Zhou Daqian, Liu Tao, Mei Yongliang, Lv Jiale, Cheng Kang, Cai Weiye, Gao Silong, Guo Daru, Xie Xianping, Liu Zongchao
Department of Orthopedics, The Affiliated Traditional Chinese Medicine Hospital Southwest Medical University Luzhou Sichuan Province China.
Department of Orthopedics Luzhou Longmatan District People's Hospital Luzhou Sichuan China.
JOR Spine. 2024 Oct 18;7(4):e70004. doi: 10.1002/jsp2.70004. eCollection 2024 Dec.
Intervertebral disc degeneration (IVDD) is an age-related orthopedic degenerative disease characterized by recurrent episodes of lower back pain, the pathogenesis of which is not fully understood. This study aimed to identify key biomarkers of IVDD and its causes.
We acquired three gene expression profiles from the Gene Expression Omnibus (GEO) database, GSE56081, GSE124272, and GSE153761, and used limma fast differential analysis to identify differentially expressed genes (DEGs) between normal and IVDD samples after removing batch effects. We applied weighted gene co-expression network (WGCNA) to identify the key modular genes in GSE124272 and intersected these with DEGs. Next, A protein-protein interaction network (PPI) was constructed, and Cytoscape was used to identify the Top 10 hub genes. Functional enrichment analyses were performed using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Three key genes were validated using Western Blot (WB) and qRT-PCR. Additionally, we predicted miRNAs involved in hub gene co-regulation and analyzed miRNA microarray data from GSE116726 to identify four differentially expressed miRNAs.
We identified 10 hub genes using bioinformatics analysis, gene function enrichment analysis revealed that they were primarily enriched in pathways, such as the TNF signaling pathway. We chose JUNB, SOCS3, and CEBPB as hub genes and used WB and qRT-PCR to confirm their expression. All three genes were overexpressed in the IVDD model group compared to the control group. Furthermore, we identified four miRNAs involved in the co-regulation of the hub genes using miRNet prediction: mir-191-5p, mir-20a-5p, mir-155-5p, and mir-124-3p. Using limma difference analysis, we discovered that mir-191-5p, mir-20a-5p, and mir-155-5p were all down-regulated and expressed in IVDD samples, but mir-124-3p showed no significant change.
JUNB, SOCS3, and CEBPB were identified as key genes in IVDD, regulated by specific miRNAs, providing potential biomarkers for early diagnosis and therapeutic targets.
椎间盘退变（IVDD）是一种与年龄相关的骨科退行性疾病，其特征为反复发作的下背部疼痛，其发病机制尚未完全明确。本研究旨在确定IVDD的关键生物标志物及其病因。
我们从基因表达综合数据库（GEO）中获取了三个基因表达谱，即GSE56081、GSE124272和GSE153761，并在去除批次效应后，使用limma快速差异分析来识别正常样本与IVDD样本之间的差异表达基因（DEG）。我们应用加权基因共表达网络（WGCNA）来识别GSE124272中的关键模块基因，并将这些基因与DEG进行交集分析。接下来，构建蛋白质-蛋白质相互作用网络（PPI），并使用Cytoscape来识别前10个枢纽基因。使用基因本体论（GO）和京都基因与基因组百科全书（KEGG）数据库进行功能富集分析。使用蛋白质免疫印迹法（WB）和实时定量逆转录聚合酶链反应（qRT-PCR）对三个关键基因进行验证。此外，我们预测了参与枢纽基因共同调控的微小RNA（miRNA），并分析了来自GSE116726的miRNA微阵列数据，以识别四个差异表达的miRNA。
我们通过生物信息学分析确定了10个枢纽基因，基因功能富集分析表明它们主要富集于肿瘤坏死因子（TNF）信号通路等途径。我们选择JUNB、SOCS3和CEBPB作为枢纽基因，并使用WB和qRT-PCR来确认它们的表达。与对照组相比，所有这三个基因在IVDD模型组中均过表达。此外，我们使用miRNet预测确定了四个参与枢纽基因共同调控的miRNA：mir-191-5p、mir-20a-5p、mir-155-5p和mir-124-3p。使用limma差异分析，我们发现mir-191-5p、mir-20a-5p和mir-155-5p在IVDD样本中均下调并表达，但mir-124-3p无显著变化。
JUNB、SOCS3和CEBPB被确定为IVDD中的关键基因，并受特定miRNA调控，为早期诊断提供了潜在的生物标志物和治疗靶点。
