@article{6eb53bb369124823b6ea78f1e4f4b602,
title = "Dysregulated lipid and fatty acid metabolism link perfluoroalkyl substances exposure and impaired glucose metabolism in young adults",
abstract = "Background: Per- and polyfluoroalkyl substances (PFASs) exposure is ubiquitous among the US population and has been linked to adverse health outcomes including cardiometabolic diseases, immune dysregulation and endocrine disruption. However, the metabolic mechanism underlying the adverse health effect of PFASs exposure is unknown. Objective: The aim of this project is to investigate the association between PFASs exposure and altered metabolic pathways linked to increased cardiometabolic risk in young adults. Methods: A total of 102 young adults with 82% overweight or obese participants were enrolled from Southern California between 2014 and 2017. Cardiometabolic outcomes were assessed including oral glucose tolerance test (OGTT) measures, body fat and lipid profiles. High-resolution metabolomics was used to quantify plasma exposure levels of three PFAS congeners and intensity profiles of the untargeted metabolome. Fasting concentrations of 45 targeted metabolites involved in fatty acid and lipid metabolism were used to verify untargeted metabolomics findings. Bayesian Kernel Machine Regression (BKMR) was used to examine the associations between PFAS exposure mixture and cardiometabolic outcomes adjusting for covariates. Mummichog pathway enrichment analysis was used to explore PFAS-associated metabolic pathways. Moreover, the effect of PFAS exposure on the metabolic network, including metabolomic profiles and cardiometabolic outcomes, was investigated. Results: Higher exposure to perfluorooctanoic acid (PFOA) was associated with higher 30-minute glucose levels and glucose area under the curve (AUC) during the OGTT (p < 0.001). PFAS exposure was also associated with altered lipid pathways, which contributed to the metabolic network connecting PFOA and higher glucose levels following the OGTT. Targeted metabolomics analysis indicated that higher PFOA exposure was associated with higher levels of glycerol (p = 0.006), which itself was associated with higher 30-minute glucose (p = 0.006). Conclusions: Increased lipolysis and fatty acid oxidation could contribute to the biological mechanisms linking PFAS exposure and impaired glucose metabolism among young adults. Findings of this study warrants future experimental studies and epidemiological studies with larger sample size to replicate.",
keywords = "Cardiometabolic dysfunction, Lipolysis, Metabolomics, Perfluoroalkyl substances, Young adults, β-oxidation",
author = "Zhanghua Chen and Tingyu Yang and Walker, {Douglas I.} and Thomas, {Duncan C.} and Chenyu Qiu and Leda Chatzi and Alderete, {Tanya L.} and Kim, {Jeniffer S.} and Conti, {David V.} and Breton, {Carrie V.} and Donghai Liang and Hauser, {Elizabeth R.} and Jones, {Dean P.} and Gilliland, {Frank D.}",
note = "Funding Information: Z.C. led the study design, statistical analyses and paper writing. T.Y. and C.Q. helped to perform the statistical analysis and paper writing. F.D.G. D.J. D.I.W. D.C.T. E.R.H. L.C. and C.B. all contributed to the study design and development of the study protocol. Z.C. F.D.G. D.I.W. J.K. T.L.A. L.C. and E.R.H. contributed to the data collection. Z.C. E.R.H. D.C.T. D.L. and D.V.C. contributed to the development of statistical methods. All authors reviewed, edited the article and contributed to discussion. Z.C. is the guarantor of this work, and as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. All authors declare that they have no conflict of interest. Data management of the untargeted metabolomics data was supported by CHEAR Center for Data Science at ICAHN School of Medicine at Mount Sinai, NY (grant U2CES026555). The laboratory analysis of targeted metabolomics data was conducted by Drs. Olga Ilkayeva, Mike Muehlbauer and Christopher Newgard at Duke Molecular Physiology Institute Metabolomics/Biomarker Core Laboratory. This work was supported by [CHEAR project 2016-1448, grants (U2CES026560 and U2CES026555)] from the National Institute of Environmental Health Sciences as part of the Children's Environmental Health Analysis Resource (CHEAR) and National Exposure Laboratory at Emory University. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Environmental Health Sciences (NIEHS). This project was also supported by NIEHS awards R00ES027870 and Southern California Children's Environmental Health Center grant funded by NIEHS (5P01ES022845-03) and United States Environmental Protection Agency (RD83544101). Additional grants support included NIEHS (5P01ES011627, R00ES027853, and R01ES029944); the Southern California Environmental Health Sciences Center grant (5P30ES007048) funded by NIEHS; and the Hastings Foundation. Funding Information: Data management of the untargeted metabolomics data was supported by CHEAR Center for Data Science at ICAHN School of Medicine at Mount Sinai, NY (grant U2CES026555). The laboratory analysis of targeted metabolomics data was conducted by Drs. Olga Ilkayeva, Mike Muehlbauer and Christopher Newgard at Duke Molecular Physiology Institute Metabolomics/Biomarker Core Laboratory. Funding Information: This work was supported by [CHEAR project 2016-1448, grants (U2CES026560 and U2CES026555)] from the National Institute of Environmental Health Sciences as part of the Children{\textquoteright}s Environmental Health Analysis Resource (CHEAR) and National Exposure Laboratory at Emory University. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Environmental Health Sciences (NIEHS). This project was also supported by NIEHS awards R00ES027870 and Southern California Children's Environmental Health Center grant funded by NIEHS (5P01ES022845-03) and United States Environmental Protection Agency (RD83544101). Additional grants support included NIEHS (5P01ES011627, R00ES027853, and R01ES029944); the Southern California Environmental Health Sciences Center grant (5P30ES007048) funded by NIEHS; and the Hastings Foundation. Publisher Copyright: {\textcopyright} 2020 The Author(s)",
year = "2020",
month = dec,
doi = "10.1016/j.envint.2020.106091",
language = "English",
volume = "145",
journal = "Environment international",
issn = "0160-4120",
publisher = "Elsevier Ltd.",
}