Interaction network analysis revealed biomarkers in myocardial infarction

Area of Science:

• Genomics
• Immunology
• Cardiovascular Disease Research

Background:

• Myocardial infarction (MI) leads to cardiac cell death due to prolonged ischemia.
• Identifying novel diagnostic and therapeutic targets for MI is crucial.

Purpose of the Study:

• To identify novel diagnostic and therapeutic targets for myocardial infarction (MI).
• To analyze gene expression profiles and construct interaction networks in MI patients.

Main Methods:

• Utilized Gene Expression Omnibus (GEO) datasets (GSE22229, GSE29111) for gene expression analysis.
• Identified differentially expressed genes (DEGs) using a p-value < 0.05 and |logFC| > 1 threshold.
• Constructed gene interaction networks and sub-networks using NetBox, identifying linker genes and calculating gene degrees.

Main Results:

• Identified 246 DEGs in MI patients, significantly enriched in immune response pathways.
• Key genes with high network degrees, including CD3E, CD4, and CD3G, were identified.
• Network modules and DEGs were predominantly associated with immune response pathways.

Conclusions:

• High-degree genes within the identified network may serve as potential biomarkers for MI diagnosis.
• These findings suggest immune response pathways are critical in MI pathogenesis and present therapeutic targets.