Evidence mapPaperPMID 39968099Full record

ArticleJournal of inflammation research2025

Identifying Therapeutic Targets and Potential Drugs for Diabetic Retinopathy: Focus on Oxidative Stress and Immune Infiltration.

Hongsong Peng, Qiang Hu, Xue Zhang, Jiayang Huang, Shan Luo, Yiming Zhang, Bo Jiang, Dawei Sun

Abstract read
In one paragraph

Article in Journal of inflammation research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Hongsong Peng *Department of Ophthalmology, The second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, People's Republic of China.ORCID 0009-0000-7807-6214
Qiang Hu *Department of Ophthalmology, The second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, People's Republic of China.
Xue Zhang *Department of Ophthalmology, The second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, People's Republic of China.
Jiayang HuangDepartment of Ophthalmology, The second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, People's Republic of China.ORCID 0009-0000-4219-6281
Shan LuoDepartment of Ophthalmology, The second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, People's Republic of China.
Yiming ZhangDepartment of Ophthalmology, The second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, People's Republic of China.
Bo JiangDepartment of Ophthalmology, The second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, People's Republic of China.
Dawei SunDepartment of Ophthalmology, The second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, People's Republic of China.ORCID 0000-0002-9717-0190

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Diabetic retinopathy (DR), a microvascular disorder linked to diabetes, is on the rise globally. Oxidative stress and immune cell infiltration are linked to illness initiation and progression, according to recent study. This study investigated biomarkers connected to DR and oxidative stress and their connection with immune cell infiltration using bioinformatics analysis and found possible therapeutic medications. Methods: The Gene Expression Omnibus (GEO) database was used to obtain the gene expression data for DR. Differentially expressed genes (DEGs) and oxidative stress (OS)-related genes were intersected. The Enrichment analyses concentrate on OS-related differentially expressed genes (DEOSGs). Analysis of protein-protein interaction (PPI) networks and machine learning algorithms were used to identify hub genes. Single-gene Gene Set Enrichment Analysis (GSEA) identified biological functions, while nomograms and ROC curves assessed diagnostic potential. Immune infiltration analysis and regulatory networks were constructed. Drug prediction was validated through molecular docking, and hub gene expression was confirmed in dataset and animal models. Results: Compared to the control group, 91 DEOSGs were found. Enrichment analyses showed that these DEOSGs were largely connected to oxidative stress response, PI3K/Akt pathway, inflammatory pathways, and immunological activation. Four hub genes were found via PPI networks and machine learning. These hub genes were diagnostically promising according to nomogram and ROC analysis. Analysis of immune cell infiltration highlighted the role of immune cells. Gene regulatory networks for transcription factor (TF) and miRNA were created. Using structural data, molecular docking shows potential drugs and hub genes have high binding affinity. Dataset analysis, Real-Time Quantitative Polymerase Chain Reaction (RT-qPCR) and Western Blot (WB) confirmed the CCL4 expression difference between DR and controls. Conclusion: CCL4 was identified as potential oxidative stress-related biomarker in DR, providing new insights for DR diagnosis and treatment.

Indexed as

diabetic retinopathyhub genesimmune infiltrationmolecular dockingoxidative stress

Identifiers

PMID39968099
PMCPMC11834741

What Socratic holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.