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Computational drug repurposing for inflammatory bowel disease using genetic information

As knowledge of the genetics behind inflammatory bowel disease (IBD) has continually improved, there has been a demand for methods that can use this data in a clinically significant way. Genome-wide association analyses for IBD have identified 232 risk genetic loci for the disorder. While identifica...

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Autores principales: Grenier, Liam, Hu, Pingzhao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6352300/
https://www.ncbi.nlm.nih.gov/pubmed/30728920
http://dx.doi.org/10.1016/j.csbj.2019.01.001
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author Grenier, Liam
Hu, Pingzhao
author_facet Grenier, Liam
Hu, Pingzhao
author_sort Grenier, Liam
collection PubMed
description As knowledge of the genetics behind inflammatory bowel disease (IBD) has continually improved, there has been a demand for methods that can use this data in a clinically significant way. Genome-wide association analyses for IBD have identified 232 risk genetic loci for the disorder. While identification of these risk loci enriches our understanding of the underlying biology of the disorder, their identification does not serve a clinical purpose. A potential use of this genetic information is to look for potential IBD drugs that target these loci in a procedure known as drug repurposing. The demand for new drug treatments for IBD is high due to the side effects and high costs of current treatments. We hypothesize that IBD genetic variants obtained from GWAS and the candidate genes prioritized from the variants have a causal relationship with IBD drug targets. A computational drug repositioning study was done due to its efficiency and inexpensiveness compared to traditional in vitro or biochemical approaches. Our approach for drug repurposing was multi-layered; it not only focused on the interactions between drugs and risk IBD genes, but also the interactions between drugs and all of the biological pathways the risk genes are involved in. We prioritized IBD candidate genes using identified genetic variants and identified potential drug targets and drugs that can be potentially repositioned or developed for IBD using the identified candidate genes. Our analysis strategy can be applied to repurpose drugs for other complex diseases using their risk genes identified from genetic analysis.
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spelling pubmed-63523002019-02-06 Computational drug repurposing for inflammatory bowel disease using genetic information Grenier, Liam Hu, Pingzhao Comput Struct Biotechnol J Research Article As knowledge of the genetics behind inflammatory bowel disease (IBD) has continually improved, there has been a demand for methods that can use this data in a clinically significant way. Genome-wide association analyses for IBD have identified 232 risk genetic loci for the disorder. While identification of these risk loci enriches our understanding of the underlying biology of the disorder, their identification does not serve a clinical purpose. A potential use of this genetic information is to look for potential IBD drugs that target these loci in a procedure known as drug repurposing. The demand for new drug treatments for IBD is high due to the side effects and high costs of current treatments. We hypothesize that IBD genetic variants obtained from GWAS and the candidate genes prioritized from the variants have a causal relationship with IBD drug targets. A computational drug repositioning study was done due to its efficiency and inexpensiveness compared to traditional in vitro or biochemical approaches. Our approach for drug repurposing was multi-layered; it not only focused on the interactions between drugs and risk IBD genes, but also the interactions between drugs and all of the biological pathways the risk genes are involved in. We prioritized IBD candidate genes using identified genetic variants and identified potential drug targets and drugs that can be potentially repositioned or developed for IBD using the identified candidate genes. Our analysis strategy can be applied to repurpose drugs for other complex diseases using their risk genes identified from genetic analysis. Research Network of Computational and Structural Biotechnology 2019-01-07 /pmc/articles/PMC6352300/ /pubmed/30728920 http://dx.doi.org/10.1016/j.csbj.2019.01.001 Text en © 2019 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Research Article
Grenier, Liam
Hu, Pingzhao
Computational drug repurposing for inflammatory bowel disease using genetic information
title Computational drug repurposing for inflammatory bowel disease using genetic information
title_full Computational drug repurposing for inflammatory bowel disease using genetic information
title_fullStr Computational drug repurposing for inflammatory bowel disease using genetic information
title_full_unstemmed Computational drug repurposing for inflammatory bowel disease using genetic information
title_short Computational drug repurposing for inflammatory bowel disease using genetic information
title_sort computational drug repurposing for inflammatory bowel disease using genetic information
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6352300/
https://www.ncbi.nlm.nih.gov/pubmed/30728920
http://dx.doi.org/10.1016/j.csbj.2019.01.001
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