Gaussian graphical modeling of the serum exposome and metabolome reveals interactions between environmental chemicals and endogenous metabolites.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
07 04 2021
Historique:
received: 17 10 2020
accepted: 23 03 2021
entrez: 8 4 2021
pubmed: 9 4 2021
medline: 16 11 2021
Statut: epublish

Résumé

Given the complex exposures from both exogenous and endogenous sources that an individual experiences during life, exposome-wide association studies that interrogate levels of small molecules in biospecimens have been proposed for discovering causes of chronic diseases. We conducted a study to explore associations between environmental chemicals and endogenous molecules using Gaussian graphical models (GGMs) of non-targeted metabolomics data measured in a cohort of California women firefighters and office workers. GGMs revealed many exposure-metabolite associations, including that exposures to mono-hydroxyisononyl phthalate, ethyl paraben and 4-ethylbenzoic acid were associated with metabolites involved in steroid hormone biosynthesis, and perfluoroalkyl substances were linked to bile acids-hormones that regulate cholesterol and glucose metabolism-and inflammatory signaling molecules. Some hypotheses generated from these findings were confirmed by analysis of data from the National Health and Nutrition Examination Survey. Taken together, our findings demonstrate a novel approach to discovering associations between chemical exposures and biological processes of potential relevance for disease causation.

Identifiants

pubmed: 33828161
doi: 10.1038/s41598-021-87070-9
pii: 10.1038/s41598-021-87070-9
pmc: PMC8027000
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

7607

Subventions

Organisme : NIEHS NIH HHS
ID : R01 ES027051
Pays : United States

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Auteurs

Vincent Bessonneau (V)

Silent Spring Institute, 320 Nevada Street, Newton, MA, 02460, USA.
Inserm, EHESP, Irset (Institut de Recherche en Santé, Environnement Et Travail) - UMR_S 1085, Univ. Rennes, 35000, Rennes, France.

Roy R Gerona (RR)

Clinical Toxicology and Environmental Biomonitoring Lab, Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco, CA, USA.

Jessica Trowbridge (J)

School of Public Health, University of California, 130 Mulford, Hall #3144, Berkeley, CA, 94720, USA.

Rachel Grashow (R)

Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

Thomas Lin (T)

Clinical Toxicology and Environmental Biomonitoring Lab, Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco, CA, USA.

Heather Buren (H)

United Fire Service Women, San Francisco, CA, USA.

Rachel Morello-Frosch (R)

School of Public Health, University of California, 130 Mulford, Hall #3144, Berkeley, CA, 94720, USA. rmf@berkeley.edu.
Department of Environmental Science, Policy and Management, University of California, Berkeley, CA, USA. rmf@berkeley.edu.

Ruthann A Rudel (RA)

Silent Spring Institute, 320 Nevada Street, Newton, MA, 02460, USA. rudel@silentspring.org.

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Classifications MeSH