Adverse outcome pathways, key events, and radiation risk assessment

Increasing global concern over COVID-19 has recently brought greater attention to studies due to the ease of person-to-person transmission and the current lack of effective antiviral therapy. Here, we proposed the application of the adverse outcome pathway (AOP) framework to support re-search on the pathogenesis of viral disease. We first constructed adverse outcome pathways (AOPs) applicable to COVID-19 management to understand whether the infection causes severe acute respiratory distress. Based on the AOP framework where mechanistic elucidation of the pathway from the interaction of chemicals (or viruses) to apical endpoints is represented, our COVID-19 AOP indicated that the molecular initiating event (MIE) was angiotensin-converting enzyme 2 (ACE2) interaction, and the key events (KEs) were the increased pro-inflammatory cytokines in immune cells, with increased mortality as an apical adverse outcome (AO). However, there is still limited information on the toxicity mechanisms of AOPs in COVID-19; therefore, detailed KEs and AOs on toxicity mechanisms will be required to fill these gaps in the data. This study demonstrated that the COVID-19 AOP framework is a suitable tool to design new drugs and to integrate crowded-sourced information for the battle against the COVID-19 pandemic.

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Providing Adverse Outcome Pathways from the AOP-Wiki in Semantic Web Format to Increase Usability and Accessibility of the Content

10.26434/chemrxiv.13524191.v1 ◽

2021 ◽

Author(s):

Marvin Martens ◽

Chris Evelo ◽

Egon Willighagen

Keyword(s):

Resource Description Framework ◽

Adverse Outcome ◽

Semantic Annotation ◽

Adverse Outcome Pathway ◽

Dublin Core ◽

Description Framework ◽

Federated Queries ◽

Key Events ◽

Adverse Outcome Pathways ◽

Resource Description

<div>The AOP-Wiki is the main environment for the development and storage of Adverse Outcome Pathways. These Adverse Outcome Pathways describe mechanistic information about toxicodynamic processes and can be used to develop effective risk assessment strategies. However, it is challenging to automatically and systematically parse, filter, and use its contents. We explored solutions to better structure the AOP-Wiki content and to link it with chemical and biological resources. Together this allows more detailed exploration which can be automated.</div><div><br></div><div>We converted the complete AOP-Wiki content into Resource Description Framework. We used over twenty ontologies for the semantic annotation of property-object relations, including the ChemInformatics Ontology, Dublin Core, and the Adverse Outcome Pathway Ontology. The latter was used over 8,000 times. Furthermore, over 3,500 link-outs were added to twelve chemical databases and over 6,500 link-outs to four gene and protein databases. </div><div><br></div><div>SPARQL queries can be used against the Resource Description Framework to answer biological and toxicological questions, such as listing measurement methods for all Key Events leading to an Adverse Outcome of interest. The full power that the use of this new resource provides becomes apparent when combining the content with external databases using federated queries. For example, we can link genes related to Key Events with molecular pathway on WikiPathways in which they occur and find all Adverse Outcome Pathways caused by stressors that are part of a particular chemical group. Overall, the AOP-Wiki Resource Description Framework allows new ways to explore the rapidly growing Adverse Outcome Pathway knowledge and makes the integration of this database in automated workflows possible.</div>

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