Screening and bioinformatics analysis of key autophagy-related genes in alcoholic hepatitis
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摘要:
目的 筛选酒精性肝炎（AH）的自噬关键基因，探讨AH潜在的生物标志物和治疗靶点。 方法 采用基因表达综合数据库（GEO）中的2个AH基因芯片和从MSigDB、GeneCards数据库中获得的自噬相关数据集，通过加权基因共表达网络分析（WGCNA）获取关键基因。对筛选的关键基因进行基因本体（GO）、京都基因和基因组百科全书（KEGG）功能富集分析，蛋白质相互作用（PPI）分析，免疫浸润分析，构建信使RNA（mRNA）-微小RNA（miRNA）网络，进行酒精性肝病不同分期的自噬相关关键基因的表达差异分析，并进一步通过实时荧光定量逆转录聚合酶链反应（RT-qPCR）在AH患者和小鼠肝脏组织中验证。 结果 本研究筛选得到了11个与AH自噬相关的基因（EEF1A2、CFTR、SOX4、TREM2、CTHRC1、HSPB8、TUBB3、PRKAA2、RNASE1、MTCL1、HGF），均为上调基因。在AH患者和小鼠肝脏组织中，SOX4、TREM2、HSPB8、PRKAA2在AH组中的相对表达量均高于对照组。 结论 SOX4、TREM2、HSPB8、PRKAA2可能是AH潜在的生物标志物和治疗靶点。 -
关键词:
- 酒精性肝炎 /
- 自噬 /
- 关键基因 /
- 生物信息学 /
- 加权基因共表达网络分析（WGCNA） /
- 基因本体（GO） /
- 京都基因和基因组百科全书（KEGG） /
- 蛋白质相互作用（PPI）
Abstract:Objective To screen key autophagy-related genes in alcoholic hepatitis (AH) and investigate potential biomarkers and therapeutic targets for AH. Methods Two AH gene chips in Gene Expression Omnibus (GEO) and autophagy-related data sets obtained from MSigDB and GeneCards databases were used, and the key genes were verified and obtained by weighted gene co-expression network analysis (WGCNA). The screened key genes were subject to gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), protein-protein interaction (PPI) and immune infiltration analyses. Messenger RNA (mRNA)- microRNA (miRNA) network was constructed to analyze the expression differences of key autophagy-related genes during different stages of AH, which were further validated by real-time fluorescence quantitative polymerase chain reaction (RT-qPCR) in the liver tissues of AH patients and mice. Results Eleven autophagy-related genes were screened in AH (EEF1A2, CFTR, SOX4, TREM2, CTHRC1, HSPB8, TUBB3, PRKAA2, RNASE1, MTCL1 and HGF), all of which were up-regulated. In the liver tissues of AH patients and mice, the relative expression levels of SOX4, TREM2, HSPB8 and PRKAA2 in the AH group were higher than those in the control group. Conclusions SOX4, TREM2, HSPB8 and PRKAA2 may be potential biomarkers and therapeutic targets for AH. -
图 1 AH相关关键基因的筛选
注：A图为GSE28619的PCA结果；B图为GSE142530的PCA结果；C图为火山图显示GSE28619中的DEG；D图为火山图显示GSE142530中的DEG；E图为GSE28619数据集中所有基因的树状图基于不同度量聚类（1-TOM）；F图为GSE142530数据集中所有基因的树状图基于不同度量聚类（1-TOM）；G图为GSE28619数据集中基因聚类模块与AH相关性的热图；H图为GSE142530数据集中基因聚类模块与AH的热图。
Figure 1. Screening of key genes associated with AH
图 2 AH中ARG的筛选及功能分析
注：A图为AH和自噬相关基因的重叠的韦恩图；B图为GSE28619中DEARG的热图；C图为GSE142530中DEARG的热图；D图示DEARG在染色体上的位置；E图为PPI图；F图为KEGG相关通路分析；G、H、I图分别示生物过程、细胞组分、分子功能的KEGG分析。
Figure 2. Screening and functional analysis of ARG associated with AH
图 3 免疫浸润分析-ssGSEA算法
注：A图为每个样本中免疫细胞含量叠加图；B图示免疫细胞之间的相关性；C图为免疫细胞含量直方图，与对照组比较，aP<0.05；D图为AH患者中的11个关键基因与免疫细胞含量的相关性分析，*P<0.05，**P<0.01，***P<0.001。
Figure 3. Immune infiltration analysis-ssGSEA algorithm
图 4 免疫浸润分析-CIBERSORT算法
注：A图为每个样本中免疫细胞含量叠加柱状图；B图示免疫细胞之间的相关性；C图为免疫细胞含量直方图，与对照组比较，aP<0.05；D图为AH患者中的11个关键基因与免疫细胞含量的相关性分析，*P<0.05，**P<0.01，***P<0.001。
Figure 4. Immune infiltration analysis-CIBERSORT algorithm
图 5 GSE155907、GSE143318数据集验证和AH不同分期的基因表达
注：A图为GSE155907数据集PCA的结果图；B图示GSE155907数据集火山图验证了11个基因均上调；C图为GSE155907数据集中11个基因表达情况箱形图；D图为GSE143318数据集PCA的结果图；E图示GSE143318数据集火山图验证了11个基因均上调；F图为GSE143318数据集中11个基因表达情况箱形图；G～P图示酒精性肝病不同分期的10种hub基因表达；与对照组比较，aP<0.05；与酒精性脂肪变性比较，bP<0.05；与急性AH比较，cP<0.05。
Figure 5. Datasets validation of GSE155907 and GSE143318 and gene expression of AH at different stages
图 6 mRNA-miRNA和mRNA-TF网络图
注：A图为mRNA-miRNA网络图；B图为描述miRNA和通路相关性的热图。
Figure 6. mRNA-miRNA and mRNA-TF network diagram
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