激素性股骨头坏死风险模型构建及潜在的中药治疗预测  

Construction of a risk model of steroid-induced necrosis of the femoral head and prediction of potential Chinese medicine treatments

作　　者：章晓云[1] 高振罡 陈锋[1] 曾浩 刘桦 苏允裕[2] Zhang Xiaoyun;Gao Zhengang;Chen Feng;Zeng Hao;Liu Hua;Su Yunyu(Ruikang Hospital Affiliated to Guangxi University of Traditional Chinese Medicine,Nanning 530011,Guangxi Zhuang Autonomous Region,China;The First People’s Hospital of Qinzhou,Qinzhou 535000,Guangxi Zhuang Autonomous Region,China)

机构地区：[1]广西中医药大学附属瑞康医院,广西壮族自治区南宁市530011 [2]广西钦州市第一人民医院,广西壮族自治区钦州市535000

出　　处：《中国组织工程研究》2023年第28期4539-4545,共7页Chinese Journal of Tissue Engineering Research

基　　金：广西自然科学基金青年基金(2020GXNSFBA159053),项目负责人:章晓云;国家自然科学基金资助项目(81960803),项目参与人:章晓云;广西中医药大学一流学科课题(2019XK029),项目负责人:章晓云;广西中医药大学青年创新研究团队项目(2021TD001),项目负责人:章晓云;广西临床重点专科(创伤外科)建设项目(桂卫医发{2021}17号),项目参与人:章晓云。

摘　　要：背景:随着疾病治疗模式的改变,人们已经意识到中医药在激素性股骨头坏死治疗过程中的重要性,因此利用生物信息学从分子水平分析激素性股骨头坏死的发病机制,构建疾病风险模型,并预测具有潜在治疗作用的中药,为后期中医药治疗激素性股骨头坏死提供一定的理论依据。目的:基于生物信息学挖掘激素性股骨头坏死的竞争性内源RNA(ceRNA)调控网络,分析其在激素性股骨头坏死中的分子调控机制,预测相关疾病靶点并构建疾病风险模型,同时预测具有潜在治疗作用的中药。方法:检索GEO数据库,下载激素性股骨头坏死的矩阵文件GSE123568和基因注释文件GPL15207。借助R语言等软件分析得到差异表达的长链非编码RNA与mRNA,并通过公共数据库预测与差异表达长链非编码RNA关联的miRNA-mRNA,再将预测到的mRNA与差异表达mRNA取交集,整合得到ceRNA网络。随后采用STRING数据库和Cytoscape软件筛选关键基因,利用R语言分析关键基因的功能与相关通路,并挖掘关键ceRNA网络。最后根据关键基因构建激素性股骨头坏死的风险模型,并进行中药预测。结果与结论:(1)与健康对照相比,激素性股骨头坏死患者共有7个长链非编码RNA和1763个mRNAs存在差异表达;(2)筛选出STAT3、KAT2B、AGO4、JAK2、JAK1、PTGS2共6个关键基因;(3)关键基因所富集的功能包括对肽激素的反应、白细胞介素6介导的信号通路、细胞对白细胞介素6的反应等生物学过程,涉及JAK-STAT、脂肪细胞因子、催乳素等信号通路;(4)4种mi RNAs(mi R-135a-5p、mi R-137、mi R-17-5p、miR-20b-5p)和2种长链非编码RNA(SNHG11、C20orf197)可能在导致激素性股骨头坏死发生发展过程中发挥关键作用;(5)KAT2B最有可能是激素性股骨头坏死发生发展的风险因子;(6)郁金、淫羊藿、黄芪具备治疗激素性股骨头坏死疾病靶点的可能。通过对激素性股骨头坏死相关长链非编码RNA�BACKGROUND:With the change of disease treatment mode,people have realized the importance of traditional Chinese medicine in the treatment of steroidinduced necrosis of the femoral head(SANFH).Therefore,bioinfo rmatics is used to analyze the pathogenesis of SANFH at the molecular level,build a disease risk model,and predict the potential therapeutic effects of traditional Chinese medicine,so as to provide a theoretical basis for the treatment of SANFH by traditional Chinese medicine in the future.OBJECTIVE:To mine the competing endogenous RNA regulatory network of SANFH based on bioinformatics,analyze its molecular regulato ry mechanism in SANFH,predict relevant disease targets,build disease risk models,and predict Chinese herbal medicines with potential therapeutic effects.METHODS:The GEO database was searched to download the SANFH matrix file GSE123568 and gene annotation file GPL15207.The differentially expressed long non-coding RNAs and mRNAs were obtained by software analysis such as R language,and the miRNA-mRNAs associated with the differentially expressed long non-coding RNAs were predicted through the public database.Then,predicted and differentially expressed mRNAs were intersected and integrated to obtain the competing endogenous RNA network.STRING database and Cytoscape software were used to screen key genes and R language was used to analyze the functions and related pathways of key genes and mine the key competing endogenous RNA network.Finally,the risk model of SANFH was constructed according to the key genes and the prediction of tra ditional Chinese medicine was carried out.RESULTS AND CONCLUSION:Compared with healthy controls,a total of 7 long non-coding RNAs and 1763 mRNAs were differentially expressed in SANFH patients.Six key genes including STAT3,KAT2 B,AGO4,JAK2,JAK1,and PTGS2 were identified.The enriched functions of key genes include biological processes such as response to peptide hormones,inte rleukin-6-mediated signaling pathways,and cell responses to interleukin-6,and are involved in s

关 键 词：激素性股骨头坏死 长链非编码RNA 竞争性内源RNA 生物信息学 中药预测 

分 类 号：R459.9[医药卫生—治疗学] R318[医药卫生—临床医学] R681.8