Screening of TNF signaling pathway-related genes in knee osteoarthritis (KOA) using WGCNA and machine learning

Area of Science:

• Biomedical Science
• Genomics
• Bioinformatics

Background:

• Knee osteoarthritis (KOA) is a widespread degenerative joint disease.
• Its pathogenesis involves intricate inflammatory responses and signal pathway dysregulation.
• The tumor necrosis factor (TNF) signaling pathway's role in KOA requires further elucidation.

Purpose of the Study:

• To investigate the mechanistic role of the TNF signaling pathway in KOA pathogenesis.
• To identify key genes and molecular mechanisms underlying KOA development.
• To provide insights for developing targeted therapies and precision medicine for KOA.

Main Methods:

• Differential gene expression analysis.
• Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses.
• Weighted gene co-expression network analysis (WGCNA).
• LASSO regression and Boruta algorithm for gene selection.
• Immune infiltration analysis.

Main Results:

• Identified 222 significantly differentially expressed genes in KOA.
• Enrichment analyses highlighted involvement in inflammatory responses and cytokine signaling.
• WGCNA identified a key module (MEbrown) associated with KOA.
• Selected 20 key TNF signaling pathway-related genes, including MCL1, JUN, and GADD45B, validated for classification.
• Observed significant differences in immune cell distribution in KOA samples.

Conclusions:

• The TNF signaling pathway plays a critical role in KOA pathogenesis.
• Specific genes like MCL1, JUN, and GADD45B are important regulators in KOA.
• Inflammation and immune cell infiltration are central to KOA progression.
• This research provides a foundation for personalized treatment strategies in KOA.