Evaluation of Database-Derived Pathway Development for Enabling Biomarker Discovery for Hepatotoxicity

Abstract

Current testing models for predicting drug-induced liver injury are inadequate, as they basically under-report human health risks. We present here an approach towards developing pathways based on hepatotoxicity-associated gene groups derived from two types of publicly accessible hepatotoxicity databases, in order to develop drug-induced liver injury biomarker profiles. One human liver ‘omics-based and four text-mining-based databases were explored for hepatotoxicity-associated gene lists. Over-representation analysis of these gene lists with a hepatotoxicant-exposed primary human hepatocytes data set showed that human liver ‘omics gene lists performed better than text-mining gene lists and the results of the latter differed strongly between databases. However, both types of databases contained gene lists demonstrating biomarker potential. Visualizing those in pathway format may aid in interpreting the biomolecular background. We conclude that exploiting existing and openly accessible databases in a dedicated manner seems promising in providing venues for translational research in toxicology and biomarker development.

KEYWORDS::

• ‘omics databases
• biomarker
• DILI
• diXa
• drug-induced liver injury
• hepatotoxicity
• over-representation analysis
• pathway development
• text-mining databases
• toxicogenomics

Acknowledgements

The authors would like to thank A Dutta from the Maastricht University BiGCaT department for her contributions to the data analysis.

Financial & competing interests disclosure

This work was supported by diXa, a part of the EU Seventh Framework Programme, under grant agreement number RI-283775. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

No writing assistance was utilized in the production of this manuscript.

Additional information

Funding

This work was supported by diXa, a part of the EU Seventh Framework Programme, under grant agreement number RI-283775. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.