Systems level analysis and identification of pathways and networks associated with liver fibrosis

Abstract

Toxic liver injury causes necrosis and fibrosis, which may lead to cirrhosis and liver failure. Despite recent progress in mechanism of liver fibrosis, our knowledge of the molecular-level details of this disease is stillThe elucidation of networks and pathways associated with liver fibrosis can provide insight into the underlying of the disease, as well as identify potential diagnostic or prognostic biomarkers. Towards this end, rat gene expression data from a range of chemical exposures that produced observable periportal liver fibrosis in DrugMatrix, a publicly available toxicogenomics database. We identified genes relevant to liver fibrosis differential expression and co-expression analyses, and then used these genes in pathway enrichment andprotein interaction (PPI) network analyses. We identified a PPI network module associated with liver fibrosis that liver fibrosis-relevant genes, such as tissue inhibitor of metalloproteinase-1, galectin-3, connective tissue, and lipocalin-2. We also identified several new genes, such as perilipin-3, legumain, and myocilin, which were liver fibrosis. We further analyzed the expression pattern of the genes in the PPI network module across a of 640 chemical exposure conditions in DrugMatrix and identified early indications of liver fibrosis for carbon lipopolysaccharide exposures. Although it is well known that carbon tetrachloride and lipopolysaccharide liver fibrosis, our network analysis was able to link these compounds to potential fibrotic damage before associated with liver fibrosis appeared. These results demonstrated that our approach is capable early-stage indicators of liver fibrosis and underscore its potential to aid in predictive toxicity, biomarkerand to generally identify disease-relevant pathways.