You are here:
Identification of Differentially Expressed Genes (DEGs) and Networks Related to Hepatic Lipid Homeostatic Dysfunction Using a Gene Expression Approach
Citation:
Abedini, J. AND H. El-Masri. Identification of Differentially Expressed Genes (DEGs) and Networks Related to Hepatic Lipid Homeostatic Dysfunction Using a Gene Expression Approach. NCSOT, Durham, North Carolina, October 15, 2018.
Impact/Purpose:
This research illustrates a method to identify genes and biological pathways that may be linked to key events in adverse outcome pathways (AOPs) using publicly available databases. These events can help in developing putative AOPs and identify biological factors for susceptibility among exposed populations.
Description:
DrugMatrix is a database that contains standardized rodent chemical exposure data from 637 chemicals (mostly drugs), along with differential gene expression data and corresponding associated pathological changes. Using this database, we identified 13 chemical exposure treatments resulting in pathologically confirmed incidences of hepatic lipid dysfunction (p-value =< 0.05 and severity score greater than one). Microarray data collected from these exposures were further analyzed to generate a differential gene expression data set associated with hepatic lipid dysfunction. Further analysis of this gene expression set resulted in 224 upregulated genes and 175 genes that were down regulated. Meanwhile, 33 genes were both up regulated and down regulated. All identified genes were uploaded in DAVID for gene ontology enrichments and to identify biological events using Kyoto Encyclopedia of Genes and Genome (KEGG) pathways analysis. These pathways included steroid hormone biosynthesis, retinol metabolism, and metabolism of xenobiotics by cytochrome P450. Additionally, ingenuity canonical pathways were enriched using the Ingenuity Pathway Analysis software by QUIGEN. These enriched pathways included acetone degradation I, xenobiotic metabolism signaling, cholesterol biosynthesis, retinol biosynthesis, p53 signaling and RXR activation. All identified pathways were then visualized in Cytoscape to create a biochemical network of biochemical events related to hepatic lipid dysfunction. The enrichment and clarification of the pathways and networks from the DEGs related to hepatic lipid dysfunction provide knowledge that can be used to understand the underlying molecular mechanism and assist in the development of putative Adverse Outcome Pathways for hepatic steatosis. This abstract does not necessarily reflect U.S. EPA policy.