Gene expression and immune infiltration analysis comparing lesioned and preserved subchondral bone in osteoarthritis

Abstract

Background Osteoarthritis (OA) is a degenerative disease requiring additional research. This study compared gene expression and immune infiltration between lesioned and preserved subchondral bone. The results were validated using multiple tissue datasets and experiments. Methods Differentially expressed genes (DEGs) between the lesioned and preserved tibial plateaus of OA patients were identified in the GSE51588 dataset. Moreover, functional annotation and protein–protein interaction (PPI) network analyses were performed on the lesioned and preserved sides to explore potential therapeutic targets in OA subchondral bones. In addition, multiple tissues were used to screen coexpressed genes, and the expression levels of identified candidate DEGs in OA were measured by quantitative real-time polymerase chain reaction. Finally, an immune infiltration analysis was conducted. Results A total of 1,010 DEGs were identified, 423 upregulated and 587 downregulated. The biological process (BP) terms enriched in the upregulated genes included “skeletal system development”, “sister chromatid cohesion”, and “ossification”. Pathways were enriched in “Wnt signaling pathway” and “proteoglycans in cancer”. The BP terms enriched in the downregulated genes included “inflammatory response”, “xenobiotic metabolic process”, and “positive regulation of inflammatory response”. The enriched pathways included “neuroactive ligand–receptor interaction” and “AMP-activated protein kinase signaling”. JUN, tumor necrosis factor α, and interleukin-1β were the hub genes in the PPI network. Collagen XI A1 and leucine-rich repeat-containing 15 were screened from multiple datasets and experimentally validated. Immune infiltration analyses showed fewer infiltrating adipocytes and endothelial cells in the lesioned versus preserved samples. Conclusion Our findings provide valuable information for future studies on the pathogenic mechanism of OA and potential therapeutic and diagnostic targets.

Keywords

• Osteoarthritis
• Weighted gene co-expression network analysis (wgcna)
• Hub genes
• Transcriptional regulatory-immune network
• Multiple tissues