Abstract：
BACKGROUND: Ischemic cardiomyopathy (IC) is primarily due to long-term ischemia/hypoxia of the coronary arteries, leading to impaired cardiac contractile or diastolic function. A new form of cell death induced by copper, called \"cuproptosis\" is related to the development and progression of multiple diseases. The cuproptosis-related gene (CuGs) plays an important role in acute myocardial infarction, while the specific mechanisms of CuGs in ischemic cardiomyopathy remain unclear.
METHODS: The expressions of CuGs and their immune characteristics were analyzed with the IC datasets obtained from the Gene Expression Omnibus, namely GSE5406 and GSE57338, identifying core genes associated with IC development. By comparing RF, SVM, GLM and XGB models, the optimal machine learning model was selected. The expression of marker genes was validated based on the GSE57345, GSE48166 and GSE42955 datasets. Construct a CeRNA network based on core genes. Therapeutic chemiacals targeting core genes were acquired using the CTD database, and molecular docking was performed using Autodock vina software. By ligating the left anterior descending (LAD) coronary artery, an IC mouse model is established, and core genes were experimentally validated using Western blot (WB) and immunohistochemistry (IHC) methods.
RESULTS: We identified 14 CuGs closely associated with the onset of IC. The SVM model exhibited superior discriminative power (AUC = 0.914), with core genes being DLST, ATP7B, FDX1, SLC31A1 and DLAT. Core genes were validated on the GSE42955, GSE48166 and GSE57345 datasets, showing excellent performance (AUC = 0.943, AUC = 0.800, and AUC = 0.932). The CeRNA network consists of 218 nodes and 264 lines, including 5 core diagnostic genes, 52 miRNAs, and 161 lncRNAs. Chemicals predictions indicated 8 chemicals have therapeutic effects on the core diagnostic genes, with benzo(a)pyrene molecular docking showing the highest affinity (-11.3 kcal/mol). Compared to the normal group, the IC group,which was established by LAD ligation, showed a significant decrease in LVEF as indicated by cardiac ultrasound, and increased fibrosis as shown by MASSON staining, WB results suggest increased expression of DLST and ATP7B, and decreased expression of FDX1, SLC31A1 and DLAT in the myocardial ischemic area (p < 0.05), which was also confirmed by IHC in tissue sections.
CONCLUSIONS: In summary, this study comprehensively revealed that DLST, ATP7B, FDX1, SLC31A1 and DLAT could be identified as potential immunological biomarkers in IC, and validated through an IC mouse model, providing valuable insights for future research into the mechanisms of CuGs and its diagnostic value to IC.
METHODS: The expressions of CuGs and their immune characteristics were analyzed with the IC datasets obtained from the Gene Expression Omnibus, namely GSE5406 and GSE57338, identifying core genes associated with IC development. By comparing RF, SVM, GLM and XGB models, the optimal machine learning model was selected. The expression of marker genes was validated based on the GSE57345, GSE48166 and GSE42955 datasets. Construct a CeRNA network based on core genes. Therapeutic chemiacals targeting core genes were acquired using the CTD database, and molecular docking was performed using Autodock vina software. By ligating the left anterior descending (LAD) coronary artery, an IC mouse model is established, and core genes were experimentally validated using Western blot (WB) and immunohistochemistry (IHC) methods.
RESULTS: We identified 14 CuGs closely associated with the onset of IC. The SVM model exhibited superior discriminative power (AUC = 0.914), with core genes being DLST, ATP7B, FDX1, SLC31A1 and DLAT. Core genes were validated on the GSE42955, GSE48166 and GSE57345 datasets, showing excellent performance (AUC = 0.943, AUC = 0.800, and AUC = 0.932). The CeRNA network consists of 218 nodes and 264 lines, including 5 core diagnostic genes, 52 miRNAs, and 161 lncRNAs. Chemicals predictions indicated 8 chemicals have therapeutic effects on the core diagnostic genes, with benzo(a)pyrene molecular docking showing the highest affinity (-11.3 kcal/mol). Compared to the normal group, the IC group,which was established by LAD ligation, showed a significant decrease in LVEF as indicated by cardiac ultrasound, and increased fibrosis as shown by MASSON staining, WB results suggest increased expression of DLST and ATP7B, and decreased expression of FDX1, SLC31A1 and DLAT in the myocardial ischemic area (p < 0.05), which was also confirmed by IHC in tissue sections.
CONCLUSIONS: In summary, this study comprehensively revealed that DLST, ATP7B, FDX1, SLC31A1 and DLAT could be identified as potential immunological biomarkers in IC, and validated through an IC mouse model, providing valuable insights for future research into the mechanisms of CuGs and its diagnostic value to IC.
摘要：
背景：缺血性心肌病（IC）主要是由于冠状动脉的长期缺血/缺氧，导致心脏收缩或舒张功能受损。铜诱导的一种新形式的细胞死亡，所谓的“角化凋亡”与多种疾病的发展和进展有关。角化相关基因(CuGs)在急性心肌梗死中发挥重要作用,而CuGs在缺血性心肌病中的具体机制尚不清楚。
方法：使用从基因表达Omnibus获得的IC数据集分析CuGs的表达及其免疫特性，即GSE5406和GSE57338，鉴定与IC发育相关的核心基因。通过比较RF,SVM,GLM和XGB型号，选择了最优的机器学习模型。基于GSE57345、GSE48166和GSE42955数据集验证标记基因的表达。构建基于核心基因的CeRNA网络。使用CTD数据库获得靶向核心基因的治疗化疗药物，使用Autodockvina软件进行分子对接。通过结扎左前降支(LAD)冠状动脉,建立了IC小鼠模型，和核心基因使用蛋白质印迹（WB）和免疫组织化学（IHC）方法进行实验验证。
结果：我们确定了14个与IC发病密切相关的CuG。SVM模型表现出优越的判别能力(AUC=0.914)，核心基因是DLST，ATP7B,FDX1、SLC31A1和DLAT。核心基因在GSE42955、GSE48166和GSE57345数据集上进行了验证，表现出优异的性能(AUC=0.943,AUC=0.800,和AUC=0.932)。CeRNA网络由218个节点和264个细胞系组成，包括5个核心诊断基因，52个miRNAs,和161个lncRNAs。化学品预测表明8种化学品对核心诊断基因有治疗作用，苯并（a）芘分子对接显示出最高的亲和力（-11.3kcal/mol）。与正常组相比，IC集团,这是通过LAD结扎建立的，心脏超声显示LVEF显着降低，和增加的纤维化如MASSON染色所示，WB结果表明DLST和ATP7B的表达增加，心肌缺血区FDX1、SLC31A1和DLAT的表达降低(p<0.05),组织切片中的IHC也证实了这一点。
结论：总之，这项研究全面揭示了DLST，ATP7B,FDX1、SLC31A1和DLAT可以被鉴定为IC中潜在的免疫学生物标志物，并通过IC小鼠模型验证，为今后研究CuGs的机制及其对IC的诊断价值提供有价值的见解。
方法：使用从基因表达Omnibus获得的IC数据集分析CuGs的表达及其免疫特性，即GSE5406和GSE57338，鉴定与IC发育相关的核心基因。通过比较RF,SVM,GLM和XGB型号，选择了最优的机器学习模型。基于GSE57345、GSE48166和GSE42955数据集验证标记基因的表达。构建基于核心基因的CeRNA网络。使用CTD数据库获得靶向核心基因的治疗化疗药物，使用Autodockvina软件进行分子对接。通过结扎左前降支(LAD)冠状动脉,建立了IC小鼠模型，和核心基因使用蛋白质印迹（WB）和免疫组织化学（IHC）方法进行实验验证。
结果：我们确定了14个与IC发病密切相关的CuG。SVM模型表现出优越的判别能力(AUC=0.914)，核心基因是DLST，ATP7B,FDX1、SLC31A1和DLAT。核心基因在GSE42955、GSE48166和GSE57345数据集上进行了验证，表现出优异的性能(AUC=0.943,AUC=0.800,和AUC=0.932)。CeRNA网络由218个节点和264个细胞系组成，包括5个核心诊断基因，52个miRNAs,和161个lncRNAs。化学品预测表明8种化学品对核心诊断基因有治疗作用，苯并（a）芘分子对接显示出最高的亲和力（-11.3kcal/mol）。与正常组相比，IC集团,这是通过LAD结扎建立的，心脏超声显示LVEF显着降低，和增加的纤维化如MASSON染色所示，WB结果表明DLST和ATP7B的表达增加，心肌缺血区FDX1、SLC31A1和DLAT的表达降低(p<0.05),组织切片中的IHC也证实了这一点。
结论：总之，这项研究全面揭示了DLST，ATP7B,FDX1、SLC31A1和DLAT可以被鉴定为IC中潜在的免疫学生物标志物，并通过IC小鼠模型验证，为今后研究CuGs的机制及其对IC的诊断价值提供有价值的见解。
