Mapping the Human Exposome to Uncover the Causes of Breast Cancer.


Journal

International journal of environmental research and public health
ISSN: 1660-4601
Titre abrégé: Int J Environ Res Public Health
Pays: Switzerland
ID NLM: 101238455

Informations de publication

Date de publication:
27 12 2019
Historique:
received: 30 11 2019
revised: 20 12 2019
accepted: 21 12 2019
entrez: 2 1 2020
pubmed: 2 1 2020
medline: 1 5 2020
Statut: epublish

Résumé

Breast cancer is an important cause of morbidity and mortality for women, yet a significant proportion of variation in individual risk is unexplained. It is reasonable to infer that unexplained breast cancer risks are caused by a myriad of exposures and their interactions with genetic factors. Most epidemiological studies investigating environmental contribution to breast cancer risk have focused on a limited set of exposures and outcomes based on a priori knowledge. We hypothesize that by measuring a rich set of molecular information with omics (e.g., metabolomics and adductomics) and comparing these profiles using a case-control design we can pinpoint novel environmental risk factors. Specifically, exposome-wide association study approaches can be used to compare molecular profiles between controls and either breast cancer cases or participants with phenotypic measures associated with breast cancer (e.g., high breast density, chronic inflammation). Current challenges in annotating compound peaks from biological samples can be addressed by creating libraries of environmental chemicals that are breast cancer relevant using publicly available high throughput exposure and toxicity data, and by mass spectra fragmentation. This line of discovery and innovation will extend understanding of how environmental exposures interact with genetics to affect health, and provide evidence to support new breast cancer prevention strategies.

Identifiants

pubmed: 31892107
pii: ijerph17010189
doi: 10.3390/ijerph17010189
pmc: PMC6982073
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

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Auteurs

Vincent Bessonneau (V)

Silent Spring Institute, 320 Nevada Street Newton, Newton, MA 02460, USA.

Ruthann A Rudel (RA)

Silent Spring Institute, 320 Nevada Street Newton, Newton, MA 02460, USA.

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Classifications MeSH