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Developing putative AOPs from high content dataDeveloping putative AOPs from high content dataDeveloping putative AOPs from high content dataDeveloping putative AOPs from high content data
Citation:
Bell, S. AND S. Edwards. Developing putative AOPs from high content dataDeveloping putative AOPs from high content dataDeveloping putative AOPs from high content dataDeveloping putative AOPs from high content data. Presented at NIEHS Genomics DAY, RTP, NC, May 01, 2014.
Impact/Purpose:
The work presented in this abstract is aimed at addressing the question "can we use toxicogenomics data to identify putative AOPs"?
Description:
Developing putative AOPs from high content data Shannon M. Bell1,2, Stephen W. Edwards2 1 Oak Ridge Institute for Science and Education 2 Integrated Systems Toxicology Division, National Health and Environmental Effects Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA The adverse outcome pathway (AOP) framework provides a high-level description of the biological processes connecting molecular perturbations in response to an exposure event to an adverse health endpoint affecting whole organisms or populations of individuals. Development of detailed AOPs from traditional experimental results is a slow, tedious process and is unrealistic when covering the breadth of perturbations in response to the >83,000 chemicals in commerce. Large toxicogenomic screening studies, such as the Toxicogenomics Project-Genomics Assisted Toxicity Evaluation system (TG-GATEs), offer an opportunity to link molecular changes in response to chemical exposure to an adverse outcome. In this work we test the hypothesis that putative AOPs can be developed from high content assays using the TG GATEs rat liver microarray and pathology data. Associations based on frequent itemset mining identified and prioritized top candidate associations based on differential expression of biological pathways. Integration of pathology and transcriptomics data enabled the identification of a putative AOP for nonalcoholic steatohepatitis. Short term effects (<=24hrs) such as necrosis were distinguishable from the regenerative proliferation that presented from repeat chemical exposure. Putative biomarkers distinguishing different toxicological pathways are described. This work highlights the utility of toxicogenomic data for AOP discovery and in the identification of candidates for high throughput screening. The views expressed in this abstract are those of the authors and do not necessarily reflect the views or policies of the U.S. Environmental Protection Agency.