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Probable Treatment Targets for Diabetic Retinopathy Based on an Integrated Proteomic and Genomic Analysis

PURPOSE: Using previously approved medications for new indications can expedite the lengthy and expensive drug development process. We describe a bioinformatics pipeline that integrates genomics and proteomics platforms to identify already-approved drugs that might be useful to treat diabetic retino...

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Autores principales: Valdivia, Anddre Osmar, He, Ye, Ren, Xinjun, Wen, Dejia, Dong, Lijie, Nazari, Hossein, Li, Xiaorong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Association for Research in Vision and Ophthalmology 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9910385/
https://www.ncbi.nlm.nih.gov/pubmed/36745438
http://dx.doi.org/10.1167/tvst.12.2.8
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author Valdivia, Anddre Osmar
He, Ye
Ren, Xinjun
Wen, Dejia
Dong, Lijie
Nazari, Hossein
Li, Xiaorong
author_facet Valdivia, Anddre Osmar
He, Ye
Ren, Xinjun
Wen, Dejia
Dong, Lijie
Nazari, Hossein
Li, Xiaorong
author_sort Valdivia, Anddre Osmar
collection PubMed
description PURPOSE: Using previously approved medications for new indications can expedite the lengthy and expensive drug development process. We describe a bioinformatics pipeline that integrates genomics and proteomics platforms to identify already-approved drugs that might be useful to treat diabetic retinopathy (DR). METHODS: Proteomics analysis of vitreous humor samples from 12 patients undergoing pars plana vitrectomy for DR and a whole genome dataset (UKBiobank TOPMed-imputed) from 1330 individuals with DR and 395,155 controls were analyzed independently to identify biological pathways associated with DR. Common biological pathways shared between both datasets were further analyzed (STRING and REACTOME analyses) to identify target proteins for probable drug modulation. Curated target proteins were subsequently analyzed by the BindingDB database to identify chemical compounds they interact with. Identified chemical compounds were further curated through the Expasy SwissSimilarity database for already-approved drugs that interact with target proteins. RESULTS: The pathways in each dataset (proteomics and genomics) converged in the upregulation of a previously unknown pathway involved in DR (RUNX2 signaling; constituents MMP-13 and LGALS3), with an emphasis on its role in angiogenesis and blood–retina barrier. Bioinformatics analysis identified U.S. Food and Drug Administration (FDA)-approved medications (raltitrexed, pemetrexed, glyburide, probenecid, clindamycin hydrochloride, and ticagrelor) that, in theory, may modulate this pathway. CONCLUSIONS: The bioinformatics pipeline described here identifies FDA-approved drugs that can be used for new alternative indications. These theoretical candidate drugs should be validated with experimental studies. TRANSLATIONAL RELEVANCE: Our study suggests possible drugs for DR treatment based on an integrated proteomics and genomics pipeline. This approach can potentially expedite the drug discovery process by identifying already-approved drugs that might be used for new indications.
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spelling pubmed-99103852023-02-10 Probable Treatment Targets for Diabetic Retinopathy Based on an Integrated Proteomic and Genomic Analysis Valdivia, Anddre Osmar He, Ye Ren, Xinjun Wen, Dejia Dong, Lijie Nazari, Hossein Li, Xiaorong Transl Vis Sci Technol Retina PURPOSE: Using previously approved medications for new indications can expedite the lengthy and expensive drug development process. We describe a bioinformatics pipeline that integrates genomics and proteomics platforms to identify already-approved drugs that might be useful to treat diabetic retinopathy (DR). METHODS: Proteomics analysis of vitreous humor samples from 12 patients undergoing pars plana vitrectomy for DR and a whole genome dataset (UKBiobank TOPMed-imputed) from 1330 individuals with DR and 395,155 controls were analyzed independently to identify biological pathways associated with DR. Common biological pathways shared between both datasets were further analyzed (STRING and REACTOME analyses) to identify target proteins for probable drug modulation. Curated target proteins were subsequently analyzed by the BindingDB database to identify chemical compounds they interact with. Identified chemical compounds were further curated through the Expasy SwissSimilarity database for already-approved drugs that interact with target proteins. RESULTS: The pathways in each dataset (proteomics and genomics) converged in the upregulation of a previously unknown pathway involved in DR (RUNX2 signaling; constituents MMP-13 and LGALS3), with an emphasis on its role in angiogenesis and blood–retina barrier. Bioinformatics analysis identified U.S. Food and Drug Administration (FDA)-approved medications (raltitrexed, pemetrexed, glyburide, probenecid, clindamycin hydrochloride, and ticagrelor) that, in theory, may modulate this pathway. CONCLUSIONS: The bioinformatics pipeline described here identifies FDA-approved drugs that can be used for new alternative indications. These theoretical candidate drugs should be validated with experimental studies. TRANSLATIONAL RELEVANCE: Our study suggests possible drugs for DR treatment based on an integrated proteomics and genomics pipeline. This approach can potentially expedite the drug discovery process by identifying already-approved drugs that might be used for new indications. The Association for Research in Vision and Ophthalmology 2023-02-06 /pmc/articles/PMC9910385/ /pubmed/36745438 http://dx.doi.org/10.1167/tvst.12.2.8 Text en Copyright 2023 The Authors https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License.
spellingShingle Retina
Valdivia, Anddre Osmar
He, Ye
Ren, Xinjun
Wen, Dejia
Dong, Lijie
Nazari, Hossein
Li, Xiaorong
Probable Treatment Targets for Diabetic Retinopathy Based on an Integrated Proteomic and Genomic Analysis
title Probable Treatment Targets for Diabetic Retinopathy Based on an Integrated Proteomic and Genomic Analysis
title_full Probable Treatment Targets for Diabetic Retinopathy Based on an Integrated Proteomic and Genomic Analysis
title_fullStr Probable Treatment Targets for Diabetic Retinopathy Based on an Integrated Proteomic and Genomic Analysis
title_full_unstemmed Probable Treatment Targets for Diabetic Retinopathy Based on an Integrated Proteomic and Genomic Analysis
title_short Probable Treatment Targets for Diabetic Retinopathy Based on an Integrated Proteomic and Genomic Analysis
title_sort probable treatment targets for diabetic retinopathy based on an integrated proteomic and genomic analysis
topic Retina
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9910385/
https://www.ncbi.nlm.nih.gov/pubmed/36745438
http://dx.doi.org/10.1167/tvst.12.2.8
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