Research Article: Drug Repositioning for Diabetes Based on ‘Omics’ Data Mining

Date Published: May 6, 2015

Publisher: Public Library of Science

Author(s): Ming Zhang, Heng Luo, Zhengrui Xi, Ekaterina Rogaeva, Ramasamy Paulmurugan.

http://doi.org/10.1371/journal.pone.0126082

Abstract

Drug repositioning has shorter developmental time, lower cost and less safety risk than traditional drug development process. The current study aims to repurpose marketed drugs and clinical candidates for new indications in diabetes treatment by mining clinical ‘omics’ data. We analyzed data from genome wide association studies (GWAS), proteomics and metabolomics studies and revealed a total of 992 proteins as potential anti-diabetic targets in human. Information on the drugs that target these 992 proteins was retrieved from the Therapeutic Target Database (TTD) and 108 of these proteins are drug targets with drug projects information. Research and preclinical drug targets were excluded and 35 of the 108 proteins were selected as druggable proteins. Among them, five proteins were known targets for treating diabetes. Based on the pathogenesis knowledge gathered from the OMIM and PubMed databases, 12 protein targets of 58 drugs were found to have a new indication for treating diabetes. CMap (connectivity map) was used to compare the gene expression patterns of cells treated by these 58 drugs and that of cells treated by known anti-diabetic drugs or diabetes risk causing compounds. As a result, 9 drugs were found to have the potential to treat diabetes. Among the 9 drugs, 4 drugs (diflunisal, nabumetone, niflumic acid and valdecoxib) targeting COX2 (prostaglandin G/H synthase 2) were repurposed for treating type 1 diabetes, and 2 drugs (phenoxybenzamine and idazoxan) targeting ADRA2A (Alpha-2A adrenergic receptor) had a new indication for treating type 2 diabetes. These findings indicated that ‘omics’ data mining based drug repositioning is a potentially powerful tool to discover novel anti-diabetic indications from marketed drugs and clinical candidates. Furthermore, the results of our study could be related to other disorders, such as Alzheimer’s disease.

Partial Text

Diabetes mellitus is one of the most prevalent diseases in the world, affecting approximately 382 million people around the world in 2013, costing at least $548 billion in 2013 according to the international diabetes federation (IDF). Diabetic drug safety is a big concern during the development of new drugs. Avandia from GSK, for example, was found to be associated with risk of heart attack [1], resulting in a recommendation of suspension by European Medicines Agency (EMA) in 2010. Aleglitazar from Roche, a Peroxisome proliferator-activated receptor gamma (PPARG) agonist, was terminated in phase III clinical trial in 2013 due to safety concerns for bone fractures, heart failure and gastrointestinal bleeding. Among the current diabetic drug developmental pipelines in leading pharmaceutical companies, 24 drugs have survived the early stages of drug development (phase I, II clinical trials) and are now in phase III clinical trials or post-market surveillance. Among the 24 drugs, 17 (71%) are incretin analogs, DPP4-inhibitors or insulin analogs (S1 Table). However, the association between incretin therapy and risk of pancreatitis and cancer is still uncertain and under investigations by the FDA and EMA [2]. It has been long recognized that the traditional drug development process requires a lot of time (10–17 years) and is extremely costly, but has a low success rate (< 10%) and high safety risk. Therefore, novel strategies are needed for developing novel diabetic drugs in a more efficient way with lower safety risks. Using ‘omics’ data mining and pathogenesis information, the current study repurposed 58 drugs for potential diabetes treatment. Gene expression profile comparison indicated 9 drugs with a higher potential in treating diabetes.   Source: http://doi.org/10.1371/journal.pone.0126082