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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. Carolinas Society of Environmental Toxicology and Chemistry Conference (2022), Research Triangle Park, NC, April 06 - 08, 2022. https://doi.org/10.23645/epacomptox.19651107
Impact/Purpose:
Presentation to the Carolinas Society of Environmental Toxicology and Chemistry (CSETAC) Conference April 2022. 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 the alterations. Defects were organized into four skeletal phenotype groupings: cranial, post-cranial axial, appendicular, and other 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 or any government agency.
URLs/Downloads:
DOI: Identification of Chemicals Associated with Retinoid Signaling Pathway Disturbance and Skeletal Dysmorphogenesis Through Predictive Computational Toxicology Models![Exit EPA's Web Site](images/exitingepa.gif)
PIERRO CSETAC MTG 2022 ATRA_SKEL-M.PDF (PDF, NA pp, 4515.928 KB, about PDF)