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

R. Hoehndorf, A. Oellrich, D. Rebholz-Schuhmann, P. N. Schofield, G. V. Gkoutos

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)388-399
Number of pages12
JournalPacific Symposium on Biocomputing. Proceedings.
Publication statusPublished - 2012


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