Carolyn J. Mattingly, Ph.D.
North Carolina State University
An NIEHS grantee and colleagues combined gene data from the Gene Ontology (GO) database with information on gene-disease interactions from the Comparative Toxicogenomics Database (CTD) to uncover potential biological similarities between seemingly unrelated diseases. Identifying commonalities among disparate diseases can reveal the biological underpinnings of diseases, pointing toward new therapeutics and diseases that might benefit from existing pharmaceuticals.
CTD is a public database that contains manually curated and coded data from scientific research papers that describe chemical-gene, chemical-disease, and gene-disease interactions. By combining CTD information on genes known to be associated with diseases and GO’s gene data, researchers were able to identify inferred relationships. For example, if gene A is tied to biological process B in GO, and gene A is independently linked with disease C in CTD, then the integrated datasets would show an inferred relationship between biological process B and disease C via gene A.
The researchers produced a resource linking over 15,000 GO annotations to 4,200 human diseases, giving them the ability to detect similarities in biological activities and processes. Using this resource, they discovered and ranked 39 drugs that may be potential therapies for treating chronic B-cell leukemia.
Citation: Davis AP, Wiegers TC, King BL, Wiegers J, Grondin CJ, Sciaky D, Johnson RJ, Mattingly CJ. 2016. Generating gene ontology-disease inferences to explore mechanisms of human disease at the Comparative Toxicogenomics Database. PLoS One 11(5):e0155530.