骨关节炎差异表达基因和关键基因的生物信息学分析

Bioinformatics Analysis of Differentially Expressed Genes and Key Genes in Osteoarthritis

目的:通过对GEO数据库中骨关节炎相关基因芯片数据分析,探究骨关节炎相关的差异和关键基因、信号通路等。方法:采用生物信息学分析方法,从GEO数据库下载人OA相关数据集GSE16464、GSE169077,应用Perl语言、R语言、R软件和Rstudio软件,进行基因的差异表达分析、功能注释等,并应用GSE117999数据集进行验证。结果:共筛选出108个差异表达基因,其中34个上调,74个下调,ABCA6、AOX1为关键基因。通路水平主要与昼夜节律、ECM-受体相互作用、p53信号通路相关。结论:多种途径参与了骨关节炎发病过程,关键基因ABCA6、AOX1在骨关节炎发病过程中起重要作用。

To explore the differences, key genes and signaling pathways related to osteoarthritis by analyzing the gene chip data related to osteoarthritis in GEO database. Methods: Bioinformatics analysis method was used to download human OA related datasets GSE16464 and GSE169077 from GEO database. Perl language, R language, R software and Rstudio software were used to analyze the dif-ferential expression of genes, functional annotation, etc., and the GSE117999 dataset was used for verification. Results: A total of 108 differentially expressed genes were screened, of which 34 were up-regulated and 74 were down-regulated. ABCA6 and AOX1 were key genes. The pathway level is mainly related to circadian rhythm, ECM-receptor interaction, and p53 signaling pathway. Conclu-sion : A variety of pathways are involved in the pathogenesis of osteoarthritis, and the key genes ABCA6 and AOX1 play an important role in the pathogenesis of osteoarthritis.