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

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  • Carl‐Gustaf Bornehag
  • Efthymia Kitraki
  • Antonios Stamatakis
  • Emily Panagiotidou
  • Christina Rudén
  • Huan Shu
  • Christian Lindh
  • Joelle Ruegg
  • Chris Gennings

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” 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%).

Suggested Citation

  • Carl‐Gustaf Bornehag & Efthymia Kitraki & Antonios Stamatakis & Emily Panagiotidou & Christina Rudén & Huan Shu & Christian Lindh & Joelle Ruegg & Chris Gennings, 2019. "A Novel Approach to Chemical Mixture Risk Assessment—Linking Data from Population‐Based Epidemiology and Experimental Animal Tests," Risk Analysis, John Wiley & Sons, vol. 39(10), pages 2259-2271, October.
  • Handle: RePEc:wly:riskan:v:39:y:2019:i:10:p:2259-2271
    DOI: 10.1111/risa.13323
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    References listed on IDEAS

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    1. Scott Marshall & Chris Gennings & Linda K. Teuschler & LeAnna G. Stork & Rogelio Tornero‐Velez & Kevin M. Crofton & Glenn E. Rice, 2013. "An Empirical Approach to Sufficient Similarity: Combining Exposure Data and Mixtures Toxicology Data," Risk Analysis, John Wiley & Sons, vol. 33(9), pages 1582-1595, September.
    2. Hoda Izadi & Jean E. Grundy & Ranjan Bose, 2012. "Evaluation of the Benchmark Dose for Point of Departure Determination for a Variety of Chemical Classes in Applied Regulatory Settings," Risk Analysis, John Wiley & Sons, vol. 32(5), pages 830-835, May.
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