Ontology-based semantic mapping of chemical toxicities. (15th January 2019)

• Record Type: Journal Article
• Authors: Wang, Rong-Lin; Edwards, Stephen; Ives, Cataia
• Is Part Of: Toxicology. Volume 412(2019)
• Page Start: 89
• Page End: 100
• Publication Date: 2019-01-15
• Subjects: CSPP chemical-species phenotypic profile -- CTD Comparative Toxicogenomics Database -- EPA Environmental Protection Agency -- EQ Entity-Quality -- ECOTOX ECOTOXicology Knowledgebase -- GO Gene Ontology -- HP Human Phenotype Ontology -- IC information content -- ID identification -- KEGG Kyoto Encyclopedia of Genes and Genomes -- MICA most informative common ancestor -- MOA mechanism of action -- MP Mammalian Phenotype Ontology -- OBO Open Biological and biomedical Ontology -- OMIM Online Mendelian Inheritance in Man -- OWL Web Ontology Language -- OWLAPI OWL Application Programming Interface -- PATO Phenotype And Trait Ontology -- RDF/XML Resource Description Framework/Extensible Markup Language -- RO Relations Ontology -- SML Semantic Measure Library -- TDCPP Tris(1, 3-dichloroisopropyl) phosphate -- ZP Zebrafish Phenotype Ontology; Chemical toxicity -- Ontology -- Phenotype -- Phenomics -- Semantic analysis; Toxicology -- Periodicals; Chemicals -- Physiological effect -- Periodicals; 615.9005
• DOI: 10.1016/j.tox.2018.11.005
• Languages: English
• ISSNs: 0300-483X

Abstract

Abstract: This study was undertaken to evaluate the use of ontology-based semantic mapping (OS-Mapping) in chemical toxicity assessment. Nineteen chemical-species phenotypic profiles (CSPPs) were constructed by ontologically annotating the toxicity responses reported in more than seven hundred published studies of ten chemicals on six vertebrate species. The CSPPs were semantically compared to more than 29, 000 publicly available phenotypic profiles of genes, KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways, and diseases based on a cross-species phenotype ontology. OS-Mapping was shown to differentiate chemical toxicities among themselves as well as within and across species. It also revealed cases of chemical by species interactions. In addition to confirming similar MOAs (mechanisms of action) for a few chemicals, OS-Mapping also generated novel insights into the MOAs underlying some seemingly different, yet phenotypically similar, classes of chemicals. The nature of a unified cross-species phenotype ontology and its representation of diverse knowledge domains allowed the construction of a complete phenotypic continuum for the 17α-ethynylestradiol_fathead minnow across the biological levels of organization, which complemented a similar one derived from the Comparative Toxicogenomics Database but based primarily on 17α-ethynylestradiol-induced molecular phenotypes. Overall, OS-Mapping has been demonstrated to offer a powerful approach to help bridge the gap between the molecular and non-molecular phenotypes of chemicals characterized by using high throughput or traditional omics methods and their apical endpoints of greater regulatory relevance, which are typically phenotypes found at the higher levels of biological organization. OS-Mapping also enables comparative toxicity assessment among chemicals, both within and across species. Furthermore, the semantic analysis of phenotypes can reveal additional novel MOAs for some well-known chemicals and discover candidate MOAs for chemicals that are less molecularly characterized. A full phenotypic continuum based on OS-Mapping will also be conducive to the future development of adverse outcome pathways. As phenomics continues to advance and the ontological annotation of literature becomes more automated, the power of OS-Mapping will be further enhanced.