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Characterization of the Mechanistic Linkages Between Iodothyronine Deiodinase Inhibition and Impaired Thyroid-Mediated Growth and Development in Xenopus laevis Using Iopanoic Acid.

Jonathan T HaselmanJennifer H OlkerPatricia A KosianJoseph J KorteJeffrey S DennyJoseph E TietgeMichael W HornungSigmund J Degitz
Published in: Toxicological sciences : an official journal of the Society of Toxicology (2022)
Iodothyronine deiodinases (DIO) are key enzymes that influence tissue-specific thyroid hormone levels during thyroid-mediated amphibian metamorphosis. Within the larger context of evaluating chemicals for thyroid system disrupting potential, chemical activity toward DIOs is being evaluated using high-throughput in vitro screening assays as part of U.S. EPA's ToxCast program. However, existing data gaps preclude any inferences between in vitro chemical inhibition of DIOs and in vivo outcomes relevant to ecological risk assessment. This study aimed to generate targeted data in a laboratory model species (Xenopus laevis) using a model DIO inhibitor, iopanoic acid (IOP), to characterize linkages between in vitro potency, in vivo biochemical responses, and adverse organismal outcomes. In vitro potency of IOP toward DIOs was evaluated using previously developed in vitro screening assays, which showed concentration-dependent inhibition of human DIO1 (IC50: 97 µM) and DIO2 (IC50: 231 µM) but did not inhibit human or X. laevis DIO3 under the assay conditions. In vivo exposure of larval X. laevis to 0, 2.6, 5.3, and 10.5 µM IOP caused thyroid-related biochemical profiles in the thyroid gland and plasma consistent with hyperthyroxinemia but resulted in delayed metamorphosis and significantly reduced growth in the highest 2 exposure concentrations. Independent evaluations of dio gene expression ontogeny, together with existing literature, supported interpretation of IOP-mediated effects resulting in a proposed adverse outcome pathway for DIO2 inhibition leading to altered amphibian metamorphosis. This study highlights the types of mechanistic data needed to move toward predicting in vivo outcomes of regulatory concern from in vitro bioactivity data.
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