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生物信息学分析鉴定肺动脉高压的信号通路和枢纽基因。

Identification of Signal Pathways and Hub Genes of Pulmonary Arterial Hypertension by Bioinformatic Analysis.

机构信息

Department of Pulmonary and Critical Care Medicine, Beijing Chaoyang Hospital Affiliated to the Capital Medical University, Beijing 100020, China.

Department of Pulmonary and Critical Care Medicine, Beijing Anzhen Hospital Affiliated to the Capital Medical University, Beijing 100029, China.

出版信息

Can Respir J. 2022 Aug 29;2022:1394088. doi: 10.1155/2022/1394088. eCollection 2022.

Abstract

Pulmonary arterial hypertension (PAH) is a progressive and complex pulmonary vascular disease with poor prognosis. The aim of this study was to provide a new understanding of the pathogenesis of disease and potential treatment targets for patients with PAH based on multiple-microarray analysis.Two microarray datasets (GSE53408 and GSE113439) downloaded from the Gene Expression Omnibus (GEO) database were analysed. All the raw data were processed by R, and differentially expressed genes (DEGs) were screened out by the "limma" package. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed and visualized by R and Cytoscape software. Protein-protein interactions (PPI) of DEGs were analysed based on the NetworkAnalyst online tool. A total of 442 upregulated DEGs and 84 downregulated DEGs were identified. GO enrichment analysis showed that these DEGs were mainly enriched in mitotic nuclear division, organelle fission, chromosome segregation, nuclear division, and sister chromatid segregation. Significant KEGG pathway enrichment included ribosome biogenesis in eukaryotes, RNA transport, proteoglycans in cancer, dilated cardiomyopathy, rheumatoid arthritis, vascular smooth muscle contraction, focal adhesion, regulation of the actin cytoskeleton, and hypertrophic cardiomyopathy. The PPI network identified 10 hub genes including HSP90AA1, CDC5L, MDM2, LRRK2, CFTR, IQGAP1, CAND1, TOP2A, DDX21, and HIF1A. We elucidated potential biomarkers and therapeutic targets for PAH by bioinformatic analysis, which provides a theoretical basis for future study.

摘要

肺动脉高压(PAH)是一种进行性和复杂的肺血管疾病,预后不良。本研究旨在通过多微阵列分析为 PAH 患者的疾病发病机制和潜在治疗靶点提供新的认识。从基因表达综合数据库(GEO)下载了两个微阵列数据集(GSE53408 和 GSE113439),并进行了分析。所有原始数据均由 R 处理,使用“limma”软件包筛选出差异表达基因(DEGs)。使用 R 和 Cytoscape 软件进行基因本体论(GO)和京都基因与基因组百科全书(KEGG)通路富集分析,并进行可视化。基于 NetworkAnalyst 在线工具分析 DEGs 的蛋白质-蛋白质相互作用(PPI)。鉴定出 442 个上调 DEGs 和 84 个下调 DEGs。GO 富集分析表明,这些 DEGs 主要富集于有丝分裂核分裂、细胞器分裂、染色体分离、核分裂和姐妹染色单体分离。显著的 KEGG 通路富集包括真核生物核糖体生物发生、RNA 转运、癌症中的蛋白聚糖、扩张型心肌病、类风湿性关节炎、血管平滑肌收缩、焦点黏附、肌动蛋白细胞骨架的调节和肥厚型心肌病。PPI 网络鉴定出 10 个关键基因,包括 HSP90AA1、CDC5L、MDM2、LRRK2、CFTR、IQGAP1、CAND1、TOP2A、DDX21 和 HIF1A。通过生物信息学分析,我们阐明了 PAH 的潜在生物标志物和治疗靶点,为未来的研究提供了理论基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7a55/9444450/8429ba9a8af6/CRJ2022-1394088.001.jpg

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