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Birolli WG, Lanças FM, Silveira HCS, Santos-Neto ÁJ. Development of a unified method for the determination of legacy and metabolites of current pesticides in serum for exposure assessment. Anal Bioanal Chem 2024; 416:5701-5710. [PMID: 39190144 DOI: 10.1007/s00216-024-05488-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2024] [Revised: 08/07/2024] [Accepted: 08/09/2024] [Indexed: 08/28/2024]
Abstract
The use of pesticides is often regarded as a fundamental aspect of conventional agriculture. However, these compounds have gained recognition as some of the oldest and most widely employed xenobiotic contaminants, necessitating effective strategies for human biomonitoring. In this context, a method was developed for the determination of 16 legacy organochlorine pesticides, 6 metabolites of current pesticides (2,4-D, malathion, parathion, fipronil, pyraclostrobin, cypermethrin, permethrin, cyfluthrin), and 1 triazine herbicide (atrazine) in serum. Samples were prepared with water, formic acid, acetonitrile, and ultrasound irradiation, followed by solid-phase extraction with Oasis Prime HLB. Subsequently, metabolites from current pesticides underwent derivatization using MTBSTFA with 1% TBDMSCl for analysis via gas chromatography-tandem mass spectrometry (GC-MS/MS), employing an SLB-5MS fused silica capillary column. Analytical curves were generated with limits of quantification from 0.3 to 4.0 ng.mL-1. Accuracy ranged from 69 to 124%, and the coefficient of variation from 2 to 28%. Moreover, determining 1-(4-chlorophenyl)-1H-pyrazol-3-ol was suggested as a biomarker for pyraclostrobin biomonitoring. This analytical approach facilitated the determination of both legacy and metabolites of current pesticides in the same serum sample, presenting an interesting and cost-effective option for large cohorts, and multi-omics studies that evaluate time-dependent biomarkers in blood samples, thereby enabling biomonitoring within the same matrix. Furthermore, a proof-of-concept involving 10 volunteers demonstrated exposure to 9 pesticides at mean concentrations measured in ng mL-1, consistent with findings from various biomonitoring initiatives.
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Affiliation(s)
- Willian G Birolli
- Chromatography Group, São Carlos Institute of Chemistry, University of São Paulo, São Carlos, São Paulo, Brazil.
- Molecular Oncology Research Center, Barretos Cancer Hospital, Barretos, São Paulo, Brazil.
| | - Fernando M Lanças
- Chromatography Group, São Carlos Institute of Chemistry, University of São Paulo, São Carlos, São Paulo, Brazil
| | - Henrique C S Silveira
- Molecular Oncology Research Center, Barretos Cancer Hospital, Barretos, São Paulo, Brazil
| | - Álvaro J Santos-Neto
- Chromatography Group, São Carlos Institute of Chemistry, University of São Paulo, São Carlos, São Paulo, Brazil
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Xie C, Yang S, Li Y, Zhang M, Xu Q, Wan Z, Song L, Lv Y, Luo D, Li Q, Wang Y, Chen H, Mei S. Associations of exposure to organochlorine pesticides and polychlorinated biphenyls with chronic kidney disease among adults: the modifying effects of lifestyle. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:45192-45203. [PMID: 38961018 DOI: 10.1007/s11356-024-34201-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Accepted: 06/27/2024] [Indexed: 07/05/2024]
Abstract
Exposure to organochlorine pesticides (OCPs) and polychlorinated biphenyls (PCBs) has been reported to be associated with renal impairment and chronic kidney disease (CKD). Nevertheless, the research results thus far have exhibited inconsistency, and the effect of lifestyle on their association is not clear. In this study, we assessed the correlation between serum OCPs/PCBs and CKD and renal function indicators including estimated glomerular filtration rate (eGFR) and albumin-to-creatinine ratio (ACR) among 1721 Chinese adults. In order to further investigate the potential impact of lifestyle, we conducted joint associations of lifestyle and OCPs/PCBs on CKD. We found a negative correlation between p,p'-DDE and eGFR, while logistic regression results showed a positive correlation between PCB-153 and CKD (OR, 1.92; 95% CI, 1.21, 3.06). Quantile g-computation regression analyses showed that the association between co-exposure to OCPs/PCBs and CKD was not significant, but p,p'-DDE and PCB-153 were the main contributors to the negative and positive co-exposure effects of eGFR and CKD, respectively, which is consistent with the regression results. Participants with both relatively high PCB-153 exposure and an unhealthy lifestyle had the highest risk of CKD, in the joint association analysis. The observed associations were generally supported by the FAS-eGFR method. Our research findings suggest that exposure to OCPs/PCBs may be associated with decreased eGFR and increased prevalence of CKD in humans, and a healthy lifestyle can to some extent alleviate the adverse association between PCB-153 exposure and CKD.
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Affiliation(s)
- Chang Xie
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, #13 Hangkong Road, Wuhan, 430030, Hubei, China
| | - Sijie Yang
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, #13 Hangkong Road, Wuhan, 430030, Hubei, China
| | - Yaping Li
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, #13 Hangkong Road, Wuhan, 430030, Hubei, China
| | - Mingye Zhang
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, #13 Hangkong Road, Wuhan, 430030, Hubei, China
| | - Qitong Xu
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, #13 Hangkong Road, Wuhan, 430030, Hubei, China
| | - Zhengce Wan
- Health Management Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Lulu Song
- Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yongman Lv
- Health Management Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Dan Luo
- Analytical Application Center, Shimadzu (China) Co., LTD., Wuhan Branch, No 96 Linjiang Avenue, Wuhan, 430060, China
| | - Qiang Li
- Analytical Application Center, Shimadzu (China) Co., LTD., Wuhan Branch, No 96 Linjiang Avenue, Wuhan, 430060, China
| | - Youjie Wang
- Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Hui Chen
- Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Surong Mei
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, #13 Hangkong Road, Wuhan, 430030, Hubei, China.
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3
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Wang M, Wang X, Huang K, Han B, Li R, Shen Y, Zhuang Z, Wang Z, Wang L, Zhou Y, Jing T. Human Biomonitoring of Environmental Chemicals among Elderly in Wuhan, China: Prioritizing Risks Using EPA's ToxCast Database. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:10001-10014. [PMID: 38788169 DOI: 10.1021/acs.est.4c00362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2024]
Abstract
In line with the "healthy aging" principle, we aim to assess the exposure map and health risks of environmental chemicals in the elderly. Blood samples from 918 elderly individuals in Wuhan, China, were analyzed using the combined gas/liquid-mass spectrometry technology to detect levels of 118 environmental chemicals. Cluster analysis identified exposure profiles, while risk indexes and bioanalytical equivalence percentages were calculated using EPA's ToxCast database. The detection rates for 87 compounds exceeded 70%. DEHP, DiBP, naphthalene, phenanthrene, DnBP, pyrene, anthracene, permethrin, fluoranthene, and PFOS showed the highest concentrations. Fat-soluble pollutants varied across lifestyles. In cluster 2, which was characterized by higher concentrations of fat-soluble substances, the proportion of smokers or drinkers was higher than that of nonsmokers or nondrinkers. Pesticides emerged as the most active environmental chemicals in peroxisome proliferator-activated receptor gamma antagonist, thyroid hormone receptor (TR) antagonist, TR agonist, and androgen receptor (AR) agonist activity assays. Additionally, PAEs and polycyclic aromatic hydrocarbons played significant roles as active contaminants for the corresponding targets of AR antagonists and estrogen receptor alpha. We proposed a list of priority pollutants linked to endocrine-disrupting toxic effects in the elderly, which may provide the groundwork for further research into environmental etiology.
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Affiliation(s)
- Mengyi Wang
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, #13 Hangkong Road, Wuhan, Hubei 430030, China
| | - Xiu Wang
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, #13 Hangkong Road, Wuhan, Hubei 430030, China
- The State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang 310003, PR China
| | - Kai Huang
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, #13 Hangkong Road, Wuhan, Hubei 430030, China
| | - Bin Han
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, #13 Hangkong Road, Wuhan, Hubei 430030, China
| | - Ruifang Li
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, #13 Hangkong Road, Wuhan, Hubei 430030, China
| | - Yang Shen
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, #13 Hangkong Road, Wuhan, Hubei 430030, China
| | - Zhijia Zhuang
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, #13 Hangkong Road, Wuhan, Hubei 430030, China
| | - Zhu Wang
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, #13 Hangkong Road, Wuhan, Hubei 430030, China
| | - Lulu Wang
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, #13 Hangkong Road, Wuhan, Hubei 430030, China
| | - Yikai Zhou
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, #13 Hangkong Road, Wuhan, Hubei 430030, China
| | - Tao Jing
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, #13 Hangkong Road, Wuhan, Hubei 430030, China
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You L, Kou J, Wang M, Ji G, Li X, Su C, Zheng F, Zhang M, Wang Y, Chen T, Li T, Zhou L, Shi X, Zhao C, Liu X, Mei S, Xu G. An exposome atlas of serum reveals the risk of chronic diseases in the Chinese population. Nat Commun 2024; 15:2268. [PMID: 38480749 PMCID: PMC10937660 DOI: 10.1038/s41467-024-46595-z] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 03/04/2024] [Indexed: 03/17/2024] Open
Abstract
Although adverse environmental exposures are considered a major cause of chronic diseases, current studies provide limited information on real-world chemical exposures and related risks. For this study, we collected serum samples from 5696 healthy people and patients, including those with 12 chronic diseases, in China and completed serum biomonitoring including 267 chemicals via gas and liquid chromatography-tandem mass spectrometry. Seventy-four highly frequently detected exposures were used for exposure characterization and risk analysis. The results show that region is the most critical factor influencing human exposure levels, followed by age. Organochlorine pesticides and perfluoroalkyl substances are associated with multiple chronic diseases, and some of them exceed safe ranges. Multi-exposure models reveal significant risk effects of exposure on hyperlipidemia, metabolic syndrome and hyperuricemia. Overall, this study provides a comprehensive human serum exposome atlas and disease risk information, which can guide subsequent in-depth cause-and-effect studies between environmental exposures and human health.
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Affiliation(s)
- Lei You
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian, 116023, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Liaoning Province Key Laboratory of Metabolomics, Dalian, 116023, China
| | - Jing Kou
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, # 13 Hangkong Road, Wuhan, Hubei, 430030, China
| | - Mengdie Wang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian, 116023, China
- Liaoning Province Key Laboratory of Metabolomics, Dalian, 116023, China
- School of Public Health, China Medical University, No. 77 Puhe Road, Shenbei New District, Shenyang, 110122, China
| | - Guoqin Ji
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian, 116023, China
- Liaoning Province Key Laboratory of Metabolomics, Dalian, 116023, China
- School of Life Science, China Medical University, No. 77 Puhe Road, Shenbei New District, Shenyang, 110122, China
| | - Xiang Li
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, # 13 Hangkong Road, Wuhan, Hubei, 430030, China
| | - Chang Su
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, 100050, China
| | - Fujian Zheng
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian, 116023, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Liaoning Province Key Laboratory of Metabolomics, Dalian, 116023, China
| | - Mingye Zhang
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, # 13 Hangkong Road, Wuhan, Hubei, 430030, China
| | - Yuting Wang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian, 116023, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Liaoning Province Key Laboratory of Metabolomics, Dalian, 116023, China
| | - Tiantian Chen
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian, 116023, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Liaoning Province Key Laboratory of Metabolomics, Dalian, 116023, China
| | - Ting Li
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian, 116023, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Liaoning Province Key Laboratory of Metabolomics, Dalian, 116023, China
| | - Lina Zhou
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian, 116023, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Liaoning Province Key Laboratory of Metabolomics, Dalian, 116023, China
| | - Xianzhe Shi
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian, 116023, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Liaoning Province Key Laboratory of Metabolomics, Dalian, 116023, China
| | - Chunxia Zhao
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian, 116023, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Liaoning Province Key Laboratory of Metabolomics, Dalian, 116023, China
| | - Xinyu Liu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian, 116023, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Liaoning Province Key Laboratory of Metabolomics, Dalian, 116023, China.
| | - Surong Mei
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, # 13 Hangkong Road, Wuhan, Hubei, 430030, China.
| | - Guowang Xu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian, 116023, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Liaoning Province Key Laboratory of Metabolomics, Dalian, 116023, China.
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ZHI M, WANG J. [Advances in the applications of exposomics in the identification of environmental pollutants and their health hazards]. Se Pu 2024; 42:142-149. [PMID: 38374594 PMCID: PMC10877475 DOI: 10.3724/sp.j.1123.2023.12011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Indexed: 02/21/2024] Open
Abstract
Environmental pollution has become a prominent global problem, and the potential health hazards of pollutants have caused widespread concern. However, revealing the relationship between complex-pollutant exposure and disease development remains an immense challenge. The core of environmental-health research and risk assessment is the identification of contaminants and their effects. Exposomics provides a new approach in the study of the relationship between environmental factors and human health. Both "top-down" and "bottom-up" strategies are employed in exposomics research. The development of new technologies for chemical detection and "multi-omics" has greatly facilitated the implementation of these strategies. Exposomics focuses on the measurement of an individual's lifelong exposure and aims to identify the health effects of such exposure. It involves the dynamic monitoring of external and internal exposure levels at different stages of life through traditional biomonitoring and exposomic methods. It also includes the identification of biomarkers, which indicate specific environmental exposures and the adverse effects of these exposures on health. Compared with traditional environmental-health studies, exposomics can more accurately reflect the diversity of exposure factors such as pollutants, natural factors, and lifestyles in the real environment, as well as the complexity of their in vivo processes and the responses they trigger in an organism. Powerful chemical analytical tools such as high-resolution mass spectrometry (HRMS) are widely used in studies related to the field of exposomics. Liquid chromatography-mass spectrometry (LC-MS) has been applied in the detection and analysis of environmental pollutants. Proteomics and metabolomics, as two important tools for biomarker identification and effects analysis, are widely used to explore the relationship between environmental factors and diseases. Pollutants can lead to pathological changes and even toxic effects by interacting with proteins. In the case of mixed exposure, some contaminants may present joint toxicity. The interaction between contaminants may change their environmental behavior or the amount of each contaminant that enters the human body, which, in turn, affects their health effects.
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ZHANG M, CAO Y, LI X, KOU J, XU Q, YANG S, ZHENG Z, LIU J, MEI S. [Exposure characteristics and health risk assessment of 97 typical chemical pollutants in human serum]. Se Pu 2024; 42:217-223. [PMID: 38374603 PMCID: PMC10877476 DOI: 10.3724/sp.j.1123.2023.11022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2023] [Indexed: 02/21/2024] Open
Abstract
Rapid industrial and agricultural developments in China have led to the wide use and discharge of chemical products and pesticides, resulting in extensive residues in environmental media. These residues can enter the human body through various pathways, leading to high exposure risks and health hazards. Because the human body is exposed to a variety of chemical pollutants, accurately quantifying the exposure levels of these pollutants in the human body and evaluating their health risks are of great importance. In this study, the serum concentrations of 97 typical chemical pollutants of 60 adults in central China were simultaneously determined using solid-phase extraction coupled with gas chromatography-tandem mass spectrometry (SPE-GC-MS/MS). In this method, 200 μL of a serum sample was mixed with 10 μL of an isotope-labeled internal standard solution. The sample was vortexed and refrigerated overnight at 4 ℃. Each sample was then deproteinized by the addition of 200 μL of 15% formic acid aqueous solution and vortexed. The serum sample was loaded into a preconditioned Oasis® PRiME HLB SPE cartridge and rinsed with 3 mL of methanol-water (6∶1, v/v). The SPE cartridge was subsequently vacuumed. The analytes were eluted with 3 mL of dichloromethane followed by 3 mL of n-hexane. The eluent was concentrated to near dryness under a gentle nitrogen stream and reconstituted with 100 μL of acetone. The samples were determined by GC-MS/MS and separated on a DB-5MS capillary column (30 m×0.25 mm×0.25 μm) with temperature programming. The column temperature was maintained at 70 ℃ for 2 min, increased at a rate of 25 ℃/min to 150 ℃, increased at a rate of 3 ℃/min to 200 ℃, and then held for 2 min. Finally, the column temperature was increased at a rate of 8 ℃/min to 300 ℃ and maintained at this temperature for 8 min. The samples were detected in multiple-reaction monitoring (MRM) mode and quantitatively analyzed using the internal standard method. Multiple linear regression models were used to analyze the effects of demographic characteristics, lifestyle habits, and diet on the concentrations of the chemical pollutants in the serum samples, and known biomonitoring equivalents (BEs) and human biomonitoring (HBM) values were combined to compute hazard quotients (HQs) and hazard indices (HIs) and evaluate the health risks of single and cumulative exposures to the chemical pollutants. The results showed that the main pollutants detected in human serum were organochlorine pesticides (OCPs), polychlorinated biphenyls (PCBs), and polycyclic aromatic hydrocarbons (PAHs). The detection rates of eight pollutants, including hexachlorobenzene (HCB) (100%), pentachlorophenol (PCP) (100%), p,p'-dichlorodiphenylene (p,p'-DDE) (100%), PCB-138 (100%), PCB-153 (98.3%), β-hexachlorocyclohexane (β-HCH) (91.7%), fluorene (Flu) (85.0%), and anthracene (Ant) (75.0%), were greater than 70%. The serum levels of β-HCH were higher in females than in males, and age was positively correlated with exposure to p,p'-DDE, PCB-138, PCB-153, and β-HCH. Increased exposure levels to p,p'-DDE and β-HCH may be associated with a high frequency of meat intake, whereas increased exposure level to PCP may be associated with a high frequency of vegetable intake. The serum HQ of PCP was greater than 1 in 6.7% of the samples, and no risk was observed for HCB and p,p'-DDE exposure in the study population. Approximately 28.3% of the study subjects had HI values greater than 1. Overall, the general adult population in this region is widely exposed to a wide range of chemical pollutants, and gender, age, and diet are likely to be the main factors influencing the concentration of chemical pollutants. The health risk of single and compound exposures to chemical pollutants should not be ignored.
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Bi J, Liu Q, Fan G, Fang Q, Zhang X, Qin X, Wu M, Wan Z, Lv Y, Wang Y, Song L. Exposure to organochlorine pesticides and polychlorinated biphenyls, adherence to an ideal cardiovascular health, and arterial stiffness among Chinese adults. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2023; 46:10. [PMID: 38142250 DOI: 10.1007/s10653-023-01791-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 11/17/2023] [Indexed: 12/25/2023]
Abstract
This study aimed to assess the relationships between exposure to individual organochlorine pesticides (OCPs), polychlorinated biphenyls (PCBs), and their mixture and arterial stiffness and explore whether adherence to an ideal cardiovascular health (CVH) could mitigate these associations. The cross-sectional study enrolled 1437 Chinese adults between March and May 2019 in Wuhan, China. OCPs and PCBs concentrations were measured using solid phase extraction coupled with gas chromatography-tandem mass spectrometry. Arterial stiffness was evaluated by brachial-ankle pulse wave velocity (baPWV). CVH was determined by three behavioral and four biological metrics and categorized as ideal, intermediate, and poor CVH. We applied generalized linear model and weighted quantile sum (WQS) regression to evaluate the associations of exposure to individual OCPs or PCBs and their mixture with baPWV, respectively. We found that participants with detectable levels of heptachlor epoxide, PCB-153, and PCB-180 had higher baPWV (β: 34.25, 95% CI 14.28-54.22; β: 27.64, 95% CI 7.90-47.38; and β: 30.51, 95% CI 10.68-50.35) than those with undetectable levels. In WQS regression, the mixture of OCPs and PCBs was related to a higher baPWV (β: 24.93, 95% CI 2.70-47.15). Compared with participants with ideal CVH and undetectable OCPs or PCBs levels, those with poor CVH and detectable OCPs or PCBs levels had the highest increase in baPWV (heptachlor epoxide: β: 147.94, 95% CI 112.52-183.55; PCB-153: β: 150.22, 95% CI 115.40-185.04; PCB-180: β: 147.02, 95% CI 111.66-182.38). Our findings suggested that individual OCPs, PCBs, and their mixture exposure were positively associated with arterial stiffness, and adherence to an ideal CVH may mitigate the adverse effect.
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Affiliation(s)
- Jianing Bi
- Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Hangkong Road 13, Wuhan, 430030, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and Ministry of Environmental Protection, State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Qing Liu
- Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Hangkong Road 13, Wuhan, 430030, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and Ministry of Environmental Protection, State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Gaojie Fan
- Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Hangkong Road 13, Wuhan, 430030, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and Ministry of Environmental Protection, State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Qing Fang
- Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Hangkong Road 13, Wuhan, 430030, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and Ministry of Environmental Protection, State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xukuan Zhang
- Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Hangkong Road 13, Wuhan, 430030, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and Ministry of Environmental Protection, State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xiya Qin
- Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Hangkong Road 13, Wuhan, 430030, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and Ministry of Environmental Protection, State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Mingyang Wu
- Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Hangkong Road 13, Wuhan, 430030, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and Ministry of Environmental Protection, State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Zhengce Wan
- Health Management Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yongman Lv
- Health Management Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Youjie Wang
- Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Hangkong Road 13, Wuhan, 430030, Hubei, China.
- Key Laboratory of Environment and Health, Ministry of Education and Ministry of Environmental Protection, State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
| | - Lulu Song
- Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Hangkong Road 13, Wuhan, 430030, Hubei, China.
- Key Laboratory of Environment and Health, Ministry of Education and Ministry of Environmental Protection, State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
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8
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Lu Y, Shen Q, Zhai C, Yan H, Shen S. Ant nest-like hierarchical porous imprinted resin-dispersive solid-phase extraction for selective extraction and determination of polychlorinated biphenyls in milk. Food Chem 2023; 406:135076. [PMID: 36455312 DOI: 10.1016/j.foodchem.2022.135076] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 11/22/2022] [Accepted: 11/23/2022] [Indexed: 11/29/2022]
Abstract
Polychlorinated biphenyls (PCBs) are persistent toxic, organic chemicals that tend to accumulate in the food chain. This study reports the rapid and selective extraction and determination of PCBs (PCB81, 153, 105, 126, and 157) in milk samples by a dispersive solid-phase extraction (DSPE) coupled with gas chromatography-tandem mass spectrometry (GC-MS/MS). An ionic liquid-molecularly imprinted porous resin (IL-MIPPR) as a DSPE adsorbent was synthesized from m-aminophenol, formaldehyde, and 2,2'-benzidinedisulfonic acid as the monomer, crosslinker, and virtual template, respectively. The IL-MIPPR had a fast mass transfer (1.0 min) and good selectivity (imprinting factors of 1.8-3.0). The IL-MIPPR - DSPE - GC-MS/MS method exhibited good linearity (R2 ≥ 0.9995), the limit of detections (LODs) < 0.6 pg/g, and the recoveries ranged from 82.8 % to 106 % with relative standard deviations ≤ 6.6 %. This method is thus better than previously reported methods in terms of the LOD, the adsorbent dosage, and the extraction time.
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Affiliation(s)
- Yanke Lu
- Key Laboratory of Analytical Science and Technology of Hebei Province, College of Chemistry and Environmental Science, Hebei University, Baoding 071002, China; Key Laboratory of Public Health Safety of Hebei Province, Key Laboratory of Medicinal Chemistry and Molecular Diagnosis of Ministry of Education, College of Pharmaceutical Sciences, Hebei University, Baoding 071002, China
| | - Qi Shen
- Institute of Chemistry, Chinese Academy of Science, Beijing 100190, China
| | - Chengcheng Zhai
- Key Laboratory of Public Health Safety of Hebei Province, Key Laboratory of Medicinal Chemistry and Molecular Diagnosis of Ministry of Education, College of Pharmaceutical Sciences, Hebei University, Baoding 071002, China
| | - Hongyuan Yan
- Key Laboratory of Public Health Safety of Hebei Province, Key Laboratory of Medicinal Chemistry and Molecular Diagnosis of Ministry of Education, College of Pharmaceutical Sciences, Hebei University, Baoding 071002, China.
| | - Shigang Shen
- Key Laboratory of Analytical Science and Technology of Hebei Province, College of Chemistry and Environmental Science, Hebei University, Baoding 071002, China.
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9
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Han M, Ma A, Dong Z, Yin J, Shao B. Organochlorine pesticides and polycyclic aromatic hydrocarbons in serum of Beijing population: Exposure and health risk assessment. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 860:160358. [PMID: 36436633 DOI: 10.1016/j.scitotenv.2022.160358] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 11/05/2022] [Accepted: 11/16/2022] [Indexed: 06/16/2023]
Abstract
Organochlorine pesticides (OCPs) and polycyclic aromatic hydrocarbons (PAHs) are widespread environmental contaminants, but large-scale human biomonitoring and health risk assessment data on these contaminants remain limited. In this study, concentrations of 6 OCPs and 5 PAHs were determined by GC-MS/MS in 1268 human serum samples which were collected from the participants in 2017 Beijing Chronic Disease and Risk Factor Surveillance. The detection frequencies of OCPs and PAHs ranged from 64.7 % to 96.5 % and 89.4 % to 99.6 %, respectively. The most abundant contaminants in OCPs and PAHs were pentachlorophenol (PCP) and pyrene (Pyr) with median concentrations reaching up to 3.13 and 8.48 μg/L, respectively. Nonparametric tests were employed to assess the correlations among contaminants levels, demographic characteristics (age, gender, body mass index, residence) and serum biochemical indexes. Significantly higher serum levels of all PAHs were observed in suburb residents than that in urban residents (P < 0.001). Binary logistic regression analysis demonstrated that exposure to benzo(a)pyrene (OR 2.17 [1.29, 3.63]), phenanthrene (OR 1.06 [1.02, 1.11]), fluoranthene (OR 1.04 [1.02, 1.07]) and Pyr (OR 1.02 [1.01, 1.03]) might increase the occurrence of hyperglycemia, and exposure to hexachlorobenzene (HCB) (OR 1.53 [1.05, 2.22]) and pentachlorobenzene (OR 1.14 [1.02, 1.27]) were positively associated with hyperlipidemia. Furthermore, the hazard quotients (HQs) for serum HCB, PCP and p,p'-dichlorodiphenyldichloroethylene were calculated based on health-based guidance values to predict health risks. 0.2 % and 4.3 % of serum samples showed HQ values exceeding 1 for HCB and PCP, respectively, in case of the non-carcinogenic risk, while 23.1 % of HQs for HCB were above 1 in case of the carcinogenic risk for a risk level 10-5. Our study reveals that the body burden of the Beijing general population relative to OCPs and PAHs was nonnegligible. The past exposure of HCB and PCP might adversely affect the health status of the Beijing population.
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Affiliation(s)
- Muke Han
- School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Key Laboratory of Diagnostic and Traceability Technologies for Food Poisoning, Beijing Center for Disease Prevention and Control, Beijing 100013, China
| | - Aijuan Ma
- Institute of Non-communicable Chronic Disease Control and Prevention, Beijing Center for Disease Prevention and Control, Beijing 100013, China
| | - Zhong Dong
- Institute of Non-communicable Chronic Disease Control and Prevention, Beijing Center for Disease Prevention and Control, Beijing 100013, China.
| | - Jie Yin
- School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Key Laboratory of Diagnostic and Traceability Technologies for Food Poisoning, Beijing Center for Disease Prevention and Control, Beijing 100013, China.
| | - Bing Shao
- School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Key Laboratory of Diagnostic and Traceability Technologies for Food Poisoning, Beijing Center for Disease Prevention and Control, Beijing 100013, China
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