Ischemic stroke (IS) is one of the major causes of death and disability worldwide. However, the specific mechanism of gene interplay and the biological function in IS are not clear. Therefore, more research into IS is necessary. Dataset GSE110993 including 20 ischemic stroke (IS) and 20 control specimens are used to establish both groups and the raw RNA-seq data were analysed. Weighted gene co-expression network analysis (WGCNA) was used to screen the key micro-RNA modules. The centrality of key genes were determined by module membership (mm) and gene significance (GS). The key pathways were identified by enrichment analysis with Kyoto Protocol Gene and Genome Encyclopedia (KEGG), and the key genes were validated by protein-protein interactions network. Result: Upon investigation, 1185 up- and down-regulated genes were gathered and distributed into three modules in response to their degree of correlation to clinical traits of IS, among which the turquoise module show a trait-correlation of 0.77. The top 140 genes were further identified by GS and MM. KEGG analysis showed two pathways may evolve in the progress of IS. Discussion: CXCL12 and EIF2a may be important biomarkers for the accurate diagnosis and treatment in IS.

中文翻译：

---

加权基因共表达网络分析（WGCNA），其与缺血性卒中中微小RNA相关的关键途径和中枢基因。

缺血性中风（IS）是世界范围内死亡和残疾的主要原因之一。但是，尚不清楚IS中基因相互作用的具体机制和生物学功能。因此，有必要对IS进行更多的研究。使用包括20个缺血性中风（IS）和20个对照标本的数据集GSE110993建立两组，并对原始RNA-seq数据进行分析。加权基因共表达网络分析（WGCNA）用于筛选关键的微RNA模块。关键基因的中心性由模块成员（mm）和基因重要性（GS）决定。通过《京都议定书》基因和基因组百科全书（KEGG）的富集分析，确定了关键途径，并通过蛋白质-蛋白质相互作用网络验证了关键基因。结果：经调查，根据它们与IS临床特征的相关程度，收集了1185个上调和下调的基因并分配到三个模块中，其中绿松石模块的特征相关性为0.77。GS和MM进一步鉴定了前140个基因。KEGG分析显示，IS的发展可能有两种途径。讨论：CXCL12和EIF2a可能是IS准确诊断和治疗的重要生物标志物。