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Identification of Chemicals Associated with Retinoid Signaling Pathway Disturbance and Skeletal Dysmorphogenesis Through Predictive Computational Toxicology Models.
Citation:
Pierro, J., B. Ahir, N. Baker, AND T. Knudsen. Identification of Chemicals Associated with Retinoid Signaling Pathway Disturbance and Skeletal Dysmorphogenesis Through Predictive Computational Toxicology Models. Society of Toxicology (FutureTox V), Chapel Hill, NC, May 10 - 11, 2022. https://doi.org/10.23645/epacomptox.19692319
Impact/Purpose:
Presentation to the FutureTox V (SOT) Conference May 2022. Our findings guided the development of potential AOPs (pAOPs) and will further advance our dynamic mechanistic modeling to strengthen evidence for causality. Furthermore, NAMs identified 20 chemicals without previous evidence of retinoic acid pathway disturbance and skeletal defects association. Extrapolations of these vertebrate findings shed light on potential avenues for new mechanistic discoveries related to retinoic acid pathway disruption and associated skeletal dysmorphogenesis in human fetuses.
Description:
All-trans retinoic acid (ATRA) gradients determine skeletal patterning morphogenesis and can be disrupted by diverse genetic or environmental factors, leading to fetal skeleton malformations. Here, a data-driven model was constructed to identify chemicals associated with both ATRA pathway bioactivity and prenatal non-human, mammalian skeletal defects. We classified altered skeletal phenotypes in prenatal developmental toxicity studies in ToxRefDB and/or ToxCast high-throughput screening (HTS) and identified 370 chemicals associated with alterations. Defects were organized into four skeletal phenotype groupings: cranial, post-cranial axial, appendicular, and non-specified skeletal defects. To build a multivariate statistical model, HTS results from >8,070 chemicals in ToxCast/Tox21 across 10 in vitro assays, representing key nodes in the retinoid signaling system were evaluated and compared to candidate reference chemicals for in vitro testing. A set of 48 chemicals were identified for constructing data-driven models to link this in vitro data with adverse skeletal outcomes for computational modeling. Adverse Outcome Pathway (AOP) frameworks for ATRA metabolism, signaling, and homeostasis allow for the development of new approach methodologies (NAMs) to improve predictive toxicology without animal experimentation. Our findings guided the development of potential AOPs (pAOPs) and will further advance our dynamic mechanistic modeling to strengthen evidence for causality. Furthermore, NAMs identified 20 chemicals without previous evidence of retinoic acid pathway disturbance and skeletal defects association. Extrapolations of these vertebrate findings shed light on potential avenues for new mechanistic discoveries related to retinoic acid pathway disruption and associated skeletal dysmorphogenesis in human fetuses. This abstract does not represent the official views of EPA.
URLs/Downloads:
DOI: Identification of Chemicals Associated with Retinoid Signaling Pathway Disturbance and Skeletal Dysmorphogenesis Through Predictive Computational Toxicology Models.
FUTURETOXV_ATRASKEL_V.1.PDF (PDF, NA pp, 1278.684 KB, about PDF)