medRxivGenetic & Genomic MedicinePreprint
A genetics-guided integrative framework for drug repurposing: identifying antihypertensive drug telmisartan for type 2 diabetes
Xue Yun ZhongiD, Qiang WeiiD, Anshul TiwariiD, Quan WangiD, Yuting J. TaniD, Rui CheniD, Yan YaniD, Nancy Jean CoxiD, Bingshan LiiD
Abstract
Drug development is a long and costly process, and repurposing existing drugs for use toward a different disease or condition may serve as a cost-effective alternative. As drug targets with genetic support have a doubled success rate, genetics-informed drug repurposing holds promise in translating genetic findings into therapeutics. In this study, we developed a Genetics Informed Network-based Drug Repurposing via in silico Perturbation (GIN-DRIP) framework and applied the framework to repurpose drugs for type-2 diabetes (T2D). In GIN-DRIP for T2D, it integrates multi-level omics data to translate T2D GWAS signals into a genetics-informed network that simultaneously encodes gene importance scores and a directional effect (up/down) of risk genes for T2D; it then bases on the GIN to perform signature matching with drug perturbation experiments to identify drugs that can counteract the effect of T2D risk alleles. With this approach, we identified 3 high-confidence FDA-approved candidate drugs for T2D, and validated telmisartan, an anti-hypertensive drug, in our EHR data with over 3 million patients. We found that telmisartan users were associated with a reduced incidence of T2D compared to users of other anti-hypertensive drugs and non-users, supporting the therapeutic potential of telmisartan for T2D. Our framework can be applied to other diseases for translating GWAS findings to aid drug repurposing for complex diseases.
- organism: human
- assay: GWAS summary statistics
- assay: electronic health records
- research focus: drug response / drug discovery
- research focus: benchmarking
- research focus: database / resource
- research focus: software / tool
- approach: statistical model
- Citations
- 1
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