脑卒中和骨质疏松症相关关键基因的生物信息学分析  

Bioinformatics analysis of key differential expressed genes related to stroke and osteoporosis

作　　者：魏群[1] 赵杭 赵静[3] 吴永强 任静[4] 侯慧玉[1] 杭景仙[1] 宋艳梅[1] 张玮[2] Wei Qun;Zhao Hang;Zhao Jing;Wu Yongqiang;Ren Jing;Hou Huiyu;Hang Jingxian;Song Yanmei;Zhang Wei(Department of Hospital Infection Control/Department of Public Health,Hebei General Hospital,Shijiazhuang 050051,China;Center of Metabolic Diseases and Tumor Research,Hebei Key Laboratory of kidney disease,Department of Pathology,Hebei Medical University,Hebei Shijiazhuang 050017,China;Department of Chinese Medicine and Pharmacology,College of Integrated Chinese and Western Medicine,Hebei Medical University,Hebei Shijiazhuang 050017,China;Hebei Blood Center,Shijiazhuang 050000,China)

机构地区：[1]河北省人民医院医院感染管理科/公共卫生科,石家庄050051 [2]河北医科大学病理教研室河北省肾脏病重点实验室代谢性疾病与肿瘤研究中心,石家庄050017 [3]河北医科大学中西医结合学院中药与中药药理教研室,石家庄050017 [4]河北省血液中心,石家庄050000

出　　处：《中华老年骨科与康复电子杂志》2021年第6期364-371,共8页Chinese Journal of Geriatric Orthopaedics and Rehabilitation(Electronic Edition)

基　　金：国家自然科学基金(81800623);河北省自然科学基金(H2021206127);河北省卫健委重点科技研究计划(20180044);河北省高等学校科学技术研究项目(QN2021097)。

摘　　要：目的通过生物信息学方法分析脑卒中和骨质疏松症之间发生发展相关的差异基因与调控信号通路。方法分别检索美国国立生物技术信息中心(NCBI)公共基因芯片数据平台(GEO)数据库中脑卒中和骨质疏松症表达基因的芯片数据,并按照纳入标准筛选芯片样本。对数据进行汇总,运用R语言和GEO2R在线工具获取矫正后差异基因表达水平的标准化数据。借助基因本体论数据库、京都基因和基因组数据库(KEGG)、WikiPathways、Reactome数据库、基因/蛋白质相互作用关系检索工具、R语言、Cytoscape分析软件及Metascape等数据库和分析工具,进行差异表达基因分析、功能注释和富集分析。结果筛选出与脑卒中和骨质疏松症二者均相关的72个DEGs,GO分析显示DEGs生物学功能主要涉及干细胞分化过程的负向调控,KEGG、WikiPathways、Reactome等数据库显示DEGs主要参与免疫系统中的细胞因子信号转导等信号通路。蛋白质相互作用网络筛选出SMARCA4、SMARCA2、SMC1A、MSL3、CBX5、NFKB2、HIRA、CASP1、VCP和CD86共10个关键基因。结论采用生物信息学技术筛选出与脑卒中骨质疏松患者发病相关的DEGs主要参与免疫系统中的细胞因子信号转导等信号通路,为进一步探讨二者发生发展的关联及其分子机制提供新的研究线索及方向。Objective To analyse the key differential expressed genes and regulatory signaling pathways between stroke and osteoporosis by bioinformatics methods.Methods The microarray data of stroke and osteoporosis genes were retrieved from the GEO database of the National Center for Biotechnology Information(NCBI),and the microarray samples were screened according to the inclusion criteria.The data were aggregated and were normalized before analysis by the R language and the GEO2R online tool to obtain differential expressed genes between patients and controls.Then,the Gene Ontology database,Kyoto Gene and Genome Database(KEGG),WikiPathways,Reactome database,gene/protein interaction retrieval tool,R language,Cytoscape analysis software and Metascape databases and analysis tools were used to perform differentially expressed gene analysis,functional annotation,and enrichment analysis.Results A total of 72 DEGs associated with both stroke and osteoporosis were screened out.GO analysis showed that the biological function of DEGs was mainly involved in the negative regulation of stem cell differentiation.KEGG,WikiPathways,Reactome and other databases show that DEGs is mainly enriched in cytokine signal transductions and other signaling pathways in the immune system.Ten key genes,SMARCA4,SMARCA2,SMC1A,MSL3,CBX5,NFKB2,HIRA,CASP1,VCP and CD86,were screened by protein interaction network.Conclusion The DEGs screened by bioinformatics technology,which related to the pathogenesis of stroke patients and osteoporosis,mainly involved in cytokine signaling in immune system,providing new research clues and directions for further exploring the correlation between the occurrence and development of the two and their molecular mechanism.

关 键 词：脑卒中 骨质疏松 差异基因表达 生物信息学 

分 类 号：R743.3[医药卫生—神经病学与精神病学] R580[医药卫生—临床医学]