Gaussian graphical modeling of the serum exposome and metabolome reveals interactions between environmental chemicals and endogenous metabolites
Abstract 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...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2021-04-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-021-87070-9 |
| _version_ | 1818751596455002112 |
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| author | Vincent Bessonneau Roy R. Gerona Jessica Trowbridge Rachel Grashow Thomas Lin Heather Buren Rachel Morello-Frosch Ruthann A. Rudel |
| author_facet | Vincent Bessonneau Roy R. Gerona Jessica Trowbridge Rachel Grashow Thomas Lin Heather Buren Rachel Morello-Frosch Ruthann A. Rudel |
| author_sort | Vincent Bessonneau |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-12-18T04:38:05Z |
| format | Article |
| id | doaj.art-ec5fc71903e14229b6f75ed6290d024c |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-12-18T04:38:05Z |
| publishDate | 2021-04-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-ec5fc71903e14229b6f75ed6290d024c2022-12-21T21:20:48ZengNature PortfolioScientific Reports2045-23222021-04-0111111510.1038/s41598-021-87070-9Gaussian graphical modeling of the serum exposome and metabolome reveals interactions between environmental chemicals and endogenous metabolitesVincent Bessonneau0Roy R. Gerona1Jessica Trowbridge2Rachel Grashow3Thomas Lin4Heather Buren5Rachel Morello-Frosch6Ruthann A. Rudel7Silent Spring InstituteClinical Toxicology and Environmental Biomonitoring Lab, Department of Obstetrics, Gynecology and Reproductive Sciences, University of CaliforniaSchool of Public Health, University of CaliforniaDepartment of Environmental Health, Harvard T.H. Chan School of Public HealthClinical Toxicology and Environmental Biomonitoring Lab, Department of Obstetrics, Gynecology and Reproductive Sciences, University of CaliforniaUnited Fire Service WomenSchool of Public Health, University of CaliforniaSilent Spring InstituteAbstract 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.https://doi.org/10.1038/s41598-021-87070-9 |
| spellingShingle | Vincent Bessonneau Roy R. Gerona Jessica Trowbridge Rachel Grashow Thomas Lin Heather Buren Rachel Morello-Frosch Ruthann A. Rudel Gaussian graphical modeling of the serum exposome and metabolome reveals interactions between environmental chemicals and endogenous metabolites Scientific Reports |
| title | Gaussian graphical modeling of the serum exposome and metabolome reveals interactions between environmental chemicals and endogenous metabolites |
| title_full | Gaussian graphical modeling of the serum exposome and metabolome reveals interactions between environmental chemicals and endogenous metabolites |
| title_fullStr | Gaussian graphical modeling of the serum exposome and metabolome reveals interactions between environmental chemicals and endogenous metabolites |
| title_full_unstemmed | Gaussian graphical modeling of the serum exposome and metabolome reveals interactions between environmental chemicals and endogenous metabolites |
| title_short | Gaussian graphical modeling of the serum exposome and metabolome reveals interactions between environmental chemicals and endogenous metabolites |
| title_sort | gaussian graphical modeling of the serum exposome and metabolome reveals interactions between environmental chemicals and endogenous metabolites |
| url | https://doi.org/10.1038/s41598-021-87070-9 |
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