骨髓炎患者静脉血栓形成的潜在分子基础和机制：基于数据的分析。
The Underlying Molecular Basis and Mechanisms of Venous Thrombosis in Patients with Osteomyelitis: A Data-Driven Analysis.
机构信息
Department of Orthopaedics, Fuzhou Second Hospital of Xiamen University, School of Medicine, Xiamen University, Fuzhou 350007, China.
Department of Orthopaedics, Fuzhou Second Hospital, The Third Clinical Medical College, Fujian Medical University, Fuzhou 350007, China.
出版信息
Genet Res (Camb). 2022 Jun 6;2022:5672384. doi: 10.1155/2022/5672384. eCollection 2022.
OBJECTIVE
Osteomyelitis (OM) is one of the most risky and challenging diseases. Emerging evidence indicates OM is a risk factor for increasing incidence of venous thromboembolism (VTE) development. However, the mechanisms have not been intensively investigated.
METHODS
The OM-related dataset GSE30119 and VTE-related datasets GSE19151 and GSE48000 were downloaded from the Gene Expression Omnibus (GEO) database and analyzed to identify the differentially expressed genes (DEGs) (OMGs1 and VTEGs1, respectively). Functional enrichment analyses of Gene Ontology (GO) terms were performed. VTEGs2 and OMGs2 sharing the common GO biological process (GO-BP) ontology between OMGs1 and VTEGs1 were detected. The TRRUST database was used to identify the upstream transcription factors (TFs) that regulate VTEGs2 and OMGs2. The protein-protein interaction (PPI) network between VTEGs2 and OMGs2 was constructed using the Search Tool for the Retrieval of Interacting Genes (STRING) database and then visualized in Cytoscape. Topological properties of the PPI network were calculated by NetworkAnalyzer. The Molecular Complex Detection (MCODE) plugin was utilized to perform module analysis and choose the hub modules of the PPI network.
RESULTS
A total of 587 OMGs1 and 382 VTEGs1 were identified from the related dataset, respectively. GO-BP terms of OMGs1 and shared DGEs1 were mainly enriched in the neutrophil-related immune response process, and the shared GO-BP terms of OMGs1 and VTEGs1 seemed to be focused on cell activation, immune, defense, and inflammatory response to stress or biotic stimulus. 230 VTEGs2, 333 OMGs2, and 13 shared DEGs2 were detected. 3 TF-target gene pairs (SP1-LSP1, SPI1-FCGR1A, and STAT1-FCGR1A) were identified. The PPI network contained 1611 interactions among 467 nodes. The top 10 hub proteins were TP53, IL4, MPO, ELANE, FOS, CD86, HP, SOCS3, ICAM1, and SNRPG. Several core nodes (such as MPO, ELANE, and CAMP) were essential components of the neutrophil extracellular traps (NETs) network.
CONCLUSION
This is the first data-mining study to explore shared signatures between OM and VTE by the integrated bioinformatic approach, which can help uncover potential biomarkers and therapeutic targets of OM-related VTE.
目的
骨髓炎（OM）是最危险和最具挑战性的疾病之一。新出现的证据表明，OM 是静脉血栓栓塞（VTE）发展发病率增加的一个危险因素。然而，其机制尚未得到深入研究。
方法
从基因表达综合数据库（GEO）下载 OM 相关数据集 GSE30119 和 VTE 相关数据集 GSE19151 和 GSE48000，并进行分析以识别差异表达基因（DEGs）（OMGs1 和 VTEGs1）。进行基因本体论（GO）术语的功能富集分析。在 OMGs1 和 VTEGs1 之间的共同 GO 生物学过程（GO-BP）本体中检测到 VTEGs2 和 OMGs2。使用 TRRUST 数据库识别调节 VTEGs2 和 OMGs2 的上游转录因子（TF）。使用 Search Tool for the Retrieval of Interacting Genes（STRING）数据库构建 VTEGs2 和 OMGs2 之间的蛋白质-蛋白质相互作用（PPI）网络，然后在 Cytoscape 中可视化。使用 NetworkAnalyzer 计算 PPI 网络的拓扑属性。使用 Molecular Complex Detection（MCODE）插件进行模块分析并选择 PPI 网络的枢纽模块。
结果
从相关数据集中共鉴定出 587 个 OMGs1 和 382 个 VTEGs1。OMGs1 的 GO-BP 术语和共享的 DGEs1 主要富集在中性粒细胞相关的免疫反应过程中，而 OMGs1 和 VTEGs1 之间的共享 GO-BP 术语似乎集中在细胞激活、免疫、防御和对压力或生物刺激的炎症反应上。检测到 230 个 VTEGs2、333 个 OMGs2 和 13 个共享的 DEGs2。鉴定出 3 个 TF-靶基因对（SP1-LSP1、SPI1-FCGR1A 和 STAT1-FCGR1A）。PPI 网络包含 467 个节点之间的 1611 个相互作用。前 10 个枢纽蛋白是 TP53、IL4、MPO、ELANE、FOS、CD86、HP、SOCS3、ICAM1 和 SNRPG。一些核心节点（如 MPO、ELANE 和 CAMP）是中性粒细胞胞外陷阱（NETs）网络的重要组成部分。
结论
这是首次通过综合生物信息学方法探索 OM 和 VTE 之间共享特征的数据分析研究，这有助于发现 OM 相关 VTE 的潜在生物标志物和治疗靶点。
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