# Integrated network pharmacology and in vivo experiments to reveal the anti-inflammatory mechanism of Qinghuo Rougan Formula in uveitis

**Authors:** Changying Jing, Yaqi Sun, Hongsheng Bi, Junguo Guo, Cong Ren, Jike Song, Beibei Wang, Qingmei Tian, Dadong Guo, Pengjuan He, Lijie Li, Xiaofeng Xie

PMC · DOI: 10.3389/fmolb.2025.1632027 · Frontiers in Molecular Biosciences · 2025-07-11

## TL;DR

This study explores how Qinghuo Rougan Formula treats uveitis by combining network pharmacology and in vivo experiments to identify key anti-inflammatory targets and pathways.

## Contribution

The study integrates network pharmacology and in vivo validation to uncover the anti-inflammatory mechanism of a traditional Chinese medicine in treating uveitis.

## Key findings

- QHRGF targets 18 genes and immune/inflammation-related pathways linked to uveitis.
- Six hub genes were identified as potential biomarkers for uveitis using LASSO and WGCNA.
- In vivo experiments confirmed QHRGF's anti-inflammatory effects in uveitis.

## Abstract

Uveitis is a complex intraocular inflammatory disease and pathology results from the continuous production of proinflammatory cytokines in the optical axis. Qinghuo Rougan Formula (QHRGF), a traditional Chinese medicine (TCM) is now used to treat uveitis with desirable effect. However, the mechanism of action is still unclear. This study aimed to explore the potential diagnostic and therapeutic biomarkers for uveitis using systems biology methods, including network pharmacology and weighted gene co-expression network analysis (WGCNA).

A molecular drug-compound-target-uveitis interaction network was established using network pharmacology. Functional enrichment analyses were performed to screen potential signaling pathways. The uveitis gene expression dataset from the Gene Expression Omnibus database was subjected to WGCNA to identify gene co-expression modules related to uveitis and explore the potential hub genes. The least absolute shrinkage and selection operator (LASSO) model was used to identify the hub genes. Additionally, molecular docking was performed to verify the accuracy and stability of the model. Finally, the suppressive effects of QHRGF on uveitis were experimentally verified in vivo.

Network pharmacology and functional enrichment analysis showed that 18 targets and immune/inflammation-related pathways were associated with the QHRGF-targeted pathway network. The yellow module contained 120 genes had a strong correlation with uveitis using WGCNA. In total, 12 putative targets of QHRGF, differentially expressed genes, and yellow module genes were determined. Six hub genes were identified using LASSO model and the receiving operating characteristic curve analysis demonstrated the model can serve as biomarkers for uveitis. The advantages of these genes were approved using molecular docking. Finally, in vivo experiments provided evidence confirming that QHRGF was identified as the key target of the anti-inflammatory effect of uveitis.

In conclusion, this research revealed that QHRGF can be used to treat uveitis through multiple components and targets. Meanwhile, the potential anti-inflammatory action of QHRGF in the treatment of uveitis was verified by combining network pharmacology and in vivo experiments, suggesting its potential as a quite prospective agent for the therapy of uveitis.

## Linked entities

- **Diseases:** uveitis (MONDO:0020283)

## Full-text entities

- **Diseases:** intraocular (MESH:D064090), Uveitis (MESH:D014605), inflammation (MESH:D007249)

## Full text

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## Figures

8 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12289509/full.md

## References

41 references — full list in the complete paper: https://tomesphere.com/paper/PMC12289509/full.md

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Source: https://tomesphere.com/paper/PMC12289509