加权相关网络生物信息学揭示了驱动左侧心力衰竭的关键分子生物标志物。
Weighted correlation network bioinformatics uncovers a key molecular biosignature driving the left-sided heart failure.
机构信息
Department of Cardiology, The First Affiliated Hospital of Nanchang University, No. 17 Yongwaizheng Street, Nanchang, 330006, Jiangxi province, China.
Hypertension Research Institute of Jiangxi Province, Nanchang, 330006, China.
出版信息
BMC Med Genomics. 2020 Jul 3;13(1):93. doi: 10.1186/s12920-020-00750-9.
BACKGROUND
Left-sided heart failure (HF) is documented as a key prognostic factor in HF. However, the relative molecular mechanisms underlying left-sided HF is unknown. The purpose of this study is to unearth significant modules, pivotal genes and candidate regulatory components governing the progression of left-sided HF by bioinformatical analysis.
METHODS
A total of 319 samples in GSE57345 dataset were used for weighted gene correlation network analysis (WGCNA). ClusterProfiler package in R was used to conduct functional enrichment for genes uncovered from the modules of interest. Regulatory networks of genes were built using Cytoscape while Enrichr database was used for identification of transcription factors (TFs). The MCODE plugin was used for identifying hub genes in the modules of interest and their validation was performed based on GSE1869 dataset.
RESULTS
A total of six significant modules were identified. Notably, the blue module was confirmed as the most crucially associated with left-sided HF, ischemic heart disease (ISCH) and dilated cardiomyopathy (CMP). Functional enrichment conveyed that genes belonging to this module were mainly those driving the extracellular matrix-associated processes such as extracellular matrix structural constituent and collagen binding. A total of seven transcriptional factors, including Suppressor of Zeste 12 Protein Homolog (SUZ12) and nuclear factor erythroid 2 like 2 (NFE2L2), adrenergic receptor (AR), were identified as possible regulators of coexpression genes identified in the blue module. A total of three key genes (OGN, HTRA1 and MXRA5) were retained after validation of their prognostic value in left-sided HF. The results of functional enrichment confirmed that these key genes were primarily involved in response to transforming growth factor beta and extracellular matrix.
CONCLUSION
We uncovered a candidate gene signature correlated with HF, ISCH and CMP in the left ventricle, which may help provide better prognosis and therapeutic decisions and in HF, ISCH and CMP patients.
背景
左心衰竭（HF）已被证明是 HF 的一个关键预后因素。然而，左心衰竭的相对分子机制尚不清楚。本研究旨在通过生物信息学分析挖掘出调控左心衰竭进展的重要模块、关键基因和候选调控成分。
方法
使用 GSE57345 数据集的 319 个样本进行加权基因相关网络分析（WGCNA）。使用 R 中的 ClusterProfiler 包对感兴趣的模块中发现的基因进行功能富集。使用 Cytoscape 构建基因调控网络，使用 Enrichr 数据库识别转录因子（TFs）。使用 MCODE 插件识别感兴趣模块中的枢纽基因，并基于 GSE1869 数据集进行验证。
结果
共鉴定出 6 个显著模块。值得注意的是，蓝色模块被证实与左心衰竭、缺血性心脏病（ISCH）和扩张型心肌病（CMP）最密切相关。功能富集表明，属于该模块的基因主要是驱动细胞外基质相关过程的基因，如细胞外基质结构成分和胶原结合。共鉴定出 7 个转录因子，包括抑制素 Zeste 12 蛋白同源物（SUZ12）和核因子红细胞 2 样 2（NFE2L2）、肾上腺素能受体（AR），可能是蓝色模块中鉴定的共表达基因的调控因子。经过验证，有 3 个关键基因（OGN、HTRA1 和 MXRA5）保留下来，其在左心衰竭中的预后价值得到验证。功能富集的结果证实，这些关键基因主要参与转化生长因子β和细胞外基质的反应。
结论
我们发现了一个与左心室 HF、ISCH 和 CMP 相关的候选基因特征，这可能有助于为 HF、ISCH 和 CMP 患者提供更好的预后和治疗决策。
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