Department of Neurology , The Affiliated Hospital of Qingdao University , Qingdao , China.
Int J Neurosci. 2019 Nov;129(11):1098-1102. doi: 10.1080/00207454.2019.1634072. Epub 2019 Aug 7.
Ischemic stroke (IS) is a complex disease affected by various environmental factors, genetic factors and their interactions. Because genetic factors occupy an irreplaceable place in the pathogenesis of IS, the identification of genetic factors has become one of the hot spots in the current research. In the present study, we aimed to identify possible gene targets and relevant drug molecules in the pathogenesis of IS. Microarray dataset of GSE16561 was downloaded from Gene Expression Omnibus database. The differentially expressed genes (DEGs) between IS group and control group were obtained using limma package in R. Ground-Operation Simulation package in R language was used to cluster DEGs according to their biological process, cellular components and molecular functions with respect to the GO annotation. The DEGs were analyzed by Search Tool for the Retrieval of Interacting Genes online database and Cytoscape software to predict their interaction relationship. Finally, the DEGs were submitted to DGIdb dataset and related drug molecules were retrieved. 20 DEGs were identified from IS group including 1 downregulated and 19 upregulated genes. The function enrichment analysis revealed that the DEGs were enriched in three GO terms, mainly including inflammatory response, positive regulation of protein kinase activity and innate immune response. Finally, 10 drug molecules were identified from the DEGs. Our study identified some potential biological targets and drug molecules for the treatment of IS.
缺血性脑卒中（IS）是一种受多种环境因素、遗传因素及其相互作用影响的复杂疾病。由于遗传因素在 IS 的发病机制中占有不可替代的地位，因此遗传因素的鉴定已成为当前研究的热点之一。本研究旨在确定 IS 发病机制中的可能基因靶点和相关药物分子。从基因表达综合数据库中下载 GSE16561 的微阵列数据集。使用 R 语言中的 limma 包获取 IS 组和对照组之间的差异表达基因（DEGs）。使用 R 语言中的 Ground-Operation Simulation 包根据其生物过程、细胞成分和分子功能对 GO 注释对 DEGs 进行聚类。通过在线数据库 Search Tool for the Retrieval of Interacting Genes 和 Cytoscape 软件对 DEGs 进行分析，以预测其相互作用关系。最后，将 DEGs 提交到 DGIdb 数据集，并检索相关药物分子。从 IS 组中鉴定出 20 个 DEGs，包括 1 个下调基因和 19 个上调基因。功能富集分析表明，DEGs 主要富集在三个 GO 术语中，主要包括炎症反应、蛋白激酶活性的正调控和固有免疫反应。最后，从 DEGs 中鉴定出 10 种药物分子。本研究鉴定了一些治疗 IS 的潜在生物靶点和药物分子。
