■骨关节炎(OA)是最常见的关节疾病。线粒体功能障碍与OA的发病机理有关。这项研究的主要目的是揭示线粒体在驱动OA发展的机制中的关键作用。
■我们从基因表达Omnibus(GEO)数据库中获取了七个大量RNA-seq数据集,并检查了OA中与线粒体相关的差异表达基因的表达水平。我们利用单样本基因集富集分析(ssGSEA),基因集富集分析(GSEA),和加权基因共表达网络分析(WGCNA)分析,以探索与这些基因相关的功能机制。七种机器学习算法用于识别集线器线粒体相关基因并开发预测模型。进一步的分析包括途径富集,免疫浸润,基因-疾病关系,以及基于这些hub线粒体相关基因的mRNA-miRNA网络构建。使用GeneAtlas数据库进行全基因组关联研究(GWAS)分析.GSEA,基因集变异分析(GSVA),蛋白质途径分析,和WGCNA用于研究亚型的相关途径。使用Harmonizome数据库来分析各种人体组织中集线器线粒体相关基因的表达。进行单细胞数据分析以检查基因表达分布和伪时间变化的模式。此外,实时聚合酶链反应(RT-PCR)用于验证这些集线器线粒体相关基因的表达。
■在OA中,线粒体相关通路被显著激活。9个集线器线粒体相关基因(SIRT4,DNAJC15,NFS1,FKBP8,SLC25A37,CARS2,MTHFD2,ETFDH,和PDK4)被鉴定。他们构建了具有良好预测OA能力的预测模型。这些基因主要与巨噬细胞相关。无监督共识聚类确定了主要与代谢相关的两种线粒体相关同工型。单细胞分析表明,它们均在单细胞中表达,并随细胞分化而变化。RT-PCR显示它们均在OA中显著表达。
■SIRT4,DNAJC15,NFS1,FKBP8,SLC25A37,CARS2,MTHFD2,ETFDH,和PDK4是研究OA的潜在线粒体靶基因。线粒体相关同工型的分类有助于OA患者的个性化治疗。
UNASSIGNED: Osteoarthritis (OA) stands as the most prevalent joint disorder. Mitochondrial dysfunction has been linked to the pathogenesis of OA. The main goal of this study is to uncover the pivotal role of mitochondria in the mechanisms driving OA development.
UNASSIGNED: We acquired seven bulk RNA-seq datasets from the Gene Expression Omnibus (GEO) database and examined the expression levels of differentially expressed genes related to mitochondria in OA. We utilized single-sample gene set enrichment analysis (ssGSEA), gene set enrichment analysis (GSEA), and weighted gene co-expression network analysis (WGCNA) analyses to explore the functional mechanisms associated with these genes. Seven machine learning algorithms were utilized to identify hub mitochondria-related genes and develop a predictive model. Further analyses included pathway enrichment, immune infiltration, gene-disease relationships, and mRNA-miRNA network construction based on these hub mitochondria-related genes. genome-wide association studies (GWAS) analysis was performed using the Gene Atlas database. GSEA, gene set variation analysis (GSVA), protein pathway analysis, and WGCNA were employed to investigate relevant pathways in subtypes. The Harmonizome database was employed to analyze the expression of hub mitochondria-related genes across various human tissues. Single-cell data analysis was conducted to examine patterns of gene expression distribution and pseudo-temporal changes. Additionally, The real-time polymerase chain reaction (RT-PCR) was used to validate the expression of these hub mitochondria-related genes.
UNASSIGNED: In OA, the mitochondria-related pathway was significantly activated. Nine hub mitochondria-related genes (SIRT4, DNAJC15, NFS1, FKBP8, SLC25A37, CARS2, MTHFD2, ETFDH, and PDK4) were identified. They constructed predictive models with good ability to predict OA. These genes are primarily associated with macrophages. Unsupervised consensus clustering identified two mitochondria-associated isoforms that are primarily associated with metabolism. Single-cell analysis showed that they were all expressed in single cells and varied with cell differentiation. RT-PCR showed that they were all significantly expressed in OA.
UNASSIGNED: SIRT4, DNAJC15, NFS1, FKBP8, SLC25A37, CARS2, MTHFD2, ETFDH, and PDK4 are potential mitochondrial target genes for studying OA. The classification of mitochondria-associated isoforms could help to personalize treatment for OA patients.