Identification and Validation of Calcium-Related Diagnostic Markers for Acute Myocardial Infarction via...

Area of Science:

• Biomolecular analysis
• Cardiovascular research
• Genomic medicine

Background:

• Acute myocardial infarction (AMI) incidence is rising, with current diagnostics lacking early detection capabilities.
• Calcium (Ca2+) levels are strongly linked to AMI initiation, suggesting calcium-related genes as potential early diagnostic biomarkers.
• Existing diagnostic methods for AMI face limitations in timely and accurate early detection.

Purpose of the Study:

• To identify novel calcium-related genes as biomarkers for early acute myocardial infarction (AMI) diagnosis.
• To develop and evaluate a diagnostic model for AMI based on identified signature genes.
• To explore the immune cell infiltration landscape and construct regulatory networks (ceRNA, drug interactions) related to AMI.

Main Methods:

• Weighted gene correlation network analysis (WGCNA) and machine learning algorithms (LASSO, SVM-RFE, Random Forest) were used to identify signature genes from gene expression data.
• CIBERSORT and ssGSEA algorithms analyzed immune cell infiltration in AMI patients versus normal samples.
• Cytoscape and DGIdb were utilized to construct competing endogenous RNA (ceRNA) networks and identify potential drug interactions.

Main Results:

• A high-performance diagnostic model was developed using four identified signature genes.
• Significant differences in immune cell infiltration were observed between AMI patients and normal individuals.
• A ceRNA network involving lncRNAs and miRNAs targeting signature genes was elucidated, alongside potential drugs (niacin, nitroglycerin, arsenic disulfide, quercetin) interacting with these genes.

Conclusions:

• Four calcium-related genes were validated as potential diagnostic biomarkers for acute myocardial infarction (AMI).
• The study provides insights into immune cell dynamics and regulatory networks in AMI.
• The identified ceRNA and drug interaction networks offer novel therapeutic strategies for AMI treatment.