国际麻醉学与复苏杂志   2022, Issue (10): 0-0
    
脓毒症相关性脑病差异基因以及发病机制的数据分析
林桦, 刘鹏, 宋程程, 秦超, 于泳浩1()
1.天津医科大学总医院
Data analysis of differentially expressed genes and mechanism of sepsis‑related encephalopathy
 全文:
摘要:

目的 探讨脓毒症相关性脑病(sepsis‑associated encephalopathy, SAE)的相关差异表达基因(differentially expressed gene, DEG)和信号转导途径。 方法 基于基因表达数据库(gene expression omnibus, GEO)的脓毒症患者脑组织的基因组数据,采用基因本体(gene ontology, GO)富集分析和京都基因与基因组百科全书(kyoto encyclopedia of genes and genomes, KEGG)富集分析,以及蛋白‑蛋白相互作用网络(protein‑protein interaction, PPI)分析,确定SAE的DEG。 结果 DEG在免疫应答、炎症反应、凋亡过程的负调控、蛋白质水解等方面显著富集。通过PPI分析筛选出10个枢纽基因,包括固醇调节元件结合转录因子1(sterol regulatory element binding transcription factor 1, SREBF1)、细胞因子信号转导抑制因子‑3(suppressor of cytokine signaling 3, SOCS3)、封闭蛋白5(claudin 5, CLDN5)、免疫球蛋白结构域蛋白4(V‑set and immunoglobulin domain containing 4, VSIG4)、DNA损伤诱导蛋白45β(growth arrest and DNA damage inducible protein 45β, GADD45β)、细胞间黏附分子‑1(intercellular adhesion molecule 1, ICAM1)、血管生成素‑2基因(angiopoietin 2, ANGPT2)、CD14、CD163、血栓反应蛋白1(thrombospondin 1, THBS1)。 结论 通过生物信息学方法挖掘出与SAE相关的10个枢纽基因,这些基因和机体的免疫炎症相关。

关键词: 脓毒症; 脑病; 基因; 计算生物学; 免疫炎症
Abstract:

Objective To explore the differentially expressed gene (DEG) and signaling pathways of sepsis‑associated encephalopathy (SAE). Methods The DEG were determined, based on the genomic data of SAE patients in the gene expression omnibus (GEO) database, gene ontology (GO) and kyoto encyclopedia of genes and genomes(KEGG) enrichment analysis, protein‑protein interaction (PPI) network analysis. Results DEG were enriched in immune response, inflammatory reactions, negative regulation of apoptotic process, and protein hydrolysis pathways. PPI network analysis revealed 10 hub genes, including sterol regulatory element binding transcription factor 1 (SREBF1), suppressor of cytokine signaling 3 (SOCS3), claudin 5 (CLDN5), V‑set and immunoglobulin domain containing 4 (VSIG4), growth arrest and DNA damage inducible protein 45β (GADD45β), intercellular adhesion molecule 1 (ICAM1), angiopoietin 2 (ANGPT2), CD14, CD163, and thrombospondin 1 (THBS1). Conclusion Ten hub genes related to sepsis‑associated encephalopathy are identified through bioinformatics methods, and the mechanism is related to regulating the immunity and inflammation response to infection.

Key words: Sepsis; Encephalopathy; Genes; Computational biology; Immune inflammation