Linking PharmGKB to phenotype studies and animal models of disease for drug repurposing

Pac Symp Biocomput. 2012:388-99.


The investigation of phenotypes in model organisms has the potential to reveal the molecular mechanisms underlying disease. The large-scale comparative analysis of phenotypes across species can reveal novel associations between genotypes and diseases. We use the PhenomeNET network of phenotypic similarity to suggest genotype-disease association, combine them with drug-gene associations available from the PharmGKB database, and infer novel associations between drugs and diseases. We evaluate and quantify our results based on our method's capability to reproduce known drug-disease associations. We find and discuss evidence that levonorgestrel, tretinoin and estradiol are associated with cystic fibrosis (p < 2.65 · 10(-6), p < 0.002 and p < 0.031, Wilcoxon signed-rank test, Bonferroni correction) and that ibuprofen may be active in chronic lymphocytic leukemia (p < 2.63 · 10(-23), Wilcoxon signed-rank test, Bonferroni correction). To enable access to our results, we implement a web server and make our raw data freely available. Our results are the first steps in implementing an integrated system for the analysis and prediction of drug-disease associations for rare and orphan diseases for which the molecular basis is not known.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Computational Biology
  • Databases, Factual
  • Databases, Genetic
  • Disease / genetics
  • Disease Models, Animal
  • Drug Discovery / statistics & numerical data
  • Humans
  • Knowledge Bases*
  • Pharmacogenetics / statistics & numerical data*
  • Phenotype