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International Journal of Toxicology
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Predictive Modeling of a Mixture of Thyroid Hormone Disrupting Chemicals That Affect Production and Clearance of Thyroxine

J. L. Flippin
J. M. Hedge
M. J. DeVito
G. A. LeBlanc
K. M. Crofton

From the Department of Environmental and Molecular Toxicology, North Carolina State University, Raleigh (JLF, GAL); and Integrated Systems Toxicology Division, National Health and Environmental Effects Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina (JMH, MJD, KMC).

Correspondence: Kevin M. Crofton, Neurotoxicology Division, MD: B105-04, National Health and Environmental Effects Research Laboratory, ORD, US EPA, Research Triangle Park, NC 27711; e-mail: crofton.kevin{at}epa.gov.

Thyroid hormone (TH) disrupting compounds interfere with both thyroidal and extrathyroidal mechanisms to decrease circulating thyroxine (T4). This research tested the hypothesis that serum T4 concentrations of rodents exposed to a mixture of both TH synthesis inhibitors (pesticides) and stimulators of T4 clearance in the liver (polyhalogenated aromatic hydrocarbons, PHAHs) could be best predicted by an integrated addition model. Female Long-Evans rats, 23 days of age, were dosed with dilutions of a mixture of 18 PHAHs (2 dioxins, 4 dibenzofurans, and 12 PCBs, including dioxin-like and non-dioxin like PCBs) and a mixture of 3 pesticides (thiram, pronamide, and mancozeb) for four consecutive days. Serum was collected 24 hours after the last exposure and T4 concentrations were measured by radioimmunoassay. Animals exposed to the highest dose of the mixture experienced a 45% decrease in serum T4. Three additivity model predictions (dose addition, effect addition, and integrated addition) were generated based on single chemical data, and the results were compared. Effect addition overestimated the effect produced by the combination of all 21 chemicals. The results of the dose- and integrated-addition models were similar, and both provided better predictions than the effect-addition model. These results support the use of dose- and integrated additivity models in predicting the effects of complex mixtures.

Key Words: thyroid hormone disruption • mixture modeling • pronamide • mancozeb • thiram • polyhalogenated aromatic hydrocarbons

International Journal of Toxicology, Vol. 28, No. 5, 368-381 (2009)
DOI: 10.1177/1091581809341883
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