Identification of Potential Crucial Biomarkers in STEMI Through Integrated Bioinformatic Analysis

Area of Science:

• Cardiovascular biology
• Bioinformatics
• Molecular diagnostics

Background:

• ST-segment elevation myocardial infarction (STEMI) is a leading cause of global mortality.
• Early diagnosis of STEMI is crucial for intervention and prognosis.
• Biomarker discovery for STEMI remains an active area of research.

Purpose of the Study:

• To identify potential crucial biomarkers for ST-segment elevation myocardial infarction (STEMI) using bioinformatics analysis.
• To explore the molecular mechanisms underlying STEMI progression.

Main Methods:

• Utilized gene expression data (GSE59867) to identify differentially expressed genes (DEGs) between STEMI and stable coronary artery disease (SCAD) patients.
• Performed enrichment analysis, constructed protein-protein interaction networks, and identified hub genes.
• Analyzed related microRNAs (miRNAs) and transcription factors, and validated candidate biomarkers using a separate dataset (GSE62646).

Main Results:

• Identified 133 DEGs between SCAD and STEMI, with pathways related to inflammation, metabolism, and immunity being pivotal.
• Predicted key regulatory miRNAs (has-miR-124, has-miR-130a/b, has-miR-301a/b) and transcription factors (EVI1, AML1, GATA1, PPARG).
• MS4A3, KLRC4, KLRD1, AQP9, and CD14 demonstrated high sensitivity and specificity (AUC > 75%) as potential STEMI biomarkers.

Conclusions:

• Immunity, metabolism, and inflammation are key processes in STEMI development from SCAD.
• Six genes (MS4A3, KLRC4, KLRD1, AQP9, CD14, and CCR1) are identified as promising candidate biomarkers for STEMI diagnosis.