Turning genome-wide association study findings into opportunities for drug repositioning

Computational and Structural Biotechnology Journal
Alexandria LAU, Hon-Cheong So

Abstract

Drug development is a very costly and lengthy process, while repositioned or repurposed drugs could be brought into clinical practice within a shorter time-frame and at a much reduced cost. Numerous computational approaches to drug repositioning have been developed, but methods utilizing genome-wide association studies (GWASs) data are less explored. The past decade has observed a massive growth in the amount of data from GWAS; the rich information contained in GWAS has great potential to guide drug repositioning or discovery. While multiple tools are available for finding the most relevant genes from GWAS hits, searching for top susceptibility genes is only one way to guide repositioning, which has its own limitations. Here we provide a comprehensive review of different computational approaches that employ GWAS data to guide drug repositioning. These methods include selecting top candidate genes from GWAS as drug targets, deducing drug candidates based on drug-drug and disease-disease similarities, searching for reversed expression profiles between drugs and diseases, pathway-based methods as well as approaches based on analysis of biological networks. Each method is illustrated with examples, and their respective strengths an...Continue Reading

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Citations

Apr 16, 2021·Cardiovascular Drugs and Therapy·Haocheng LuMinerva T Garcia-Barrio
Aug 28, 2021·Seminars in Cell & Developmental Biology·Tayaza FadasonWilliam Schierding
Oct 26, 2021·Future Microbiology·Amanda M MalacridaTerezinha Ie Svidzinski

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Datasets Mentioned

BETA
GEUVADIS

Methods Mentioned

BETA
chips
in silico methods
FAIRE-seq
ChIP-seq
RNA-seq

Software Mentioned

modENCODE
Connectivity Map ( CMap )
PAINTOR
FUMA
PREDICT
SNPinfo
CMap
MetaCore
MetaBase
ENCODE

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