Characterization of chemically induced liver injuries using gene co-expression modules

PLoS One. 2014 Sep 16;9(9):e107230. doi: 10.1371/journal.pone.0107230. eCollection 2014.


Liver injuries due to ingestion or exposure to chemicals and industrial toxicants pose a serious health risk that may be hard to assess due to a lack of non-invasive diagnostic tests. Mapping chemical injuries to organ-specific damage and clinical outcomes via biomarkers or biomarker panels will provide the foundation for highly specific and robust diagnostic tests. Here, we have used DrugMatrix, a toxicogenomics database containing organ-specific gene expression data matched to dose-dependent chemical exposures and adverse clinical pathology assessments in Sprague Dawley rats, to identify groups of co-expressed genes (modules) specific to injury endpoints in the liver. We identified 78 such gene co-expression modules associated with 25 diverse injury endpoints categorized from clinical pathology, organ weight changes, and histopathology. Using gene expression data associated with an injury condition, we showed that these modules exhibited different patterns of activation characteristic of each injury. We further showed that specific module genes mapped to 1) known biochemical pathways associated with liver injuries and 2) clinically used diagnostic tests for liver fibrosis. As such, the gene modules have characteristics of both generalized and specific toxic response pathways. Using these results, we proposed three gene signature sets characteristic of liver fibrosis, steatosis, and general liver injury based on genes from the co-expression modules. Out of all 92 identified genes, 18 (20%) genes have well-documented relationships with liver disease, whereas the rest are novel and have not previously been associated with liver disease. In conclusion, identifying gene co-expression modules associated with chemically induced liver injuries aids in generating testable hypotheses and has the potential to identify putative biomarkers of adverse health effects.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Algorithms
  • Animals
  • Biomarkers
  • Chemical and Drug Induced Liver Injury / diagnosis
  • Chemical and Drug Induced Liver Injury / genetics*
  • Chemical and Drug Induced Liver Injury / metabolism
  • Cluster Analysis
  • Computational Biology / methods
  • Databases, Genetic
  • Gene Expression Profiling*
  • Gene Expression*
  • Gene Regulatory Networks*
  • Humans
  • Rats
  • Reproducibility of Results
  • Signal Transduction
  • Transcriptome


  • Biomarkers

Grants and funding

The authors were supported by the Military Operational Medicine Research Program and the U.S. Army's Network Science Initiative, U.S. Army Medical Research and Materiel Command (, Ft. Detrick, MD. This research was supported in part by an appointment to the Postgraduate Research Participation Program at the U.S. Army Center for Environmental Health Research ( administered by the Oak Ridge Institute for Science and Education through an interagency agreement between the U.S. Department of Energy and USAMRMC. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.