Investigating molecular markers linked to acute myocardial infarction and cuproptosis: bioinformatics analysis and validation in the AMI mice model

Abstract

Cuproptosis-related key genes play a significant role in the pathological processes of acute myocardial infarction (AMI). However, a complete understanding of the molecular mechanisms behind this participation remains elusive. This study was designed to identify genes and immune cells critical to AMI pathogenesis. Based on the GSE48060 dataset (31 AMI patients and 21 healthy persons, GPL570-55999), we identified genes associated with dysregulated cuproptosis and the activation of immune responses between normal subjects and patients with a first myocardial attack. Two molecular clusters associated with cuproptosis were defined in patients with AMI. Immune infiltration analysis showed that there was significant immunity heterogeneity among different clusters. Multiple immune responses were closely associated with Cluster2-specific differentially expressed genes (DEGs). The generalized linear model machine model presented the best discriminative performance with relatively lower residual and root mean square error, and a higher area under the curve (AUC = 0.870). A final two-gene-based generalized linear model was constructed, exhibiting satisfactory performance in two external validation datasets (AUC = 0.719, GSE66360 and AUC = 0.856, GSE123342). Column graph, calibration curve, and decision curve analyses also proved the accuracy of AMI prediction. We also constructed a mouse C57BL/6 model of AMI (3 h, 48 h, and 1 week) and used qRT-PCR and immunofluorescence to detect the expression changes of CBLB and ZNF302. In this study, we present a systematic analysis of the complex relationship between cuproptosis and a first AMI attack, and provide new insights into the diagnosis and treatment of AMI.

Keywords

• AMI
• Cuproptosis
• Machine learning
• WGCNA
• Immune infiltration