中国组织工程研究

中国组织工程研究 ›› 2022, Vol. 26 ›› Issue (29): 4672-4679.doi: 10.12307/2022.883

• 组织构建临床实践 clinical practice in tissue construction • 上一篇    下一篇

骨关节炎外周血生物学标志物及治疗药物的生物信息学分析

杨  威1，韩清民2   

  1. 1广州中医药大学第三临床医学院，广东省广州市  510405；2广州中医药大学第三附属医院，广东省广州市  510405
  • 收稿日期:2021-09-30 接受日期:2021-12-11 出版日期:2022-10-18 发布日期:2022-03-28
  • 通讯作者: 韩清民，博士，主任医师，教授，博士生导师，广州中医药大学第三附属医院，广东省广州市 510405
  • 作者简介:杨威，男，1988年生，湖北省公安县人，汉族，广州中医药大学第三临床医学院在读博士，主治医师，主要从事中医药治疗骨伤疾病研究。
  • 基金资助:
    重大疑难疾病中西医临床协作试点项目-退行性骨关节病(广东)(国中医药办医政发[2018]3号)，协作单位项目负责人：韩清民

Exploring peripheral blood biomarkers and therapeutic drugs for osteoarthritis based on bioinformatics

Yang Wei1, Han Qingmin2    

  1. 1The Third Clinical Medical College of Guangzhou University of Chinese Medicine, Guangzhou 510405, Guangdong Province, China; 2The Third Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou 510405, Guangdong Province, China
  • Received:2021-09-30 Accepted:2021-12-11 Online:2022-10-18 Published:2022-03-28
  • Contact: Han Qingmin, MD, Chief physician, Professor, Doctoral supervisor, The Third Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou 510405, Guangdong Province, China
  • About author:Yang Wei, MD candidate, Attending physician, The Third Clinical Medical College of Guangzhou University of Chinese Medicine, Guangzhou 510405, Guangdong Province, China
  • Supported by:
    A Pilot Project of Clinical Collaboration between Traditional Chinese Medicine and Western Medicine for the Major and Difficult Diseases-Degenerative Osteoarthrosis (Guangdong), No. State Council Medical Affairs Office [2018]3 (to HQM)

PDF

129

摘要：

文题释义：
外周血单个核细胞(peripheral blood mononuclear cells，PBMCs)：是外周循环血中具有单个核细胞的总称，单个核是相对多个核或分叶核粒细胞而言，除少数祖细胞群体外，主要包括淋巴细胞、单核细胞(Monocyte)、树突状细胞和自然杀伤(NK)细胞等，单核细胞可以发育为各种组织巨噬细胞，外周血单个核细胞为免疫系统的主要组成部分，参与人体固有或适应性免疫应答。
关联性图谱(CMap)：全称为Connectivity Map(https://www.clue.io/)，用世界上最大的扰动驱动基因表达数据集解开生物学奥秘，它运用全基因组转录谱系统全面地描述疾病、生理病理及药物诱导等生物学过程，以基因集富集分析(GSEA)算法提取并比较这些生物学过程的基因表达标识，将相似或相反功能药物、药物适用疾病及其作用途径(基因、通路)等联系起来，最常用于识别治疗疾病的候选药物。

背景：目前没有监测骨关节炎发生或进展的敏感标志物，检测骨关节炎活动期外周血基因表达谱变化，有助于探寻血液中精确的诊疗靶点及阐释发病机制。
目的：通过生物信息学方法同时分析骨关节炎与正常人外周血单个核细胞及滑膜基因表达谱差异，从分子层面探索血液中骨关节炎的诊疗靶点和治疗药物，为研究骨关节炎提供新思路。
方法：从GEO和ArrayExpress数据库中找到GSE48556和GSE55235数据集。共纳入105例骨关节炎患者血液、24例正常人血液、10例骨关节炎患者滑膜和10例正常滑膜。用R语言limma包分别筛选出骨关节炎和正常人之间血液和滑膜的差异表达基因，取交集。通过DAVID对差异表达基因进行GO和KEGG通路分析。用STRING和Cytoscape软件构件PPI网络，Mcode插件进行模块分析，Cytohubba筛选出关键基因。将差异表达基因导入关联性图谱(CMap)在线平台筛选负相关的前10小分子药物。
结果与结论：①共获得142个差异表达基因，其中上调基因75个，下调基因67个。②对所有差异表达基因进行GO富集分析，主要集中在T细胞活化、白细胞迁移、白细胞-细胞黏附、细胞黏附的正调控和淋巴细胞活化的调节等条目；KEGG主要富集在MAPK信号通路、Rap1信号通路、Ras信号通路、B细胞受体信号通路和趋化因子信号通路等通路。③利用PPI网络及相关插件筛选出丝裂原活化蛋白激酶1、血管内皮生长因子A、生长因子受体结合蛋白2、早期生长反应蛋白1和Ras相关C3肉毒杆菌毒素底物2等基因与骨关节炎细胞凋亡和免疫炎症高度相关。④CMap筛选出一些具有潜在治疗作用的小分子物：靛玉红和倍氯米松等。⑤通过生物信息学分析发现骨关节炎和正常人的外周血单个核细胞和滑膜基因表达差异集中在细胞凋亡和炎症反应的生物学事件中，从而使血液表达谱成为监测骨关节炎靶点标记物和研究其潜在分子药物的有效突破口。
缩略语：外周血单个核细胞：peripheral blood mononuclear cells，PBMCs

https://orcid.org/0000-0003-1264-8122 (杨威) 

中国组织工程研究杂志出版内容重点：组织构建；骨细胞；软骨细胞；细胞培养；成纤维细胞；血管内皮细胞；骨质疏松；组织工程

关键词: 骨关节炎, 外周血单个核细胞, 滑膜, 基因表达谱, 凋亡, 炎症, 关联性图谱, 生物信息学

Abstract: BACKGROUND: There are still no sensitive markers for monitoring the occurrence or progression of osteoarthritis. The detection of changes in peripheral blood gene expression profiles during the active period of osteoarthritis is helpful to explore the precise targets for diagnosis and treatment in the blood and explain the pathogenesis. 
OBJECTIVE: To simultaneously analyze the differences in gene expression profiles of peripheral blood mononuclear cells and synovium between osteoarthritis and normal human using bioinformatics methods, to explore the diagnosis and treatment targets and therapeutic drugs of osteoarthritis in the blood from the molecular level, and to provide a new perspective on the study of osteoarthritis.
METHODS: We found GSE48556 and GSE55235 data sets from GEO and ArrayExpress databases. Blood samples from 105 patients with osteoarthritis and 24 normal controls and synovial samples from 10 patients with osteoarthritis and 10 normal controls were included. We used the R language limma package to screen differentially expressed genes in blood and synovium between osteoarthritis and normal controls and to identify the intersected genes. The gene ontology and KEGG pathways of differentially expressed genes were analyzed by DAVID. We used STRING and Cytoscape software to construct a protein-protein interaction network, used Mcode plug-in for module analysis, and used Cytohubba to screen out key genes. We imported differentially expressed genes into the online platform of Connectivity Map to screen out the top 10 small molecule drugs that are negatively related.
RESULTS AND CONCLUSION: A total of 142 differentially expressed genes were obtained, of which 75 were up-regulated genes and 67 were down-regulated genes. The gene ontology enrichment analysis of all differentially expressed genes mainly focused on T cell activation, leukocyte migration, leukocyte-cell adhesion, positive regulation of cell adhesion, and regulation of lymphocyte activation. The kyotoencyclopedia of genes and genomes was mainly enriched in the MAPK signaling pathway, Rap1 signaling pathway, Ras signaling pathway, B cell receptor signaling pathway, and chemokine signaling pathway. The protein-protein interaction network and related plug-ins were used to screen out 10 genes including mitogen-activated protein kinase 1, vascular endothelial growth factor A, growth factor receptor binding protein 2, early growth response protein 1 and ras-related c3 botulinum toxin substrate 2, which were highly related to cell apoptosis and immune inflammation in osteoarthritis. Connectivity Map screened out some small molecules with potential therapeutic effects, such as indirubin and beclomethasone. To conclude, the bioinformatics analysis can indicate that the differences of gene expression in peripheral blood mononuclear cells and synovium between osteoarthritis patients and normal controls are concentrated in the biological events of apoptosis and inflammation, so that the blood expression profile becomes an effective breakthrough for monitoring target markers of osteoarthritis and studying their potential molecules for drugs.

Key words: osteoarthritis, peripheral blood mononuclear cell, synovium, gene expression profile, apoptosis, inflammation, Connectivity Map, bioinformatics

中图分类号: