You are here:
An AOP-based Ontology for Spina Bifida Caused by Disturbance in Retinoic Acid Signaling
Citation:
Piersma, A., N. Baker, L. Burgoon, G. Daston, T. Knudsen, AND Y. Staal. An AOP-based Ontology for Spina Bifida Caused by Disturbance in Retinoic Acid Signaling. Presented at Society of Toxicology annual meeting, Baltimore, MD, March 10 - 14, 2019.
Impact/Purpose:
The retinoic acid (RA) pathway serves as a prototype for adverse outcome pathway (AOP) elucidation for developmental defects. The biology of the RA pathway was used for the construction of an ontology for neural tube closure defects. Ultimately, this network can be dynamically modeled in silico, providing an integrated computational systems model allowing toxicity predictions at the level of adverse outcomes in the intact individual. A battery of cell-based in vitro assays can be used to monitor the critical rate-determining steps in the network, providing a tiered testing strategy to collect data feeding into the systems model. Integrating the dynamic model with information from exposure and kinetic models allows quantitative hazard and risk assessment while avoiding animal testing.
Description:
The retinoic acid (RA) pathway serves as a prototype for adverse outcome pathway (AOP) elucidation for developmental defects. The biology of the RA pathway was used for the construction of an ontology for neural tube closure defects. The ontology describes an AOP network incorporating retinoid homeostasis and putative molecular initiating events in chemical teratogenesis. Basic elements in the ontology are subjects (enzymes, receptors, cell types) and their quantitative relationships (response-response relationships), forming a network of biological interactions to be mapped to a vulnerable developmental window for e.g. teratogen-induced spina bifida. We have searched the available literature data using text-mining tools to map known molecular interactions, genetic signals and responses that: (a) play a crucial role in cellular differentiation; (b) establish anterior-posterior gradients (FGF and RA signaling) and dorsal-ventral gradients [zinc factors (Zic) and BMP signaling] for regional specification. Molecular initiating events important for RA balance (like CYP26 enzymes and RALDH2) potentially affected by xenobiotic compounds (based on high-through-put screening data), were connected with toxicological data on the development of posterior neural tube defects. Ultimately, this network can be dynamically modeled in silico, providing an integrated computational systems model allowing toxicity predictions at the level of adverse outcomes in the intact individual. A battery of cell-based in vitro assays can be used to monitor the critical rate-determining steps in the network, providing a tiered testing strategy to collect data feeding into the systems model. Integrating the dynamic model with information from exposure and kinetic models allows quantitative hazard and risk assessment while avoiding animal testing. The views presented in this abstract do not necessarily reflect current or future opinion or policy of the U.S. Environmental Protection Agency and the U.S. Army Corps of Engineers.