基于整合蛋白质组学和基因组学分析的糖尿病视网膜病变可能治疗靶点。

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

机构信息

Department of Ophthalmology and Visual Neuroscience, University of Minnesota Medical School, Minneapolis, MN, USA.

Tianjin Key Laboratory of Retinal Functions and Diseases, Tianjin Branch of National Clinical Research Center for Ocular Disease, Eye Institute and School of Optometry, Tianjin Medical University Eye Hospital, Tianjin, China.

出版信息

Transl Vis Sci Technol. 2023 Feb 1;12(2):8. doi: 10.1167/tvst.12.2.8.

DOI:10.1167/tvst.12.2.8

PMID:36745438

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9910385/

Abstract

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.

摘要

目的

将已批准的药物用于新的适应证可以加快漫长而昂贵的药物开发过程。我们描述了一个生物信息学管道，该管道整合了基因组学和蛋白质组学平台，以鉴定可能对治疗糖尿病性视网膜病变（DR）有用的已批准药物。

方法

对 12 例因 DR 接受玻璃体切除术的患者的玻璃体样本进行蛋白质组学分析，并对来自 1330 例 DR 患者和 395155 例对照者的全基因组数据集（UKBiobank TOPMed 推断）进行独立分析，以鉴定与 DR 相关的生物学途径。对两个数据集之间共有的常见生物学途径进行进一步分析（STRING 和 REACTOME 分析），以鉴定可能用于药物调节的靶蛋白。随后通过 BindingDB 数据库分析经过精心挑选的靶蛋白，以鉴定与其相互作用的化学化合物。进一步通过 Expasy SwissSimilarity 数据库对与靶蛋白相互作用的已批准药物进行已鉴定化学化合物的精选。

结果

每个数据集（蛋白质组学和基因组学）中的途径都集中在一个以前未知的与 DR 相关的途径上调，该途径涉及 RUNX2 信号转导；其成分包括 MMP-13 和 LGALS3），重点是其在血管生成和血液视网膜屏障中的作用。生物信息学分析鉴定出美国食品和药物管理局（FDA）批准的药物（雷替曲塞、培美曲塞、格列本脲、丙磺舒、盐酸克林霉素和替格瑞洛），理论上这些药物可以调节该途径。