Chronic Low-Dose Exposure to Xenoestrogen Ambient Air Pollutants and Breast Cancer Risk: XENAIR Protocol for a Case-Control Study Nested Within the French E3N Cohort (Preprint)
Authors: Amadou Amina , Coudon Thomas , Praud Delphine , Salizzoni Pietro , Leffondre Karen , Lévêque Emilie , Boutron-Ruault Marie-Christine , Danjou Aurélie M N , Morelli Xavier , Le Cornet Charlotte , Perrier Lionel , Couvidat Florian , Bessagnet Bertrand , Caudeville Julien , Faure Elodie , Mancini Francesca Romana , Gulliver John , Severi Gianluca , Fervers Béatrice 
Published: September 2020

BACKGROUND

Breast cancer is the most frequent cancer in women in industrialized countries. Lifestyle and environmental factors, particularly endocrine-disrupting pollutants, have been suggested to play a role in breast cancer risk. Current epidemiological studies, although not fully consistent, suggest a positive association of breast cancer risk with exposure to several International Agency for Research on Cancer Group 1 air-pollutant carcinogens, such as particulate matter, polychlorinated biphenyls (PCB), dioxins, Benzo[a]pyrene (BaP), and cadmium. However, epidemiological studies remain scarce and inconsistent. It has been proposed that the menopausal status could modify the relationship between pollutants and breast cancer and that the association varies with hormone receptor status.

OBJECTIVE

The XENAIR project will investigate the association of breast cancer risk (overall and by hormone receptor status) with chronic exposure to selected air pollutants, including particulate matter, nitrogen dioxide (NO2), ozone (O3), BaP, dioxins, PCB-153, and cadmium.

METHODS

Our research is based on a case-control study nested within the French national E3N cohort of 5222 invasive breast cancer cases identified during follow-up from 1990 to 2011, and 5222 matched controls. A questionnaire was sent to all participants to collect their lifetime residential addresses and information on indoor pollution. We will assess these exposures using complementary models of land-use regression, atmospheric dispersion, and regional chemistry-transport (CHIMERE) models, via a Geographic Information System. Associations with breast cancer risk will be modeled using conditional logistic regression models. We will also study the impact of exposure on DNA methylation and interactions with genetic polymorphisms. Appropriate statistical methods, including Bayesian modeling, principal component analysis, and cluster analysis, will be used to assess the impact of multipollutant exposure. The fraction of breast cancer cases attributable to air pollution will be estimated.

RESULTS

The XENAIR project will contribute to current knowledge on the health effects of air pollution and identify and understand environmental modifiable risk factors related to breast cancer risk.

CONCLUSIONS

The results will provide relevant evidence to governments and policy-makers to improve effective public health prevention strategies on air pollution. The XENAIR dataset can be used in future efforts to study the effects of exposure to air pollution associated with other chronic conditions.

INTERNATIONAL REGISTERED REPORT

DERR1-10.2196/15167