Case Study
AOPLink – Identification and Linking of Data related to AOPWiki

Summary

The Adverse Outcome Pathway (AOP) concept has been introduced to support risk assessment (Ankley et al., 2010). An AOP comprises a number of events and the adverse outcome: a molecular initiation event (MIE) is followed by one or more key events (KEs), leading to the adverse outcome (AO). The AOPWiki is a collaborative to exchange AOPs.

The use of AOPs for regulatory purposes requires detailed validation and linking to existing knowledge (Knapen et al., 2015; Burgdorf et al., 2017). Part of the development of AOPs is the search for data that supports the occurrence and biological plausibility of KEs and their relationships (KERs). This data can be found in literature and increasingly in databases.

This case study focuses on establishing links between AOPs and data that supports a particular AOP. This will allow finding AOPs related to experimental data, and finding data related to a particular AOP.

Objectives

For this case study we aim to develop:

  • FAIR version of AOPWiki and WikiPathways;
  • Identifier mappings for MIEs, KEs, and biological and chemical entities (genes, proteins, metabolites);
  • Establish links between MIEs and KEs to biological assays;
  • Establish links between assays and biological and chemical entities;
  • Establish interoperable databases (see below).

Risk assessment framework

AOPLink will allow finding relevant experimental data for given compounds and nanomaterials and KEs (Tier 0, step 3), identify biological processes affected by exposure to those chemicals supporting hypothesis generation (Tier 1, step 6), and using these sources of information to determine if an AOP can be applied to that chemical and if not what information is missing (Tier 3, step 9).

With respect to the other case studies, AOPLink can take as input from SysGroup on similar chemicals (same group) in case no direct search results are found. Furthermore, TGX may provide predicted data to complement experimental data, to support searching. Because AOPLink may result in hypothesis and list KERs, these results can be passed to ModelRX for further prediction and read across.

Use Cases Associated

This case study is associated with UC3 - Search and Retrieve Assay Data based on Ontological Terms.

Databases and tools

  • AOPWiki, AOP knowledgebase (AOPKB);
  • WikiPathways, Reactome: biological pathway database;
  • BridgeDb: identifier mapping;
  • diXa, BioStudies, ArrayExpress, etc: experimental data;
  • Effectopedia, PathVisio: pathway analysis;
  • PubMed, ContentMine: literature for key events and their molecular processes.

Service integration

Services provided by SysGroup:

  • Grouping service that takes a compound or nanomaterial.

Services provided by TGX:

  • API to access predicted data.

Other services:

  • Search capability for the aforementioned databases;
  • Identifier mapping service;
  • PathVisioRPC;
  • Text mining services to find relevant literature.

Currently available services:

Related resources

Webinar recording
AOP-DB: The Adverse Outcome Pathway Database
Holly Mortensen, Ph.D. (US EPA), Phillip Langley (ORAU-SSC) and Trevor Levey (ORAU-SSC)
16 Apr 2019

Target audience: Risk assessors, Researchers, Students, Developers, OpenRiskNet stakeholders, Bioinformaticians
Open access: yes
Licence: Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
Organisations involved: EwC, UM
Webinar recording
Presentation
AOP-DB: The Adverse Outcome Pathway Database
Holly Mortensen, Ph.D. (US EPA), Phillip Langley (ORAU-SSC) and Trevor Levey (ORAU-SSC)
8 Apr 2019
Additional materials:
Slides

Target audience: Risk assessors, Researchers, Students, OpenRiskNet stakeholders, Regulators, Data modellers
Open access: yes
Licence: Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
Organisations involved: UM
Presentation
Webinar recording
Identification and linking of data related to AOPWiki
Marvin Martens and Egon Willighagen (Department of Bioinformatics, Maastricht University, The Netherlands), Thomas Exner (Edelweiss Connect GmbH, Switzerland)
27 Mar 2019

Publisher: OpenRiskNet
Target audience: Risk assessors, Researchers, Students, Data modellers, Bioinformaticians
Open access: yes
Licence: Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
Organisations involved: EwC, UM
Webinar recording
Presentation
AOPLink - Linking experimental data to Adverse Outcome Pathways
Marvin Martens, Egon Willighagen, Chris Evelo (Department of Bioinformatics, Maastricht University, The Netherlands)
27 Mar 2019
Additional materials:
Slides

Publisher: OpenRiskNet
Target audience: Risk assessors, Researchers, Students, Data modellers, Bioinformaticians
Open access: yes
Licence: Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
Organisations involved: UM
Presentation
Poster
Expanding Adverse Outcome Pathway knowledge by creating AOP-Wiki RDF with semantic annotations to facilitate risk assessment of chemicals.
Marvin Martens, Chris Evelo, Egon Willighagen
19 Feb 2019
Abstract:
1. Introduction With the ever-growing number of chemicals that require toxicological risk assessment, there is a need for faster, more efficient use of existing data to assemble effective assessment strategies [1]. Therefore, the concept of Adverse Outcome Pathways (AOPs) was introduced [2], a framework to organize existing mechanistic information about toxicological processes into a chain of smaller pieces of knowledge, called Key Events (KEs). These allow the structuring of toxicological knowledge and reduce the effort needed to capture all information before performing risk assessment [2, 3]. In order to facilitate a community effort in gathering toxicological knowledge, the AOP-Wiki was created by the European Commission JRC and the US EPA. To integrate this knowledge base more easily with other resources, we explored the use of semantic web technologies to link AOP-Wiki with other chemical and biological databases. 2. Approach The AOP-Wiki provides quarterly permanent downloads for the full database XML (https://aopwiki.org/downloads/). We parsed the AOP-Wiki knowledge with Python 3.5 and the ElementTree XML API and converted it into a semantic web RDF format, which allows for accurate description with ontological annotations, including the AOPO, CHEMINF, and Dublin Core. Chemical compounds are identified in the AOP-Wiki with CAS numbers and biological processes with a variety of ontologies, e.g. GO, Mammalian Phenotype Ontology, and Molecular Interactions ontology. These annotations are used to create Internationalized Resource Identifiers. To integrate and test the RDF, a variety of federated SPARQL queries were written and executed in Blazegraph (build version 2.1.4). 3. Results We created an AOP-Wiki RDF scheme and converted the XML into Turtle syntax. The RDF was tested with a variety of SPARQL queries to answer biological question relevant to risk assessment, such as: - What measurement / test-method information is available for a given AOP? - Which of the stressor chemicals on the AOP-Wiki can be linked molecular pathways on WikiPathways? 4. Discussion The RDF transformation of AOP-Wiki content can assist in the accessibility and expansion of toxicological knowledge by allowing semantic interoperability. The created RDF of the AOP-Wiki allows the querying and providing of additional information for stressor chemicals, genes, and proteins involved in KEs, the underlying molecular pathways, but also for the applicability of AOPs by cell types or species. This semantic approach allows novel ways to explore the rapidly growing AOP knowledge with every new publication related to toxicological studies. There is work in progress on a Virtuoso SPARQL endpoint Docker image to simplify the use of the data, and integrate the database in the OpenRiskNet e-infrastructure to provide AOP knowledge useful for automated risk assessment workflows. Funding This project has received funding from the European Union’s Horizon 2020 (EU 2020) research and innovation program under grant agreement no. 681002 (EU-ToxRisk) and EINFRA-22-2016 program under grant agreement no. 731075 (OpenRiskNet).
Related services:
AOP-Wiki SPARQL Endpoint

Target audience: Risk assessors, Researchers, Data managers, Data owners, OpenRiskNet stakeholders, Regulators, Bioinformaticians, Software developers, Data providers
Open access: yes
Licence: Attribution 4.0 International (CC BY 4.0)
Organisations involved: UM
Poster
Tutorial
Workflow: Access TG-GATEs data for seleted compounds, select differentially expressed genes and identifier relevant pathways
Thomas Exner
13 Sep 2018
Abstract:
Example workflow based on OpenRiskNet tools - Pathway identification workflow related to DataCure and AOPlink case studies. This notebook downloads TG-Gates data of 4 compounds and selects genes overexpressed in all sample. The Affymetrix probe sets are then translated into Ensembl gene identifiers using the BridgeDB service and pathways associated with the genes are identified using the WikiPathways service.

Publisher: OpenRiskNet
Target audience: Risk assessors, Researchers, Data modellers
Open access: yes
Licence: Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
Organisations involved: EwC
Tutorial