中国组织工程研究 ›› 2019, Vol. 23 ›› Issue (3): 335-340.doi: 10.3969/j.issn.2095-4344.0797

• 骨组织构建 bone tissue construction • 上一篇    下一篇

骨关节炎基因差异谱的生物信息学分析

董政权1,魏  垒2   

  1.  (1山西医科大学第二医院骨科,山西省太原市  030001;2美国布朗大学医学院/罗德岛州医院骨科,美国罗德岛州  RI02903)
  • 收稿日期:2018-03-10 出版日期:2019-01-28 发布日期:2019-01-28
  • 通讯作者: 魏垒,博士,主任医师,美国布朗大学医学院/罗德岛州医院骨科,美国罗德岛州 RI02903
  • 作者简介:董政权,男,1991年生,山西省忻州市人,汉族,山西医科大学在读硕士。
  • 基金资助:

    国家自然科学基金(81572098),项目负责人:魏垒

Gene expression profiles in osteoarthritis: a bioinformatic analysis 

Dong Zhengquan1, Wei Lei2   

  1.  (1Department of Orthopedics, the Second Hospital of Shanxi Medical University, Taiyuan 030001, Shanxi Province, China; 2Department of Orthopedics, Warren Alpert Medical School, Brown University, Providence, RI 02903, USA)
  • Received:2018-03-10 Online:2019-01-28 Published:2019-01-28
  • Contact: Wei Lei, MD, Chief physician, Department of Orthopedics, Warren Alpert Medical School, Brown University, Providence, RI 02903, USA
  • About author:Dong Zhengquan, Master candidate, Department of Orthopedics, the Second Hospital of Shanxi Medical University, Taiyuan 030001, Shanxi Province, China
  • Supported by:

    the National Natural Science Foundation of China, No. 81572098 (to WL)

摘要:

文章快速阅读:

文题释义:
基因芯片:是目前高通量研究疾病基因表达谱的一种重要手段,可在短时间内检测大量的基因信息。
骨关节炎:是一种以退行性病理改变为基础的疾患,最常见于中老年人膝关节,其症状多表现为膝盖红肿痛、上下楼梯痛、坐起立行时膝部酸痛不适等,也会有患者表现肿胀、弹响、积液等症状,如不及时治疗,则会引起关节畸形。
摘要
背景:
骨关节炎对中老年人群的健康具有重要的威胁,其疾病发生发展受到多个基因的调控,但其具体机制尚未明确。
目的:应用生物信息学方法研究骨关节炎的差异基因表达。
方法:从GEO在线数据库中下载并分析获得在骨关节炎发生时关节滑膜组织中明显表达差异的158个基因。通过DAVID数据库对基因进行功能富集。通过STRING数据库分析蛋白质与蛋白质间相互作用关系。
结果与结论:共筛选出158个差异基因,其中上调12个,下调146个。利用DAVID数据库对差异基因进行GO和KEGG Pathway分析显示,差异基因主要富集在破骨细胞分化的正性调节、细胞连接等功能以及MAPK信号通路、PI3K-Akt信号通路及ECM受体相互作用等信号通路。将差异基因进行蛋白质相互作用分析后筛选出网络的核心基因为VEGFA,JUN,PRKACA,PXN,SPTAN1,核心基因之间存在复杂的相互作用。结果证实,差异基因的相互作用可能与骨关节炎的发生有关,可为骨关节炎的诊疗提供新的靶点。

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
ORCID: 0000-0002-9975-7542(董政权)

关键词: 骨关节炎, 生物信息学分析, 差异基因, 基因芯片, 生物功能, 组织工程, 破骨细胞分化, 细胞连接, MAKP信号通路, P13K-Akt信号通路, 蛋白质相互作用

Abstract:

BACKGROUND: Osteoarthritis is a threat for middle-aged and older adults. The development and occurrence of osteoarthritis is regulated by various genes, however, the signaling pathways remain unclear.
OBJECTIVE: To investigate the gene expression profiles of osteoarthritis based on a bioinformatics analysis.
METHODS: Totally 158 differentially expressed genes during the process of osteoarthritis were obtained from the analysis of synovial tissue data downloaded from the Gene Expression Omnibus database. The functional annotation of gene expression difference was analyzed by DAVID online database. The protein-protein interactions were evaluated by STRING online database.
RESULTS AND CONCLUSION: Total 158 differentially expressed genes were identified, including 12 up-regulated genes and 146 down-regulated genes. The Gene Ontology annotation analysis and the KEGG pathway enrichment analysis were performed on DAVID online database, and the results showed that these differentially expressed genes were mainly involved in positive regulation of osteoclast differentiation and cell-cell adhesion, and these pathways were mainly involved in MAPK signaling pathway, P13K-Akt signaling pathway and ECM receptor. The protein-protein interactions of target genes were analyzed and the hub genes such as VEGFA, JUN, PRKACA, PXN and SPTAN1 were identified. In summary, the interaction of these genes may be involved in the process of osteoarthritis, and the network provides a potential target for the diagnosis and treatment of osteoarthritis.

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

Key words: Tissue Engineering, Gene Regulatory Networks, Computational Biology

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