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

Anddre Osmar Valdivia, Ye He, Xinjun Ren, Dejia Wen, Lijie Dong, Hossein Nazari, Xiaorong Li

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Purpose: Using previously approved medications for new indications can expedite the lengthy and expensive drug development process. We describe a bioinformat-ics 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 undergo-ing pars plana vitrectomy for DR and a whole genome dataset (UKBiobank TOPMed-imputed) from 1330 individuals with DR and 395,155 controls were analyzed indepen-dently 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 Adminis-tration (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.

Original languageEnglish (US)
Article number8
JournalTranslational Vision Science and Technology
Volume12
Issue number2
DOIs
StatePublished - Feb 2023

Bibliographical note

Funding Information:
Supported by grants from the Natural Science Foundation of Tianjin (19JCZDJC64000 to XL) and National Natural Science Foundation of China (82171085 to XL).

Publisher Copyright:
© 2023 The Authors.

Keywords

  • LGALS3
  • MMP-13
  • RUNX2
  • bioinformatics
  • diabetic retinopathy
  • drug discovery
  • genomics
  • proteomics

PubMed: MeSH publication types

  • Journal Article
  • Research Support, Non-U.S. Gov't

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