Serum Cytokine Profile in Relation to the Severity of Coronary Artery Disease

Area of Science:

• Cardiovascular Medicine
• Immunology
• Biochemistry

Background:

• Coronary artery disease (CAD) poses a significant global health burden.
• Biomarkers for assessing CAD severity are crucial for effective patient management.
• Cytokines are implicated in inflammatory processes underlying atherosclerosis.

Purpose of the Study:

• To investigate the association between serum cytokine levels and the severity of coronary artery disease (CAD).
• To identify independent predictors of CAD severity.
• To evaluate a risk prediction model combining cytokines and clinical factors.

Main Methods:

• Serum cytokine concentrations (IFN-γ, TNF-α, IL-2, IL-4, IL-6, IL-10, IL-9, IL-17) were measured in 201 patients using xMAP multiplex technology.
• Coronary artery disease severity was quantified using the Gensini score (GS).
• Statistical analyses, including correlation, regression, and ROC curve analysis, were performed.

Main Results:

• Significantly higher serum levels of TNF-α, IL-6, IL-9, IL-10, and IL-17 were observed in patients with high GS (≥38.5) compared to those with low GS (<38.5).
• Positive correlations were found between these cytokines and CAD severity.
• IL-6, IL-9, IL-17, creatinine, and LDL-C were identified as independent predictors of increased CAD severity.

Conclusions:

• Serum cytokines IL-6, IL-9, and IL-17, along with clinical factors creatinine and LDL-C, are significant predictors of CAD severity.
• A combinatorial risk prediction model incorporating these factors demonstrates good performance in assessing CAD severity.
• This approach may aid in risk stratification for angina patients, particularly in resource-limited settings.