转录组学测序解析难治性高血压基因表达特征及核心差异基因
收稿日期: 2025-04-11
修回日期: 2025-06-18
网络出版日期: 2025-07-04
基金资助
山东省自然科学基金重点项目(ZR2020KH034);中国博士后科学基金项目(2023M732139)
Characterizing transcriptomic signatures and identifying hub differentially expressed genes in resistant hypertension
Received date: 2025-04-11
Revised date: 2025-06-18
Online published: 2025-07-04
Supported by
Natural Science Foundation of Shandong Province(ZR2020KH034);China Postdoctoral Science Foundation(2023M732139)
难治性高血压(resistant hypertension, RH)是高血压疾病谱中危险类型之一，发病机制复杂。为探寻该病相关核心差异基因，本研究对2022年收集自山东中医药大学附属医院及济南市第五人民医院的30份血液样本(10例高血压患者、10例RH患者、10名健康对照者)进行了转录组测序。利用DESeq2分析筛选出731个差异表达基因(differentially expressed genes, DEGs)，并通过加权基因共表达网络分析(weighted gene co-expression network analysis, WGCNA)鉴定出2个与RH显著相关的模块(含1,944个基因)。将模块基因与DEGs取交集获得229个关键DEGs。基因本体(Gene Ontology, GO)分析显示，这些关键DEGs显著富集于药物分解代谢过程、血红蛋白复合体、过氧化物酶活性等条目；京都基因与基因组百科全书(Kyoto Encyclopedia of Genes and Genomes, KEGG)通路分析表明，这些DEGs与VEGF信号通路和线粒体自噬等通路相关。进一步构建蛋白质-蛋白质互作(protein-protein interaction, PPI)网络，并运用Cytoscape软件的cytohubba插件整合12种算法筛选核心基因(取各算法前20名基因交集)，初步确定GATA1、EPB42、ANK1、SNCA为核心差异基因。qRT-PCR验证结果证实GATA1与EPB42的表达变化与测序结果一致。该研究表明，RH的发生涉及多基因协同作用，核心基因(如GATA1、EPB42)及相关通路(如VEGF信号通路、线粒体自噬)的扰动可能在疾病进程中发挥重要作用，这为深入理解RH的病理机制提供了新线索。
关键词： 难治性高血压; 转录组学; 加权基因共表达网络分析
姜彤, 彭世靖, 王姗姗, 王昱琪, 赵文杰, 杨雯晴 . 转录组学测序解析难治性高血压基因表达特征及核心差异基因[J]. 遗传, 2026 , 48(1) : 76 -86 . DOI: 10.16288/j.yczz.25-104
Resistant hypertension (RH) is one of the high-risk types within the spectrum of hypertensive disorders, characterized by a complex pathogenesis. To identify hub differentially expressed genes (DEGs) associated with this disease, this study performed transcriptome sequencing on 30 blood samples collected in 2022 from the Affiliated Hospital of Shandong University of Traditional Chinese Medicine and Jinan Fifth People's Hospital (comprising 10 hypertensive patients, 10 RH patients, and 10 healthy controls). Using DESeq2 analysis, 731 DEGs were initially screened. Subsequently, weighted gene co-expression network analysis (WGCNA) identified 2 modules significantly associated with RH (containing 1,944 genes). Taking the intersection of these module genes and the DEGs yielded 229 key DEGs. Gene Ontology (GO) enrichment analysis revealed that these key DEGs were significantly enriched in biological processes such as drug catabolic process, cellular components like hemoglobin complex, and molecular functions including peroxidase activity. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated that these DEGs were associated with pathways such as the VEGF signaling pathway and mitophagy. A protein-protein interaction (PPI) network was further constructed. Using the cytohubba plugin in Cytoscape software, hub genes were identified by integrating the results from 12 algorithms (taking the intersection of the top 20 genes from each algorithm), preliminarily determining GATA1, EPB42, ANK1, and SNCA as the hub DEGs. Validation by qRT-PCR confirmed that the expression changes of GATA1 and EPB42 were consistent with the sequencing results. This study suggests that the development of RH involves the synergistic action of multiple genes, and perturbations in hub genes (GATA1, EPB42) and related pathways (VEGF signaling pathway, mitophagy) may play significant roles in the disease process. These findings provide new insights for a deeper understanding of the pathological mechanisms underlying RH.
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