Shared M0 macrophage infiltration-related gene signatures in osteoarthritis and osteomyelitis by integrating bulk and single-cell RNA transcriptome.

backgroundOsteoarthritis (OA) and osteomyelitis (OM) are prevalent orthopedic diseases, characterized by complex immune and inflammatory responses that impact bone regeneration. Macrophages play a crucial role in the immune regulation of osteoblast function, with M0 macrophages polarizing toward M1 and M2 phenotypes, influencing pro-inflammatory or anti-inflammatory responses. Despite evidence linking M0 macrophages with inflammation in OA and OM, the underlying pathogenic and immune regulatory mechanisms remain unclear.

methodsTo examine the immune microenvironment in OA and OM, we analyzed 6 OA datasets and 3 OM datasets from the GEO database. Shared M0 macrophages-related differentially Expressed Genes (M0R-DEGs) in OA and OM were identified by differential expression analysis, immune cell infiltration analysis, and correlation analysis. Characteristic M0R-DEGs were selected through random forest (RF), support vector machine-recursive feature elimination (SVM-RFE) and least absolute shrinkage and selection operator (LASSO) regression model. Subsequently, diagnostic models and molecular subtypes for OA and OM were established, further exploring the differences in M0R-molecular patterns and immune infiltration. In addition, the distribution, potential biological functions, and pathways of OA synovial cell types and M0R-DEGs were analyzed using scRNA datasets Finally, the expression of shared M0R-DEGs was validated through RT-qPCR and immunohistochemistry (IHC) staining.

resultsCombining immune infiltration analysis, correlation analysis, and machine learning models, five shared M0R-DEGs were identified, associated with the immune and metabolic processes of autoimmune diseases. Next, diagnostic models based on these genes were demonstrated to have strong diagnostic performance for OA and OM in both training and validation sets, effectively distinguishing between disease and healthy samples. Subsequently, two different M0R molecular patterns were further constructed, with OA cluster 1 and OM cluster 2 associated with immune activation and inflammatory responses in OA and OM, respectively. In OA synovial samples, TIMP1 was downregulated in M2 macrophages and may be involved in the function of M2 macrophages by downregulating TNF-α and NF-κB signaling pathways. The expressions of MMP9 and SPARC in OA and OM rat models were consistent with bioinformatics findings, confirmed by RT-qPCR and IHC.

conclusionThis study identified five shared M0R-DEGs between OA and OM, linked to immune activation and response in various immune diseases. The diagnostic model revealed shared M0R-DEGs have good diagnostic efficacy, with significant differences in immune and inflammatory factors such as IL4 and MMP2 between the two molecular patterns. These findings may provide valuable insights for identifying potential shared biomarkers in OA and OM.