Department of Cardiology, The Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai 264000, China.
Dis Markers. 2022 Aug 22;2022:2081590. doi: 10.1155/2022/2081590. eCollection 2022.
This research is aimed at identifying the key genes and pathways of cardiac hypertrophy using bioinformatics and at providing a new target for the identification of cardiac hypertrophy.
Microarray data GSE1621 and GSE18801 were acquired from the GEO database. The DEGs of GSE1621 and GSE18801 were analyzed using the online tool GEO2R. "ggplot2" package of R software was utilized to generate the volcano plots. The top and bottom 10 genes were mapped as a heat map. GO functional annotation analysis and KEGG pathway enrichment analysis were performed separately for DEGs using the online software DAVID. Histograms were plotted using the R "ggplot2" package. The DEGs were imported into the STRING online database for constructing PPI networks and analyzing the DEG interaction relationships.
In the present study, 469 DEGs were screened in GSE1621 and a total of 793 DEGs were screened in GSE18801. GO analyses indicate that DEGs were mainly involved in cardiac muscle contraction, regulation of blood circulation, regulation of muscle contraction, muscle contraction, striated muscle contraction, regulation of heart contraction, regulation of striated muscle contraction, and tissue remodeling. KEGG analyses indicate that DEGs were mainly involved in Th17 cell differentiation, Th1 and Th2 cell differentiation, HIF-1 signaling pathway, pathways in cancer, hematopoietic cell lineage, Chagas disease and cell adhesion molecules, viral myocarditis, central carbon metabolism in cancer, acute myeloid leukemia, and JAK-STAT signaling pathway. Eight hub genes were screened, including Akt1, Lox, Timp1, Col1al, Spp1, Ccnd1, Mmp3, and Egfr.
The DEGs associated with cardiac hypertrophy were screened via bioinformatics analysis, and eight hub genes were identified, including Akt1, Lox, Timp1, Col1al, Spp1, Ccnd1, Mmp3, and Egfr, which might be a new target for the identification of cardiac hypertrophy.
本研究旨在利用生物信息学鉴定心肌肥厚的关键基因和途径，为心肌肥厚的鉴定提供新的靶点。
从 GEO 数据库中获取微阵列数据 GSE1621 和 GSE18801。使用在线工具 GEO2R 分析 GSE1621 和 GSE18801 的差异表达基因（DEGs）。使用 R 软件的“ggplot2”包生成火山图。将前 10 个和后 10 个基因映射为热图。使用在线软件 DAVID 分别对 DEGs 进行 GO 功能注释分析和 KEGG 通路富集分析。使用 R“ggplot2”包绘制直方图。将 DEGs 导入 STRING 在线数据库，构建 PPI 网络并分析 DEG 相互作用关系。
在本研究中，在 GSE1621 中筛选出 469 个 DEGs，在 GSE18801 中筛选出总共 793 个 DEGs。GO 分析表明，DEGs 主要参与心肌收缩、血液循环调节、肌肉收缩调节、肌肉收缩、横纹肌收缩、心脏收缩调节、横纹肌收缩调节和组织重塑。KEGG 分析表明，DEGs 主要参与 Th17 细胞分化、Th1 和 Th2 细胞分化、HIF-1 信号通路、癌症途径、造血细胞谱系、恰加斯病和细胞黏附分子、病毒性心肌炎、癌症中中心碳代谢、急性髓细胞白血病和 JAK-STAT 信号通路。筛选出 8 个枢纽基因，包括 Akt1、Lox、Timp1、Col1al、Spp1、Ccnd1、Mmp3 和 Egfr。
通过生物信息学分析筛选出与心肌肥厚相关的 DEGs，鉴定出 8 个枢纽基因，包括 Akt1、Lox、Timp1、Col1al、Spp1、Ccnd1、Mmp3 和 Egfr，可能成为心肌肥厚鉴定的新靶点。
