Our results are valuable for the development of primary prevention strategies, improvement of breast cancer risk stratification in the general population, and identification of novel breast cancer risk factors.
We used a two-sample Mendelian randomization approach and selected genetic instrumental variables from large-scale genome-wide association studies. Publicly available summary-level Breast Cancer Association Consortium data (n = 247,173; 133,384 cases, 113,789 controls) for the following subtypes were included: luminal A-like (45,253 cases), luminal B-/HER2-negative-like (6,350 cases), luminal B-like (6,427 cases), HER2-enriched (2,884 cases), and triple-negative (8,602 cases). We employed multiple Mendelian randomization methods to evaluate the strength of causal evidence for each risk factor-subtype association.
Collectively, our analyses indicated that increased height and decreased BMI are probable causal risk factors for all five subtypes. For the other risk factors, the strength of evidence for causal effects differed across subtypes. Heterogeneity in the magnitude of causal effect estimates for age at menopause and breast density was explained by null findings for triple-negative tumors. Regular smoking was the sole risk factor for which there was no evidence of a causal effect on any subtype.
This study suggests that established breast cancer risk factors differ across hormone receptor subtypes.
It is unclear if established breast cancer risk factors exert similar causal effects across hormone receptor breast cancer subtypes. We estimated and compared causal estimates of height, body mass index (BMI), type 2 diabetes, age at menarche, age at menopause, breast density, alcohol consumption, regular smoking, and physical activity across these subtypes.
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