Department of Cardiovascular Surgery, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of South China Structural Heart Disease, Guangdong Provincial People's Hospital & Guangdong Academy of Medical Sciences, School of Medicine, South China University of Technology, Guangzhou, China.
Department of Cardiovascular Surgery, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of South China Structural Heart Disease, Guangdong Provincial People's Hospital & Guangdong Academy of Medical Sciences, School of Medicine, South China University of Technology, Guangzhou, China.
Life Sci. 2021 Jan 15;265:118830. doi: 10.1016/j.lfs.2020.118830. Epub 2020 Nov 28.
AIMS: The molecular networks and pathways involved in heart failure (HF) are still largely unknown. The present study aimed to systematically investigate the genes associated with HF, comprehensively explore their interactions and functions, and identify possible regulatory networks involved in HF. MAIN METHODS: The weighted gene coexpression network analysis (WGCNA), crosstalk analysis, and Pivot analysis were used to identify gene connections, interaction networks, and molecular regulatory mechanisms. Functional analysis and protein-protein interaction (PPI) were performed using DAVID and STRING databases. Gene set variation analysis (GSVA) and receiver operating characteristic (ROC) curve analysis were also performed to evaluate the relationship of the hub genes with HF. KEY FINDINGS: A total of 5968 HF-related genes were obtained to construct the co-expression networks, and 18 relatively independent and closely linked modules were identified. Pivot analysis suggested that four transcription factors and five noncoding RNAs were involved in regulating the process of HF. The genes in the module with the highest positive correlation to HF was mainly enriched in cardiac remodeling and response to stress. Five upregulated hub genes (ASPN, FMOD, NT5E, LUM, and OGN) were identified and validated. Furthermore, the GSVA scores of the five hub genes for HF had a relatively high areas under the curve (AUC). SIGNIFICANCE: The results of this study revealed specific molecular networks and their potential regulatory mechanisms involved in HF. These may provide new insight into understanding the mechanisms underlying HF and help to identify more effective therapeutic targets for HF.
目的:心力衰竭(HF)相关的分子网络和途径仍知之甚少。本研究旨在系统地研究与 HF 相关的基因,全面探索它们的相互作用和功能,并确定可能与 HF 相关的调控网络。
方法:采用加权基因共表达网络分析(WGCNA)、串扰分析和枢纽分析来识别基因联系、相互作用网络和分子调控机制。使用 DAVID 和 STRING 数据库进行功能分析和蛋白质-蛋白质相互作用(PPI)分析。还进行了基因集变异分析(GSVA)和接受者操作特征(ROC)曲线分析,以评估关键基因与 HF 的关系。
主要发现:共获得 5968 个与 HF 相关的基因来构建共表达网络,鉴定出 18 个相对独立且紧密相连的模块。枢纽分析表明,有四个转录因子和五个非编码 RNA 参与调节 HF 过程。与 HF 呈正相关的模块中的基因主要富集在心脏重构和应激反应中。鉴定并验证了五个上调的关键基因(ASPN、FMOD、NT5E、LUM 和 OGN)。此外,这五个关键基因的 HF GSVA 评分的曲线下面积(AUC)相对较高。
意义:本研究结果揭示了 HF 涉及的特定分子网络及其潜在的调控机制。这些可能为理解 HF 的机制提供新的见解,并有助于为 HF 确定更有效的治疗靶点。
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