You are here:
Computationally-Predicted AOPs and Systems Toxicology
Citation:
Edwards, S., N. Oki, S. Bell, M. Nelms, AND C. Tan. Computationally-Predicted AOPs and Systems Toxicology. 20th North American ISSX Meeting, Orlando, FL, October 18 - 22, 2015.
Impact/Purpose:
This presentation will highlight our efforts to streamline AOP discovery and development by creating computationally-predicted AOPS through data mining. It should increase awareness of this work and provide us feedback on best practices we should consider while pursuing this research.
Description:
The Adverse Outcome Pathway has emerged as an internationally harmonized mechanism for organizing biological information in a chemical agnostic manner. This construct is valuable for interpreting the results from high-throughput toxicity (HTT) assessment by providing a mechanistic connection to adverse outcomes of regulatory interest. To facilitate the development and use of AOPs, an international knowledgebase (AOPKB; https://aopkb.org) was developed to house this information with the public release of the first module (http://aopwiki.org) in September 2014. However, the AOPs currently stored in the AOPKB include the intended targets for only a small number of HTT assays currently used for toxicity screening. To generate more AOPs within the KB, we have developed bioinformatic approaches to expedite the inclusion of computationally-predicted AOPs (cpAOPs) that include biological pathways containing ToxCast assay targets. A variety of input data sources have been used including large-scale toxicogenomics data such as the Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System (TG-GATEs) and public annotation databases such as the Comparative Toxicogenomics Database (CTD). This cpAOP approach has successfully identified both novel and established modes of action such as liver toxicity via CCl4 exposure. The cpAOPs have also uniquely linked mechanistic information to adverse outcomes that have not been previously documented in public annotation databases, such as the role for CYP1B1 in AhR-mediated glaucoma. In all, the current cpAOP network provides annotation information for >200 EPA ToxCast assays. Through a crowd-sourcing model enabled by the AOPKB, these cpAOPs can be rapidly assessed by any scientist working in mechanistic toxicology to assemble putative AOPs. Detailed AOP development can be focused on problems where high precision is needed whereas putative AOPs may be sufficient for decisions when less quantitation and/or weight of evidence is required. If the AOPs are then combined with exposure and absorption, distribution, metabolism, excretion (ADME) predictions developed in a similar manner, we can recapitulate the mode of action for a given chemical from reusable components allowing more extensive use of AOPs in risk assessment. [This is an abstract or a proposed presentation and does not necessarily reflect EPA policy. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.]