You are here:
Semantic characterization of adverse outcome pathways
Citation:
Wang, R. Semantic characterization of adverse outcome pathways. AQUATIC TOXICOLOGY. Elsevier Science Ltd, New York, NY, 222:1-14, (2020). https://doi.org/10.1016/j.aquatox.2020.105478
Impact/Purpose:
The concept of adverse outcome pathways is increasingly adopted as a framework to aid the toxicology paradigm shift from traditional animal testing to in vitro, in silico, and short-term in vivo methods. There have been many AOPs developed by domain subject experts. This study reports a novel ontology/semantics-based approach to objectively assess the quality of these AOPS. The findings suggest that this approach also has promising applications in developing additional semantics-based AOPs in the future.
Description:
This study was undertaken to systematically assess the utilities and performance of semantic analysis in adverse outcome pathway (AOP) research. With an increasing number of AOPs developed by scientific domain experts to organize toxicity information and facilitate chemical risk assessment, there is a pressing need for objective approaches to evaluate the quality of these AOPs. Powered by biological ontologies covering a wide variety of biological domains, abundant phenotypic data annotated ontologically, and some sophisticated knowledge computing tools, semantic analysis has great potential in this area of application. With the events in the AOP-Wiki first annotated into logical definitions and then grouped into phenotypic profiles by individual AOPs, the qualities of AOPs were assessed at several levels: paired key event relationships (KER), all possible event pair combinations within AOPs, and the phenotypic profiles of AOPs, genes, biological pathways, human diseases, and selected chemicals. The semantic similarities were assessed at all these levels based on a unified cross-species vertebrate phenotype ontology encompassing the logical definitions of AOP events as well as many other domain ontologies. A substantial number of KERs and AOPs in the AOP-Wiki were found to be semantically coherent. These same coherent AOPs also mapped to many more genes, pathways, and diseases biologically aligned with the intended chain of events therein leading to their respective adverse outcomes. Significantly, this finding implies that semantic analysis should also have utilities in developing future AOPs by selecting candidate events from either the existing AOP-Wiki events or a broader collection of ontology terms semantically similar to the molecular initiating events or adverse outcomes of interest. In addition, semantic analysis enabled AOP networks to be constructed at the level of phenotypic profiles based on similarities, complementing those based on event sharing by bringing genes, pathways, diseases, and chemicals into the networks too thus greatly expanding the biological scope and our understanding of AOPs.
