Integrative transcriptomic analysis identifies synovium-derived biomarkers for OA-related synovitis and builds a...

Area of Science:

• Genomics and Bioinformatics
• Immunology
• Molecular Biology

Background:

• Osteoarthritis (OA) is a degenerative joint disease characterized by inflammation of the synovial membrane (synovitis).
• Accurate diagnostic biomarkers for OA-related synovitis are crucial for effective management and treatment strategies.
• Current diagnostic methods may lack specificity and sensitivity in identifying early-stage or specific subtypes of OA synovitis.

Purpose of the Study:

• To identify and validate diagnostic biomarkers for osteoarthritis (OA)-related synovitis using synovial tissue gene expression data.
• To develop a predictive diagnostic nomogram for OA-related synovitis based on identified biomarkers.
• To explore the association between identified biomarkers, immune cell infiltration, and potential therapeutic targets.

Main Methods:

• Analysis of publicly available gene expression datasets (GEO) for synovial tissue from OA patients and controls.
• Application of weighted gene correlation network analysis (WGCNA) and machine learning models (SVM, RF, XGB, GLM) to identify differentially expressed genes and hub genes.
• Construction and validation of a multigene nomogram, followed by pathway analysis, immune profiling (ssGSEA), and molecular docking studies.

Main Results:

• A 5-gene signature (CTSH, ephrin-B2, YIPF2, ZNF671, SLC27A6) was identified as a robust diagnostic biomarker for OA-related synovitis.
• The developed nomogram demonstrated good diagnostic utility and calibration in both training and external validation datasets.
• OA synovium showed enriched immune pathways and increased infiltration of immune cells (B cells, macrophages, mast cells, T cells), with hub genes linked to immune signaling.

Conclusions:

• The 5-gene nomogram serves as a validated tool for diagnosing OA-related synovitis based on synovial tissue gene expression.
• The identified hub genes are associated with immune responses in OA synovitis, suggesting their role in disease pathogenesis.
• Molecular docking suggests potential interactions between identified biomarkers and anti-inflammatory drugs like dexamethasone and triamcinolone acetonide, warranting further investigation.