基于生物信息学筛选骨关节炎免疫浸润相关基因

Screening of Genes Related to Immune Infiltration in Osteoarthritis Based on Bioinformatics

摘要

为筛选骨关节炎(osteoarthritis, OA)免疫浸润相关基因, 从基因表达数据库(Gene Expression Omnibus, GEO)中获取多个芯片数据, 分为训练集以及验证集, 筛选出差异表达基因(differentially expressed gene, DEG); 采用基因集富集分析(Gene Set Enrichment Analysis, GSEA)软件对训练集所有基因进行基因本体论(Gene Ontology, GO)与京都基因和基因组数据库(Kyoto Encyclopedia of Genes and Genomes, KEGG)分析, 同时对DEG进行GO及KEGG分析, 并构建DEG蛋白质相互作用网络, 筛选关键基因; 利用验证集对关键基因进行差异验证, 并判断关键基因的诊断价值; 通过单样本基因集富集分析(single sample gene set enrichment analysis, ssGSEA)算法获得28种免疫细胞在OA的含量及比例; 利用Spearman相关性分析计算关键基因表达与免疫细胞浸润的相关性。结果显示, OA与正常软骨组织之间有27个DEG; OA样本的基因表达改变主要涉及体液免疫反应与组氨酸代谢信号通路等过程; DEG与金黄色葡萄球菌感染相关信号通路和NOD样受体信号通路相关; 从DEG中筛选得到4个关键基因, 即CAMP、S100A8、DEFA3和COL5A2, 它们在OA组织中异常表达并具有较高的诊断价值。进一步的免疫细胞浸润分析结果显示, 在OA软骨组织中活化B细胞等免疫细胞变化显著, 且4个关键基因与免疫浸润有显著的相关性。研究结果表明, 活化B细胞等免疫相关细胞在OA的发生发展中有着重要的作用; CAMP、S100A8、DEFA3和COL5A2是免疫浸润相关的关键基因, 与OA发生发展密切相关。

Abstract

To screen immune infiltration related genes in osteoarthritis (OA), multiple microarray data were obtained from Gene Expression Omnibus (GEO) database, and divided into a training set and a validation set to screen out the differentially expressed genes (DEGs). Then all genes in the training set were analyzed using Gene Set Enrichment Analysis (GSEA) software for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Subsequently, GO and KEGG analyses of DEGs were performed, and a pro-tein-protein interaction (PPI) network of the DEGs was constructed to screen hub genes. The validation set was used for differential validation of hub genes and determination of their diagnostic value. The content and proportion of 28 immune cells in the OA samples were obtained using the single sample gene set enrichment analysis (ssGSEA) algorithm, and the correlation between key gene expression and immune cell infiltration was calculated by Spearman’s correlation analysis. There were 27 DEGs found between the OA and normal car-tilage tissues. The GSEA results showed that gene expression changes in the OA samples were mainly in-volved in the processes such as humoral immune responses and histidine metabolic signaling pathways. GO and KEGG analyses of DEGs showed that the DEGs were associated with signaling pathways related to Staphylococcus aureus infection and NOD-like receptor signaling pathways. Four hub genes CAMP, S100A8, DEFA3, and COL5A2 were screened out from the DEGs, and their abnormal expressions in the OA tissues and high diagnostic value were confirmed. Further analysis of immune cell infiltration showed that obvious changes occurred in activated B cells and other immune cells in the OA cartilage tissues, and the four hub genes were significantly correlated with immune infiltration. The results indicated that activated B cells and other immune cells play an important role in the occurrence and development of OA, and CAMP, S100A8, DEFA3, and COL5A2 are hub genes associated with immune infiltration, which are closely related to the occurrence and development of OA.

关键词

生物信息学 / 骨关节炎(OA) / 基因集富集分析(GSEA) / 免疫浸润 / 关键基因

Key words

bioinformatics / osteoarthritis (OA) / Gene Set Enrichment Analysis (GSEA) / immune infiltration / hub gene