通过对骨关节炎半月板进行单细胞和微阵列转录组综合分析,确定枢纽基因。

IF 2.8 3区 医学 Q1 ORTHOPEDICS Journal of Orthopaedic Surgery and Research Pub Date : 2024-10-23 DOI:10.1186/s13018-024-05175-z
Yanzhu Shen, Ruichen Jiang, Yanjun Huang, Yuming Wang, Sizheng Zhan, Xiangsheng Tang, Ping Yi
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引用次数: 0

摘要

背景:骨关节炎(OA)以关节软骨和软骨下骨的逐渐退化为特征。人们对驱动 OA 中半月板退化的确切分子机制,尤其是单细胞水平的机制仍知之甚少:我们分析了 GEO 数据库中的两个数据集 GSE220243 和 GSE98918,重点是 OA 和非 OA 患者的半月板组织测序数据。采用标准的 Seurat 程序处理单细胞数据并识别差异表达基因(DEGs)。使用微环境细胞群(MCP)计数器和 CIBERSORT 算法评估了免疫细胞浸润情况。对于微阵列数据,使用 limma 软件包识别 DEGs,并使用 ClusterProfiler 进行基因本体(GO)和京都基因组百科全书(KEGG)分析。两个数据集中的重叠 DEGs 被导入 Cytoscape,以生成蛋白质-蛋白质相互作用(PPI)网络并识别中心基因。使用 NetworkAnalyst 分析了转录因子(TF)和 miRNA 相互作用网络,并通过 DSigDB 平台富集了与基因相关的预测性药物:结果:经过质量控制,共分析了 34,763 个来自 OA 患者的细胞和 34,145 个来自健康对照组的细胞。UMAP识别并注释了14个细胞群。我们选取了10个最大的细胞群进行进一步分析。OA 组半月板中的巨噬细胞明显增加,细胞毒性淋巴细胞和内皮细胞减少。在 GSE98918 中确定了 220 个 DEGs,Cytoscape 中的 MCODE 插件确定了一个包含 12 个候选基因的关键模块。MCC 方法过滤了每个 GSE220243 簇中的前 20 个 DEGs。来自 GSE220243 和 GSE98918 的重叠 DEGs 发现 COL1A1、COL3A1、COL5A2、COL6A3、LOX 和 VEGFA 在 OA 中显著减少,而 COL3A1、COL5A2、LOX 和 VEGFA 在半月板软骨细胞中上调。相互作用网络强调了 3 个关键 miRNA 和 13 个共享 TF。研究还发现了 10 个与基因相关的预测性药物分子:这项研究强调了 OA 半月板中的关键基因,并揭示了软骨细胞和非软骨细胞之间不同的调控模式。这些发现加深了我们对驱动 OA 发病机制的分子机制的理解,并有助于确定潜在的药物靶点。
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Identification of hub genes through integrated single-cell and microarray transcriptome analysis in osteoarthritic meniscus.

Background: Osteoarthritis (OA) is marked by the progressive degradation of joint cartilage and subchondral bone. The precise molecular mechanisms driving meniscus deterioration in OA, especially at the single-cell level, remain poorly understood.

Method: We analyzed two datasets from the GEO database, GSE220243 and GSE98918, focusing on meniscus tissue sequencing data from OA and non-OA patients. The standard Seurat procedure was employed to process single-cell data and identify differentially expressed genes (DEGs). Immune cell infiltration was assessed using the Microenvironment Cell Populations (MCP) counter and CIBERSORT algorithms. For the microarray data, DEGs were identified with the limma package, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using ClusterProfiler. The overlapping DEGs from both datasets were imported into Cytoscape to generate protein-protein interaction (PPI) networks and identify hub genes. Transcription factor (TF) and miRNA interaction networks were analyzed using NetworkAnalyst, and gene-related predictive drugs were enriched through the DSigDB platform.

Result: After quality control, 34,763 cells from the OA patients and 34,145 cells from the healthy controls were analyzed. UMAP identified and SingleR annotated 14 cell clusters. The 10 largest cell clusters were selected for further analysis. The OA group exhibited a notable increase in macrophages and a reduction in cytotoxic lymphocytes and endothelial cells in the meniscus. In GSE98918, 220 DEGs were identified, and the MCODE plug-in in Cytoscape pinpointed a key module containing 12 candidate genes. The MCC methodfiltered the top 20 DEGs in each GSE220243 cluster. Overlapping DEGs from GSE220243 and GSE98918 identified COL1A1, COL3A1, COL5A2, COL6A3, LOX, and VEGFA as significantly decreased in OA, with COL3A1, COL5A2, LOX, and VEGFA upregulated in meniscal chondrocytes. The interaction network highlighted 3 key miRNAs and 13 shared TFs. Ten gene-related predictive drug molecules were identified.

Conclusion: This research highlights crucial genes in the OA meniscus and uncovers their differing regulatory patterns between chondrocytes and non-chondrocytes. These findings enhance our understanding of the molecular mechanisms driving OA pathogenesis and aid in identifying potential drug targets.

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来源期刊
CiteScore
4.10
自引率
7.70%
发文量
494
审稿时长
>12 weeks
期刊介绍: Journal of Orthopaedic Surgery and Research is an open access journal that encompasses all aspects of clinical and basic research studies related to musculoskeletal issues. Orthopaedic research is conducted at clinical and basic science levels. With the advancement of new technologies and the increasing expectation and demand from doctors and patients, we are witnessing an enormous growth in clinical orthopaedic research, particularly in the fields of traumatology, spinal surgery, joint replacement, sports medicine, musculoskeletal tumour management, hand microsurgery, foot and ankle surgery, paediatric orthopaedic, and orthopaedic rehabilitation. The involvement of basic science ranges from molecular, cellular, structural and functional perspectives to tissue engineering, gait analysis, automation and robotic surgery. Implant and biomaterial designs are new disciplines that complement clinical applications. JOSR encourages the publication of multidisciplinary research with collaboration amongst clinicians and scientists from different disciplines, which will be the trend in the coming decades.
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