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Flow Cytometry Analysis of Immune Cells Within Murine Aortas
Published on: July 1, 2011
Interleukin-4 and Interleukin-17 are associated with coronary artery disease
Chenyang Wang1, Sheng Liu1, Yunxiao Yang1
1Center for Coronary Heart Disease, Beijing Anzhen Hospital, Capital Medical University, Beijing, China.
Insights
Serum interleukin-4 (IL-4) and IL-17 levels are independent predictors of coronary artery disease (CAD). A model integrating these cytokines with clinical factors accurately identifies CAD patients.
Area of Science:
- Cardiovascular Medicine
- Immunology
- Biomarker Discovery
Background:
- Coronary artery disease (CAD) is a leading global cause of mortality.
- Inflammatory factors are strongly associated with CAD development.
- Predicting CAD incidence and distinguishing lesion presence is crucial.
Purpose of the Study:
- To investigate the correlation between serum cytokine levels and CAD incidence.
- To identify independent predictors of CAD.
- To develop a predictive model for CAD diagnosis.
Main Methods:
- Recruited 487 patients with suspected CAD (no acute myocardial infarction).
- Measured serum levels of 12 cytokines using multiplexed flow cytometry.
- Employed multivariate logistic regression and ROC curve analysis for prediction.
Main Results:
- Serum levels of IL-4, IL-12p70, IL-17, IFN-α, and IFN-γ were lower in the CAD group.
- IL-4 and IL-17 were identified as independent predictors of CAD.
- A model combining IL-4, IL-17, HDL-C, sex, smoking, and diabetes showed strong predictive performance (AUC=0.826).
Conclusions:
- Serum IL-4 and IL-17 are significant independent predictors of CAD.
- A novel risk prediction model integrating cytokines and clinical factors can differentiate CAD patients.
- This model aids in distinguishing CAD from suspected cases without acute myocardial infarction.
Introduction:
The present study aimed to examine the correlation between serum cytokine levels and the incidence of coronary artery disease (CAD), a leading cause of mortality globally, which is known to have a strong association with inflammatory factors. The study further sought to determine the predictors of CAD to distinguish patients with coronary artery lesions from those suspected of having CAD.
Methods And Results:
In this study, 487 patients who underwent coronary angiography as a result of suspected CAD but without acute myocardial infarction (AMI) were recruited. The serum levels of the cytokines interleukin (IL)-1β, IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, IL-12p70, IL-17, tumor necrosis factor-α, interferon (IFN)-α, and IFN-γ were measured using a multiplexed particle-based flow cytometric assay technique. The results of the study revealed that the levels of IL-4, IL-12p70, IL-17, IFN-α, and IFN-γ in the CAD group were significantly lower compared to those in the non-CAD group. Multivariate logistic regression analysis indicated that two serum cytokines (IL-4 and IL-17), one protective factor (high-density lipoprotein cholesterol [HDL-C]), and three risk factors (sex, smoking, and diabetes) were independently predictive of CAD. The receiver operating characteristic curve analysis showed that the combined use of these predictors in a multivariate model demonstrated good predictive performance for CAD, as evidenced by an area under the curve value of 0.826.
Conclusion:
The results of the study indicated that serum IL-4 and IL-17 levels serve as independent predictors of CAD. The risk prediction model established in the research, which integrates these serum cytokines (IL-4 and IL-17) with relevant clinical risk factors (gender, smoking, and diabetes) and the protective factor HDL-C, holds the potential to differentiate patients with CAD from those suspected of having CAD but without AMI.
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