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Background Growing epidemiological evidence suggests an association between exposure to air pollutants and breast cancer. Yet, the underlying mechanisms remain poorly understood. This study explored the mediating role of thirteen metabolic health biomarkers in the relationship between exposure to three air pollutants, i.e. nitrogen dioxide (NO 2 ), polychlorinated biphenyls 153 (PCB153), and benzo[a]pyrene (BaP), and breast cancer risk. Methods We used data from a nested case–control study within the French national prospective E3N-Generations cohort, involving 523 breast cancer cases and 523 matched controls. The four-way decomposition mediation of total effects for thirteen biomarkers was applied to estimate interaction and mediation effects (controlled direct, reference interaction, mediated interaction, and pure indirect effects). Results The analyses indicated a significant increase in breast cancer risk associated with BaP exposure (odds ratio (OR) Q4 vs Q1  = 2.32, 95% confidence intervals (CI): 1.00–5.37). PCB153 exposure showed a positive association only in the third quartile (OR Q3 vs Q1  = 2.25, CI 1.13–4.57), but it appeared to be non-significant in the highest quartile (OR Q4 vs Q1  = 2.07, CI 0.93–4.61). No association was observed between NO 2 exposure and breast cancer risk. Estradiol was associated with an increased risk of breast cancer (OR per one standard deviation (SD) increment = 1.22, CI 1.05–1.42), while thyroid-stimulating hormone was inversely related to breast cancer risk (OR per 1SD increase = 0.87, CI 0.75–1.00). We observed a suggestive mediated effect of the association between the three pollutants and breast cancer risk, through albumin, high-density lipoproteins cholesterol, low-density lipoprotein cholesterol, parathormone, and estradiol. Conclusion Although limited by a lack of statistical power, this study provides relevant insights into the potential mediating role of certain biomarkers in the association between air pollutant exposure and breast cancer risk, highlighting the need for further in-depth studies in large populations.

Air pollution is a complex mixture of closely correlated pollutants, making it challenging to assess both the overall mixture effect and to isolate the individual impact of each pollutant on breast cancer (BC) risk. This study assessed the effect of exposure to a mixture of seven correlated air pollutants (benzo[a]pyrene, cadmium, dioxins, polychlorinated biphenyl 153 (PCB153), nitrogen dioxide (NO ), particulate matter (PM and PM )) on BC risk. The study was based on a case-control study nested within the French E3N-Generations cohort (5222 incident BC cases/5222 matched controls). Annual average concentrations of each pollutant were estimated using the CHIMERE chemistry-transport model, based on participants' residential addresses from 1990 to the index date. Bayesian kernel machine regression (BKMR) and quantile G-computation (QGC) were used to evaluate the joint effect of the pollutant mixture, individual pollutant contributions, and potential interactions. In all women, the BKMR model showed an increasing trend in BC risk associated with a joint increase in exposure to the seven pollutants. Among individual pollutants, NO₂, PCB153, and PM showed the strongest positive dose-response associations. The QGC model also found a significant association between the pollutant mixture and BC risk (odds ratio (OR) = 1.12; 95% confidence interval (CI) = 1.02-1.24) per quartile increase in the mixture. This study provides evidence of a positive association between exposure to a mixture of seven air pollutants and the risk of BC for the two statistical approaches. NO contributed most significantly to the overall effect, followed by PCB153 and PM. These findings underscore the necessity of evaluating combined pollutant mixtures in risk assessment, identifying high-risk subpopulations, and designing targeted preventive strategies.