Easton, Douglas |b 21 |
| 700 | 1 | _ | |a Hartman, Mikael |b 22 |
| 700 | 1 | _ | |a Li, Jingmei |b 23 |
| 773 | _ | _ | |a 10.1093/ije/dyz124 |g p. dyz124 |0 PERI:(DE-600)1494592-7 |n 3 |p 781-794 |t International journal of epidemiology |v 48 |y 2019 |x 1464-3685 |
| 909 | C | O | |p VDB |o oai:inrepo02.dkfz.de:144148 |
| 910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 9 |6 P:(DE-He78)90d5535ff896e70eed81f4a4f6f22ae2 |
| 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 2019 |
| 915 | _ | _ | |a Nationallizenz |0 StatID:(DE-HGF)0420 |2 StatID |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0310 |2 StatID |b NCBI Molecular Biology Database |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0320 |2 StatID |b PubMed Central |
| 915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b INT J EPIDEMIOL : 2017 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0600 |2 StatID |b Ebsco Academic Search |
| 915 | _ | _ | |a Peer Review |0 StatID:(DE-HGF)0030 |2 StatID |b ASC |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0110 |2 StatID |b Science Citation Index |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0111 |2 StatID |b Science Citation Index Expanded |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1110 |2 StatID |b Current Contents - Clinical Medicine |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1030 |2 StatID |b Current Contents - Life Sciences |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1050 |2 StatID |b BIOSIS Previews |
| 915 | _ | _ | |a IF >= 5 |0 StatID:(DE-HGF)9905 |2 StatID |b INT J EPIDEMIOL : 2017 |
| 920 | 1 | _ | |0 I:(DE-He78)C070-20160331 |k C070 |l Klinische Epidemiologie und Alternsforschung |x 0 |
| 920 | 1 | _ | |0 I:(DE-He78)C120-20160331 |k C120 |l Präventive Onkologie |x 1 |
| 920 | 1 | _ | |0 I:(DE-He78)L101-20160331 |k L101 |l DKTK Heidelberg |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)L101-20160331 |
| 980 | _ | _ | |a UNRESTRICTED |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|