Deng Ya-Jun, Wang Xin-Gang, Li Zhi, Wang Bo, Li Jie, Ma Jun, Xue Xiong, Tian Xin, Liu Quan-Cheng, Liu Jia-Yuan, Zhang Ying, Yuan Bin
Department of Spine Surgery, Xi'an Daxing Hospital, Yanan University, Xi'an, China.
Front Mol Biosci. 2023 Dec 22;10:1296782. doi: 10.3389/fmolb.2023.1296782. eCollection 2023.
This study aims to identify the key senescence genes and potential regulatory mechanisms that contribute to the etiology of intervertebral disc degeneration (IDD). 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. 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. Our diagnostic model, based on key senescence-related DEGs and immune cell infiltration, offers new insights into IDD pathogenesis and immunotherapy strategies.
本研究旨在确定导致椎间盘退变（IDD）病因的关键衰老基因和潜在调控机制。我们分析了GSE34095和GSE70362数据集，使用套索回归确定IDD中与衰老相关的关键差异表达基因（DEG）。风险评分将患者分为高风险组和低风险组。我们比较了这些组之间的信号通路、功能和免疫浸润情况。使用受试者工作特征（ROC）曲线评估诊断能力，并使用列线图预测IDD发病率。在单细胞数据集GSE165722中，我们评估了与衰老相关的关键DEG的表达。我们确定了12个区分高风险和低风险IDD患者的与衰老相关的关键DEG。富集分析揭示了细胞应激反应、凋亡信号通路和蛋白激酶激活方面的差异。免疫细胞分析显示，低风险组中嗜酸性粒细胞增多，高风险组中效应记忆CD8 T细胞、中枢记忆CD4 T细胞、髓源性抑制细胞、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和自然杀伤T细胞增加。使用曲线下面积（AUC）>0.75的基因（CXCL8、MAP4K4、MINK1和TNIK）构建的列线图对IDD发病率具有良好的预测诊断能力。在中性粒细胞中观察到高衰老评分。我们基于与衰老相关的关键DEG和免疫细胞浸润的诊断模型为IDD发病机制和免疫治疗策略提供了新的见解。
