椎间盘退变中巨噬细胞极化相关基因的生物信息学分析与鉴定
Bioinformatic analysis and identification of macrophage polarization-related genes in intervertebral disc degeneration.
作者信息
Liu Lei, Peng Shengxin, Shi Bin, Yu Gongchang, Liang Yuanhao, Zhang Yixiang, Xiao Wenshan, Xu Rui
机构信息
Academy of Medical Engineering and Translational Medicine, Tianjin University Tianjin, China.
Department of Painology, The First Affiliated Hospital of Shandong First Medical University Jinan, Shandong, China.
出版信息
Am J Transl Res. 2024 May 15;16(5):1891-1906. doi: 10.62347/HBDY5086. eCollection 2024.
BACKGROUND
The relationship between macrophage polarization-related genes (MPRGs) and intervertebral disc degeneration (IDD) is unclear. The purpose of this study was to identify biomarkers associated with IDD.
METHODS
Three transcriptome sequencing datasets, GSE124272, GSE70362 and GSE56081 were included in this study. Differential expressed genes (DEGs) were obtained by overlapping DEGs1 from the GSE124272 and DEGs2 from the GSE70362. The key module genes associated with the score of MPRGs were identified by weighted gene co-expression network analysis (WGCNA) in GSE12472. Differentially expressed (DE)-MPRGs were acquired by overlapping key module genes and DEGs. Candidate genes were obtained by SVM-RFE algorithm. Biomarkers were obtained by expression level analysis. In addition, immune analysis, enrichment analysis and construction of a ceRNA network were completed. The blood samples from 9 IDD patients (IDD group) and 9 healthy individuals (Control group) were used to verify the expression levels of these biomarkers through RT-qPCR.
RESULTS
A sum of 39 DEGs were obtained by overlapping DEGs1 and DEGs2, and 1,633 key module genes were obtained by WGCNA. 9 DE-MPRGs were obtained by overlapping DEGs and key module genes, and ST6GALNAC2, SMIM3, and IFITM2 were identified as biomarkers. These biomarkers were enriched in KEGG_RIBOSOME pathway. Check-point, Cytolytic_activity, T_cell_co-stimulation, Neutrophils, Th2_cells and TIL differed between IDD and control groups. Some relationships such as SMIM3-hsa-miR-107-LINC02381 were identified in the network. Moreover, the functional analysis results of biomarkers showed that FITM2 and SMIM3 could predict IDD and nociceptive pain. The RT-qPCR showed that ST6GALNAC2 and IFITM2 were significantly expressed in IDD group in contrast to the control group.
CONCLUSION
The macrophage polarization related biomarkers (ST6GALNAC2, SMIM3 and IFITM2) were associated with IDD, among which IFITM2 could be considered as a key gene for IDD. This may provide a new direction for the biological treatment and mechanism research into IDD.
背景
巨噬细胞极化相关基因（MPRGs）与椎间盘退变（IDD）之间的关系尚不清楚。本研究旨在鉴定与IDD相关的生物标志物。
方法
本研究纳入了三个转录组测序数据集，即GSE124272、GSE70362和GSE56081。通过重叠GSE124272中的差异表达基因1（DEGs1）和GSE70362中的差异表达基因2（DEGs2）来获得差异表达基因（DEGs）。通过加权基因共表达网络分析（WGCNA）在GSE12472中鉴定与MPRGs评分相关的关键模块基因。通过重叠关键模块基因和DEGs来获得差异表达（DE）-MPRGs。通过支持向量机-递归特征消除（SVM-RFE）算法获得候选基因。通过表达水平分析获得生物标志物。此外，还完成了免疫分析、富集分析和ceRNA网络构建。使用来自9例IDD患者（IDD组）和9名健康个体（对照组）的血液样本，通过逆转录-定量聚合酶链反应（RT-qPCR）验证这些生物标志物的表达水平。
结果
通过重叠DEGs1和DEGs2获得了39个DEGs，通过WGCNA获得了1633个关键模块基因。通过重叠DEGs和关键模块基因获得了9个DE-MPRGs，并将ST6GALNAC2、SMIM3和IFITM2鉴定为生物标志物。这些生物标志物在KEGG_RIBOSOME途径中富集。IDD组和对照组在检查点、细胞溶解活性、T细胞共刺激、中性粒细胞、Th2细胞和肿瘤浸润淋巴细胞方面存在差异。在网络中鉴定出了一些关系，如SMIM3-hsa-miR-107-LINC02381。此外，生物标志物的功能分析结果表明，FITM2和SMIM3可以预测IDD和伤害性疼痛。RT-qPCR结果显示，与对照组相比，ST6GALNAC2和IFITM2在IDD组中显著表达。
结论
巨噬细胞极化相关生物标志物（ST6GALNAC2、SMIM3和IFITM2）与IDD相关，其中IFITM2可被视为IDD的关键基因。这可能为IDD的生物治疗和机制研究提供新的方向。
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