Unraveling the pivotal role of cellular senescence genes in intervertebral disc degeneration: insights from bioinformatics analysis and experimental validation

Abstract Intervertebral disc degeneration (IVDD) is a complex age-related physiological change involving mainly cellular senescence (CS), inflammation, impaired tissue biomechanical function, and degradation of the extracellular matrix, and is a major cause of lumbar disc herniation and low back pain. Nonetheless, the specific role of CS and its associated genes in IVDD remains unclear. In this study, we first obtained 53 differentially expressed CS-related genes (CSRGs) by differential analyses of IVDD patients and non-IVDD patients from the GSE124272 and GSE150408 microarray expression datasets of the GEO database. We then performed GO and KEGG pathway enrichment analysis on these 53 CSRGs to explore their functions and pathways. To find the key genes from these 53 CSRGs, we first built a protein-protein interaction (PPI) network to recognize hub genes, and then on top of that we also applied the support vector machine recursive feature elimination (SVM-RFE) algorithm, random forest (RF) algorithm, and least absolute shrinkage and selection operator (LASSO) analysis. We finally obtained 4 hub CSRGs (DUSP3, MAPKAPK5, SP1 and VEGFA) to forecast the risk of IVDD. Based on the four hub genes we previously obtained, we built a nomogram model and performed a decision curve analysis, which ultimately suggested that the model was beneficial to patients. Based on the selected 4 hub CSRGs, we classified IVDD patients into two Hub gene patterns (hub gene clusters A and B) by the consensus clustering method, while the 297 DEGs obtained by screening based on the two hub gene clusters were classified into two gene patterns using the same method. We then applied a PCA algorithm to determine Hub gene scores for each sample to measure Hub gene patterns and found that patients in cluster A had higher Hub gene scores than those in cluster B. We also showed the correlation of two Hub gene patterns and Gene patterns with immune cell infiltration and the differential expression levels of four Hub genes by constructing heat maps and histograms. We performed GO enrichment analysis on these 297 DEGs to explore their role in IVDD. Finally, we used qPCR analysis and western blot to verify the expression levels of mRNA and protein in normal and IVDD cells of 4 hub CSRGs. In summary, CSRGs play an important role in the pathogenesis of IVDD, and our study of the hub gene cluster may guide future therapeutic strategies for IVDD.