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Cheng R, Huang P, Ding TT, Gu ZW, Tao MT, Liu SS. Time-dependent hormesis transfer from five high-frequency personal care product components to mixtures. ENVIRONMENTAL RESEARCH 2024; 248:118418. [PMID: 38316386 DOI: 10.1016/j.envres.2024.118418] [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: 11/04/2023] [Revised: 01/25/2024] [Accepted: 02/02/2024] [Indexed: 02/07/2024]
Abstract
There is potential for personal care products (PCPs) components and mixtures to induce hormesis. How hormesis is related to time and transmitted from components to mixtures are not clear. In this paper, we conducted determination of components in 16 PCP products and then ran frequent itemset mining on the component data. Five high-frequency components (HFCs), betaine (BET), 1,3-butanediol (BUT), ethylenediaminetetraacetic acid disodium salt (EDTA), glycerol (GLO), and phenoxyethanol (POE), and 14 mixtures were identified. For each mixture system, one mixture ray with the actual mixture ratios in the products was selected. Time-dependent microplate toxicity analysis was used to test the luminescence inhibition toxicity of five HFCs and 14 mixture rays to Vibrio qinghaiensis sp.-Q67 at 12 concentration gradients and eight exposure times. It is showed that BET, EDTA, POE, and 13 mixture rays containing at least one J-type component showed time-dependent hormesis. Characteristic parameters used to describe hormesis revealed that the absolute value of the maximum stimulatory effect (|Emin|) generally increased with time. Notably, mixtures composed of POE and S-type components showed greater |Emin| than POE alone at the same time. Importantly, the maximum stimulatory effective concentration, NOEC/the zero effective concentration point, and EC50 remained relatively stable. Nine hormesis transmission phenomena were observed in different mixture rays. While all mixtures primarily exhibited additive action, varying degrees of synergism and antagonism were noted in binary mixtures, with no strong synergism or antagonism observed in ternary and quaternary mixtures. These findings offer valuable insights for the screening of HFCs and their mixtures, as well as the study of hormesis transmission in personal care products.
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Affiliation(s)
- Rujun Cheng
- Key Laboratory of Yangtze River Water Environment, Ministry of Education, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China; State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China
| | - Peng Huang
- Key Laboratory of Yangtze River Water Environment, Ministry of Education, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China; Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, China
| | - Ting-Ting Ding
- Key Laboratory of Yangtze River Water Environment, Ministry of Education, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China; State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China
| | - Zhong-Wei Gu
- Key Laboratory of Yangtze River Water Environment, Ministry of Education, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China; Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, China
| | - Meng-Ting Tao
- Key Laboratory of Yangtze River Water Environment, Ministry of Education, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China; State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China
| | - Shu-Shen Liu
- Key Laboratory of Yangtze River Water Environment, Ministry of Education, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China; State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China; Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, China.
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Stanfield Z, Setzer RW, Hull V, Sayre RR, Isaacs KK, Wambaugh JF. Characterizing Chemical Exposure Trends from NHANES Urinary Biomonitoring Data. ENVIRONMENTAL HEALTH PERSPECTIVES 2024; 132:17009. [PMID: 38285237 PMCID: PMC10824265 DOI: 10.1289/ehp12188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 10/19/2023] [Accepted: 12/12/2023] [Indexed: 01/30/2024]
Abstract
BACKGROUND Xenobiotic metabolites are widely present in human urine and can indicate recent exposure to environmental chemicals. Proper inference of which chemicals contribute to these metabolites can inform human exposure and risk. Furthermore, longitudinal biomonitoring studies provide insight into how chemical exposures change over time. OBJECTIVES We constructed an exposure landscape for as many human-exposure relevant chemicals over as large a time span as possible to characterize exposure trends across demographic groups and chemical types. METHODS We analyzed urine data of nine 2-y cohorts (1999-2016) from the National Health and Nutrition Examination Survey (NHANES). Chemical daily intake rates (in milligrams per kilogram bodyweight per day) were inferred, using the R package bayesmarker, from metabolite concentrations in each cohort individually to identify exposure trends. Trends for metabolites and parents were clustered to find chemicals with similar exposure patterns. Exposure variation by age, gender, and body mass index were also assessed. RESULTS Intake rates for 179 parent chemicals were inferred from 151 metabolites (96 measured in five or more cohorts). Seventeen metabolites and 44 parent chemicals exhibited fold-changes ≥ 10 between any two cohorts (deltamethrin, di-n -octyl phthalate, and di-isononyl phthalate had the greatest exposure increases). Di-2-ethylhexyl phthalate intake began decreasing in 2007, whereas both di-isobutyl and di-isononyl phthalate began increasing shortly before. Intake for four parabens was markedly higher in females, especially reproductive-age females, compared with males and children. Cadmium and arsenobetaine exhibited higher exposure for individuals > 65 years of age and lower for individuals < 20 years of age. DISCUSSION With appropriate analysis, NHANES indicates trends in chemical exposures over the past two decades. Decreases in exposure are observable as the result of regulatory action, with some being accompanied by increases in replacement chemicals. Age- and gender-specific variations in exposure were observed for multiple chemicals. Continued estimation of demographic-specific exposures is needed to both monitor and identify potential vulnerable populations. https://doi.org/10.1289/EHP12188.
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Affiliation(s)
- Zachary Stanfield
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, North Carolina, USA
| | - R. Woodrow Setzer
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, North Carolina, USA
| | - Victoria Hull
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, North Carolina, USA
- Oak Ridge Associated Universities, Oak Ridge, Tennessee, USA
| | - Risa R. Sayre
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, North Carolina, USA
- Oak Ridge Associated Universities, Oak Ridge, Tennessee, USA
| | - Kristin K. Isaacs
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, North Carolina, USA
| | - John F. Wambaugh
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, North Carolina, USA
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Gu ZW, Xie Y, Huang P, Ding TT, Tao MT, Liu SS. Time-dependent hormetic dose responses of skin care product mixtures to Vibrio qinghaiensis sp.-Q67: Appearance and quantification. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 904:166651. [PMID: 37647971 DOI: 10.1016/j.scitotenv.2023.166651] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 08/24/2023] [Accepted: 08/26/2023] [Indexed: 09/01/2023]
Abstract
Hormesis is a widely recognized and extensively studied phenomenon. However, few studies have described the quantitative characteristics of hormesis required for appropriate risk assessment. Although skin care product (SCP) mixtures and their active ingredients can induce the hormesis of Vibrio qinghaiensis sp.-Q67 (Q67), the quantitative characteristics of time-dependent hormetic dose responses in SCPs have not yet been investigated. In this study, 28 SCP mixtures were tested for luminescence toxicity against Q67 after five exposure durations (0.25, 3, 6, 9, and 12 h). With increasing exposure duration, the concentration response curves (CRCs) were classified as constant monotonic nonlinear (S-shaped) for four SCPs, S- to hormetic (J-shaped) for 13 SCPs, and constant J-shaped for 11 SCPs. Of 140 CRCs, 98 were J-shaped. An increased frequency of SCPs inducing hormesis was observed. The toxicity (pEC50) of the SCPs was independent of the exposure duration and product type. The maximum stimulatory effect (Emin) of the 12 SCPs increased with exposure duration. We proposed a modified parameter, the width of inhibition dose zone (WIDZ; EC50/EC10), to depict the width of inhibition dose zone. The WIDZ of S-shaped CRCs were significantly larger than that of J-shaped CRCs. In addition, the characteristic parameters reported in the general literature were analyzed. The good linear relationship between EC50 and the maximum stimulatory effective concentration (ECmin) indicated that toxicity may be transformed into stimulatory effects over exposure durations. The width of stimulation dose zone (WSDZ) and Emin of the seven SCPs had the same increasing trends with increasing exposure duration. The combination of WIDZ with other characteristic parameters (e.g., zero effective concentration point, ECmin, etc.) could better depict hormesis with low-dose stimulation and high-dose inhibition. The quantitative characteristics of the dose-responses of hormesis-inducing SCPs could provide reference basis for the risk assessment of SCP mixtures.
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Affiliation(s)
- Zhong-Wei Gu
- State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China; Key Laboratory of Yangtze River Water Environment, Ministry of Education, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China.
| | - Yu Xie
- State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China; Key Laboratory of Yangtze River Water Environment, Ministry of Education, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China
| | - Peng Huang
- State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China; Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, China
| | - Ting-Ting Ding
- State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China; Key Laboratory of Yangtze River Water Environment, Ministry of Education, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China
| | - Meng-Ting Tao
- State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China; Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, China
| | - Shu-Shen Liu
- State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China; Key Laboratory of Yangtze River Water Environment, Ministry of Education, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China; Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, China.
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Møller FT, Junker TG, Kold Sørensen K, Eves C, Wohlfahrt J, Dillner J, Torp-Pedersen C, Wilkowski B, Chong S, Pers TH, Yakimov V, Müller H, Ethelberg S, Melbye M. Assessing household lifestyle exposures from consumer purchases, the My Purchases cohort. Sci Rep 2023; 13:21601. [PMID: 38062070 PMCID: PMC10703931 DOI: 10.1038/s41598-023-47534-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Accepted: 11/14/2023] [Indexed: 12/18/2023] Open
Abstract
Consumer purchase data (CPD) is a promising instrument to assess the impact of purchases on health, but is limited by the need for manual scanning, a lack of access to data from multiple retailers, and limited information on product data and health outcomes. Here we describe the My Purchases cohort, a web-app enabled, prospective collection of CPD, covering several large retail chains in Denmark, that enables linkage to health outcomes. The cohort included 459 participants as of July 03, 2023. Up to eight years of CPD have been collected, with 2,225,010 products purchased, comprising 223,440 unique products. We matched 88.5% of all products by product name or item number to one generic food database and three product databases. Combined, the databases enable analysis of key exposures such as nutrients, ingredients, or additives. We found that increasing the number of retailers that provide CPD for each consumer improved the stability of individual CPD profiles and when we compared kilojoule information from generic and specific product matches, we found a median modified relative difference of 0.23. Combined with extensive product databases and health outcomes, CPD could provide the basis for extensive investigations of how what we buy affects our health.
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Affiliation(s)
- Frederik T Møller
- Department of Infectious Disease Epidemiology and Prevention, Statens Serum Institut, Copenhagen, Denmark.
| | - Thor Grønborg Junker
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Kathrine Kold Sørensen
- Department of Cardiology, North Zealand Hospital, Hillerød, Denmark
- Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Caroline Eves
- Department of Infectious Disease Epidemiology and Prevention, Statens Serum Institut, Copenhagen, Denmark
| | - Jan Wohlfahrt
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
- Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Joakim Dillner
- Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Stockholm, Sweden
| | - Christian Torp-Pedersen
- Department of Cardiology, North Zealand Hospital, Hillerød, Denmark
- Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Bartlomiej Wilkowski
- Department for Digital Infrastructure, Statens Serum Institut, Copenhagen, Denmark
| | - Steven Chong
- Department for Digital Infrastructure, Statens Serum Institut, Copenhagen, Denmark
| | - Tune H Pers
- The Novo Nordisk Foundation, Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Victor Yakimov
- Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark
| | - Heimo Müller
- Diagnostic and Research Center for Molecular BioMedicine, Medical University of Graz, Graz, Austria
| | - Steen Ethelberg
- Department of Infectious Disease Epidemiology and Prevention, Statens Serum Institut, Copenhagen, Denmark
- Department of Public Health, Global Health Section, University of Copenhagen, Copenhagen, Denmark
| | - Mads Melbye
- Danish Cancer Society Research Center, Copenhagen, Denmark
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Buckley TJ, Egeghy PP, Isaacs K, Richard AM, Ring C, Sayre RR, Sobus JR, Thomas RS, Ulrich EM, Wambaugh JF, Williams AJ. Cutting-edge computational chemical exposure research at the U.S. Environmental Protection Agency. ENVIRONMENT INTERNATIONAL 2023; 178:108097. [PMID: 37478680 PMCID: PMC10588682 DOI: 10.1016/j.envint.2023.108097] [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: 03/21/2023] [Revised: 06/05/2023] [Accepted: 07/12/2023] [Indexed: 07/23/2023]
Abstract
Exposure science is evolving from its traditional "after the fact" and "one chemical at a time" approach to forecasting chemical exposures rapidly enough to keep pace with the constantly expanding landscape of chemicals and exposures. In this article, we provide an overview of the approaches, accomplishments, and plans for advancing computational exposure science within the U.S. Environmental Protection Agency's Office of Research and Development (EPA/ORD). First, to characterize the universe of chemicals in commerce and the environment, a carefully curated, web-accessible chemical resource has been created. This DSSTox database unambiguously identifies >1.2 million unique substances reflecting potential environmental and human exposures and includes computationally accessible links to each compound's corresponding data resources. Next, EPA is developing, applying, and evaluating predictive exposure models. These models increasingly rely on data, computational tools like quantitative structure activity relationship (QSAR) models, and machine learning/artificial intelligence to provide timely and efficient prediction of chemical exposure (and associated uncertainty) for thousands of chemicals at a time. Integral to this modeling effort, EPA is developing data resources across the exposure continuum that includes application of high-resolution mass spectrometry (HRMS) non-targeted analysis (NTA) methods providing measurement capability at scale with the number of chemicals in commerce. These research efforts are integrated and well-tailored to support population exposure assessment to prioritize chemicals for exposure as a critical input to risk management. In addition, the exposure forecasts will allow a wide variety of stakeholders to explore sustainable initiatives like green chemistry to achieve economic, social, and environmental prosperity and protection of future generations.
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Affiliation(s)
- Timothy J Buckley
- U.S. Environmental Protection Agency, Office of Research & Development, Center for Computational Toxicology & Exposure (CCTE), 109 TW Alexander Drive, Research Triangle Park, NC 27711, United States.
| | - Peter P Egeghy
- U.S. Environmental Protection Agency, Office of Research & Development, Center for Computational Toxicology & Exposure (CCTE), 109 TW Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Kristin Isaacs
- U.S. Environmental Protection Agency, Office of Research & Development, Center for Computational Toxicology & Exposure (CCTE), 109 TW Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Ann M Richard
- U.S. Environmental Protection Agency, Office of Research & Development, Center for Computational Toxicology & Exposure (CCTE), 109 TW Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Caroline Ring
- U.S. Environmental Protection Agency, Office of Research & Development, Center for Computational Toxicology & Exposure (CCTE), 109 TW Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Risa R Sayre
- U.S. Environmental Protection Agency, Office of Research & Development, Center for Computational Toxicology & Exposure (CCTE), 109 TW Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Jon R Sobus
- U.S. Environmental Protection Agency, Office of Research & Development, Center for Computational Toxicology & Exposure (CCTE), 109 TW Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Russell S Thomas
- U.S. Environmental Protection Agency, Office of Research & Development, Center for Computational Toxicology & Exposure (CCTE), 109 TW Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Elin M Ulrich
- U.S. Environmental Protection Agency, Office of Research & Development, Center for Computational Toxicology & Exposure (CCTE), 109 TW Alexander Drive, Research Triangle Park, NC 27711, United States
| | - John F Wambaugh
- U.S. Environmental Protection Agency, Office of Research & Development, Center for Computational Toxicology & Exposure (CCTE), 109 TW Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Antony J Williams
- U.S. Environmental Protection Agency, Office of Research & Development, Center for Computational Toxicology & Exposure (CCTE), 109 TW Alexander Drive, Research Triangle Park, NC 27711, United States
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Online coupling of matrix solid-phase dispersion to direct analysis in real time mass spectrometry for high-throughput analysis of regulated chemicals in consumer products. Anal Chim Acta 2023; 1239:340677. [PMID: 36628757 DOI: 10.1016/j.aca.2022.340677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2022] [Revised: 11/23/2022] [Accepted: 11/24/2022] [Indexed: 11/27/2022]
Abstract
The current work is the first study on online coupling of matrix solid-phase dispersion (MSPD) to direct analysis in real time mass spectrometry (DART-MS) bridging with solid-phase analytical derivatization (SPAD) based on a graphene oxide nanosheets (GONs)-coated cotton swab. Proof-of-concept demonstrations were explored for high-throughput analysis of a diversity of regulated chemicals in consumer products such as textiles, toys, and cosmetics. On-demand sorbent combinations were blended with samples, packed into MSPD columns, and mounted on a homemade 3D-printed rack module for automated sample feeding. To achieve good synergy between MSPD and DART-MS, a cotton swab with a conical tip deposited with GONs was attached to the bottom of the MSPD column. The swabs serve as a solid-phase microextraction probe for convenient enrichment of the eluted analytes from MSPD, thermal desorption of the enriched analytes by DART, and sensitive detection by a hybrid quadrupole-Orbitrap mass spectrometer. Furthermore, the utility of an on-swab SPAD strategy was demonstrated for the detection of formaldehyde by use of the derivatizing reagent of dansyl hydrazine, contributing to improved ionization efficiency without compromising the overall coherence of the analytical workflow. The MSPD-DART-MS methodology was systematically optimized and validated, obtaining acceptable recovery (71.7-110.3%), repeatability (11.8-19.3%), and sensitivity (limits of detection and quantitation in the ranges of 6.2-19.5 and 23.7-75.9 μg/kg) for 32 target analytes. The developed protocol streamlined sample extraction, clean-up, desorption, ionization, and detection, highlighting the appealing potential for high-throughput analysis of samples with complex matrices.
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Braun G, Escher BI. Prioritization of mixtures of neurotoxic chemicals for biomonitoring using high-throughput toxicokinetics and mixture toxicity modeling. ENVIRONMENT INTERNATIONAL 2023; 171:107680. [PMID: 36502700 DOI: 10.1016/j.envint.2022.107680] [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: 07/29/2022] [Revised: 12/05/2022] [Accepted: 12/05/2022] [Indexed: 06/17/2023]
Abstract
Modern society continues to pollute the environment with larger quantities of chemicals that have also become more structurally and functionally diverse. Risk assessment of chemicals can hardly keep up with the sheer numbers that lead to complex mixtures of increasing chemical diversity including new chemicals, substitution products on top of still abundant legacy compounds. Fortunately, over the last years computational tools have helped us to identify and prioritize chemicals of concern. These include toxicokinetic models to predict exposure to chemicals as well as new approach methodologies such as in-vitro bioassays to address toxicodynamic effects. Combined, they allow for a prediction of mixtures and their respective effects and help overcome the lack of data we face for many chemicals. In this study we propose a high-throughput approach using experimental and predicted exposure, toxicokinetic and toxicodynamic data to simulate mixtures, to which a virtual population is exposed to and predict their mixture effects. The general workflow is adaptable for any type of toxicity, but we demonstrated its applicability with a case study on neurotoxicity. If no experimental data for neurotoxicity were available, we used baseline toxicity predictions as a surrogate. Baseline toxicity is the minimal toxicity any chemical has and might underestimate the true contribution to the mixture effect but many neurotoxicants are not by orders of magnitude more potent than baseline toxicity. Therefore, including baseline-toxic effects in mixture simulations yields a more realistic picture than excluding them in mixture simulations. This workflow did not only correctly identify and prioritize known chemicals of concern like benzothiazoles, organochlorine pesticides and plasticizers but we were also able to identify new potential neurotoxicants that we recommend to include in future biomonitoring studies and if found in humans, to also include in neurotoxicity screening.
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Affiliation(s)
- Georg Braun
- Department of Cell Toxicology, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany.
| | - Beate I Escher
- Department of Cell Toxicology, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany; Environmental Toxicology, Department of Geosciences, Eberhard Karls University Tübingen, Tübingen, Germany
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Wambaugh JF, Rager JE. Exposure forecasting - ExpoCast - for data-poor chemicals in commerce and the environment. JOURNAL OF EXPOSURE SCIENCE & ENVIRONMENTAL EPIDEMIOLOGY 2022; 32:783-793. [PMID: 36347934 PMCID: PMC9742338 DOI: 10.1038/s41370-022-00492-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 10/21/2022] [Accepted: 10/21/2022] [Indexed: 05/10/2023]
Abstract
Estimates of exposure are critical to prioritize and assess chemicals based on risk posed to public health and the environment. The U.S. Environmental Protection Agency (EPA) is responsible for regulating thousands of chemicals in commerce and the environment for which exposure data are limited. Since 2009 the EPA's ExpoCast ("Exposure Forecasting") project has sought to develop the data, tools, and evaluation approaches required to generate rapid and scientifically defensible exposure predictions for the full universe of existing and proposed commercial chemicals. This review article aims to summarize issues in exposure science that have been addressed through initiatives affiliated with ExpoCast. ExpoCast research has generally focused on chemical exposure as a statistical systems problem intended to inform thousands of chemicals. The project exists as a companion to EPA's ToxCast ("Toxicity Forecasting") project which has used in vitro high-throughput screening technologies to characterize potential hazard posed by thousands of chemicals for which there are limited toxicity data. Rapid prediction of chemical exposures and in vitro-in vivo extrapolation (IVIVE) of ToxCast data allow for prioritization based upon risk of adverse outcomes due to environmental chemical exposure. ExpoCast has developed (1) integrated modeling approaches to reliably predict exposure and IVIVE dose, (2) highly efficient screening tools for chemical prioritization, (3) efficient and affordable tools for generating new exposure and dose data, and (4) easily accessible exposure databases. The development of new exposure models and databases along with the application of technologies like non-targeted analysis and machine learning have transformed exposure science for data-poor chemicals. By developing high-throughput tools for chemical exposure analytics and translating those tools into public health decisions ExpoCast research has served as a crucible for identifying and addressing exposure science knowledge gaps.
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Affiliation(s)
- John F Wambaugh
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. EPA, Research Triangle Park, NC, USA.
- Department of Environmental Sciences & Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
| | - Julia E Rager
- Department of Environmental Sciences & Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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Gibson EA, Zhang J, Yan J, Chillrud L, Benavides J, Nunez Y, Herbstman JB, Goldsmith J, Wright J, Kioumourtzoglou MA. Principal Component Pursuit for Pattern Identification in Environmental Mixtures. ENVIRONMENTAL HEALTH PERSPECTIVES 2022; 130:117008. [PMID: 36416734 PMCID: PMC9683097 DOI: 10.1289/ehp10479] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Revised: 08/24/2022] [Accepted: 09/15/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Environmental health researchers often aim to identify sources or behaviors that give rise to potentially harmful environmental exposures. OBJECTIVE We adapted principal component pursuit (PCP)-a robust and well-established technique for dimensionality reduction in computer vision and signal processing-to identify patterns in environmental mixtures. PCP decomposes the exposure mixture into a low-rank matrix containing consistent patterns of exposure across pollutants and a sparse matrix isolating unique or extreme exposure events. METHODS We adapted PCP to accommodate nonnegative data, missing data, and values below a given limit of detection (LOD). We simulated data to represent environmental mixtures of two sizes with increasing proportions < LOD and three noise structures. We applied PCP-LOD to evaluate its performance in comparison with principal component analysis (PCA). We next applied principal component pursuit with limit of detection (PCP-LOD) to an exposure mixture of 21 persistent organic pollutants (POPs) measured in 1,000 U.S. adults from the 2001-2002 National Health and Nutrition Examination Survey (NHANES). We applied singular value decomposition to the estimated low-rank matrix to characterize the patterns. RESULTS PCP-LOD recovered the true number of patterns through cross-validation for all simulations; based on an a priori specified criterion, PCA recovered the true number of patterns in 32% of simulations. PCP-LOD achieved lower relative predictive error than PCA for all simulated data sets with up to 50% of the data < LOD . When 75% of values were < LOD , PCP-LOD outperformed PCA only when noise was low. In the POP mixture, PCP-LOD identified a rank-three underlying structure and separated 6% of values as extreme events. One pattern represented comprehensive exposure to all POPs. The other patterns grouped chemicals based on known structure and toxicity. DISCUSSION PCP-LOD serves as a useful tool to express multidimensional exposures as consistent patterns that, if found to be related to adverse health, are amenable to targeted public health messaging. https://doi.org/10.1289/EHP10479.
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Affiliation(s)
- Elizabeth A. Gibson
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, New York, USA
| | - Junhui Zhang
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, New York, USA
| | - Jingkai Yan
- Department of Electrical Engineering, Columbia University Data Science Institute, New York, New York, USA
| | - Lawrence Chillrud
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, New York, USA
| | - Jaime Benavides
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, New York, USA
| | - Yanelli Nunez
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, New York, USA
| | - Julie B. Herbstman
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, New York, USA
| | - Jeff Goldsmith
- Department of Biostatistics, Columbia University Mailman School of Public Health, New York, New York, USA
| | - John Wright
- Department of Electrical Engineering, Columbia University Data Science Institute, New York, New York, USA
| | - Marianthi-Anna Kioumourtzoglou
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, New York, USA
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10
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Rietdijk J, Aggarwal T, Georgieva P, Lapins M, Carreras-Puigvert J, Spjuth O. Morphological profiling of environmental chemicals enables efficient and untargeted exploration of combination effects. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 832:155058. [PMID: 35390365 DOI: 10.1016/j.scitotenv.2022.155058] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 04/01/2022] [Accepted: 04/01/2022] [Indexed: 06/14/2023]
Abstract
Environmental chemicals are commonly studied one at a time, and there is a need to advance our understanding of the effect of exposure to their combinations. Here we apply high-content microscopy imaging of cells stained with multiplexed dyes (Cell Painting) to profile the effects of Cetyltrimethylammonium bromide (CTAB), Bisphenol A (BPA), and Dibutyltin dilaurate (DBTDL) exposure on four human cell lines; both individually and in all combinations. We show that morphological features can be used with multivariate data analysis to discern between exposures from individual compounds, concentrations, and combinations. CTAB and DBTDL induced concentration-dependent morphological changes across the four cell lines, and BPA exacerbated morphological effects when combined with CTAB and DBTDL. Combined exposure to CTAB and BPA induced changes in the ER, Golgi apparatus, nucleoli and cytoplasmic RNA in one of the cell lines. Different responses between cell lines indicate that multiple cell types are needed when assessing combination effects. The rapid and relatively low-cost experiments combined with high information content make Cell Painting an attractive methodology for future studies of combination effects. All data in the study is made publicly available on Figshare.
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Affiliation(s)
- Jonne Rietdijk
- Department of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Sweden
| | - Tanya Aggarwal
- Department of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Sweden
| | - Polina Georgieva
- Department of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Sweden
| | - Maris Lapins
- Department of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Sweden
| | - Jordi Carreras-Puigvert
- Department of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Sweden.
| | - Ola Spjuth
- Department of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Sweden.
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11
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Barupal DK, Mahajan P, Fakouri-Baygi S, Wright RO, Arora M, Teitelbaum SL. CCDB: A database for exploring inter-chemical correlations in metabolomics and exposomics datasets. ENVIRONMENT INTERNATIONAL 2022; 164:107240. [PMID: 35461097 PMCID: PMC9195052 DOI: 10.1016/j.envint.2022.107240] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 04/01/2022] [Accepted: 04/08/2022] [Indexed: 05/18/2023]
Abstract
Inter-chemical correlations in metabolomics and exposomics datasets provide valuable information for studying relationships among chemicals reported for human specimens. With an increase in the number of compounds for these datasets, a network graph analysis and visualization of the correlation structure is difficult to interpret. We have developed the Chemical Correlation Database (CCDB), as a systematic catalogue of inter-chemical correlation in publicly available metabolomics and exposomics studies. The database has been provided via an online interface to create single compound-centric views. We have demonstrated various applications of the database to explore: 1) the chemicals from a chemical class such as Per- and Polyfluoroalkyl Substances (PFAS), polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), phthalates and tobacco smoke related metabolites; 2) xenobiotic metabolites such as caffeine and acetaminophen; 3) endogenous metabolites (acyl-carnitines); and 4) unannotated peaks for PFAS. The database has a rich collection of 35 human studies, including the National Health and Nutrition Examination Survey (NHANES) and high-quality untargeted metabolomics datasets. CCDB is supported by a simple, interactive and user-friendly web-interface to retrieve and visualize the inter-chemical correlation data. The CCDB has the potential to be a key computational resource in metabolomics and exposomics facilitating the expansion of our understanding about biological and chemical relationships among metabolites and chemical exposures in the human body. The database is available at www.ccdb.idsl.me site.
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Affiliation(s)
- Dinesh Kumar Barupal
- Department of Environmental Medicine and Public Health, Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, 17 E 102nd St, CAM Building, New York 10029, USA.
| | - Priyanka Mahajan
- Department of Environmental Medicine and Public Health, Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, 17 E 102nd St, CAM Building, New York 10029, USA
| | - Sadjad Fakouri-Baygi
- Department of Environmental Medicine and Public Health, Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, 17 E 102nd St, CAM Building, New York 10029, USA
| | - Robert O Wright
- Department of Environmental Medicine and Public Health, Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, 17 E 102nd St, CAM Building, New York 10029, USA
| | - Manish Arora
- Department of Environmental Medicine and Public Health, Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, 17 E 102nd St, CAM Building, New York 10029, USA
| | - Susan L Teitelbaum
- Department of Environmental Medicine and Public Health, Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, 17 E 102nd St, CAM Building, New York 10029, USA
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12
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Buckley J, Kuiper JR, Bennett DH, Barrett ES, Bastain T, Breton CV, Chinthakindi S, Dunlop AL, Farzan SF, Herbstman JB, Karagas MR, Marsit CJ, Meeker JD, Morello-Frosch R, O’Connor TG, Romano ME, Schantz S, Schmidt RJ, Watkins DJ, Zhu H, Pellizzari ED, Kannan K, Woodruff TJ. Exposure to Contemporary and Emerging Chemicals in Commerce among Pregnant Women in the United States: The Environmental influences on Child Health Outcome (ECHO) Program. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:6560-6573. [PMID: 35536918 PMCID: PMC9118548 DOI: 10.1021/acs.est.1c08942] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 04/21/2022] [Accepted: 04/22/2022] [Indexed: 05/10/2023]
Abstract
Prenatal chemical exposures can influence maternal and child health; however, few industrial chemicals are routinely biomonitored. We assessed an extensive panel of contemporary and emerging chemicals in 171 pregnant women across the United States (U.S.) and Puerto Rico in the Environmental influences on Child Health Outcomes (ECHO) Program. We simultaneously measured urinary concentrations of 89 analytes (103 total chemicals representing 73 parent compounds) in nine chemical groups: bactericides, benzophenones, bisphenols, fungicides and herbicides, insecticides, organophosphate esters (OPEs), parabens, phthalates/alternative plasticizers, and polycyclic aromatic hydrocarbons (PAHs). We estimated associations of creatinine-adjusted concentrations with sociodemographic and specimen characteristics. Among our diverse prenatal population (60% non-Hispanic Black or Hispanic), we detected 73 of 89 analytes in ≥1 participant and 36 in >50% of participants. Five analytes not currently included in the U.S. biomonitoring were detected in ≥90% of samples: benzophenone-1, thiamethoxam, mono-2-(propyl-6-carboxy-hexyl) phthalate, monocarboxy isooctyl phthalate, and monohydroxy-iso-decyl phthalate. Many analyte concentrations were higher among women of Hispanic ethnicity compared to those of non-Hispanic White women. Concentrations of certain chemicals decreased with the calendar year, whereas concentrations of their replacements increased. Our largest study to date identified widespread exposures to prevalent and understudied chemicals in a diverse sample of pregnant women in the U.S.
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Affiliation(s)
- Jessie
P. Buckley
- Department
of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 21218, United States
| | - Jordan R. Kuiper
- Department
of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 21218, United States
| | - Deborah H. Bennett
- Department
of Public Health Sciences, University of California Davis, Davis, California 95616, United States
| | - Emily S. Barrett
- Department
of Biostatistics and Epidemiology, Rutgers
School of Public Health, Piscataway, New Jersey 08854, United States
| | - Tracy Bastain
- Department
of Population and Public Health Sciences, University of Southern California, Los Angeles, California 90032, United States
| | - Carrie V. Breton
- Department
of Population and Public Health Sciences, University of Southern California, Los Angeles, California 90032, United States
| | - Sridhar Chinthakindi
- Department
of Pediatrics and Department of Environmental Medicine, New York University School of Medicine, New York, New York 10016, United States
| | - Anne L. Dunlop
- Department
of Gynecology and Obstetrics, Emory University
School of Medicine, Atlanta, Georgia 30322, United States
| | - Shohreh F. Farzan
- Department
of Population and Public Health Sciences, University of Southern California, Los Angeles, California 90032, United States
| | - Julie B. Herbstman
- Department
of Environmental Health Sciences, Columbia, New York, NY 10032, United States
| | - Margaret R. Karagas
- Department
of Epidemiology, Dartmouth Geisel School
of Medicine, Lebanon, New Hampshire 03756, United States
| | - Carmen J. Marsit
- Department
of Environmental Health, Rollins School
of Public Health, Emory University, Atlanta, Georgia 30322, United States
| | - John D. Meeker
- Department
of Environmental Health Sciences, University
of Michigan School of Public Health, Ann Arbor, Michigan 48109, United States
| | - Rachel Morello-Frosch
- Department
of Environmental Science, Policy and Management and School of Public
Health, University of California, Berkeley California 94720, United States
| | - Thomas G. O’Connor
- Department
of Psychiatry, University of Rochester, Rochester, New York 14627, United States
| | - Megan E. Romano
- Department
of Epidemiology, Dartmouth Geisel School
of Medicine, Lebanon, New Hampshire 03756, United States
| | - Susan Schantz
- Beckman
Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, Illinois 61801, United States
| | - Rebecca J. Schmidt
- Department
of Public Health Sciences, University of California Davis, Davis, California 95616, United States
| | - Deborah J. Watkins
- Department
of Environmental Health Sciences, University
of Michigan School of Public Health, Ann Arbor, Michigan 48109, United States
| | - Hongkai Zhu
- Department
of Pediatrics and Department of Environmental Medicine, New York University School of Medicine, New York, New York 10016, United States
| | - Edo D. Pellizzari
- RTI International, Research Triangle
Park, North Carolina 27709, United States
| | - Kurunthachalam Kannan
- Department
of Pediatrics and Department of Environmental Medicine, New York University School of Medicine, New York, New York 10016, United States
| | - Tracey J. Woodruff
- Department
of Obstetrics, Gynecology, and Reproductive Sciences and the Philip
R. Lee Institute for Health Policy Studies, University of California San Francisco, San Francisco, California 94143, United States
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13
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Chemical Mixtures in Household Environments: In Silico Predictions and In Vitro Testing of Potential Joint Action on PPARγ in Human Liver Cells. TOXICS 2022; 10:toxics10050199. [PMID: 35622613 PMCID: PMC9146550 DOI: 10.3390/toxics10050199] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 04/16/2022] [Indexed: 01/27/2023]
Abstract
There are thousands of chemicals that humans can be exposed to in their everyday environments, the majority of which are currently understudied and lack substantial testing for potential exposure and toxicity. This study aimed to implement in silico methods to characterize the chemicals that co-occur across chemical and product uses in our everyday household environments that also target a common molecular mediator, thus representing understudied mixtures that may exacerbate toxicity in humans. To detail, the Chemical and Products Database (CPDat) was queried to identify which chemicals co-occur across common exposure sources. Chemicals were preselected to include those that target an important mediator of cell health and toxicity, the peroxisome proliferator activated receptor gamma (PPARγ), in liver cells that were identified through query of the ToxCast/Tox21 database. These co-occurring chemicals were thus hypothesized to exert potential joint effects on PPARγ. To test this hypothesis, five commonly co-occurring chemicals (namely, benzyl cinnamate, butyl paraben, decanoic acid, eugenol, and sodium dodecyl sulfate) were tested individually and in combination for changes in the expression of PPARγ and its downstream target, insulin receptor (INSR), in human liver HepG2 cells. Results showed that these likely co-occurring chemicals in household environments increased both PPARγ and INSR expression more significantly when the exposures occurred as mixtures vs. as individual chemicals. Future studies will evaluate such chemical combinations across more doses, allowing for further quantification of the types of joint action while leveraging this method of chemical combination prioritization. This study demonstrates the utility of in silico-based methods to identify chemicals that co-occur in the environment for mixtures toxicity testing and highlights relationships between understudied chemicals and changes in PPARγ-associated signaling.
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14
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Association between household cleaning product profiles evaluated by the Ménag’Score® index and asthma symptoms among women from the SEPAGES cohort. Int Arch Occup Environ Health 2022; 95:1719-1729. [DOI: 10.1007/s00420-022-01860-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Accepted: 03/24/2022] [Indexed: 11/25/2022]
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15
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Sauvé JF, Emili A, Mater G. Application of Pattern Mining Methods to Assess Exposures to Multiple Airborne Chemical Agents in Two Large Occupational Exposure Databases from France. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19031746. [PMID: 35162769 PMCID: PMC8835122 DOI: 10.3390/ijerph19031746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 01/31/2022] [Accepted: 02/01/2022] [Indexed: 12/10/2022]
Abstract
Surveys of the French working population estimate that approximately 15% of all workers may be exposed to at least three different chemical agents, but the most prevalent coexposure situations and their associated health risks remain relatively understudied. To characterize occupational coexposure situations in France, we extracted personal measurement data from COLCHIC and SCOLA, two large administrative occupation exposure databases. We selected 118 chemical agents that had ≥100 measurements with detected concentrations over the period 2010-2019, including 31 carcinogens (IARC groups 1, 2A, and 2B). We grouped measurements by work situations (WS, combination of sector, occupation, task, and year). We characterized the mixtures across WS using frequent itemset mining and association rules mining. The 275,213 measurements extracted came from 32,670 WS and encompassing 4692 unique mixtures. Workers in 32% of all WS were exposed to ≥2 agents (median 3 agents/WS) and 13% of all WS contained ≥2 carcinogens (median 2 carcinogens/WS). The most frequent coexposures were ethylbenzene-xylene (1550 WS), quartz-cristobalite (1417 WS), and toluene-xylene (1305 WS). Prevalent combinations of carcinogens also included hexavalent chromium-lead (368 WS) and benzene-ethylbenzene (314 WS). Wood dust (6% of WS exposed to at least one other agent) and asbestos (8%) had the least amount of WS coexposed with other agents. Tasks with the highest proportions of coexposure to carcinogens include electric arc welding (37% of WS with coexposure), polymerization and distillation (34%), and construction drilling and excavating (34%). Overall, the coexposure to multiple chemical agents, including carcinogens, was highly prevalent in the databases, and should be taken into account when assessing exposure risks in the workplace.
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16
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Li D, Li L. Human Chemical Exposure from Background Emissions in the United States and the Implication for Quantifying Risks from Marginal Emission Increase. TOXICS 2021; 9:308. [PMID: 34822699 PMCID: PMC8621763 DOI: 10.3390/toxics9110308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 11/08/2021] [Accepted: 11/12/2021] [Indexed: 11/16/2022]
Abstract
The linear dose-response relationship has long been assumed in assessments of health risk from an incremental chemical emission relative to background emissions. In this study, we systematically examine the relevancy of such an assumption with real-world data. We used the reported emission data, as background emissions, from the 2017 U.S. National Emission Inventory for 95 organic chemicals to estimate the central tendencies of exposures of the general U.S. population. Previously published nonlinear dose-response relationships for chemicals were used to estimate health risk from exposure. We also explored and identified four intervals of exposure in which the nonlinear dose-response relationship may be linearly approximated with fixed slopes. Predicted rates of exposure to these 95 chemicals are all within the lowest of the four intervals and associated with low health risk. The health risk may be overestimated if a slope on the dose-response relationship extrapolated from toxicological assays based on high response rates is used for a marginal increase in emission not substantially higher than background emissions. To improve the confidence of human health risk estimates for chemicals, future efforts should focus on deriving a more accurate dose-response relationship at lower response rates and interface it with exposure assessments.
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Affiliation(s)
| | - Li Li
- Correspondence: (D.L.); (L.L.)
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17
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Pascual F. A New View of the Things We Use: Using Purchasing Data to Predict Common Mixture Exposures. ENVIRONMENTAL HEALTH PERSPECTIVES 2021; 129:84004. [PMID: 34427455 PMCID: PMC8384071 DOI: 10.1289/ehp9911] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Accepted: 07/27/2021] [Indexed: 06/13/2023]
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