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A Novel Approach to Chemical Mixture Risk Assessment—Linking Data from Population-Based Epidemiology and Experimental Animal Tests

Bornehag, Carl Gustaf LU ; Kitraki, Efthymia ; Stamatakis, Antonios ; Panagiotidou, Emily ; Rudén, Christina ; Shu, Huan ; Lindh, Christian LU ; Ruegg, Joelle and Gennings, Chris (2019) In Risk Analysis 39(10). p.2259-2271
Abstract

Humans are continuously exposed to chemicals with suspected or proven endocrine disrupting chemicals (EDCs). Risk management of EDCs presents a major unmet challenge because the available data for adverse health effects are generated by examining one compound at a time, whereas real-life exposures are to mixtures of chemicals. In this work, we integrate epidemiological and experimental evidence toward a whole mixture strategy for risk assessment. To illustrate, we conduct the following four steps in a case study: (1) identification of single EDCs (“bad actors”)—measured in prenatal blood/urine in the SELMA study—that are associated with a shorter anogenital distance (AGD) in baby boys; (2) definition and construction of a “typical”... (More)

Humans are continuously exposed to chemicals with suspected or proven endocrine disrupting chemicals (EDCs). Risk management of EDCs presents a major unmet challenge because the available data for adverse health effects are generated by examining one compound at a time, whereas real-life exposures are to mixtures of chemicals. In this work, we integrate epidemiological and experimental evidence toward a whole mixture strategy for risk assessment. To illustrate, we conduct the following four steps in a case study: (1) identification of single EDCs (“bad actors”)—measured in prenatal blood/urine in the SELMA study—that are associated with a shorter anogenital distance (AGD) in baby boys; (2) definition and construction of a “typical” mixture consisting of the “bad actors” identified in Step 1; (3) experimentally testing this mixture in an in vivo animal model to estimate a dose–response relationship and determine a point of departure (i.e., reference dose [RfD]) associated with an adverse health outcome; and (4) use a statistical measure of “sufficient similarity” to compare the experimental RfD (from Step 3) to the exposure measured in the human population and generate a “similar mixture risk indicator” (SMRI). The objective of this exercise is to generate a proof of concept for the systematic integration of epidemiological and experimental evidence with mixture risk assessment strategies. Using a whole mixture approach, we could find a higher rate of pregnant women under risk (13%) when comparing with the data from more traditional models of additivity (3%), or a compound-by-compound strategy (1.6%).

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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Chemical exposure, mixtures, risk assessment, sexual development
in
Risk Analysis
volume
39
issue
10
pages
13 pages
publisher
John Wiley and Sons Inc.
external identifiers
  • scopus:85067401773
  • pmid:31173660
ISSN
0272-4332
DOI
10.1111/risa.13323
language
English
LU publication?
yes
id
276b86e6-6070-4a52-b41f-a3cd1f35ee97
date added to LUP
2019-07-03 10:28:27
date last changed
2020-08-05 05:27:10
@article{276b86e6-6070-4a52-b41f-a3cd1f35ee97,
  abstract     = {<p>Humans are continuously exposed to chemicals with suspected or proven endocrine disrupting chemicals (EDCs). Risk management of EDCs presents a major unmet challenge because the available data for adverse health effects are generated by examining one compound at a time, whereas real-life exposures are to mixtures of chemicals. In this work, we integrate epidemiological and experimental evidence toward a whole mixture strategy for risk assessment. To illustrate, we conduct the following four steps in a case study: (1) identification of single EDCs (“bad actors”)—measured in prenatal blood/urine in the SELMA study—that are associated with a shorter anogenital distance (AGD) in baby boys; (2) definition and construction of a “typical” mixture consisting of the “bad actors” identified in Step 1; (3) experimentally testing this mixture in an in vivo animal model to estimate a dose–response relationship and determine a point of departure (i.e., reference dose [RfD]) associated with an adverse health outcome; and (4) use a statistical measure of “sufficient similarity” to compare the experimental RfD (from Step 3) to the exposure measured in the human population and generate a “similar mixture risk indicator” (SMRI). The objective of this exercise is to generate a proof of concept for the systematic integration of epidemiological and experimental evidence with mixture risk assessment strategies. Using a whole mixture approach, we could find a higher rate of pregnant women under risk (13%) when comparing with the data from more traditional models of additivity (3%), or a compound-by-compound strategy (1.6%).</p>},
  author       = {Bornehag, Carl Gustaf and Kitraki, Efthymia and Stamatakis, Antonios and Panagiotidou, Emily and Rudén, Christina and Shu, Huan and Lindh, Christian and Ruegg, Joelle and Gennings, Chris},
  issn         = {0272-4332},
  language     = {eng},
  number       = {10},
  pages        = {2259--2271},
  publisher    = {John Wiley and Sons Inc.},
  series       = {Risk Analysis},
  title        = {A Novel Approach to Chemical Mixture Risk Assessment—Linking Data from Population-Based Epidemiology and Experimental Animal Tests},
  url          = {http://dx.doi.org/10.1111/risa.13323},
  doi          = {10.1111/risa.13323},
  volume       = {39},
  year         = {2019},
}