The genetic interplay between body mass index, breast size and breast cancer risk: a Mendelian randomization analysis

The genetic interplay between body mass index, breast size and breast cancer risk: a Mendelian randomization analysis

International Journal of Epidemiology

10.1093/ije/dyz124

https://doi.org/10.1093/ije/dyz124

Brandon Nick Sern Ooi, Huiwen Loh, Peh Joo Ho, Roger L. Milne, Graham Giles, Chi Gao, Peter Kraft, Esther M. John, Anthony Swerdlow, Hermann Brenner, Anna H. Wu, Christopher Haiman, D. Gareth Evans, Wei Zheng, Peter A. Fasching, Jose Esteban Castelao, Ava Kwong, Xia Shen, Kamila Czene, Per Hall, Alison Dunning, Douglas Easton, Mikael Hartman, Jingmei Li

26 June 2019

Brandon Nick Sern Ooi, Huiwen Loh, Peh Joo Ho, Roger L Milne, Graham Giles, Chi Gao, Peter Kraft, Esther M John, Anthony Swerdlow, Hermann Brenner, Anna H Wu, Christopher Haiman, D Gareth Evans, Wei Zheng, Peter A Fasching, Jose Esteban Castelao, Ava Kwong, Xia Shen, Kamila Czene, Per Hall, Alison Dunning, Douglas Easton, Mikael Hartman, Jingmei Li, The genetic interplay between body mass index, breast size and breast cancer risk: a Mendelian randomization analysis, International Journal of Epidemiology, Volume 48, Issue 3, June 2019, Pages 781–794, https://doi.org/10.1093/ije/dyz124

Background: 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. Methods: 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. 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). Conclusion: 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.

http://creativecommons.org/licenses/by/4.0/

This work was supported by the National Research Foundation Singapore Fellowship (NRF-NRFF2017-02) awarded to J.L. D.G.E is a NIHR Senior investigator. The body mass index association data were obtained from the Genetic Investigation of ANthropometric Traits (GIANT) consortium, whereas the breast cancer genome-wide association meta-analyses, which generated the summary statistics used here, were supported by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research, the ‘Ministère de l’Économie, de la Science et de l’Innovation du Québec’ through Genome Québec and grant PSR-SIIRI-701, The US National Institutes of Health (U19 CA148065, X01HG007492), Cancer Research UK (C1287/A10118, C1287/A16563, C1287/A10710) and The European Union (HEALTH-F2-2009–223175 and H2020 633784 and 634935). All studies and funders for the breast cancer genome-wide association analyses are listed in Michailidou et al.

https://oar.a-star.edu.sg/communities-collections/articles/15339

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