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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Association for Research in Vision and Ophthalmology
2023
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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. |
format | Online Article Text |
id | pubmed-9910385 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | The Association for Research in Vision and Ophthalmology |
record_format | MEDLINE/PubMed |
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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