Identification of SDC1 as a Key Regulator and Therapeutic Target in Rheumatoid Arthritis via JAK2‐STAT3 Pathway

TL;DR

This study identifies SDC1 as a key gene in rheumatoid arthritis, showing it drives disease progression through the JAK2-STAT3 pathway and could be a new treatment target.

Contribution

The novel integration of bioinformatics and machine learning identifies SDC1 as a central regulator of rheumatoid arthritis via the JAK2-STAT3 pathway.

Findings

SDC1 was identified as a hub gene in rheumatoid arthritis using multiple machine learning methods.

SDC1 promotes RA progression by activating the JAK2-STAT3 signaling pathway.

Targeting SDC1 may offer a new diagnostic and therapeutic approach for rheumatoid arthritis.

Abstract

Rheumatoid arthritis (RA) is a chronic autoimmune disorder with unclear molecular mechanisms, complicating early diagnosis and treatment. This study aimed to identify hub genes and pathways driving RA pathogenesis and assess their therapeutic potential.

Gene expression datasets related to RA were retrieved from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified and analyzed by functional enrichment and protein–protein interaction network construction. Machine learning approaches, including LASSO regression, random forest, and SVM‐RFE, were used to screen hub genes. Pathway associations were explored using Gene Set Enrichment Analysis (GSEA). Experimental validation was performed in collagen‐induced arthritis (CIA) rat models and MH7A synovial fibroblast cells through Western blot and functional assays.

A total of 106 DEGs were identified in RA synovial tissues, including 76 upregulated and 30 downregulated genes. Enrichment analyses revealed involvement in cytokine–cytokine receptor interaction, lymphocyte‐mediated immunity, and immunoglobulin complexes. SDC1 emerged as a key hub gene across all three machine learning methods. GSEA indicated its significant correlation with the JAK–STAT pathway. In CIA rats, SDC1 expression was markedly elevated alongside p‐JAK2 and p‐STAT3 levels. Silencing SDC1 in MH7A cells reduced cell proliferation, decreased p‐JAK2 and p‐STAT3 expression, and promoted apoptosis.

This study identifies SDC1 as a central hub gene in RA pathogenesis through activation of the JAK2–STAT3 signaling pathway. These findings highlight SDC1 as a potential biomarker for early diagnosis and a promising target for therapeutic intervention, providing new insights into RA management.

SDC1 identified as a key hub gene in RA by integrated bioinformatics and machine learning.SDC1 promotes RA progression via activation of the JAK2–STAT3 pathway.Targeting SDC1 may provide a novel diagnostic and therapeutic strategy for RA.

SDC1 identified as a key hub gene in RA by integrated bioinformatics and machine learning.

SDC1 promotes RA progression via activation of the JAK2–STAT3 pathway.

Targeting SDC1 may provide a novel diagnostic and therapeutic strategy for RA.

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