Key Lab of Environment and Health, School of Public Health, Xuzhou Medical University, Xuzhou, Xuzhou, Jiangsu, China.
Comb Chem High Throughput Screen. 2023;26(2):373-382. doi: 10.2174/1386207325666220421104617.
Tetralogy of Fallot (TOF) is the most common cyanotic congenital heart disease in clinical practice. It is mainly due to cardiovascular hypoplasia during embryonic development. The study aimed to find the etiology of TOF.
Through the mRNA expression profile analysis of the GSE35776 dataset, differentially expressed genes (DEGs) were found, and the functional analysis and protein-protein interaction (PPI) network analysis were then performed on DEGs. Likewise, the hub genes and functional clusters of DEGs were analyzed using the PPI network. Differentially expressed miRNAs were analyzed from the GSE35490 dataset, followed by miRNet predicted transcription factors (TFs) and target genes. The key TF-miRNA-gene interaction mechanism was explored through the found significant difference between genes and target genes.
A total of 191 differentially expressed genes and 57 differentially expressed miRNAs were identified. The main mechanisms involved in TOF were mitochondria-related and energy metabolism- related molecules and pathways in GO and KEGG analysis. This discovery was identical in TFs and target genes. The key miRNAs, hsa-mir-16 and hsa-mir-124, were discovered by the Venn diagram. A co-expression network with the mechanism of action centered on two miRNAs was made.
Hsa-mir-16 and hsa-mir-124 are the key miRNAs of TOF, which mainly regulate the expression of NT5DC1, ECHDC1, HSDL2, FCHO2, and ACAA2 involved in the conversion of ATP in the mitochondria and the metabolic rate of fatty acids (FA). Our research provides key molecules and pathways into the etiology of TOF, which can be used as therapeutic targets.
法洛四联症(TOF)是临床实践中最常见的发绀型先天性心脏病。它主要是由于胚胎发育过程中心血管发育不良引起的。本研究旨在寻找 TOF 的病因。
通过对 GSE35776 数据集的 mRNA 表达谱分析,找到了差异表达基因(DEGs),然后对 DEGs 进行功能分析和蛋白质-蛋白质相互作用(PPI)网络分析。同样,使用 PPI 网络分析 DEGs 的枢纽基因和功能聚类。从 GSE35490 数据集分析差异表达的 miRNAs,然后使用 miRNet 预测转录因子(TFs)和靶基因。通过比较基因和靶基因之间的显著性差异,探讨关键 TF-miRNA-基因互作机制。
共鉴定出 191 个差异表达基因和 57 个差异表达 miRNA。GO 和 KEGG 分析表明,主要机制涉及与线粒体相关的和与能量代谢相关的分子和途径。这一发现与 TFs 和靶基因相同。通过 Venn 图发现了关键 miRNAs,hsa-mir-16 和 hsa-mir-124。构建了一个以两种 miRNA 为作用机制中心的共表达网络。
hsa-mir-16 和 hsa-mir-124 是 TOF 的关键 miRNA,主要调节与线粒体中 ATP 转化和脂肪酸(FA)代谢率相关的 NT5DC1、ECHDC1、HSDL2、FCHO2 和 ACAA2 的表达。我们的研究为 TOF 的病因提供了关键的分子和途径,可以作为治疗靶点。