Integrated bioinformatics-based identification of proliferative diabetic retinopathy and idiopathic pulmonary fibrosis: Focus on fibrosis and immune infiltration

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Authors: Juanhui Cao, Fangyuan Dong, Xianfeng Li, Xuechun Zhu
Cited by: 0
References: 57

Abstract

Proliferative diabetic retinopathy (PDR) and idiopathic pulmonary fibrosis (IPF) share the common pathological feature of fibrosis, but the connecting mechanisms are not well - understood. This study aimed to identify potential shared genes and therapeutic drug candidates for fibrosis in both conditions by analyzing transcriptome datasets from the Gene Expression Omnibus (GEO). Differential expression analysis of two training datasets revealed 90 fibrosis - related genes. These genes were then analyzed for gene function enrichment, protein - protein interaction (PPI), transcription factor (TF) network, immune cell infiltration, and drug prediction. The findings underscored the role of immune activation in fibrosis progression. Among the 13 identified hub genes, however, six demonstrated strong correlations and high diagnostic potential upon further validation. The study also pinpointed six drug molecules with significant enrichment values, three of which showed promising results in blind docking simulations. These six genes and three drug molecules serve as potential targets for diagnosing and treating fibrosis in both PDR and IPF, though additional research is necessary to confirm their clinical utility.

Fields of Study & Subjects

Bioinformatics and Genomic Networks Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis Computational Drug Discovery Methods

Publication details

Journal / source
PLoS ONE
Volume
21
Issue
2
Pages
e0343398–e0343398
Publication date
23 February 2026
Language
EN