Identification and Verification of Hub Mitochondrial Dysfunction Genes in Osteoarthritis Based on Bioinformatics Analysis

IF 3.5 3区 医学 Q2 IMMUNOLOGY
Hui Niu, Xingxing Deng, Qian Zhang, Yijun Zhao, Jinfeng Wen, Wenyu Li, Huan Liu, Xiong Guo, Cuiyan Wu
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Abstract

Objective. Age-related mitochondrial dysfunction and associated oxidative stress may contribute to the development of osteoarthritis. The aim of this study was to identify hub genes associated with mitochondrial dysfunction in osteoarthritis (OA) patients, helping predict the risk of OA, and revealing the mechanism of OA progression. Methods. OA expression data and mitochondrial dysfunction genes were downloaded from GEO (GSE55235, GSE82107, and GSE114007) and GeneCard databases. The differentially expressed mitochondrial dysfunction genes (DEMDFGs) between OA and control samples were screened. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes pathways were analyzed for DEMDFGs. The hub genes were determined by WGCNA and LASSO regression analysis. ROC curves manifested the diagnostic efficacy of each hub gene. A nomogram model was constructed and validated to predict OA risk. The expression of hub genes in OA and normal chondrocytes was verified by external datasets, qRT-PCR and western blotting. Results. A total of 31 DEMDFGs were identified, with 15 genes upregulated and 16 genes downregulated. GO functional enrichment analysis revealed that DEMDFGs were enriched in biological processes related to energy metabolism and cellular respiration. By employing weighted gene coexpression network analysis, we identified four distinct coexpression modules, among which the blue module exhibited the strongest correlation with OA. The intersection between DEMDFGs and this module yielded eight candidate genes. After LASSO analysis of the data, four hub genes (ACADL, CYBA, SLC19A2, and UCP2) were identified as potential biomarkers for OA. The expression levels of these four genes were externally validated in the GSE114007 dataset. And the biologically differential expression of these four genes has been verified in OA and normal chondrocytes. Moreover, the four hub genes had good sensitivity and specificity by ROC curve analysis, and the risk model constructed with these four genes showed promising performance. In conclusion, our study may provide novel mitochondrial dysfunction hub genes with potential clinical applications for understanding the pathology, diagnosis, and treatment of OA.
基于生物信息学分析的骨关节炎中枢线粒体功能障碍基因的识别与验证
目的。与年龄有关的线粒体功能障碍和相关的氧化应激可能会导致骨关节炎的发生。本研究旨在确定骨关节炎(OA)患者中与线粒体功能障碍相关的枢纽基因,帮助预测 OA 的风险,并揭示 OA 进展的机制。研究方法从 GEO(GSE55235、GSE82107 和 GSE114007)和 GeneCard 数据库下载 OA 表达数据和线粒体功能障碍基因。筛选了 OA 样本和对照样本之间的线粒体功能障碍差异表达基因(DEMDFGs)。对 DEMDFGs 的基因本体(GO)和京都基因和基因组通路百科全书进行了分析。通过 WGCNA 和 LASSO 回归分析确定了枢纽基因。ROC 曲线显示了每个枢纽基因的诊断功效。构建并验证了预测 OA 风险的提名图模型。通过外部数据集、qRT-PCR和Western blotting验证了枢纽基因在OA和正常软骨细胞中的表达。结果。共鉴定出31个DEMDFGs,其中15个基因上调,16个基因下调。GO功能富集分析表明,DEMDFGs富集于与能量代谢和细胞呼吸相关的生物过程。通过加权基因共表达网络分析,我们发现了四个不同的共表达模块,其中蓝色模块与OA的相关性最强。DEMDFGs 与该模块的交集产生了八个候选基因。在对数据进行 LASSO 分析后,四个中心基因(ACADL、CYBA、SLC19A2 和 UCP2)被确定为 OA 的潜在生物标志物。这四个基因的表达水平在 GSE114007 数据集中得到了外部验证。这四个基因在 OA 和正常软骨细胞中的生物差异表达也得到了验证。此外,通过 ROC 曲线分析,这四个枢纽基因具有良好的灵敏度和特异性,用这四个基因构建的风险模型表现出良好的性能。总之,我们的研究为了解 OA 的病理、诊断和治疗提供了新的线粒体功能障碍枢纽基因,具有潜在的临床应用价值。
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来源期刊
CiteScore
6.90
自引率
2.40%
发文量
423
审稿时长
15 weeks
期刊介绍: Journal of Immunology Research is a peer-reviewed, Open Access journal that provides a platform for scientists and clinicians working in different areas of immunology and therapy. The journal publishes research articles, review articles, as well as clinical studies related to classical immunology, molecular immunology, clinical immunology, cancer immunology, transplantation immunology, immune pathology, immunodeficiency, autoimmune diseases, immune disorders, and immunotherapy.
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