基于加权基因共表达网络分析非动脉炎性前部缺血性视神经病变的关键基因

目的：挖掘非动脉炎性前部缺血性视神经病变的关键基因，为研究非动脉炎性前部缺血性视神经病变的发病机制提供生物信息学支持。

方法：从GEO数据库中下载大鼠GSE43671芯片数据集，使用R语言WGCNA包对基因进行分析并筛选出与临床表型相关度高的模块基因，使用ClusterProfiler包对特异性模块进行基因本体论分析(GO)及京都基因与基因组百科全书分析(KEGG)，用Cytoscape软件筛选模块内关键基因并构建关键基因-miRNA互作网络。

结果：采用WGCNA方法从GSE43671数据集中识别出22个模块，其中蓝色模块相关性系数最高。GO富集分析结果显示，模块内基因主要表现在上皮管形态发生等生物过程上，受体复合体等细胞成分上，眼晶状体结构组成等分子功能上。KEGG结果显示，模块内基因主要与神经活性配体-受体互作信号通路、人乳头瘤病毒信号通路、MAPK信号通路、PI3K/Akt信号通路等信号通路有关。通过PPI网络和Cytoscape软件筛选得到的排名前10的关键基因为Psmb9、Psma7、Map3k14、Psme1、Nfkb1、Rela、Psma5、Relb、Psmb4、Nfkb2； 预测得到6个miRNA为miR-383-5p、miR-9a-5p、miR-155-5p、miR-223-3p、miR-495、miR-325-3p。

结论：使用WGCNA方法筛选出非动脉炎性前部缺血性视神经病变的相关通路、关键基因和微小RNA，为其发病机制和治疗方法的探索提供理论依据，但该结论尚待动物实验和细胞实验加以验证。

Identification of key genes in nonarteritic anteriorischemic optic neuropathy through weighted gene co-expression network analysis

AIM: We sought to identify key genes related to nonarteritic anterior ischemic optic neuropathy(NAION)and provide bioinformatics support for elucidating the pathogenesis of NAION.

METHODS: Based on rat GSE43671 dataset, which was acquired from GEO, we identified modular genes with highly correlated clinical phenotype by WGCNA package in the R language. Then Gene Ontology(GO)and Kyoto encyclopedia of genes and genomes(KEGG)analysis were performed with ClusterProfiler package. In addition, Cytoscape was used to screen potential key genes and establish miRNA-key genes network.

RESULTS: There were 22 modules identified from the GSE43671 dataset by the WGCNA method, among which the blue module has the highest correlation coefficient. GO enrichment analysis suggested that the genes in the module mainly manifest in the epithelial tube morphogenesis and other biological processes, receptor complex and other cell components, and structural constituent of eye lens and other molecular functions. KEGG suggested that the genes in the module mainly relate to signaling pathways including neuroactive ligand-receptor interaction, human papillomavirus, MAPK and PI3K/Akt. There were 10 key genes screened by PPI network and Cytoscape including Psmb9, Psma7, Map3k14, Psme1, Nfkb1, Rela, Psma5, Relb, Psmb4 and Nfkb2, and 6 miRNA were predicted as miR-383-5p, miR-9a-5p, miR-155-5p, miR-223-3p, miR-495 and miR-325-3p.

CONCLUSION: Using the WGCNA method to screen out the relevant pathways, key genes, and microRNA for NAION, it provides a theoretical basis for exploring pathogenesis and treatment methods of NAION, however, more animal and cell experiments are needed to further validate.