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中华心脏与心律电子杂志 ›› 2023, Vol. 11 ›› Issue (01) : 32 -38. doi: 10.3877/cma.j.issn.2095-6568.2023.01.007

基础研究

肥厚型心肌病的关键基因:一项基于加权基因共表达网络的分析
华杨1, 孙劲禹1, 程晨1, 邢子琳1, 盛燕辉1, 孔祥清2, 孙伟1,()   
  1. 1. 210029 南京,南京医科大学第一附属医院(江苏省人民医院)心血管内科
    2. 215008 苏州,南京医科大学附属苏州医院心血管病中心
  • 收稿日期:2022-04-28 出版日期:2023-03-25
  • 通信作者: 孙伟

Identification of key genes and pathways in hypertrophic cardiomyopathy via weighted gene co-expression network analysis

Yang Hua1, Jinyu Sun1, Chen Cheng1, Ziling Xin1, Yanhui Sheng1, Xiangqing Kong2, Wei Sun1,()   

  1. 1. Department of Cardiology, The First Affiliated Hospital with Nanjing Medical University (Jiangsu Province Hospital), Nanjing 210029, China
    2. Center of Cardiovascular Diseases, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou 215008, China
  • Received:2022-04-28 Published:2023-03-25
  • Corresponding author: Wei Sun
引用本文:

华杨, 孙劲禹, 程晨, 邢子琳, 盛燕辉, 孔祥清, 孙伟. 肥厚型心肌病的关键基因:一项基于加权基因共表达网络的分析[J]. 中华心脏与心律电子杂志, 2023, 11(01): 32-38.

Yang Hua, Jinyu Sun, Chen Cheng, Ziling Xin, Yanhui Sheng, Xiangqing Kong, Wei Sun. Identification of key genes and pathways in hypertrophic cardiomyopathy via weighted gene co-expression network analysis[J]. Chinese Journal of Heart and Heart Rhythm(Electronic Edition), 2023, 11(01): 32-38.

目的

利用加权基因共表达网络分析(WGCNA)方法筛选与肥厚型心肌病(HCM)发生相关的关键基因,为今后的研究提供线索。

方法

首先,从公共基因表达数据库(GEO)下载GSE36961和GSE160997数据集,使用R语言中的“limma”和“WGCNA”程序包分别来筛选差异表达基因和构建基因共表达模块,并计算基因模块与样本性状之间的相关性。接着,选取相关性最强的基因模块进行基因功能基因本体论和京都基因与基因组百科全书富集分析。最后,对差异表达基因和关键模块中重叠的基因建立蛋白质相互作用网络,并使用“cytoHubba”插件筛选出内部连接度最高的枢纽基因作为HCM发病的关键基因。

结果

通过WGCNA分析构建了15个共表达基因模块,其中red模块和brown模块是与HCM相关性最高的关键模块,并通过富集分析发现关键模块内基因功能集中在细胞内阳离子稳态、含胶原细胞外基质和肌动蛋白结合等生物学过程。在文献查阅的基础上结合蛋白相互作用网络筛选出VSIG4、CD163、FCER1GLAPTM5为关键基因。

结论

本研究筛选出VSIG4、CD163、FCER1GLAPTM5为HCM的关键基因。

Objective

To identify the key genes in the occurrence and development of hypertrophic cardiomyopathy (HCM) via weighted gene co-expression network analysis.

Methods

The gene expression profiles of GSE36961 and GSE160997, downloaded from public GEO database, were analyzed by the "limma" and "WGCNA" packages in R to identify differentially expressed genes (DEGs) and key modules, respectively. Then, enrichment analysis was performed based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. A protein-protein interaction network was constructed based on the overlapped genes of DEGs and key modules, and we identified the top 4 hub genes using “cytohubba” according to inner connectivity.

Results

The red and brown modules were identified as the key modules. Enrichment analysis showed that cellular divalent inorganic cation homeostasis, collagen-containing extracellular matrix, and actin-binding were significantly enriched. Finally, VSIG4, CD163, FCER1G and LAPTM5 were identified as hub genes.

Conclusion

VSIG4, CD163, FCER1G and LAPTM5 might be hub genes associated with the progression of HCM. Further studies are required to elucidate the underlying mechanisms and provide potential therapeutic targets.

图1 GSE36961数据集(1A、1B)和GSE160997数据集(1C、1D)差异表达基因的火山图和热图[火山图中,红色为上调基因(log2差异倍数≥0.5且校正P<0.05),蓝色为下调基因(log2差异倍数≤-0.5且校正P < 0.05)]
图2 加权基因共表达网络的构建[GSE160997数据集(2A)和GSE160997数据集(2B)的样本聚类树;2C.软阈值分析;2D.模块基因聚类树(每个颜色代表一个模块,每个分支代表一个基因)]
图3 HCM关键模块的筛选(3A.全部基因的共表达网络热图;3B.模块的HCM基因显著水平分布情况;3C.ME与临床特征的相关性热图)HCM为肥厚型心肌病,ME为模块特征值
图4 关键模块的功能富集分析[red模块(4A)和brown模块(4B)的基因显著水平和模块隶属度散点图;red模块和brown模块的GO分析(4C)和KEGG分析(4D);4E.Metascape可视化基因与通路的关联;4F.基于DisGeNET和TRRUST数据库分别对临床疾病和转录调控网络水平的富集分析]BP为生物学过程,CC为细胞成分,MF为分子功能,GO为基因本体论(gene ontology,GO),KEGG为京都基因与基因组百科全书
图5 蛋白质互作网络的构建与枢纽基因的筛选[5A.关键模块的基因与差异表达基因的韦恩图;5B.“cytoHubba“插件筛选连接度最高的前10个基因;5C为重叠基因的蛋白质相互作用网络]
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