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Identification of Metabolic Syndrome-Related miRNA–mRNA Regulatory Networks and Key Genes Based on Bioinformatics Analysis
Biochemical Genetics ( IF 2.4 ) Pub Date : 2022-07-25 , DOI: 10.1007/s10528-022-10257-w
Lingyan Qiu 1, 2 , Pei Sheng 1, 2 , Xu Wang 1, 2
Affiliation  

Metabolic syndrome, which affects approximately one-quarter of the world’s population, is a combination of multiple traits and is associated with high all-cause mortality, increased cancer risk, and other hazards. It has been shown that the epigenetic functions of miRNAs are closely related to metabolic syndrome, but epigenetic studies have not yet fully elucidated the regulatory network and key genes associated with metabolic syndrome. To perform data analysis and screening of potential differentially expressed target miRNAs, mRNAs and genes based on a bioinformatics approach using a metabolic syndrome mRNA and miRNA gene microarray, leading to further analysis and identification of metabolic syndrome-related miRNAmRNA regulatory networks and key genes. The miRNA gene set (GSE98896) and mRNA gene set (GSE98895) of peripheral blood samples from patients with metabolic syndrome from the GEO database were screened, and set|logFC|> 1 and adjusted P < 0.05 were used to identify the differentially expressed miRNAs and mRNAs. Differentially expressed miRNA transcription factors were predicted using FunRich software and subjected to GO and KEGG enrichment analysis. Next, biological process enrichment analysis of differentially expressed mRNAs was performed with Metascape. Differentially expressed miRNAs and mRNAs were identified and visualized as miRNA–mRNA regulatory networks based on the complementary pairing principle. Data analysis of genome-wide metabolic syndrome-related mRNAs was performed using the gene set enrichment analysis (GSEA) database. Finally, further WGCNA of the set of genes most closely associated with metabolic syndrome was performed to validate the findings. A total of 217 differentially expressed mRNAs and 158 differentially expressed miRNAs were identified by screening the metabolic syndrome miRNA and mRNA gene sets, and these molecules mainly included transcription factors, such as SP1, SP4, and EGR1, that function in the IL-17 signalling pathway; cytokine–cytokine receptor interaction; proteoglycan syndecan-mediated signalling events; and the glypican pathway, which is involved in the inflammatory response and glucose and lipid metabolism. miR-34C-5P, which was identified by constructing a miRNA–mRNA regulatory network, could regulate DPYSL4 expression to influence insulin β-cells, the inflammatory response and glucose oxidative catabolism. Based on GSEA, metabolic syndrome is known to be closely related to oxidative phosphorylation, DNA repair, neuronal damage, and glycolysis. Finally, RStudio and DAVID were used to perform WGCNA of the gene sets most closely associated with metabolic syndrome, and the results further validated the conclusions. Metabolic syndrome is a common metabolic disease worldwide, and its mechanism of action is closely related to the inflammatory response, glycolipid metabolism, and impaired mitochondrial function. miR-34C-5P can regulate DPYSL4 expression and can be a potential research target. In addition, UQCRQ and NDUFA8 are core genes of oxidative phosphorylation and have also been identified as potential targets for the future treatment of metabolic syndrome.



中文翻译:

基于生物信息学分析的代谢综合征相关miRNA-mRNA调控网络和关键基因的鉴定

影响世界上大约四分之一人口的代谢综合征是多种特征的组合,与高全因死亡率、癌症风险增加和其他危害有关。已有研究表明miRNA的表观遗传功能与代谢综合征密切相关,但表观遗传学研究尚未完全阐明与代谢综合征相关的调控网络和关键基因。基于生物信息学方法,使用代谢综合征 mRNA 和 miRNA 基因微阵列,对潜在差异表达的靶 miRNA、mRNA 和基因进行数据分析和筛选,从而进一步分析和鉴定代谢综合征相关的 miRNA mRNA 调控网络和关键基因。从GEO数据库中筛选代谢综合征患者外周血样本的miRNA基因集(GSE98896)和mRNA基因集(GSE98895),设置|logFC|>1,调整P < 0.05 用于鉴定差异表达的 miRNA 和 mRNA。使用 FunRich 软件预测差异表达的 miRNA 转录因子,并进行 GO 和 KEGG 富集分析。接下来,使用 Metascape 对差异表达的 mRNA 进行生物过程富集分析。基于互补配对原理,差异表达的 miRNA 和 mRNA 被鉴定并可视化为 miRNA-mRNA 调控网络。使用基因集富集分析 (GSEA) 数据库对全基因组代谢综合征相关 mRNA 进行数据分析。最后,对与代谢综合征最密切相关的一组基因进行了进一步的 WGCNA,以验证这些发现。通过筛选代谢综合征miRNA和mRNA基因组共鉴定出217个差异表达的mRNA和158个差异表达的miRNA,这些分子主要包括参与IL-17信号通路的转录因子SP1、SP4、EGR1等通路;细胞因子-细胞因子受体相互作用;蛋白聚糖聚糖介导的信号事件;以及参与炎症反应和糖脂代谢的磷脂酰肌醇蛋白聚糖通路。通过构建 miRNA-mRNA 调控网络鉴定出 miR-34C-5P,可调控 DPYSL4 表达,从而影响胰岛素 β 细胞、炎症反应和葡萄糖氧化分解代谢。基于GSEA,已知代谢综合征与氧化磷酸化、DNA修复、神经元损伤和糖酵解密切相关。最后,使用RStudio和DAVID对与代谢综合征关系最密切的基因集进行了WGCNA,结果进一步验证了结论。代谢综合征是一种世界范围内常见的代谢性疾病,其作用机制与炎症反应、糖脂代谢、线粒体功能受损等密切相关。miR-34C-5P 可以调节 DPYSL4 的表达,可以成为一个潜在的研究目标。此外,UQCRQ和NDUFA8是氧化磷酸化的核心基因,也被确定为未来治疗代谢综合征的潜在靶点。其作用机制与炎症反应、糖脂代谢、线粒体功能受损等密切相关。miR-34C-5P 可以调节 DPYSL4 的表达,可以成为一个潜在的研究目标。此外,UQCRQ和NDUFA8是氧化磷酸化的核心基因,也被确定为未来治疗代谢综合征的潜在靶点。其作用机制与炎症反应、糖脂代谢、线粒体功能受损等密切相关。miR-34C-5P 可以调节 DPYSL4 的表达,可以成为一个潜在的研究目标。此外,UQCRQ和NDUFA8是氧化磷酸化的核心基因,也被确定为未来治疗代谢综合征的潜在靶点。

更新日期:2022-07-26
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