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

Int J Epidemiol. 2017 Dec 1;46(6):1814-1822. doi: 10.1093/ije/dyx131.


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.

Keywords: Body mass index; Mendelian randomization; breast cancer survival; epidemiology; genetics.

MeSH terms

  • Body Mass Index*
  • Breast Neoplasms / genetics*
  • Breast Neoplasms / mortality*
  • Causality
  • Europe / epidemiology
  • Female
  • Genetic Variation
  • Humans
  • Mendelian Randomization Analysis
  • Meta-Analysis as Topic
  • Polymorphism, Single Nucleotide
  • Receptors, Estrogen / genetics*
  • Risk Assessment
  • Risk Factors
  • Survival Analysis
  • White People / statistics & numerical data*


  • Receptors, Estrogen