ArticlePloS one2022
The integrated transcriptome bioinformatics analysis identifies key genes and cellular components for proliferative diabetic retinopathy.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 11 citations in OpenAlex.
- Inflammation-Mediated Immune Imbalance in the Pathogenesis of Diabetic Cataracts.Biomedicines · 2026Article
- Insight into dysregulated VEGF-related genes in diabetic retinopathy through bioinformatic analyses.Naunyn-Schmiedeberg's archives of pharmacology · 2025Article
- Insights into the molecular underpinning of type 2 diabetes complications.Human molecular genetics · 2025Review
- Single-cell sequencing in diabetic retinopathy: progress and prospects.Journal of translational medicine · 2025Review
- Transcriptomic Analysis and Finding of Potential Key mRNA Expression Profile in Human Cumulus Cells During in Vitro Culture and Different Passages Based on Integrated Bioinformatics Analysis.Reproductive sciences (Thousand Oaks, Calif.) · 2024Article
- Single-cell RNA sequencing in exploring the pathogenesis of diabetic retinopathy.Clinical and translational medicine · 2024Review
- Multi-omics in exploring the pathophysiology of diabetic retinopathy.Frontiers in cell and developmental biology · 2024Review
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Proliferative Diabetic Retinopathy (PDR) is a chronic complication of Diabetes and the main cause of blindness among the world's working population at present. While there have been many studies on the pathogenesis of PDR, its intrinsic molecular mechanisms have not yet been fully elucidated. In recent years, several studies have employed bulk RNA-sequencing (RNA-seq) and single-cell RNA sequencing (scRNA-seq) to profile differentially expressed genes (DEGs) and cellular components associated with PDR. This study adds to this expanding body of work by identifying PDR's target genes and cellular components by conducting an integrated transcriptome bioinformatics analysis. This study integrately examined two public bulk RNA-seq datasets(including 11 PDR patients and 7 controls) and one single-cell RNA-seq datasets(including 5 PDR patients) of Fibro (Vascular) Membranes (FVMs) from PDR patients and control. A total of 176 genes were identified as DEGs between PDR patients and control among both bulk RNA-seq datasets. Based on these DEGs, 14 proteins were identified in the protein overlap within the significant ligand-receptor interactions of retinal FVMs and Protein-Protein Interaction (PPI) network, three of which were associated with PDR (CD44, ICAM1, POSTN), and POSTN might act as key ligand. This finding may provide novel gene signatures and therapeutic targets for PDR.
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