PLoS Medicine (Aug 2016)

Genetically Predicted Body Mass Index and Breast Cancer Risk: Mendelian Randomization Analyses of Data from 145,000 Women of European Descent.

  • Yan Guo,
  • Shaneda Warren Andersen,
  • Xiao-Ou Shu,
  • Kyriaki Michailidou,
  • Manjeet K Bolla,
  • Qin Wang,
  • Montserrat Garcia-Closas,
  • Roger L Milne,
  • Marjanka K Schmidt,
  • Jenny Chang-Claude,
  • Allison Dunning,
  • Stig E Bojesen,
  • Habibul Ahsan,
  • Kristiina Aittomäki,
  • Irene L Andrulis,
  • Hoda Anton-Culver,
  • Volker Arndt,
  • Matthias W Beckmann,
  • Alicia Beeghly-Fadiel,
  • Javier Benitez,
  • Natalia V Bogdanova,
  • Bernardo Bonanni,
  • Anne-Lise Børresen-Dale,
  • Judith Brand,
  • Hiltrud Brauch,
  • Hermann Brenner,
  • Thomas Brüning,
  • Barbara Burwinkel,
  • Graham Casey,
  • Georgia Chenevix-Trench,
  • Fergus J Couch,
  • Angela Cox,
  • Simon S Cross,
  • Kamila Czene,
  • Peter Devilee,
  • Thilo Dörk,
  • Martine Dumont,
  • Peter A Fasching,
  • Jonine Figueroa,
  • Dieter Flesch-Janys,
  • Olivia Fletcher,
  • Henrik Flyger,
  • Florentia Fostira,
  • Marilie Gammon,
  • Graham G Giles,
  • Pascal Guénel,
  • Christopher A Haiman,
  • Ute Hamann,
  • Maartje J Hooning,
  • John L Hopper,
  • Anna Jakubowska,
  • Farzana Jasmine,
  • Mark Jenkins,
  • Esther M John,
  • Nichola Johnson,
  • Michael E Jones,
  • Maria Kabisch,
  • Muhammad Kibriya,
  • Julia A Knight,
  • Linetta B Koppert,
  • Veli-Matti Kosma,
  • Vessela Kristensen,
  • Loic Le Marchand,
  • Eunjung Lee,
  • Jingmei Li,
  • Annika Lindblom,
  • Robert Luben,
  • Jan Lubinski,
  • Kathi E Malone,
  • Arto Mannermaa,
  • Sara Margolin,
  • Frederik Marme,
  • Catriona McLean,
  • Hanne Meijers-Heijboer,
  • Alfons Meindl,
  • Susan L Neuhausen,
  • Heli Nevanlinna,
  • Patrick Neven,
  • Janet E Olson,
  • Jose I A Perez,
  • Barbara Perkins,
  • Paolo Peterlongo,
  • Kelly-Anne Phillips,
  • Katri Pylkäs,
  • Anja Rudolph,
  • Regina Santella,
  • Elinor J Sawyer,
  • Rita K Schmutzler,
  • Caroline Seynaeve,
  • Mitul Shah,
  • Martha J Shrubsole,
  • Melissa C Southey,
  • Anthony J Swerdlow,
  • Amanda E Toland,
  • Ian Tomlinson,
  • Diana Torres,
  • Thérèse Truong,
  • Giske Ursin,
  • Rob B Van Der Luijt,
  • Senno Verhoef,
  • Alice S Whittemore,
  • Robert Winqvist,
  • Hui Zhao,
  • Shilin Zhao,
  • Per Hall,
  • Jacques Simard,
  • Peter Kraft,
  • Paul Pharoah,
  • David Hunter,
  • Douglas F Easton,
  • Wei Zheng

DOI
https://doi.org/10.1371/journal.pmed.1002105
Journal volume & issue
Vol. 13, no. 8
p. e1002105

Abstract

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BackgroundObservational epidemiological studies have shown that high body mass index (BMI) is associated with a reduced risk of breast cancer in premenopausal women but an increased risk in postmenopausal women. It is unclear whether this association is mediated through shared genetic or environmental factors.MethodsWe applied Mendelian randomization to evaluate the association between BMI and risk of breast cancer occurrence using data from two large breast cancer consortia. We created a weighted BMI genetic score comprising 84 BMI-associated genetic variants to predicted BMI. We evaluated genetically predicted BMI in association with breast cancer risk using individual-level data from the Breast Cancer Association Consortium (BCAC) (cases = 46,325, controls = 42,482). We further evaluated the association between genetically predicted BMI and breast cancer risk using summary statistics from 16,003 cases and 41,335 controls from the Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) Project. Because most studies measured BMI after cancer diagnosis, we could not conduct a parallel analysis to adequately evaluate the association of measured BMI with breast cancer risk prospectively.ResultsIn the BCAC data, genetically predicted BMI was found to be inversely associated with breast cancer risk (odds ratio [OR] = 0.65 per 5 kg/m2 increase, 95% confidence interval [CI]: 0.56-0.75, p = 3.32 × 10-10). The associations were similar for both premenopausal (OR = 0.44, 95% CI:0.31-0.62, p = 9.91 × 10-8) and postmenopausal breast cancer (OR = 0.57, 95% CI: 0.46-0.71, p = 1.88 × 10-8). This association was replicated in the data from the DRIVE consortium (OR = 0.72, 95% CI: 0.60-0.84, p = 1.64 × 10-7). Single marker analyses identified 17 of the 84 BMI-associated single nucleotide polymorphisms (SNPs) in association with breast cancer risk at p ConclusionsBMI predicted by genome-wide association studies (GWAS)-identified variants is inversely associated with the risk of both pre- and postmenopausal breast cancer. The reduced risk of postmenopausal breast cancer associated with genetically predicted BMI observed in this study differs from the positive association reported from studies using measured adult BMI. Understanding the reasons for this discrepancy may reveal insights into the complex relationship of genetic determinants of body weight in the etiology of breast cancer.