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Identifying gene variants underlying the pathogenesis of diabetic retinopathy based on integrated genomic and transcriptomic analysis of clinical extreme phenotypes.

ABSTRACT: Diabetic retinopathy (DR) is a common complication and the leading cause of blindness in patients with type 2 diabetes. DR has been shown to be closely correlated with blood glucose levels and the duration of diabetes. However, the onset and progression of DR also display clinical heterogeneity. We applied whole-exome sequencing and RNA-seq approaches to study the gene mutation and transcription profiles in three groups of diabetic patients with extreme clinical phenotypes in DR onset, timing, and disease progression, aiming to identify genetic variants that may play roles in the pathogenesis of DR. We identified 23 putatively pathogenic genes, and ingenuity pathway analysis of these mutated genes reveals their functional association with glucose metabolism, diabetic complications, neural system activity, and dysregulated immune responses. In addition, ten potentially protective genes were also proposed. These findings shed light on the mechanisms underlying the pathogenesis of DR and may provide potential targets for developing new strategies to combat DR.

SUBMITTER: Song Q

PROVIDER: S-EPMC9399422 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Identifying gene variants underlying the pathogenesis of diabetic retinopathy based on integrated genomic and transcriptomic analysis of clinical extreme phenotypes.

Song Qiaoling Q Zhang Yuchao Y Zhang Minghui M Ma Xiaoli X Zhang Qianyue Q Zhao Chenyang C Zhang Zhongwen Z Zhao Huichen H Hu Wenchao W Zhang Xinxin X Ren Xiwen X An Ming M Yang Jinbo J Liu Yuantao Y

Frontiers in genetics 20220810

Diabetic retinopathy (DR) is a common complication and the leading cause of blindness in patients with type 2 diabetes. DR has been shown to be closely correlated with blood glucose levels and the duration of diabetes. However, the onset and progression of DR also display clinical heterogeneity. We applied whole-exome sequencing and RNA-seq approaches to study the gene mutation and transcription profiles in three groups of diabetic patients with extreme clinical phenotypes in DR onset, timing, a ...[more]

PMID: 36035153

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Project description:PurposeUsing 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).MethodsProteomics 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.ResultsThe 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.ConclusionsThe 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 relevanceOur 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.

Dataset Information

Identifying gene variants underlying the pathogenesis of diabetic retinopathy based on integrated genomic and transcriptomic analysis of clinical extreme phenotypes.

Publications

Identifying gene variants underlying the pathogenesis of diabetic retinopathy based on integrated genomic and transcriptomic analysis of clinical extreme phenotypes.

Similar Datasets

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