Intervertebral disc degeneration (IDD) is widely regarded as the primary contributor to low back pain(LBP). As an immune-privileged organ, upon the onset of IDD, various components of the nucleus pulposus (NP) are exposed to the host’s immune system, accumulating cytokines. Cytokines facilitate intercellular communication within the immune system, induce immune cells polarisation, and exacerbate oxidative stress in IDD.
Machine learning was used to identify crucial immune cells. Subsequently, Immune Response Enrichment Analysis (IREA) was conducted on the key immune cells to determine their cytokine responses and polarisation states in IDD. “CellChat” package facilitated the analysis of cell-cell communication. Differential gene expression analysis, PPI network, GO and KEGG pathway enrichment analysis, GSVA, co-expressed gene analysis and key gene-related networks were also performed to explore hub genes and their associated functions. Lastly, the differential expression and functions of key genes were validated through
Through multiple machine learning methods, monocytes were identified as the crucial immune cells in IDD, exhibiting significant differentiation capacity. IREA revealed that monocytes in IDD polarize into an IFN-a1 and IFN-b enriched Mono-a state, potentially intensifying inflammation. Cell–cell communication analysis uncovered alteration in ANNEXIN pathway and a reduction in CXCL signaling between macrophages and monocytes, suggesting immune response dysregulation. Furthermore, ten algorithms identified three hub genes. Both experiments conducted
These findings offer a multidimensional understanding of the pathogenesis of IDD, pinpointing monocytes and key genes as potential diagnostic and therapeutic targets. They provide novel insights into potential diagnostic and therapeutic targets for IDD.