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Mankiewicz Ledins P, Lin EZ, Bhattacharya C, Pollitt KJG, Dyson AH, Hénaff EM. A deployable film method to enable replicable sampling of low-abundance environmental microbiomes. Sci Rep 2024; 14:23857. [PMID: 39394219 PMCID: PMC11470061 DOI: 10.1038/s41598-024-72341-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2024] [Accepted: 09/05/2024] [Indexed: 10/13/2024] Open
Abstract
Urbanizing global populations spend over 90% of their time indoors where microbiome abundance and diversity are low. Chronic exposure to microbiomes with low abundance and diversity have demonstrated negative long-term impacts on human health. Sequencing-based analyses of environmental nucleic acids are critical to understanding the impact of the indoor microbiome on human health, however low DNA yields indoors, alongside sample collection and processing inconsistencies, currently challenge study replicability. This study presents a comparative assessment of a novel, passive, easily replicable sampling strategy using polydimethylsiloxane (PDMS) sheets alongside a representative swab-based collection protocol. Deployable, customizable PDMS films designed for whole-sample insertion into standardized extraction kits demonstrated 43% higher DNA yields per sample, and 76% higher yields per cm2 of sampler over swab-based protocols. These results indicate that this accessible, scalable method enables sufficient DNA collection to comprehensively evaluate indoor microbiome exposures and potential human health impacts using smaller, more space efficient samplers, representing an attractive alternative to swab-based collection. In addition, this process reduces the manual steps required for microbiome sampling which could address inter-study variability, transform the current microbiome sampling paradigm, and ultimately benefit the replicability and accessibility of microbiome exposure studies.
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Affiliation(s)
| | | | | | | | - Anna H Dyson
- Yale School of Architecture, 180 York Street, New Haven, CT, 06511, USA
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2
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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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Guo X, Ren H, Sun P, Ding E, Fang J, Fang K, Ma X, Li C, Li C, Xu Y, Cao K, Lin EZ, Guo P, Pollitt KJG, Tong S, Tang S, Shi X. Personal exposure to airborne organic pollutants and lung function changes among healthy older adults. ENVIRONMENTAL RESEARCH 2024; 258:119411. [PMID: 38876423 DOI: 10.1016/j.envres.2024.119411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Revised: 06/07/2024] [Accepted: 06/10/2024] [Indexed: 06/16/2024]
Abstract
Epidemiological evidence on the impact of airborne organic pollutants on lung function among the elderly is limited, and their underlying biological mechanisms remain largely unexplored. Herein, a longitudinal panel study was conducted in Jinan, Shandong Province, China, involving 76 healthy older adults monitored over a span of five months repetitively. We systematically evaluated personal exposure to a diverse range of airborne organic pollutants using a wearable passive sampler and their effects on lung function. Participants' pulmonary function indicators were assessed, complemented by comprehensive multi-omics analyses of blood and urine samples. Leveraging the power of interaction analysis, causal inference test (CIT), and integrative pathway analysis (IPA), we explored intricate relationships between specific organic pollutants, biomolecules, and lung function deterioration, elucidating the biological mechanisms underpinning the adverse impacts of these pollutants. We observed that bis (2-chloro-1-methylethyl) ether (BCIE) was significantly associated with negative changes in the forced vital capacity (FVC), with glycerolipids mitigating this adverse effect. Additionally, 31 canonical pathways [e.g., high mobility group box 1 (HMGB1) signaling, phosphatidylinositol 3-kinase (PI3K)/AKT pathway, epithelial mesenchymal transition, and heme and nicotinamide adenine dinucleotide (NAD) biosynthesis] were identified as potential mechanisms. These findings may hold significant implications for developing effective strategies to prevent and mitigate respiratory health risks arising from exposure to such airborne pollutants. However, due to certain limitations of the study, our results should be interpreted with caution.
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Affiliation(s)
- Xiaojie Guo
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China; School of Public Health, Southern Medical University, Guangzhou, Guangdong 510515, 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 100021, China; School of Public Health, China Medical University, Shenyang, Liaoning 110001, China
| | - Peijie Sun
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China; School of Public Health, China Medical University, Shenyang, Liaoning 110001, 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 100021, China; School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Jianlong Fang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Ke Fang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Xiao Ma
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China; School of Public Health, Shandong University, Jinan, Shandong 250100, 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 100021, China; School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China
| | - Chenlong Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China; School of Public Health, Shandong University, Jinan, Shandong 250100, 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 100021, China; School of Public Health, China Medical University, Shenyang, Liaoning 110001, China
| | - Kangning Cao
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China; School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China
| | - Elizabeth Z Lin
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT 06510, USA
| | - Pengfei Guo
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT 06510, USA
| | - Krystal J Godri Pollitt
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT 06510, USA
| | - Shilu Tong
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China; School of Public Health and Social Work, Queensland University of Technology, Brisbane 4001, Australia
| | - Song Tang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, 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 102206, China.
| | - Xiaoming Shi
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, 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 102206, China.
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Wang Y, Guo C, Jiang L, Hu B, Yu Z, Zeng T, Song S, Zhang H. Occurrence differences of hexachlorobutadiene and chlorobenzenes in road dust and roadside soil media in an industrial and residential mixed area in Eastern China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 344:123311. [PMID: 38195025 DOI: 10.1016/j.envpol.2024.123311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 12/22/2023] [Accepted: 01/04/2024] [Indexed: 01/11/2024]
Abstract
The road dust and roadside soil can act as both sinks and sources of hexachlorobutadiene (HCBD) and chlorobenzenes (CBzs), but comparative research on these two adjacent media is extremely limited. In this study, HCBD and CBzs were simultaneously analyzed in road dust and roadside soil samples from an area containing both industrial factories and residential communities in Eastern China. The road dust there was found to have 2-6 times higher contents of HCBD (mean 1.14 ng/g, maximum 6.44 ng/g) and ∑Cl3-Cl6CBzs (22.8 ng/g, 90.6 ng/g) than those in the roadside soil. The spatial distributions of HCBD and CBzs in road dusts were affected by various types of sources, showing no significant discrepancy among the sites. On the contrast, HCBD and CBzs contamination in roadside soils occurring near several factories were strongly correlated to their industrial point sources. Risk assessments showed, at current contamination levels in the road dust and roadside soil, HCBD and CBzs are not likely to induce carcinogenic or non-carcinogenic risks to residents in the studied area. Nevertheless, road dust ingestion, as the major exposure pathway of HCBD and CBzs, should be avoided to reduce the exposure risk. These findings based on the contamination differences between two media provide a new perspective and evidence for screening important sources and exposure pathway of HCBD and CBzs, which would be helpful to their source identification and risk control.
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Affiliation(s)
- Yaotian Wang
- School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, 310024, China; State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China; Department of Chemistry, College of Sciences, Northeastern University, Shenyang, 110819, China
| | - Chenqi Guo
- School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, 310024, China; College of Environment, Zhejiang University of Technology, Hangzhou, 310032, China
| | - Lei Jiang
- College of Environment, Zhejiang University of Technology, Hangzhou, 310032, China
| | - Boyuan Hu
- School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, 310024, China
| | - Zechen Yu
- School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, 310024, China
| | - Tao Zeng
- College of Environment, Zhejiang University of Technology, Hangzhou, 310032, China
| | - Shuang Song
- College of Environment, Zhejiang University of Technology, Hangzhou, 310032, China
| | - Haiyan Zhang
- School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, 310024, China.
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5
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Waalen J. Mobile Health and Preventive Medicine. Med Clin North Am 2023; 107:1097-1108. [PMID: 37806725 DOI: 10.1016/j.mcna.2023.06.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
Wearable devices providing health-related data (mobile health [mHealth]) have grown in numbers and types of data available over the past 2 decades. Applications in prevention with some of the longest track records are activity trackers to promote fitness (primary prevention), mobile electrocardiogram devices to detect arrhythmias (secondary prevention), and continuous glucose monitoring to improve glycemic control in type 2 diabetes (tertiary prevention). Continued integration of multiple diverse data streams and improved interfaces with individuals (such as artificial intelligence-driven health coaches), and health care teams (as in the hospital-at-home concept), promise to optimize use of mHealth to improve clinical and public health outcomes.
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Affiliation(s)
- Jill Waalen
- University of California, San Diego/San Diego State University General Preventive Medicine Residency Program & Scripps Research Translational Institute, 3344 North Torrey Pines Court, La Jolla, CA 92037, USA.
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Zhang H, Hu L, Zheng P, Jia G. Application of wearable devices for monitoring cardiometabolic dysfunction under the exposome paradigm. Chronic Dis Transl Med 2023; 9:200-209. [PMID: 37711864 PMCID: PMC10497849 DOI: 10.1002/cdt3.67] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Revised: 03/13/2023] [Accepted: 03/22/2023] [Indexed: 09/16/2023] Open
Abstract
Environmental factors, including chemical/physical pollutants, as well as lifestyle and psychological factors, contribute greatly to the pathways leading to cardiometabolic diseases with a heavy disease burden and economic loss. The concept of exposomes provides a novel paradigm for combining all exposure characteristics to evaluate disease risk. A solution-like exposome requires technological support to provide continuous data to monitor vital signs and detect abnormal fluctuations. Wearable devices allow people to conveniently monitor signals during their daily routines. These new technologies empower users to more actively prevent and manage cardiometabolic disease by reviewing risk factors of the disease, especially lifestyle factors, such as sleeping time, screen time, and mental health condition. Devices with multiple sensors can monitor electrocardiography data, oxygen saturation, intraocular pressure, respiratory rate, and heart rate to enhance the exposome study and provide precise suggestions for disease prevention and management.
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Affiliation(s)
- Haodong Zhang
- Department of Occupational and Environmental Health Sciences, School of Public HealthPeking UniversityBeijingChina
| | - Lingming Hu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University)National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital)BeijingChina
| | - Pai Zheng
- Department of Occupational and Environmental Health Sciences, School of Public HealthPeking UniversityBeijingChina
| | - Guang Jia
- Department of Occupational and Environmental Health Sciences, School of Public HealthPeking UniversityBeijingChina
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Okeme JO, Koelmel JP, Johnson E, Lin EZ, Gao D, Pollitt KJG. Wearable Passive Samplers for Assessing Environmental Exposure to Organic Chemicals: Current Approaches and Future Directions. Curr Environ Health Rep 2023:10.1007/s40572-023-00392-w. [PMID: 36821032 DOI: 10.1007/s40572-023-00392-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/11/2023] [Indexed: 02/24/2023]
Abstract
PURPOSE OF REVIEW We are continuously exposed to dynamic mixtures of airborne contaminants that vary by location. Understanding the compositional diversity of these complex mixtures and the levels to which we are each exposed requires comprehensive exposure assessment. This comprehensive analysis is often lacking in population-based studies due to logistic and analytical challenges associated with traditional measurement approaches involving active air sampling and chemical-by-chemical analysis. The objective of this review is to provide an overview of wearable passive samplers as alternative tools to active samplers in environmental health research. The review highlights the advances and challenges in using wearable passive samplers for assessing personal exposure to organic chemicals and further presents a framework to enable quantitative measurements of exposure and expanded use of this monitoring approach to the population scale. RECENT FINDINGS Overall, wearable passive samplers are promising tools for assessing personal exposure to environmental contaminants, evident by the increased adoption and use of silicone-based devices in recent years. When combined with high throughput chemical analysis, these exposure assessment tools present opportunities for advancing our ability to assess personal exposures to complex mixtures. Most designs of wearable passive samplers used for assessing exposure to semi-volatile organic chemicals are currently uncalibrated, thus, are mostly used for qualitative research. The challenge with using wearable samplers for quantitative exposure assessment mostly lies with the inherent complexity in calibrating these wearable devices. Questions remain regarding how they perform under various conditions and the uncertainty of exposure estimates. As popularity of these samplers grows, it is critical to understand the uptake kinetics of chemicals and the different environmental and meteorological conditions that can introduce variability. Wearable passive samplers enable evaluation of exposure to hundreds of chemicals. The review presents the state-of-the-art of technology for assessing personal exposure to environmental chemicals. As more studies calibrate wearable samplers, these tools present promise for quantitatively assessing exposure at both the individual and population levels.
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Affiliation(s)
- Joseph O Okeme
- Department of Environmental Health Sciences, Yale School of Public Health, 60 College Street, Room 523, New Haven, CT, 06510, USA
| | - Jeremy P Koelmel
- Department of Environmental Health Sciences, Yale School of Public Health, 60 College Street, Room 523, New Haven, CT, 06510, USA
| | - Emily Johnson
- Department of Environmental Health Sciences, Yale School of Public Health, 60 College Street, Room 523, New Haven, CT, 06510, USA
| | - Elizabeth Z Lin
- Department of Environmental Health Sciences, Yale School of Public Health, 60 College Street, Room 523, New Haven, CT, 06510, USA
| | - Dong Gao
- Department of Environmental Health Sciences, Yale School of Public Health, 60 College Street, Room 523, New Haven, CT, 06510, USA
| | - Krystal J Godri Pollitt
- Department of Environmental Health Sciences, Yale School of Public Health, 60 College Street, Room 523, New Haven, CT, 06510, USA.
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DeLay K, Lin EZ, Koelmel JP, Bornman R, Obida M, Chevrier J, Godri Pollitt KJ. Personal air pollutant exposure monitoring in South African children in the VHEMBE birth cohort. ENVIRONMENT INTERNATIONAL 2022; 170:107524. [PMID: 36260950 PMCID: PMC9982749 DOI: 10.1016/j.envint.2022.107524] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 09/02/2022] [Accepted: 09/13/2022] [Indexed: 06/16/2023]
Abstract
The burden of disease associated with environmental exposures disproportionately impacts residents of low- and middle-income countries. Children living in rural regions of these countries may experience higher exposure to insecticides from indoor residual spraying used for malaria control and household air pollution. This study evaluated environmental exposures of children living in a rural region of South Africa. Quantifying exposure levels and identifying characteristics that are associated with exposure in this geographic region has been challenging due to limitations with available monitoring techniques. Wearable passive samplers have recently been shown to be a convenient and reliable tool for assessing personal exposures. In this study, a passive sampler wristband, known as Fresh Air wristband, was worn by 49 children (five-years of age) residing in the Limpopo province of South Africa. The study leveraged ongoing research within the Venda Health Examination of Mothers, Babies, and their Environment (VHEMBE) birth cohort. A wide range of chemicals (35 in total) were detected using the wristbands, including polycyclic aromatic hydrocarbons (PAHs), organochlorine pesticides, phthalates, and organophosphate esters (OPEs) flame retardants. Higher concentrations of PAHs were observed among children from households that fell below the food poverty threshold, did not have access to electric cookstoves/burners, or reported longer times of cooking or burning materials during the sampling period. Concentrations of p,p'-DDD and p,p'-DDT were also found to be elevated for children from households falling below the food poverty threshold as well as for children whose households were sprayed for malaria control within the previous 1.5 years. This study demonstrates the feasibility of using passive sampler wristbands as a non-invasive method for personal exposure assessment of children in rural regions of South Africa to complex mixtures environmental contaminants derived from a combination of sources. Future studies are needed to further identify and understand the effects of airborne environmental contaminants on childhood development and strategies to mitigate exposures.
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Affiliation(s)
- Kayley DeLay
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT 06520, USA; Department of Chemical and Environmental Engineering, Yale School of Engineering and Applied Sciences, New Haven, CT 06520, USA
| | - Elizabeth Z Lin
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT 06520, USA
| | - Jeremy P Koelmel
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT 06520, USA
| | - Riana Bornman
- University of Pretoria Institute for Sustainable Malaria Control and School of Health Systems and Public Health, University of Pretoria, Pretoria, South Africa
| | - Muvhulawa Obida
- University of Pretoria Institute for Sustainable Malaria Control and School of Health Systems and Public Health, University of Pretoria, Pretoria, South Africa
| | - Jonathan Chevrier
- Department of Epidemiology, Biostatistics and Occupational Health, Faculty of Medicine and Health Sciences, McGill University, Montréal, QC, Canada.
| | - Krystal J Godri Pollitt
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT 06520, USA; Department of Chemical and Environmental Engineering, Yale School of Engineering and Applied Sciences, New Haven, CT 06520, USA.
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9
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Wei X, Huang Z, Jiang L, Li Y, Zhang X, Leng Y, Jiang C. Charting the landscape of the environmental exposome. IMETA 2022; 1:e50. [PMID: 38867899 PMCID: PMC10989948 DOI: 10.1002/imt2.50] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 07/13/2022] [Accepted: 07/30/2022] [Indexed: 06/14/2024]
Abstract
The exposome depicts the total exposures in the lifetime of an organism. Human exposome comprises exposures from environmental and humanistic sources. Biological, chemical, and physical environmental exposures pose potential health threats, especially to susceptible populations. Although still in its nascent stage, we are beginning to recognize the vast and dynamic nature of the exposome. In this review, we systematically summarize the biological and chemical environmental exposomes in three broad environmental matrices-air, soil, and water; each contains several distinct subcategories, along with a brief introduction to the physical exposome. Disease-related environmental exposures are highlighted, and humans are also a major source of disease-related biological exposures. We further discuss the interactions between biological, chemical, and physical exposomes. Finally, we propose a list of outstanding challenges under the exposome research framework that need to be addressed to move the field forward. Taken together, we present a detailed landscape of environmental exposome to prime researchers to join this exciting new field.
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Affiliation(s)
- Xin Wei
- Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Sciences InstituteZhejiang UniversityHangzhouZhejiangChina
| | - Zinuo Huang
- Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Sciences InstituteZhejiang UniversityHangzhouZhejiangChina
| | - Liuyiqi Jiang
- Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Sciences InstituteZhejiang UniversityHangzhouZhejiangChina
| | - Yueer Li
- Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Sciences InstituteZhejiang UniversityHangzhouZhejiangChina
| | - Xinyue Zhang
- Department of GeneticsStanford UniversityStanfordCaliforniaUSA
| | - Yuxin Leng
- Department of Intensive Care UnitPeking University Third HospitalBeijingChina
| | - Chao Jiang
- Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Sciences InstituteZhejiang UniversityHangzhouZhejiangChina
- Zhejiang Provincial Key Laboratory of Pancreatic Disease, First Affiliated HospitalZhejiang University School of MedicineHangzhouZhejiangChina
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10
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Shi W, Gao X, Cao Y, Chen Y, Cui Q, Deng F, Yang B, Lin EZ, Fang J, Li T, Tang S, Godri Pollitt KJ, Shi X. Personal airborne chemical exposure and epigenetic ageing biomarkers in healthy Chinese elderly individuals: Evidence from mixture approaches. ENVIRONMENT INTERNATIONAL 2022; 170:107614. [PMID: 36375280 DOI: 10.1016/j.envint.2022.107614] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 10/24/2022] [Accepted: 11/02/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND Air pollution is associated with accelerated biological ages determined by DNA methylation (DNAm) patterns, imposing further risks of age-related adverse effects. However, little is known about the independent and joint effects of exposure to gaseous organic chemicals that may share a common source. METHODS We conducted a panel study with the 3-day exposure assessment monthly among 73 Chinese healthy elderly people aged 60 to 69 years in Jinan, Shandong province during September 2018 to January 2019.Exposure to 26 ambient organic chemical contaminants were measured by wearable passive samplers, including volatile organic compounds, polycyclic aromatic hydrocarbons (PAHs), phthalates (PAEs), nitroaromatics (NIs), polybrominated diphenyl ethers, chlorinated hydrocarbons, and organophosphate esters. The Illumina MethylationEPIC BeadChip was used to measure DNA methylation levels in blood samples, and based on which, epigenetic ageing biomarkers, including Hannum clock, Horvath clock, DNAm PhenoAge, DNAm GrimAge, and DNAm estimator of telomere length (DNAmTL) were calculated. Linear mixed effect models were used to estimate the linear associations between 3-day personal chemical exposure and the epigenetic biomarkers, Weighted quantile sum (WQS) regression and the Bayesian kernel machine regression (BKMR) model were further used to evaluate the effect of chemical mixtures. RESULTS Multiple linear mixed effects regression models showed that DNAmPhenoAge acceleration was significantly and positively associated with exposure to PAEs, NIs, and PAHs in healthy elderly individuals. Both WQS regression and BKMR models showed a significant positive association with DNAmPhenoAge acceleration with chemical exposures, in which the effect of di-n-butyl phthalate exposure showed the greatest importance. CONCLUSION These findings suggest that exposure to a mixture of airborne chemicals significantly increase the acceleration of the epigenetic biomarker of phenotypic age. These findings serve to identify toxic chemicals in the air and facilitate the evaluation of their potentially severe health effects.
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Affiliation(s)
- Wanying Shi
- 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 and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Xu Gao
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, China
| | - Yaqiang Cao
- 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
| | - Yuanyuan Chen
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Qian Cui
- 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 Ecology and Environment, Inner Mongolia University, Hohhot, 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
| | - Bo Yang
- 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, Baotou Medical College, Inner Mongolia University of Science and Technology, Baotou, China
| | - Elizabeth Z Lin
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, 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
| | - Tiantian Li
- 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
| | - 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
| | - Krystal J Godri Pollitt
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, 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; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China.
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11
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Ding E, Wang Y, Liu J, Tang S, Shi X. A review on the application of the exposome paradigm to unveil the environmental determinants of age-related diseases. Hum Genomics 2022; 16:54. [DOI: 10.1186/s40246-022-00428-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Accepted: 10/29/2022] [Indexed: 11/11/2022] Open
Abstract
AbstractAge-related diseases account for almost half of all diseases among adults worldwide, and their incidence is substantially affected by the exposome, which is the sum of all exogenous and endogenous environmental exposures and the human body’s response to these exposures throughout the entire lifespan. Herein, we perform a comprehensive review of the epidemiological literature to determine the key elements of the exposome that affect the development of age-related diseases and the roles of aging hallmarks in this process. We find that most exposure assessments in previous aging studies have used a reductionist approach, whereby the effect of only a single environmental factor or a specific class of environmental factors on the development of age-related diseases has been examined. As such, there is a lack of a holistic and unbiased understanding of the effect of multiple environmental factors on the development of age-related diseases. To address this, we propose several research strategies based on an exposomic framework that could advance our understanding—in particular, from a mechanistic perspective—of how environmental factors affect the development of age-related diseases. We discuss the statistical methods and other methods that have been used in exposome-wide association studies, with a particular focus on multiomics technologies. We also address future challenges and opportunities in the realm of multidisciplinary approaches and genome–exposome epidemiology. Furthermore, we provide perspectives on precise public health services for vulnerable populations, public communications, the integration of risk exposure information, and the bench-to-bedside translation of research on age-related diseases.
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12
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Samon SM, Hammel SC, Stapleton HM, Anderson KA. Silicone wristbands as personal passive sampling devices: Current knowledge, recommendations for use, and future directions. ENVIRONMENT INTERNATIONAL 2022; 169:107339. [PMID: 36116363 PMCID: PMC9713950 DOI: 10.1016/j.envint.2022.107339] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 06/03/2022] [Accepted: 06/06/2022] [Indexed: 05/13/2023]
Abstract
Personal chemical exposure assessment is necessary to determine the frequency and magnitude of individual chemical exposures, especially since chemicals present in everyday environments may lead to adverse health outcomes. In the last decade, silicone wristbands have emerged as a new chemical exposure assessment tool and have since been utilized for assessing personal exposure to a wide range of chemicals in a variety of populations. Silicone wristbands can be powerful tools for quantifying personal exposure to chemical mixtures in a single sample, associating exposure with health outcomes, and potentially overcoming some of the challenges associated with quantifying the chemical exposome. However, as their popularity grows, it is crucial that they are used in the appropriate context and within the limits of the technology. This review serves as a guide for researchers interested in utilizing silicone wristbands as a personal exposure assessment tool. Along with briefly discussing the passive sampling theory behind silicone wristbands, this review performs an in-depth comparison of wristbands to other common exposure assessment tools, including biomarkers of exposure measured in biospecimens, and evaluates their utility in exposure assessments and epidemiological studies. Finally, this review includes recommendations for utilizing silicone wristbands to evaluate personal chemical exposure and provides suggestions on what research is needed to recognize silicone wristbands as a premier chemical exposure assessment tool.
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Affiliation(s)
- Samantha M Samon
- Department of Environmental & Molecular Toxicology, Oregon State University, Corvallis, OR, United States
| | - Stephanie C Hammel
- The National Research Centre for the Working Environment, Copenhagen, Denmark
| | - Heather M Stapleton
- Nicholas School of the Environment, Duke University, Durham, NC, United States
| | - Kim A Anderson
- Department of Environmental & Molecular Toxicology, Oregon State University, Corvallis, OR, United States.
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13
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Jia X, Jin Q, Fang J, Shi Y, Hou M, Dong H, Liu Y, Deng F, Zhou Y, Godri Pollitt KJ, Tang S, Shi X, Cai Y. Emerging and Legacy Per- and Polyfluoroalkyl Substances in an Elderly Population in Jinan, China: The Exposure Level, Short-Term Variation, and Intake Assessment. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:7905-7916. [PMID: 35584234 DOI: 10.1021/acs.est.2c00381] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Human exposure to per- and polyfluoroalkyl substances (PFASs) has gained worldwide attention due to their widespread presence in the environment and adverse health effects, but the exposure assessment in the elderly is still lacking. This study aimed to assess exposures to 3 emerging PFASs (chlorinated polyfluoroalkyl ether sulfonic acids, Cl-PFESAs) and 15 legacy PFASs. The temporal variability of internal exposures and intake amounts of these PFASs were evaluated among a population of 76 healthy elderly adults (age: 60-69) in Jinan, China over 5 consecutive months. Fifteen PFASs were detected in whole blood with the mean total concentration (ΣPFAS) at 20.1 ng/mL (range: 5.0-135.9 ng/mL) dominated by perfluorooctanoic acid (PFOA) (9.0 ng/mL), perfluorooctanesulfonic acid (PFOS) (5.3 ng/mL), and 6:2 Cl-PFESA (1.6 ng/mL). Across the 5 month assessment period, significant variation was only observed for short-chain (C4-C7) perfluoroalkyl carboxylic acids, and their variations ranged from 53 to 334%. The median intake of PFOA and PFOS was estimated to be 1.46 and 0.92 ng/kg bw/day, respectively. Regression analysis showed that dietary ingestion, especially fish, was likely an important exposure pathway for PFASs among the elderly adults. Various pathways (e.g., dietary, water, air, and dust) should thus be considered to fully understand human exposure to PFASs.
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Affiliation(s)
- Xuan Jia
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Qi Jin
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jianlong Fang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Yali Shi
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- School of Environment, Hangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China
| | - Minmin Hou
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, 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 100021, China
| | - Yuanyuan Liu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, 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 100021, China
| | - Yakun Zhou
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, Connecticut 06520, United States
| | - Krystal J Godri Pollitt
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, Connecticut 06520, United States
| | - Song Tang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, Jiangsu, China
| | - Xiaoming Shi
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, Jiangsu, China
| | - Yaqi Cai
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- Institute of Environment and Health, Jianghan University, Wuhan 430056, China
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14
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Fernandes VC, Pestana D. Environmental Chemicals: Integrative Approach to Human Biomonitoring and Health Effects. TOXICS 2022; 10:toxics10060314. [PMID: 35736922 PMCID: PMC9229863 DOI: 10.3390/toxics10060314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Accepted: 06/07/2022] [Indexed: 02/04/2023]
Abstract
In recent decades, citizen awareness of toxic chemicals has been a topic of interest, particularly concerning national and international policy decision makers, expert/scientific platforms, and health protection organizations (WHO, UNEP, CDC, EFSA, IPEN, etc [...].
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Affiliation(s)
- Virgínia Cruz Fernandes
- REQUIMTE/LAQV, Instituto Superior de Engenharia do Porto, Instituto Politécnico do Porto, Rua Dr. António Bernardino de Almeida 431, 4249-015 Porto, Portugal
- Correspondence: (V.C.F.); (D.P.)
| | - Diogo Pestana
- CINTESIS & NOVA Medical School | Faculdade de Ciências Médicas da Universidade Nova de Lisboa, Campo Mártires da Pátria 130, 1169-056 Lisboa, Portugal
- Correspondence: (V.C.F.); (D.P.)
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15
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Koelmel JP, Lin EZ, DeLay K, Williams AJ, Zhou Y, Bornman R, Obida M, Chevrier J, Godri Pollitt KJ. Assessing the External Exposome Using Wearable Passive Samplers and High-Resolution Mass Spectrometry among South African Children Participating in the VHEMBE Study. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:2191-2203. [PMID: 35089017 DOI: 10.1021/acs.est.1c06481] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Children in low- and middle-income countries are often exposed to higher levels of chemicals and are more vulnerable to the health effects of air pollution. Little is known about the diversity, toxicity, and dynamics of airborne chemical exposures at the molecular level. We developed a workflow employing state-of-the-art wearable passive sampling technology coupled with high-resolution mass spectrometry to comprehensively measure 147 children's personal exposures to airborne chemicals in Limpopo, South Africa, as part of the Venda Health Examination of Mothers, Babies, and Their Environment (VHEMBE). 637 environmental exposures were detected, many of which have never been measured in this population; of these 50 airborne chemical exposures of concern were detected, including pesticides, plasticizers, organophosphates, dyes, combustion products, and perfumes. Biocides detected in wristbands included p,p'-dichlorodiphenyltrichloroethane (p,p'-DDT), p,p'-dichlorodiphenyldichloroethane (p,p'-DDD), p,p'-dichlorodiphenyldichloroethylene (p,p'-DDE), propoxur, piperonyl butoxide, and triclosan. Exposures differed across the assessment period with 27% of detected chemicals observed to be either higher or lower in the wet or dry seasons.
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Affiliation(s)
- Jeremy P Koelmel
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, Connecticut 06520, United States
| | - Elizabeth Z Lin
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, Connecticut 06520, United States
| | - Kayley DeLay
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, Connecticut 06520, United States
| | - Antony J Williams
- Center for Computational Toxicology and Exposure, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, North Carolina 27711, United States
| | - Yakun Zhou
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, Connecticut 06520, United States
| | - Riana Bornman
- University of Pretoria Institute for Sustainable Malaria Control and School of Health Systems and Public Health, University of Pretoria, Pretoria 0028, South Africa
| | - Muvhulawa Obida
- University of Pretoria Institute for Sustainable Malaria Control and School of Health Systems and Public Health, University of Pretoria, Pretoria 0028, South Africa
| | - Jonathan Chevrier
- Department of Epidemiology, Biostatistics and Occupational Health, Faculty of Medicine, McGill University, Montréal, Québec H3A 1A2, Canada
| | - Krystal J Godri Pollitt
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, Connecticut 06520, United States
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16
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Tang S, Li T, Fang J, Chen R, Cha Y, Wang Y, Zhu M, Zhang Y, Chen Y, Du Y, Yu T, Thompson DC, Godri Pollitt KJ, Vasiliou V, Ji JS, Kan H, Zhang JJ, Shi X. The exposome in practice: an exploratory panel study of biomarkers of air pollutant exposure in Chinese people aged 60-69 years (China BAPE Study). ENVIRONMENT INTERNATIONAL 2021; 157:106866. [PMID: 34525388 DOI: 10.1016/j.envint.2021.106866] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Revised: 08/11/2021] [Accepted: 09/05/2021] [Indexed: 05/05/2023]
Abstract
The exposome overhauls conventional environmental health impact research paradigms and provides a novel methodological framework that comprehensively addresses the complex, highly dynamic interplays of exogenous exposures, endogenous exposures, and modifiable factors in humans. Holistic assessments of the adverse health effects and systematic elucidation of the mechanisms underlying environmental exposures are major scientific challenges with widespread societal implications. However, to date, few studies have comprehensively and simultaneously measured airborne pollutant exposures and explored the associated biomarkers in susceptible healthy elderly subjects, potentially resulting in the suboptimal assessment and management of health risks. To demonstrate the exposome paradigm, we describe the rationale and design of a comprehensive biomarker and biomonitoring panel study to systematically explore the association between individual airborne exposure and adverse health outcomes. We used a combination of personal monitoring for airborne pollutants, extensive human biomonitoring, advanced omics analysis, confounding information, and statistical methods. We established an exploratory panel study of Biomarkers of Air Pollutant Exposure in Chinese people aged 60-69 years (China BAPE), which included 76 healthy residents from a representative community in Jinan City, Shandong Province. During the period between September 2018 and January 2019, we conducted prospective longitudinal monitoring with a 3-day assessment every month. This project: (1) leveraged advanced tools for personal airborne exposure monitoring (external exposures); (2) comprehensively characterized biological samples for exogenous and endogenous compounds (e.g., targeted and untargeted monitoring) and multi-omics scale measurements to explore potential biomarkers and putative toxicity pathways; and (3) systematically evaluated the relationships between personal exposure to air pollutants, and novel biomarkers of exposures and effects using exposome-wide association study approaches. These findings will contribute to our understanding of the mechanisms underlying the adverse health impacts of air pollution exposures and identify potential adverse clinical outcomes that can facilitate the development of effective prevention and targeted intervention techniques.
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Affiliation(s)
- Song Tang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Tiantian Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Jianlong Fang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Renjie Chen
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai 200032, China
| | - Yu'e Cha
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Yanwen Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Mu Zhu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Yi Zhang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Yuanyuan Chen
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Yanjun Du
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Tianwei Yu
- Institute for Data and Decision Analytics, The Chinese University of Hong Kong, Shenzhen, Guangdong 518172, China
| | - David C Thompson
- Department of Clinical Pharmacy, School of Pharmacy, University of Colorado, Aurora, CO 80045, USA
| | - Krystal J Godri Pollitt
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT 06520, USA
| | - Vasilis Vasiliou
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT 06520, USA
| | - John S Ji
- Environmental Research Center, Duke Kunshan University, Kunshan, Jiangsu 215316, China; Global Health Institute & Nicholas School of the Environment, Duke University, Durham, NC 27708, USA
| | - Haidong Kan
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai 200032, China
| | - Junfeng Jim Zhang
- Environmental Research Center, Duke Kunshan University, Kunshan, Jiangsu 215316, China; Global Health Institute & Nicholas School of the Environment, Duke University, Durham, NC 27708, 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 100021, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China.
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17
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Zhang P, Carlsten C, Chaleckis R, Hanhineva K, Huang M, Isobe T, Koistinen VM, Meister I, Papazian S, Sdougkou K, Xie H, Martin JW, Rappaport SM, Tsugawa H, Walker DI, Woodruff TJ, Wright RO, Wheelock CE. Defining the Scope of Exposome Studies and Research Needs from a Multidisciplinary Perspective. ENVIRONMENTAL SCIENCE & TECHNOLOGY LETTERS 2021; 8:839-852. [PMID: 34660833 PMCID: PMC8515788 DOI: 10.1021/acs.estlett.1c00648] [Citation(s) in RCA: 68] [Impact Index Per Article: 22.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 08/31/2021] [Accepted: 08/31/2021] [Indexed: 05/02/2023]
Abstract
The concept of the exposome was introduced over 15 years ago to reflect the important role that the environment exerts on health and disease. While originally viewed as a call-to-arms to develop more comprehensive exposure assessment methods applicable at the individual level and throughout the life course, the scope of the exposome has now expanded to include the associated biological response. In order to explore these concepts, a workshop was hosted by the Gunma University Initiative for Advanced Research (GIAR, Japan) to discuss the scope of exposomics from an international and multidisciplinary perspective. This Global Perspective is a summary of the discussions with emphasis on (1) top-down, bottom-up, and functional approaches to exposomics, (2) the need for integration and standardization of LC- and GC-based high-resolution mass spectrometry methods for untargeted exposome analyses, (3) the design of an exposomics study, (4) the requirement for open science workflows including mass spectral libraries and public databases, (5) the necessity for large investments in mass spectrometry infrastructure in order to sequence the exposome, and (6) the role of the exposome in precision medicine and nutrition to create personalized environmental exposure profiles. Recommendations are made on key issues to encourage continued advancement and cooperation in exposomics.
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Affiliation(s)
- Pei Zhang
- Gunma
University Initiative for Advanced Research (GIAR), Gunma University, Maebashi, Gunma 371-8511, Japan
- Division
of Physiological Chemistry 2, Department of Medical Biochemistry and
Biophysics, Karolinska Institutet, Stockholm SE-171 77, Sweden
- Key
Laboratory of Drug Quality Control and Pharmacovigilance (Ministry
of Education), State Key Laboratory of Natural Medicine, China Pharmaceutical University, Nanjing 210009, P. R. China
| | - Christopher Carlsten
- Air
Pollution Exposure Laboratory, Division of Respiratory Medicine, Department
of Medicine, University of British Columbia, Vancouver, British Columbia V5Z 1M9, Canada
| | - Romanas Chaleckis
- Gunma
University Initiative for Advanced Research (GIAR), Gunma University, Maebashi, Gunma 371-8511, Japan
- Division
of Physiological Chemistry 2, Department of Medical Biochemistry and
Biophysics, Karolinska Institutet, Stockholm SE-171 77, Sweden
| | - Kati Hanhineva
- Department
of Life Technologies, Food Chemistry and Food Development Unit, University of Turku, Turku 20014, Finland
- Department
of Biology and Biological Engineering, Chalmers
University of Technology, Gothenburg SE-412 96, Sweden
- Department
of Clinical Nutrition and Public Health, University of Eastern Finland, Kuopio 70210, Finland
| | - Mengna Huang
- Channing
Division of Network Medicine, Brigham and
Women’s Hospital and Harvard Medical School, Boston, Massachusetts 02115, United States
| | - Tomohiko Isobe
- The
Japan Environment and Children’s Study Programme Office, National Institute for Environmental Sciences, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan
| | - Ville M. Koistinen
- Department
of Life Technologies, Food Chemistry and Food Development Unit, University of Turku, Turku 20014, Finland
- Department
of Clinical Nutrition and Public Health, University of Eastern Finland, Kuopio 70210, Finland
| | - Isabel Meister
- Gunma
University Initiative for Advanced Research (GIAR), Gunma University, Maebashi, Gunma 371-8511, Japan
- Division
of Physiological Chemistry 2, Department of Medical Biochemistry and
Biophysics, Karolinska Institutet, Stockholm SE-171 77, Sweden
| | - Stefano Papazian
- Science
for Life Laboratory, Department of Environmental Science, Stockholm University, Stockholm SE-114 18, Sweden
| | - Kalliroi Sdougkou
- Science
for Life Laboratory, Department of Environmental Science, Stockholm University, Stockholm SE-114 18, Sweden
| | - Hongyu Xie
- Science
for Life Laboratory, Department of Environmental Science, Stockholm University, Stockholm SE-114 18, Sweden
| | - Jonathan W. Martin
- Science
for Life Laboratory, Department of Environmental Science, Stockholm University, Stockholm SE-114 18, Sweden
| | - Stephen M. Rappaport
- Division
of Environmental Health Sciences, School of Public Health, University of California, Berkeley, California 94720-7360, United States
| | - Hiroshi Tsugawa
- RIKEN Center
for Sustainable Resource Science, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
- RIKEN Center
for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
- Department
of Biotechnology and Life Science, Tokyo
University of Agriculture and Technology, 2-24-16 Nakamachi, Koganei, Tokyo 184-8588 Japan
- Graduate
School of Medical life Science, Yokohama
City University, 1-7-22
Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan
| | - Douglas I. Walker
- Department
of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, New York10029-5674, United States
| | - Tracey J. Woodruff
- Program
on Reproductive Health and the Environment, University of California San Francisco, San Francisco, California 94143, United States
| | - Robert O. Wright
- Department
of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, New York10029-5674, United States
| | - Craig E. Wheelock
- Gunma
University Initiative for Advanced Research (GIAR), Gunma University, Maebashi, Gunma 371-8511, Japan
- Division
of Physiological Chemistry 2, Department of Medical Biochemistry and
Biophysics, Karolinska Institutet, Stockholm SE-171 77, Sweden
- Department
of Respiratory Medicine and Allergy, Karolinska
University Hospital, Stockholm SE-141-86, Sweden
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