Weighted Gene Co-Expression Network Analysis Identifies Critical Genes in the Development of Heart Failure After Acute Myocardial Infarction
Weighted Gene Co-Expression Network Analysis Identifies Critical Genes in the Development of Heart Failure After Acute Myocardial Infarction
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DOI：
10.3389/fgene.2019.01214
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发表时间：
2019-11-26
影响因子：
3.7
通讯作者：
Zhang, Zheng
中科院分区：
文献类型：
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作者：
Niu, Xiaowei;Zhang, Jingjing;Zhang, Zheng
背景：心力衰竭(HF)的发展仍然是急性心肌梗死(AMI)后的常见并发症，并与严重的不良后果有关。然而，对于脑梗塞后心力衰竭的特异性预测生物标志物和候选治疗靶点还没有完全确定。我们试图进行加权基因共表达网络分析(WGCNA)，以确定与急性心肌梗死后心衰发生有关的关键模块、中枢基因和可能的调控靶点。方法：将GSE59867数据集中不同样本中表达水平差异最大(前50%)的基因导入WGCNA。对关键模块中的基因进行基因本体论和途径富集化分析。利用基因芯片探针再注释和生物信息学数据库构建基因调控网络。从关键模块中筛选出HUB基因，并使用其他数据集进行验证。结果：在6个月内发生心力衰竭的急性心肌梗死患者和未发生心力衰竭的患者之间，共鉴定出10,265个变异最大的基因和6个模块。具体地说，蓝色模块被发现与梗死后心力衰竭的发展最显著相关。功能浓缩分析表明，蓝色模块主要与炎症反应、免疫系统和细胞凋亡有关。包括SPI1、ZBTB7A、IRF8、PPARG、P65、KLF4和Fos在内的7个转录因子被鉴定为潜在的蓝色模块中基因表达的调节因子。此外，包括miR-142-3p和LINC00537在内的非编码RNA被鉴定为与蓝色模块中的基因具有密切的相互作用。共有6个HUB基因(BCL3、HCK、PPIF、S100A9、SERPINA1和TBC1D9B)被识别并验证了它们在识别未来HF方面的预测价值。结论：通过WGCNA，我们对与急性心肌梗死后心衰发生相关的潜在分子机制和分子标志物提供了新的见解，可能有助于改善急性心肌梗死患者的危险分层、治疗决策和预后预测。
Background: The development of heart failure (HF) remains a common complication following an acute myocardial infarction (AMI), and is associated with substantial adverse outcomes. However, the specific predictive biomarkers and candidate therapeutic targets for post-infarction HF have not been fully established. We sought to perform a weighted gene co-expression network analysis (WGCNA) to identify key modules, hub genes, and possible regulatory targets involved in the development of HF following AMI.Methods: Genes exhibiting the most (top 50%) variation in expression levels across samples in a GSE59867 dataset were imported to the WGCNA. Gene Ontology and pathway enrichment analyses were performed on genes identified in the key module by Metascape. Gene regulatory networks were constructed using the microarray probe reannotation and bioinformatics database. Hub genes were screened out from the key module and validated using other datasets.Results: A total of 10,265 most varied genes and six modules were identified between AMI patients who developed HF within 6 months of follow-up and those who did not. Specifically, the blue module was found to be the most significantly related to the development of post-infarction HF. Functional enrichment analysis revealed that the blue module was primarily associated with the inflammatory response, immune system, and apoptosis. Seven transcriptional factors, including SPI1, ZBTB7A, IRF8, PPARG, P65, KLF4, and Fos, were identified as potential regulators of the expression of genes identified in the blue module. Further, non-coding RNAs, including miR-142-3p and LINC00537, were identified as having close interactions with genes from the blue module. A total of six hub genes (BCL3, HCK, PPIF, S100A9, SERPINA1, and TBC1D9B) were identified and validated for their predictive value in identifying future HFs.Conclusions: By using the WGCNA, we provide new insights into the underlying molecular mechanism and molecular markers correlated with HF development following an AMI, which may serve to improve risk stratification, therapeutic decisions, and prognosis prediction in AMI patients.