Abstract
BACKGROUND: Air pollution has been implicated in various health conditions, including cancer. However, the relationship between long-term exposure to air pollution and breast cancer risk, its subtypes, and survival remains unclear. METHODS: This study employed a two-sample Mendelian Randomization (MR) design to investigate the causal effects of PM(2.5), PM(10), NO₂, and NO(x) on breast cancer risk and survival. Genetic instruments for air pollutants were obtained from the UK Biobank, while breast cancer outcomes, were sourced from the Breast Cancer Association Consortium (BCAC) and the FinnGen study. The primary method was inverse-variance weighted (IVW), MR estimates for outcomes from various datasets were synthesized using the fixed-effects meta-analysis method. Pleiotropy and heterogeneity were evaluated with MR-Egger intercept and Cochran's Q test, while leave-one-out analysis tested the robustness of the findings. RESULTS: MR analysis demonstrated a significant causal association between genetically predicted NO₂ and PM(10) exposure and increased breast cancer risk. A one standard deviation (SD) increase in NO₂ was associated with a 68% higher risk of breast cancer, while a one SD increase in PM(10) was linked to a 36% increased risk. Subgroup analysis revealed similar associations, particularly for both ER + and ER - subtypes with PM(10). In contrast, no significant associations were observed for PM(2.5) or NO(x). Additionally, no strong evidence was found linking air pollution exposure to breast cancer survival. CONCLUSIONS: This study provides evidence of a causal link between long-term exposure to NO₂ and PM(10) and breast cancer risk, especially for hormone receptor subtypes. However, the effects of PM(2.5) and NO(x) on breast cancer risk were not significant, and air pollution exposure did not appear to impact survival. Further research is needed to elucidate the specific biological mechanisms and to extend the analysis to non-European populations.