Identifying druggable gene-related biomarkers in intervertebral disc degeneration through transcriptome sequencing and mendelian randomization analysis.

Background: Intervertebral disc degeneration (IDD) is a major contributor to low back pain, yet its molecular mechanisms remain unclear. Identifying potential druggable genes (PDGs) associated with IDD could facilitate early diagnosis and targeted therapy. This study aimed to explore the diagnostic and mechanistic significance of PDGs in IDD. Methods and Results: Three GEO datasets were merged as a training set, with another blood-based dataset as testing. PDGs were obtained from the literature and intersected with differentially expressed genes (DEGs). Functional enrichment and immune infiltration analyses were performed. A Lasso regression model was developed for diagnosis, and Mendelian Randomization (MR) analysis inferred causality. Cellular experiments validated key gene expression. Fourteen differentially expressed PDGs were identified, primarily involved in immune responses and neutrophil activity. A five-gene diagnostic model (BPI, CD160, CTSG, CYP27A1, KIF11) was constructed and demonstrated high accuracy. MR analysis confirmed a causal relationship between BPI and CTSG with IDD. GSEA revealed that BPI was negatively associated with oxidative phosphorylation, while CTSG was linked to the G2M checkpoint. Cellular experiments confirmed BPI and CTSG upregulation in TNF-α-induced NPCs. Conclusion: This study constructed a diagnostic model and identified BPI and CTSG as potential biomarkers for IDD, providing new insights into IDD treatment.