Science Inventory

Computational model for fetal skeletal defects potentially linked to disruption of retinoic acid signaling

Citation:

Pierro, J., B. Ahir, Nancy C. Baker, N. Kleinsteuer, M. Xia, AND T. Knudsen. Computational model for fetal skeletal defects potentially linked to disruption of retinoic acid signaling. Frontiers in Pharmacology. Frontiers, Lausanne, Switzerland, 13:971296, (2022). https://doi.org/10.3389/fphar.2022.971296

Impact/Purpose:

The all-trans retinoic acid (ATRA) signaling pathway plays a large role in early skeletal development. Understanding and identifying chemicals that effect the ATRA signaling pathway is key to preventing dysmorphogenesis in embryos. As such human health issues are applicable to a wide array of audiences - government agencies (EPA, NIH, NTP, etc.), communities, and the general public. Our findings of which chemicals are associated with both molecular targets on the ATRA pathway and skeletal defects can affect policymakers understanding of which chemicals require greater restrictions and consequentially prevent skeletal dysmorphogenesis in the long-term.

Description:

All-trans retinoic acid (ATRA) gradients determine skeletal patterning morphogenesis and can be disrupted by diverse genetic or environmental factors during pregnancy, leading to fetal skeleton defects. Adverse Outcome Pathway (AOP) frameworks for ATRA metabolism, signaling, and homeostasis allow for the development of new approach methods (NAMs) for predictive toxicology with less reliance on animal testing. Here, a data-driven model was constructed to identify chemicals associated with both ATRA pathway bioactivity and prenatal skeletal defects. The phenotype data was culled from ToxRefDB prenatal developmental toxicity  studies and produced a list of 363 ToxRefDB chemicals with altered skeletal observations. Defects were classified regionally as cranial, post-cranial axial, appendicular, and other (unspecified) features based on ToxRefDB descriptors. To build a multivariate statistical model, high-throughput screening bioactivity data from >8,070 chemicals in ToxCast/Tox21 across 10 in vitro assays relevant to the retinoid signaling system were evaluated and compared to literature-based candidate reference chemicals in the dataset. There were 48 chemicals identified for effects on both in vivo skeletal defects and in vitro ATRA pathway targets for computational modeling. The list included 28 chemicals with prior evidence of skeletal defects linked to retinoid toxicity and 20 chemicals without prior evidence. The combination of thoracic cage defects and DR5 (direct repeats of 5 nucleotides for RAR/RXR transactivation) disruption was the most frequently occurring phenotypic and target disturbance, respectively.  This data provides valuable AOP elucidation and validates current mechanistic understanding. These findings also shed light on potential avenues for new mechanistic discoveries related to ATRA pathway disruption and associated skeletal dysmorphogenesis due to environmental exposures.

Record Details:

Record Type:DOCUMENT( JOURNAL/ PEER REVIEWED JOURNAL)
Product Published Date:09/06/2022
Record Last Revised:11/03/2023
OMB Category:Other
Record ID: 359398