Evidence map›Paper›PMID 36152849›Full record

ArticleThe Science of the total environment2023

A geospatial modeling approach to quantifying the risk of exposure to environmental chemical mixtures via a common molecular target.

Kristin M Eccles, Agnes L Karmaus, Nicole C Kleinstreuer, Fred Parham, Cynthia V Rider, John F Wambaugh, Kyle P Messier

Open access · hybridAbstract read
In one paragraph

Article in The Science of the total environment, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.9field-weighted citation impact, top 15% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 18 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 1 country.

Kristin M EcclesNational Institute of Environmental Health Science, Division of the Translational Toxicology, Durham, USA.
Agnes L KarmausIntegrated Laboratory Systems, an Inotiv Company, Morrisville, NC, USA.
Nicole C KleinstreuerNational Institute of Environmental Health Science, Division of the Translational Toxicology, Durham, USA.
Fred ParhamNational Institute of Environmental Health Science, Division of the Translational Toxicology, Durham, USA.
Cynthia V RiderNational Institute of Environmental Health Science, Division of the Translational Toxicology, Durham, USA.
John F WambaughUnited States Environmental Protection Agency, Center for Computational Toxicology and Exposure, Durham, USA.
Kyle P MessierNational Institute of Environmental Health Science, Division of the Translational Toxicology, Durham, USA. Electronic address: kyle.messier@nih.gov.
National Institute of Environmental Health Sciences · USEnvironmental Protection Agency · USIntegrated Laboratory Systems, Inc. · US

Funding

Toxicological Assessments for the National Toxicology ProgramZIAES103316 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI WALKER, NIGEL J · 2016 to 2019
$31.9M
Scientific Cyberinfrastructure Research ProgramZIAES103385 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI WALKER, VICKIE · 2022 to 2025
$17.4M
Spatiotemporal Health Analytics: Geospatial connections to toxicologyZIAES103368 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI MESSIER, KYLE · 2021 to 2025
$5.8M
Combined Exposures and Mixtures Research ProgramZIAES103373 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI RIDER, CYNTHIA · 2022 to 2025
$5.6M
Research Operations Supporting the National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological MethodsZICES103386 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI HOGBERG-DURDOCK, HELENA · 2022 to 2025
$3.3M
Intramural EPA EPA999999Intramural NIH HHS ZIA ES103316Intramural NIH HHS ZIA ES103368Intramural NIH HHS ZIA ES103373NIEHS NIH HHS HHSN273201500010C
6 · The paper itself

Abstract

In the real world, individuals are exposed to chemicals from sources that vary over space and time. However, traditional risk assessments based on in vivo animal studies typically use a chemical-by-chemical approach and apical disease endpoints. New approach methodologies (NAMs) in toxicology, such as in vitro high-throughput (HTS) assays generated in Tox21 and ToxCast, can more readily provide mechanistic chemical hazard information for chemicals with no existing data than in vivo methods. In this paper, we establish a workflow to assess the joint action of 41 modeled ambient chemical exposures in the air from the USA-wide National Air Toxics Assessment by integrating human exposures with hazard data from curated HTS (cHTS) assays to identify counties where exposure to the local chemical mixture may perturb a common biological target. We exemplify this proof-of-concept using CYP1A1 mRNA up-regulation. We first estimate internal exposure and then convert the inhaled concentration to a steady state plasma concentration using physiologically based toxicokinetic modeling parameterized with county-specific information on ages and body weights. We then use the estimated blood plasma concentration and the concentration-response curve from the in vitro cHTS assay to determine the chemical-specific effects of the mixture components. Three mixture modeling methods were used to estimate the joint effect from exposure to the chemical mixture on the activity levels, which were geospatially mapped. Finally, a Monte Carlo uncertainty analysis was performed to quantify the influence of each parameter on the combined effects. This workflow demonstrates how NAMs can be used to predict early-stage biological perturbations that can lead to adverse health outcomes that result from exposure to chemical mixtures. As a result, this work will advance mixture risk assessment and other early events in the effects of chemicals.

Indexed as

Biological AssayEnvironmental ExposureAnimalsHumansMonte Carlo MethodRisk AssessmentDose additionExposomeHigh-throughput assayMixturesNew approaches methodologiesSpatial risk assessment

Identifiers

PMID36152849
PMCPMC9979101
OpenAlexW4296550796

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.