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Identification of differentially expressed genes and networks related to hepatic lipid dysfunction
Citation:
Abedini, J., S. Handa, S. Edwards, B. Chorley, AND H. El-Masri. Identification of differentially expressed genes and networks related to hepatic lipid dysfunction. TOXICOLOGY AND APPLIED PHARMACOLOGY. Academic Press Incorporated, Orlando, FL, 382:114757, (2019). https://doi.org/10.1016/j.taap.2019.114757
Impact/Purpose:
The National Research Council report entitled “Toxicity Testing in the 21st Century: A Vision and Strategy” set the foundations for a significant shift in chemical toxicity assessment away from in vivo testing toward in vitro methods based on pathways of biological function. The goal of this shift was to advance principles that could leverage increasing knowledge surrounding toxicological effects towards the challenge of increasing efficiency, reducing cost, and decreasing the number of animals used to determine potential of substances to adversely affect humans and the environment. Specifically, the report highlights the application of high-throughput toxicity testing (HTT) data to more apical adverse outcomes in the framework of adverse outcome pathways (AOPs). The applications of HTT data, and AOPs concepts to health risk assessment of chemical(s) exposure in view of the whole organism remains an outstanding challenge. This work illustrates the application of bioinformatics methods using publicly available large data sets to address this challenge by incorporating relevant absorption, distribution, metabolism and excretion (ADME) considerations to relate exposure to target tissue dosimetry to AO using in vitro to in vivo (IVIVE) extrapolations.
Description:
A range of chemical exposures that resulted in the specific pathology of hepatic lipid dysfunction in rats were selected from DrugMatrix, a publicly available toxicogenomic database. Raw microarray data collected from these exposures were further analyzed using bioinformatic tools to generate a differentially expressed genes (DEGs) dataset associated with hepatic lipid dysfunction. Further analysis of the DEGs dataset resulted in 324 upregulated genes, and 275 genes that were down regulated. Meanwhile, 36 genes were either up regulated or down regulated in different chemical treatments. All identified genes were uploaded in the web application for Database for Annotation, Visualization and Integrated Discovery (DAVID) for gene ontology enrichments and to identify Kyoto Encyclopedia of Genes and Genome (KEGG) pathways. Some of the identified pathways included glycolysis/gluconeogenesis, steroid hormone biosynthesis, retinol metabolism, and metabolism of xenobiotics by cytochrome P450. The same DEGs dataset was also analyzed using Ingenuity Pathway Analysis (IPA) software. IPA identified several pathways including PXR/RXR activation, Aryl hydrocarbon receptor signaling, and xenobiotic metabolism signaling. Furthermore, the generated DEGs lists were uploaded into NCATS BioPlanet platform. Some of the identified pathways were related to fatty acid omega oxidation, lipid and lipoprotein metabolism, and adipogenesis. The enrichment and clarification of the pathways and biological networks obtained from the DEGs dataset provide prior knowledge on the underlying biological key events and molecular mechanisms for the computational development of putative adverse outcome pathways (AOPs) for hepatic lipid dysfunction as a precursor to hepatic steatosis.
URLs/Downloads:
DOI: Identification of differentially expressed genes and networks related to hepatic lipid dysfunction
https://pubmed.ncbi.nlm.nih.gov/31520653/