Bian Rutao, Wang Yakuan, Li Zishuang, Xu Xuegong
Zhengzhou Hospital of Traditional Chinese Medicine, Zhengzhou, China.
Henan University of Chinese Medicine, Zhengzhou, China.
Front Mol Biosci. 2023 Apr 24;10:1154920. doi: 10.3389/fmolb.2023.1154920. eCollection 2023.
Dilated cardiomyopathy (DCM) is one of the significant causes of heart failure, and the mechanisms of metabolic ventricular remodelling due to disturbances in energy metabolism are still poorly understood in cardiac pathology. Understanding the biological mechanisms of cuproptosis in DCM is critical for drug development. The DCM datasets were downloaded from Gene Expression Omnibus, their relationships with cuproptosis-related genes (CRGs) and immune signatures were analyzed. LASSO, RF, and SVM-RFE machine learning algorithms were used to identify signature genes and the eXtreme Gradient Boosting (XGBoost) model was used to assess diagnostic efficacy. Molecular clusters of CRGs were identified, and immune Infiltration analysis was performed. The WGCNA algorithm was used to identify specific genes in different clusters. In addition, AUCell was used to analyse the cuproptosis scores of different cell types in the scRNA-seq dataset. Finally, herbal medicines were predicted from an online database, and molecular docking and molecular dynamics simulations were used to support the confirmation of the potential of the selected compounds. We identified dysregulated cuproptosis genes and activated immune responses between DCM and healthy controls. Two signature genes (FDX1, SLC31A1) were identified and performed well in an external validation dataset (AUC = 0.846). Two molecular clusters associated with cuproptosis were further defined in DCM, and immune infiltration analysis showed B-cell naive, Eosinophils, NK cells activated and T-cell CD4 memory resting is significant immune heterogeneity in the two clusters. AUCell analysis showed that cardiomyocytes had a high cuproposis score. In addition, 19 and 3 herbal species were predicted based on FDX1 and SLC31A1. Based on the molecular docking model, the natural compounds Rutin with FDX1 (-9.3 kcal/mol) and Polydatin with SLC31A1 (-5.5 kcal/mol) has high stability and molecular dynamics simulation studies further validated this structural stability. Our study systematically illustrates the complex relationship between cuproptosis and the pathological features of DCM and identifies two signature genes (FDX1 and SLC31A1) and two natural compounds (Rutin and Polydatin). This may enhance our diagnosis of the disease and facilitate the development of clinical treatment strategies for DCM.
扩张型心肌病（DCM）是心力衰竭的重要原因之一，而心脏病理学中对能量代谢紊乱导致的代谢性心室重构机制仍知之甚少。了解DCM中铜死亡的生物学机制对药物研发至关重要。从基因表达综合数据库下载DCM数据集，分析其与铜死亡相关基因（CRGs）及免疫特征的关系。使用套索回归（LASSO）、随机森林（RF）和支持向量机递归特征消除（SVM-RFE）机器学习算法识别特征基因，并使用极端梯度提升（XGBoost）模型评估诊断效能。识别CRGs的分子簇，并进行免疫浸润分析。使用加权基因共表达网络分析（WGCNA）算法识别不同簇中的特定基因。此外，使用AUCell分析单细胞RNA测序（scRNA-seq）数据集中不同细胞类型的铜死亡评分。最后，从在线数据库预测草药，并使用分子对接和分子动力学模拟来支持所选化合物潜力的确认。我们识别出DCM与健康对照之间铜死亡基因失调和免疫反应激活。鉴定出两个特征基因（FDX1、SLC31A1），并在外部验证数据集中表现良好（曲线下面积[AUC]=0.846）。在DCM中进一步定义了两个与铜死亡相关的分子簇，免疫浸润分析显示B细胞幼稚型、嗜酸性粒细胞、自然杀伤（NK）细胞激活和CD4记忆静止T细胞在这两个簇中存在显著的免疫异质性。AUCell分析表明心肌细胞具有较高的铜死亡评分。此外，基于FDX1和SLC31A1分别预测出19种和3种草药。基于分子对接模型，与FDX1结合的天然化合物芦丁（-9.3千卡/摩尔）和与SLC31A1结合的虎杖苷（-5.5千卡/摩尔）具有高稳定性，分子动力学模拟研究进一步验证了这种结构稳定性。我们的研究系统地阐明了铜死亡与DCM病理特征之间的复杂关系，鉴定出两个特征基因（FDX1和SLC31A1）和两种天然化合物（芦丁和虎杖苷）。这可能会提高我们对该疾病的诊断能力，并促进DCM临床治疗策略的开发。
