摘要： 目的 基于生物信息学挖掘肌腱粘连相关的重要基因、通路、调控网络异常。方法 从GEO数据库获取GSE26051、GSE1724芯片数据集,分析及筛选差异表达基因 (DEGs),并对其进行富集分析,联合分析差异基因,建立蛋白质-蛋白质相互作用 (PPI) 网络,预测DEGs可能结合的miRNA,构建miRNA-mRNA网络,筛选出重要基因和miRNA。结果 联合分析筛选出2个在肌腱病差异表达显著的DEGs,与成纤维细胞TGF-β通路相关。GO分析主要富集在受体配体活性、转录激活与抑制、G蛋白耦联受体、生长因子活性等。KEGG通路富集在PI3K/AKT、MAPK、钙通道等通路。miRNA多数据库联合预测提示miR-181家族在肌腱粘连中可能发挥作用。PPI网络分析显示DLG1、CASK、CNTNAP2与EPB41的联系较为重要。结论 EPB41可能与肌腱粘连的发病机制有关。

多芯片联合分析揭示肌腱粘连的分子机制

佟春晓¹, 雷则鸣^2,3

1. 中国医科大学附属第一医院产科, 沈阳 110001;
2. 沈阳医学院附属中心医院手外五科, 沈阳 110024;
3. 中国医科大学附属盛京医院骨外科, 沈阳 110004

收稿日期:2022-07-16出版日期:2022-10-30发布日期:2022-10-14
通讯作者:雷则鸣E-mail:leizem@163.com
作者简介:佟春晓(1991-),女,医师,硕士.
基金资助:沈阳市卫生健康委员会科研项目(2021053)


关键词: 肌腱粘连, 生物信息学分析, 分子机制
Abstract: Objective To explore abnormalities in important genes,pathways,and regulatory networks related to tendon adhesion using bioinformatics techniques.Methods The GSE26051 and GSE1724 microarray datasets were obtained from the Gene Expression Omnibus database.Differentially expressed genes (DEGs) were screened and analyzed by joint bioinformatics analysis.R software was used to perform enrichment analysis.Protein-protein interaction networks were then established,micro RNAs (miRNAs) that may bind to the DEGs were predicted,miRNA-mRNA networks were constructed,and important genes and miRNAs were screened.Results Combined analysis identified two DEGs that were significantly differentially expressed in tendinopathy and were related to the fibroblast TGF-β pathway.Gene Ontology analysis showed that these DEGs were mainly enriched in receptor ligand activity,transcriptional activation and inhibition,G protein-coupled receptors,and growth factor activity.Kyoto Encyclopedia of Genes and Genomes analysis found that the DEGs were enriched in the PI3K/AKT,MAPK,calcium signaling,and other pathways.Joint prediction of miRNAs using multiple databases suggested a possible role of the miR-181 family in tendon adhesion.Protein network analysis showed important relationships between DLG1,CASK,CNTNAP2,and EPB41.Conclusion EPB41 may be related to the pathogenesis of tendon adhesion.
Key words: tendon adhesion, bioinformatics analysis, molecular mechanism
PDF全文下载地址:

https://journal.cmu.edu.cn/CN/article/downloadArticleFile.do?attachType=PDF&id=3087