| 生物信息学分析缺血性脑卒中的差异表达基因 |
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| 引用本文： | 谭玉靓,唐文静,彭伊孟,唐标. 生物信息学分析缺血性脑卒中的差异表达基因[J]. 现代预防医学, 2020, 0(12): 2228-2232 |
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| 作者姓名： | 谭玉靓 唐文静 彭伊孟 唐标 |
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| 作者单位： | 湖南中医药大学医学院，湖南 长沙 410208 |
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| 基金项目： | 国家自然科学基金(81503385)；;2019年湖南省教育厅科学研究项目优秀青年项目(19B436)；;湖南省研究生科研创新项目(CX2018B515)； |
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| 摘 要： | 目的基于生物信息学,对缺血性脑卒中(IS)相关差异表达基因(DEGs)进行分子层面的分析,深入分析IS的发病机制和关键基因。方法从GEO数据库下载与IS相关的生物基因芯片,基于P值及log|FC|值对GEO原始数据进行筛选,确定DEGs。对DEGs进行GO功能富集分析和KEGG通路富集分析,了解DEGs介导的生物过程与代谢通路。利用String在线平台,构建DEGs的蛋白相互作用(PPI)网络。利用cytoscape的cyto Hubba软件,找出IS的关键基因。结果本研究共筛选出110个DEGs。功能和通路富集结果显示,上述基因参与MAPK、NF-kappa B、TNF等多种细胞因子和趋化因子的信号转导通路;共同介导炎症以及免疫应答、细胞凋亡等相关生物过程。PPI网络显示,这些基因之间具有相互作用关系。JUN、CXCL2和TNF为IS病理过程中的关键基因。结论本研究结果揭示,IS的发生发展与炎症密切相关。针对关键基因进行靶向治疗,如JUN、CXCL2和TNF,或许对临床防治IS具有重要的发展意义。
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| 关 键 词： | 缺血性脑卒中 生物信息学 差异表达基因 富集分析 |
Study on ischemic stroke-related differentially expressed genes based on bioinformatic analysis |
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| TAN Yu-jing,TANG Wen-jing,PENG Yin-meng,TANG Biao. Study on ischemic stroke-related differentially expressed genes based on bioinformatic analysis[J]. Modern Preventive Medicine, 2020, 0(12): 2228-2232 |
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| Authors: | TAN Yu-jing TANG Wen-jing PENG Yin-meng TANG Biao |
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| Affiliation: | *College of medicine, Hunan University of Chinese Medicine, Changsha Hunan 410208, China |
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| Abstract: | The aim of the study was to systematically analyze ischemic stroke(IS)-related differentially expressed genes(DEGs) based on bioinformatic analysis, explore the pathological mechanisms underlying IS and find out key genes.Methods We downloaded a set of IS-related bio-gene chips from GEO database. Subsequently, IS-related DEGs were determined by the value of log |FC | and P. The annotations of biological processes and pathways DEGs were performed by enrichment analysis methods. The network analysis approach using STRING was employed to construct protein-protein interaction(PPI) network. CytoHubba, a plugin which attached to cytoscape, was used to screen out hub genes. Results A total of 110 IS-related DEGs were identified, mainly involved in biological processes of inflammation, immune response and apoptosis. As for pathways, DEGs were associated with plenty cytokines and chemokines, such as MAPK, NF-kappa B, TNF,and so on. PPI network revealed a tight connection among IS-related DEGs. Further analysis identified that JUN, CXCL2 and TNF genes were served as crucial items in pathological process of IS. Conclusion The results of enrichment analysis and PPI network indicated that inflammation played a crucial role in the occurrence and development of IS. Medical interventions targeting hub genes like JUN, CXCL2 and TNF possess a potential capability to provide useful information for IS treatment. |
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| Keywords: | Ischemic stroke Bioinformatic analysis Differentially expressed genes Enrichment analysis |
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