基于基因共表达网络分析氧诱导小鼠视网膜新生血管模型免疫相关靶基因

Analysis of immune related target genes in oxygen induced mouse retinal neovascularization model based on gene co-expression network

摘要:

目的：通过生物信息学方法探究氧诱导小鼠视网膜新生血管(OIR)模型中与免疫相关的关键基因以及免疫细胞浸润水平。

方法：从GEO数据库获取基因芯片数据集，采用R语言环境中“limma”包获得差异表达基因(DEGs)，并进行GO功能富集和KEGG通路分析，基于CIBERSORT算法进行数据集免疫细胞浸润分析，通过加权基因共表达网络分析(WGCNA)筛选与免疫相关基因模块中的DEGs，利用STRING在线数据库及Cytoscape软件构建蛋白质互作(PPI)网络，利用cytoHubba模块筛选出最终的靶基因。

结果：筛选出467个表达具有显著差异性的基因，其中270个基因表达上调，197个基因表达下调。免疫浸润分析结果显示仅辅助型T细胞2(Th2 cells)高表达，且差异具有显著性(P<0.05)。WGCNA分析后，与免疫最相关模块中差异基因为66个，构建PPI网络后利用插件筛选出5个关键基因，即血管性血友病因子(vWF)、血管内皮生长因子A(VEGF-A)、Serping1、凋亡诱导因子1(AIF1)以及信号传导蛋白和转录激活物(STAT3)。

结论：采用生物信息学的方式进行OIR模型的免疫细胞浸润分析及筛选出与免疫相关的关键基因，可为视网膜新生血管性疾病的进一步研究与诊疗提供依据。

Abstract:

AIM: To identify immune-related key genes and the extent of immune cell infiltration in a oxygen-induced retinopathy(OIR)model by bioinformatics method.

METHODS: Microarray data were obtained from the GEO database, differentially expressed genes(DEGs)were identified using the “limma” R package, GO function enrichment and KEGG pathway analysis were conducted, and immune cell infiltration based on the CIBERSORT algorithm was analyzed. Weighted gene co-expression network analysis(WGCNA)was used to screen DEGs in the immune-related gene module, constructing a protein-protein interaction(PPI)network using STRING online database and Cytoscape software, and further screening final target genes using the cytoHubba plug-in.

RESULTS: A total of 467 DEGs were screened, including 270 up-regulated and 197 down-regulated genes. Helper T cell 2(Th2 cells), an immune cell type, exhibited significantly high expression levels(P<0.05). WGCNA analysis identified 66 differential genes in modules most closely related to immunity. After constructing the PPI network, 5 key genes were screened through plug-ins: von Willebrand factor(vWF), vascular endothelial growth factor A(VEGF-A), Serping1, apoptosis inducing factor 1(AIF1)and signal transducers and activators of transcription 3(STAT3).

CONCLUSION: The findings of this study provide valuable insights into immune cell infiltration in OIR as well as key genes related to immunity through bioinformatics analysis, which can serve as a reference for further research and treatment of retinal neovascular diseases.