Body mass index and breast cancer survival: A Mendelian randomization analysis

Qi Guo, Stephen Burgess, Constance Turman, Manjeet K. Bolla, Qin Wang, Michael Lush, Jean Abraham, Kristiina Aittomäki, Irene L. Andrulis, Carmel Apicella, Volker Arndt, Myrto Barrdahl, Javier Benitez, Christine D. Berg, Carl Blomqvist, Stig E. Bojesen, Bernardo Bonanni, Judith S. Brand, Hermann Brenner, Annegien BroeksBarbara Burwinkel, Carlos Caldas, Daniele Campa, Federico Canzian, Jenny Chang-Claude, Stephen J. Chanock, Suet Feung Chin, Fergus J. Couch, Angela Cox, Simon S. Cross, Cezary Cybulski, Kamila Czene, Hatef Darabi, Peter Devilee, W. Ryan Diver, Alison M. Dunning, Helena M. Earl, Diana M. Eccles, Arif B. Ekici, Mikael Eriksson, D. Gareth Evans, Peter A. Fasching, Jonine Figueroa, Dieter Flesch-Janys, Henrik Flyger, Susan M. Gapstur, Mia M. Gaudet, Graham G. Giles, Gord Glendon, Mervi Grip, Jacek Gronwald, Lothar Haeberle, Christopher A. Haiman, Per Hall, Ute Hamann, Susan Hankinson, Jaana M. Hartikainen, Alexander Hein, Louise Hiller, Frans B. Hogervorst, Bernd Holleczek, Maartje J. Hooning, Robert N. Hoover, Keith Humphreys, David J. Hunter, Anika Hüsing, Anna Jakubowska, Arja Jukkola-Vuorinen, Rudolf Kaaks, Maria Kabisch, Vesa Kataja, kConFab/AOCS Investigators, Julia A. Knight, Linetta B. Koppert, Veli Matti Kosma, Vessela N. Kristensen, Diether Lambrechts, Loic Le Marchand, Jingmei Li, Annika Lindblom, Sara Lindström, Jolanta Lissowska, Jan Lubinski, Mitchell J. Machiela, Arto Mannermaa, Siranoush Manoukian, Sara Margolin, Federik Marme, John W.M. Martens, Catriona McLean, Primitiva Menéndez, Roger L. Milne, Anna Marie Mulligan, Taru A. Muranen, Heli Nevanlinna, Patrick Neven, Sune F. Nielsen, Børge G. Nordestgaard, Janet E. Olson, Jose I.A. Perez, Paolo Peterlongo, Kelly Anne Phillips, Christopher J. Poole, Katri Pylkäs, Paolo Radice, Nazneen Rahman, Thomas Rüdiger, Anja Rudolph, Elinor J. Sawyer, Fredrick Schumacher, Petra Seibold, Caroline Seynaeve, Mitul Shah, Ann Smeets, Melissa C. Southey, Rob A.E.M. Tollenaar, Ian Tomlinson, Helen Tsimiklis, Hans Ulrich Ulmer, Celine Vachon, Ans M.W. van den Ouweland, Laura J. Van't Veer, Hans Wildiers, Walter Willett, Robert Winqvist, M. Pilar Zamora, Georgia Chenevix-Trench, Thilo Dörk, Douglas F. Easton, Montserrat García-Closas, Peter Kraft, John L. Hopper, Wei Zheng, Marjanka K. Schmidt, Paul D.P. Pharoah

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40 Citations (Scopus)

Abstract

Background: There is increasing evidence that elevated body mass index (BMI) is associated with reduced survival for women with breast cancer. However, the underlying reasons remain unclear. We conducted a Mendelian randomization analysis to investigate a possible causal role of BMI in survival from breast cancer. Methods: We used individual-level data from six large breast cancer case-cohorts including a total of 36 210 individuals (2475 events) of European ancestry. We created a BMI genetic risk score (GRS) based on genotypes at 94 known BMI-associated genetic variants. Association between the BMI genetic score and breast cancer survival was analysed by Cox regression for each study separately. Study-specific hazard ratios were pooled using fixed-effect meta-analysis. Results: BMI genetic score was found to be associated with reduced breast cancer-specific survival for estrogen receptor (ER)-positive cases [hazard ratio (HR)=1.11, per one-unit increment of GRS, 95% confidence interval (CI) 1.01-1.22, P=0.03). We observed no association for ER-negative cases (HR=1.00, per one-unit increment of GRS, 95% CI 0.89-1.13, P=0.95). Conclusions: Our findings suggest a causal effect of increased BMI on reduced breast cancer survival for ER-positive breast cancer. There is no evidence of a causal effect of higher BMI on survival for ER-negative breast cancer cases.

Original languageEnglish
Pages (from-to)1891-1902
Number of pages12
JournalInternational Journal of Epidemiology
Volume46
Issue number6
DOIs
Publication statusPublished - 1 Dec 2017
Externally publishedYes

Keywords

  • Body mass index
  • Breast cancer survival
  • Epidemiology
  • Genetics
  • Mendelian randomization

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