[Analysis of hub genes and molecular mechanisms in non-alcoholic steatohepatitis based on the gene expression omnibus database].

Objective: To explore the hub genes and mechanisms in the pathological process of non-alcoholic steatohepatitis (NASH) by bioinformatics methods. Methods: Microarray datasets GSE89632 were downloaded from the Gene Expression Omnibus (GEO) database, which including 20 simple non-alcoholic fatty liver disease patients, 19 NASH patients and 24 healthy control individuals. The differentially expressed genes (DEGs) in patients with simple non-alcoholic fatty liver disease and NASH were compared with healthy control individuals respectively, and the intersection of the two groups of DEGs was taken. GO functional annotation and KEGG pathway enrichment analysis of DEGs were performed with DAVID 6.8 and KOBAS 3.0 separately. Protein-protein interaction network (PPI) was constructed by STRING database, then the mRNA hub genes were selected by Cytoscape software. The Attie Lab Diabetes database was used to verify the relative expression of hub genes mRNA in the liver of 4 groups of C57BL/6 mice (4-week-old normal group, 4-week-old obese group, 10-week-old normal group and 10-week-old obese group, 5 mice in each group). Spearman's correlation analysis was performed to analyze the correlation between hub gens and prognostic clinical parameters. Results: From the GSE89632 dataset, 365 common DEGs (115 up-regulated genes and 250 down-regulated genes) were identified in patients with simple non-alcoholic fatty liver disease and NASH patients compared with control individuals. GO analysis showed that DEGs were mainly enriched in biological processes such as inflammatory response and immune response. KEGG pathway analysis showed that up-regulated genes were mainly enriched in cholesterol metabolism, bile secretion and fat digestion and absorption signal pathways. Down-regulated genes were mainly enriched in interleukin-17 signaling pathway, tumor necrosis factor signaling pathway, advanced glycation end products and their receptors of diabetic complications. Seven key hub genes were identified by PPI analysis, which were FOS, EGR1, FOSB, JUNB, FOSL1, MYC and NR4A1.The mRNA relative expression levels of EGR1 and JUNB in the liver of 10-week-old obese mice were lower than those of normal mice (P<0.05).The relative expression levels of NR4A1 in the liver of obese mice at 4-and 10-week-old were lower than those of normal mice at the same age (P values<0.05). Spearman's correlation analysis showed that the expression of EGR1 was negatively correlated with the degree of hepatic steatosis (r=-0.785, P<0.001).The expression levels of FOSB, MYC and NR4A1 were negatively correlated with the level of alanine aminotransferase (r=-0.649, -0.597 and-0.580 respectively, all P values<0.001). Conclusion: EGR1, FOSB, MYC, JUNB and NR4A1 might be the hub genes in the pathological process of NASH and the inflammatory and immune response in hepatocytes, IL-17 signaling pathway and TNF signaling pathway might be the key molecular mechanisms in the occurrence and development of NASH.目的： 采用生物信息学方法探索与非酒精性脂肪肝炎（NASH）病理进程相关的核心基因及分子机制。 方法： 由基因表达数据库（GEO）下载基因表达数据集GSE89632，包含单纯非酒精性脂肪肝患者、NASH患者和健康对照分别为20、19和24例，筛选单纯非酒精性脂肪肝患者和NASH患者相对于健康对照的差异表达基因（DEGs），对两组DEGs取交集。采用DAVID 6.8数据库对DEGs进行GO功能富集分析，采用KOBAS 3.0数据库对DEGs进行京都基因与基因组百科全书（KEGG）信号通路分析。利用STRING数据库构建DEGs蛋白相互作用网络（PPI），采用Cytoscape软件筛选核心基因。利用Attie Lab 糖尿病数据库验证核心基因在4组C57BL/6小鼠（分别为4周龄正常组、4周龄肥胖组、10周龄正常组和10周龄肥胖组，每组各5只）肝脏中mRNA相对表达量。分析核心基因和预后临床指标的相关性。 结果： 由GSE89632数据集筛选出单纯非酒精性脂肪肝患者和NASH患者相对于健康对照的365个共同DEGs，其中上调和下调基因分别为115和250个。GO分析显示DEGs主要富集于炎症反应和免疫应答等生物过程。KEGG信号通路分析显示：上调基因主要富集于胆固醇代谢、胆汁分泌和脂肪的消化吸收等信号通路；下调基因主要富集于白细胞介素-17信号通路、肿瘤坏死因子信号通路和糖尿病并发症的晚期糖基化终末产物及其受体等信号通路。PPI分析筛选出7个关键核心基因，分别为FOS、EGR1、FOSB、JUNB、FOSL1、MYC和NR4A1。10周龄肥胖小鼠肝脏中EGR1和JUNB的mRNA相对表达量均低于10周龄正常小鼠，均P<0.05；4和10周龄肥胖小鼠肝脏中NR4A1相对表达量均低于同周龄正常组小鼠，均P<0.05。EGR1基因表达水平与肝脏脂肪变性程度呈负相关（r=-0.785，P<0.001）。FOSB、MYC和NR4A1基因表达水平与血液谷丙转氨酶水平呈负相关（r=-0.649、-0.597和-0.580，均P<0.001）。 结论： EGR1、FOSB、MYC、JUNB和NR4A1等基因可能为NASH病理进程中的核心基因，肝细胞内炎症反应和免疫应答、白细胞介素-17信号通路和肿瘤坏死因子信号通路可能是NASH病理进程的关键分子机制。.