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Sun P, Guo X, Ding E, Li C, Ren H, Xu Y, Qian J, Deng F, Shi W, Dong H, Lin EZ, Guo P, Fang J, Zhang Q, Zhao W, Tong S, Lu X, Pollitt KJG, Shi X, Tang S. Association between Personal Abiotic Airborne Exposures and Body Composition Changes among Healthy Adults (60-69 Years Old): A Combined Exposome-Wide and Lipidome Mediation Approach from the China BAPE Study. ENVIRONMENTAL HEALTH PERSPECTIVES 2024; 132:77005. [PMID: 39028628 PMCID: PMC11259245 DOI: 10.1289/ehp13865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 05/25/2024] [Accepted: 06/24/2024] [Indexed: 07/21/2024]
Abstract
BACKGROUND Evidence suggested that abiotic airborne exposures may be associated with changes in body composition. However, more evidence is needed to identify key pollutants linked to adverse health effects and their underlying biomolecular mechanisms, particularly in sensitive older adults. OBJECTIVES Our research aimed to systematically assess the relationship between abiotic airborne exposures and changes in body composition among healthy older adults, as well as the potential mediating mechanisms through the serum lipidome. METHODS From September 2018 to January 2019, we conducted a monthly survey among 76 healthy adults (60-69 years old) in the China Biomarkers of Air Pollutant Exposure (BAPE) study, measuring their personal exposures to 632 abiotic airborne pollutions using MicroPEM and the Fresh Air wristband, 18 body composition indicators from the InBody 770 device, and lipidomics from venous blood samples. We used an exposome-wide association study (ExWAS) and deletion/substitution/addition (DSA) model to unravel complex associations between exposure to contaminant mixtures and body composition, a Bayesian kernel machine regression (BKMR) model to assess the overall effect of key exposures on body composition, and mediation analysis to identify lipid intermediators. RESULTS The ExWAS and DSA model identified that 2,4,5-T methyl ester (2,4,5-TME), 9,10-Anthracenedione (ATQ), 4b,8-dimethyl-2-isopropylphenanthrene, and 4b,5,6,7,8,8a,9,10-octahydro-(DMIP) were associated with increased body fat mass (BFM), fat mass indicators (FMI), percent body fat (PBF), and visceral fat area (VFA) in healthy older adults [Bonferroni-Hochberg false discovery rate ( FD R BH ) < 0.05 ]. The BKMR model demonstrated a positive correlation between contaminants (anthracene, ATQ, copaene, di-epi-α -cedrene, and DMIP) with VFA. Mediation analysis revealed that phosphatidylcholine [PC, PC(16:1e/18:1), PC(16:2e/18:0)] and sphingolipid [SM, SM(d18:2/24:1)] mediated a significant portion, ranging from 12.27% to 26.03% (p-value < 0.05 ), of the observed increase in VFA. DISCUSSION Based on the evidence from multiple model results, ATQ and DMIP were statistically significantly associated with the increased VFA levels of healthy older adults, potentially regulated through lipid intermediators. These findings may have important implications for identifying potentially harmful environmental chemicals and developing targeted strategies for the control and prevention of chronic diseases in the future, particularly as the global population is rapidly aging. https://doi.org/10.1289/EHP13865.
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Affiliation(s)
- Peijie Sun
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Department of Toxicology, School of Public Health, China Medical University, Shenyang, China
| | - Xiaojie Guo
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
| | - Enmin Ding
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Chenfeng Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Department of Occupational Health and Environment Health, School of Public Health, Anhui Medical University, Hefei, Anhui, China
| | - Huimin Ren
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Department of Toxicology, School of Public Health, China Medical University, Shenyang, China
| | - Yibo Xu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, China
| | - Jiankun Qian
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Department of Toxicology, School of Public Health, China Medical University, Shenyang, China
| | - Fuchang Deng
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Wanying Shi
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Haoran Dong
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Elizabeth Z. Lin
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, Connecticut, USA
| | - Pengfei Guo
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, Connecticut, USA
| | - Jianlong Fang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Qian Zhang
- Chinese Center for Disease Control and Prevention, National Institute for Nutrition and Health, Beijing, China
| | - Wenhua Zhao
- Chinese Center for Disease Control and Prevention, National Institute for Nutrition and Health, Beijing, China
| | - Shilu Tong
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- School of Public Health and Social Work, Queensland University of Technology, Brisbane, Australia
| | - Xiaobo Lu
- Department of Toxicology, School of Public Health, China Medical University, Shenyang, China
| | - Krystal J. Godri Pollitt
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, Connecticut, USA
| | - Xiaoming Shi
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Song Tang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
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Rishan ST, Kline RJ, Rahman MS. New prospects of environmental RNA metabarcoding research in biological diversity, ecotoxicological monitoring, and detection of COVID-19: a critical review. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:11406-11427. [PMID: 38183542 DOI: 10.1007/s11356-023-31776-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 12/26/2023] [Indexed: 01/08/2024]
Abstract
Ecosystems are multifaceted and complex systems and understanding their composition is crucial for the implementation of efficient conservation and management. Conventional approaches to biodiversity surveys can have limitations in detecting the complete range of species present. In contrast, the study of environmental RNA (eRNA) offers a non-invasive and comprehensive method for monitoring and evaluating biodiversity across different ecosystems. Similar to eDNA, the examination of genetic material found in environmental samples can identify and measure many species, including ones that pose challenges to traditional methods. However, eRNA is degraded quickly and therefore shows promise in detection of living organisms closer to their actual location than eDNA methods. This method provides a comprehensive perspective on the well-being of ecosystems, facilitating the development of focused conservation approaches to save at-risk species and uphold ecological equilibrium. Furthermore, eRNA has been recognized as a valuable method for the identification of COVID-19 in the environment, besides its established uses in biodiversity protection. The SARS-CoV-2 virus, which is accountable for the worldwide epidemic, releases RNA particles into the surrounding environment via human waste, providing insights into the feasibility of detecting it in wastewater and other samples taken from the environment. In this article, we critically reviewed the recent research activities that use the eRNA method, including its utilization in biodiversity conservation, ecological surveillance, and ecotoxicological monitoring as well as its innovative potential in identifying COVID-19. Through this review, the reader can understand the recent developments, prospects, and challenges of eRNA research in ecosystem management and biodiversity conservation.
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Affiliation(s)
- Sakib Tahmid Rishan
- Biochemistry and Molecular Biology Program, School of Integrative Biological and Chemical Sciences, University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - Richard J Kline
- Biochemistry and Molecular Biology Program, School of Integrative Biological and Chemical Sciences, University of Texas Rio Grande Valley, Brownsville, TX, USA
- School of Earth, Environmental, and Marine Sciences, University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - Md Saydur Rahman
- Biochemistry and Molecular Biology Program, School of Integrative Biological and Chemical Sciences, University of Texas Rio Grande Valley, Brownsville, TX, USA.
- School of Earth, Environmental, and Marine Sciences, University of Texas Rio Grande Valley, Brownsville, TX, USA.
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Lin W, Yan Y, Ping S, Li P, Li D, Hu J, Liu W, Wen X, Ren Y. Metformin-Induced Epigenetic Toxicity in Zebrafish: Experimental and Molecular Dynamics Simulation Studies. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:1672-1681. [PMID: 33332093 DOI: 10.1021/acs.est.0c06052] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2023]
Abstract
The increased detection of many prescription drugs in aquatic environments has heightened concerns of their potential ecotoxicological effects. In this study, the effects of metformin (MEF) exposure on tissue accumulation, gene expression, and global DNA methylation (GDM) in zebrafish were investigated. The toxic mechanism of MEF exposure was simulated by molecular dynamics (MD) to reveal any conformational changes to DNA methyltransferase 1 (DNMT1). The results showed MEF accumulation in the gills, gut, and liver of zebrafish after 30 days of exposure, and the bioaccumulation capacity was in the order of gut > liver > gills. After a 30 day recovery period, MEF could still be detected in zebrafish tissues in groups exposed to MEF concentrations ≥ 10 μg/L. Moreover, the liver was the main site of GDM, and the restoration of GDM in the liver was slower than that in the gut and gills during the recovery period. Furthermore, MEF could induce the abnormal expression of CYP3A65, GSTM1, p53, and DNMT1 genes in the liver due to the formation of hydrogen bonds between MEF and the protein residues of those genes. The MD simulation allowed for the mechanistic determination of MEF-induced three-dimensional (3D) conformational changes and changes to the catalytic activity of DNMT1.
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Affiliation(s)
- Wenting Lin
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, P. R. China
| | - Yuanyang Yan
- School of Chemical and Chemical Engineering, South China University of Technology, Guangzhou 510640, P. R. China
| | - Senwen Ping
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, P. R. China
| | - Ping Li
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, P. R. China
| | - Diandi Li
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, P. R. China
| | - Junjie Hu
- School of Environment and Civil Engineering, Dongguan University of Technology, Dongguan 523808, P. R. China
| | - Wei Liu
- School of Medicine, South China University of Technology, Guangzhou 510006, P. R. China
| | - Xiufang Wen
- School of Chemical and Chemical Engineering, South China University of Technology, Guangzhou 510640, P. R. China
| | - Yuan Ren
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, P. R. China
- The Key Lab of Pollution Control and Ecosystem Restoration in Industry Clusters, Ministry of Education, Guangzhou 510006, China
- The Key Laboratory of Environmental Protection and Eco-Remediation of Guangdong Regular Higher Education Institutions, Guangzhou 510006, China
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