Table3_Comprehensive analysis of senescence-related genes and immune infiltration in intervertebral disc degeneration: a meta-data approach utilizing bulk and single-cell RNA sequencing data.XLSX

Objectives: This study aims to identify the key senescence genes and potential regulatory mechanisms that contribute to the etiology of intervertebral disc degeneration (IDD).
Method: We analyzed GSE34095 and GSE70362 datasets, identifying key senescence-related differentially expressed genes (DEGs) in IDD using lasso regression. Risk scores classified patients into high- and low-risk groups. We compared pathways, functions, and immune infiltration between these groups. Diagnostic ability was assessed using ROC curves and a nomogram predicted IDD incidence. In single-cell dataset GSE165722, we evaluated expression of key senescence-related DEGs.
Results: We identified 12 key senescence-related DEGs distinguishing high- and low-risk IDD patients. Enrichment analysis revealed cellular stress response, apoptotic signaling pathway, and protein kinase activation differences. Immune cell analysis showed elevated eosinophils in low-risk group and increased effector memory CD8 T, central memory CD4 T, myeloid-derived suppressor, natural killer, monocyte, Type 1 T helper, plasmacytoid dendritic, and natural killer T cells in high-risk group. A nomogram using AUC >0.75 genes (CXCL8, MAP4K4, MINK1, and TNIK) predicted IDD incidence with good diagnostic power. High senescence scores were observed in neutrophils.
Conclusion: Our diagnostic model, based on key senescence-related DEGs and immune cell infiltration, offers new insights into IDD pathogenesis and immunotherapy strategies.

研究目的：本研究旨在明确参与椎间盘退变（intervertebral disc degeneration, IDD）发病机制的关键衰老基因及潜在调控机制。
研究方法：本研究分析了GSE34095与GSE70362数据集，通过套索回归（lasso regression）筛选出IDD中与衰老相关的关键差异表达基因（differentially expressed genes, DEGs）。借助风险评分将患者划分为高风险组与低风险组，比较两组间的通路富集、功能差异及免疫浸润情况。采用受试者工作特征（Receiver Operating Characteristic, ROC）曲线评估模型的诊断效能，并通过列线图（nomogram）预测IDD的发病风险。此外，在单细胞数据集GSE165722中，我们对关键衰老相关DEGs的表达水平进行了验证分析。
研究结果：本研究共筛选出12个可区分高、低风险IDD患者的关键衰老相关DEGs。富集分析结果显示，两组在细胞应激反应、凋亡信号通路及蛋白激酶激活等生物学过程中存在显著差异。免疫细胞浸润分析表明，低风险组嗜酸性粒细胞水平升高；而高风险组效应记忆CD8 T细胞、中枢记忆CD4 T细胞、髓系来源抑制细胞、自然杀伤细胞、单核细胞、1型辅助性T细胞、浆细胞样树突状细胞及自然杀伤T细胞的浸润水平均显著升高。基于AUC>0.75的基因（CXCL8、MAP4K4、MINK1及TNIK）构建的列线图可有效预测IDD发病，具备良好的诊断效能。此外，中性粒细胞中衰老评分显著升高。
研究结论：本研究基于关键衰老相关DEGs及免疫细胞浸润构建的诊断模型，为椎间盘退变的发病机制研究及免疫治疗策略开发提供了全新的学术视角。