Tracking contributions to human body burden of environmental chemicals by correlating environmental measurements with biomarkers.

The work addresses current knowledge gaps regarding causes for correlations between environmental and biomarker measurements and explores the underappreciated role of variability in disaggregating exposure attributes that contribute to biomarker levels. Our simulation-based study considers variabili...

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Main Authors: Hyeong-Moo Shin, Thomas E McKone, Michael D Sohn, Deborah H Bennett
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2014-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC3969314?pdf=render
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spelling doaj-23c2538519c4449e95e5fe370bcf9f5d2020-11-25T01:20:48ZengPublic Library of Science (PLoS)PLoS ONE1932-62032014-01-0193e9367810.1371/journal.pone.0093678Tracking contributions to human body burden of environmental chemicals by correlating environmental measurements with biomarkers.Hyeong-Moo ShinThomas E McKoneMichael D SohnDeborah H BennettThe work addresses current knowledge gaps regarding causes for correlations between environmental and biomarker measurements and explores the underappreciated role of variability in disaggregating exposure attributes that contribute to biomarker levels. Our simulation-based study considers variability in environmental and food measurements, the relative contribution of various exposure sources (indoors and food), and the biological half-life of a compound, on the resulting correlations between biomarker and environmental measurements. For two hypothetical compounds whose half-lives are on the order of days for one and years for the other, we generate synthetic daily environmental concentrations and food exposures with different day-to-day and population variability as well as different amounts of home- and food-based exposure. Assuming that the total intake results only from home-based exposure and food ingestion, we estimate time-dependent biomarker concentrations using a one-compartment pharmacokinetic model. Box plots of modeled R2 values indicate that although the R2 correlation between wipe and biological (e.g., serum) measurements is within the same range for the two compounds, the relative contribution of the home exposure to the total exposure could differ by up to 20%, thus providing the relative indication of their contribution to body burden. The novel method introduced in this paper provides insights for evaluating scenarios or experiments where sample, exposure, and compound variability must be weighed in order to interpret associations between exposure data.http://europepmc.org/articles/PMC3969314?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Hyeong-Moo Shin
Thomas E McKone
Michael D Sohn
Deborah H Bennett
spellingShingle Hyeong-Moo Shin
Thomas E McKone
Michael D Sohn
Deborah H Bennett
Tracking contributions to human body burden of environmental chemicals by correlating environmental measurements with biomarkers.
PLoS ONE
author_facet Hyeong-Moo Shin
Thomas E McKone
Michael D Sohn
Deborah H Bennett
author_sort Hyeong-Moo Shin
title Tracking contributions to human body burden of environmental chemicals by correlating environmental measurements with biomarkers.
title_short Tracking contributions to human body burden of environmental chemicals by correlating environmental measurements with biomarkers.
title_full Tracking contributions to human body burden of environmental chemicals by correlating environmental measurements with biomarkers.
title_fullStr Tracking contributions to human body burden of environmental chemicals by correlating environmental measurements with biomarkers.
title_full_unstemmed Tracking contributions to human body burden of environmental chemicals by correlating environmental measurements with biomarkers.
title_sort tracking contributions to human body burden of environmental chemicals by correlating environmental measurements with biomarkers.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2014-01-01
description The work addresses current knowledge gaps regarding causes for correlations between environmental and biomarker measurements and explores the underappreciated role of variability in disaggregating exposure attributes that contribute to biomarker levels. Our simulation-based study considers variability in environmental and food measurements, the relative contribution of various exposure sources (indoors and food), and the biological half-life of a compound, on the resulting correlations between biomarker and environmental measurements. For two hypothetical compounds whose half-lives are on the order of days for one and years for the other, we generate synthetic daily environmental concentrations and food exposures with different day-to-day and population variability as well as different amounts of home- and food-based exposure. Assuming that the total intake results only from home-based exposure and food ingestion, we estimate time-dependent biomarker concentrations using a one-compartment pharmacokinetic model. Box plots of modeled R2 values indicate that although the R2 correlation between wipe and biological (e.g., serum) measurements is within the same range for the two compounds, the relative contribution of the home exposure to the total exposure could differ by up to 20%, thus providing the relative indication of their contribution to body burden. The novel method introduced in this paper provides insights for evaluating scenarios or experiments where sample, exposure, and compound variability must be weighed in order to interpret associations between exposure data.
url http://europepmc.org/articles/PMC3969314?pdf=render
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