Medical School of Chinese PLA, Beijing, 100853, China.
Department of Cardiovascular Surgery, the First Medical Centre of Chinese PLA General Hospital, Beijing 100853, China.
Heart Surg Forum. 2022 Jan 24;25(1):E069-E078. doi: 10.1532/hsf.4263.
Aortic valve stenosis (AS) disease is the most common valvular disease in developed countries. The pathology of AS is complex, and its main processes include calcification of the valve stroma and involve genetic factors, lipoprotein deposition and oxidation, chronic inflammation, osteogenic transition of cardiac valve interstitial cells, and active valve calcification. The aim of this study was to identify potential genes associated with AS.
Three original gene expression profiles (GSE153555, GSE12644, and GSE51472) were downloaded from the Gene Expression Omnibus (GEO) database and analyzed by GEO2R tool or 'limma' in R to identify differentially expressed genes (DEGs). Functional enrichment was analyzed using the ClusterProfiler package in R Bioconductor. STRING was utilized for the Protein-Protein Interaction (PPI) Network construct, and tissue-specific gene expression were identified using BioGPS database. The hub genes were screened out using the Cytoscape software. Related miRNAs were predicted in Targetscan, miWalk, miRDB, Hoctar, and TarBase.
A total of 58 upregulated genes and 20 downregulated genes were screened out, which were mostly enriched in matrix remodeling and the immune system process. A module was thus clustered into by PPI network analysis, which mainly involved in Fc gamma R-mediated phagocytosis, Osteoclast differentiation. Ten genes (IBSP, NCAM1, MMP9, FCGR3B, COL4A3, FCGR1A, THY1, RUNX2, ITGA4, and COL10A1) with the highest degree scores were subsequently identified as the hub genes for AS by applying the CytoHubba plugin. And hsa-miR-1276 was finally identified as potential miRNA and miRNA-gene regulatory network was constructed using NetworkAnalyst.
Our analysis suggested that IBSP, NCAM1, MMP9, FCGR3B, COL4A3, FCGR1A, THY1, RUNX2, ITGA4, and COL10A1 might be hub genes associated with AS, and hsa-miR-1276 was potential miRNA. This result could provide novel insight into pathology and therapy of AS in the future.
主动脉瓣狭窄（AS）疾病是发达国家最常见的瓣膜疾病。AS 的病理学较为复杂，其主要过程包括瓣膜基质的钙化，涉及遗传因素、脂蛋白沉积和氧化、慢性炎症、心脏瓣膜间质细胞的成骨转化以及活跃的瓣膜钙化。本研究旨在确定与 AS 相关的潜在基因。
从基因表达综合数据库（GEO）下载了三个原始基因表达谱（GSE153555、GSE12644 和 GSE51472），并通过 GEO2R 工具或 R 中的“limma”分析来识别差异表达基因（DEGs）。使用 R Bioconductor 中的 ClusterProfiler 包进行功能富集分析。使用 STRING 构建蛋白质-蛋白质相互作用（PPI）网络，使用 BioGPS 数据库鉴定组织特异性基因表达。使用 Cytoscape 软件筛选出枢纽基因。使用 Targetscan、miWalk、miRDB、Hoctar 和 TarBase 预测相关 miRNA。
筛选出 58 个上调基因和 20 个下调基因，这些基因主要富集在基质重塑和免疫系统过程中。通过 PPI 网络分析聚类成一个模块，主要涉及 FcγR 介导的吞噬作用、破骨细胞分化。应用 CytoHubba 插件，随后确定了具有最高度数评分的 10 个基因（IBSP、NCAM1、MMP9、FCGR3B、COL4A3、FCGR1A、THY1、RUNX2、ITGA4 和 COL10A1）作为 AS 的枢纽基因。最后，使用 NetworkAnalyst 构建了潜在的 miRNA 和 miRNA-基因调控网络。
我们的分析表明，IBSP、NCAM1、MMP9、FCGR3B、COL4A3、FCGR1A、THY1、RUNX2、ITGA4 和 COL10A1 可能是与 AS 相关的枢纽基因，hsa-miR-1276 是潜在的 miRNA。这一结果可能为未来 AS 的病理和治疗提供新的思路。
