Identification and Analysis of PANoptosis Associated with Coronary Artery Disease Using Integrated Bioinformatics...

Area of Science:

• Biomedical research
• Molecular biology
• Bioinformatics

Background:

• Coronary artery disease (CAD) remains a leading global cause of mortality.
• Traditional diagnostic methods for CAD face limitations in accessibility and technical requirements.
• PANoptosis, a regulated cell death pathway involving apoptosis, necroptosis, and pyroptosis, is implicated in inflammation and organ damage.

Purpose of the Study:

• To investigate the association between PANoptosis and CAD using bioinformatics approaches.
• To identify key diagnostic biomarkers for CAD related to PANoptosis.
• To develop a predictive model for CAD diagnosis based on identified biomarkers.

Main Methods:

• Utilized three gene expression datasets (GSE12288, GSE20680, GSE20681) from the GEO database.
• Identified 7 PANoptosis-related differentially expressed genes (PRDEGs) through Venn diagram analysis.
• Constructed a diagnostic model for CAD and performed in vitro functional verification using HUVECs.

Main Results:

• Identified FADD, PSTPIP2, and CASP8 as core regulatory genes in CAD.
• Developed a logistic regression model using these three genes with high diagnostic efficiency (AUC=0.92).
• Functional enrichment analysis revealed PRDEGs are involved in inflammatory and cell death pathways; in vitro studies showed FADD/CASP8 inhibited HUVEC proliferation and promoted apoptosis, while PSTPIP2 had opposing effects.

Conclusions:

• Elucidated the molecular network of PANoptosis in the context of CAD.
• The developed FADD-PSTPIP2-CASP8 diagnostic model offers a novel tool for non-invasive CAD screening.
• This study provides new insights into the role of regulated cell death in cardiovascular disease.