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Potential Role of Lipometabolism-Related MicroRNAs in Peripheral Blood Mononuclear Cells as Biomarkers for Coronary Artery Disease

View Article: PubMed Central - PubMed

ABSTRACT

Aim:: To explore the relationship between lipometabolism-related microRNAs (miRNAs) in peripheral blood mononuclear cells (PBMCs) and the presence of coronary artery disease (CAD).

Methods:: In the present study, 161 stable CAD patients and 149 health controls were enrolled. The expression levels of seven miRNAs (miR-21, miR-24, miR-29a, miR-33a, miR-34a, miR-103a, and miR-122) in PBMCs were qualified by quantitative real-time polymerase chain reaction (qRT-PCR). The miRNA markers that showed significant difference between the two groups were used for further analysis. The risk of miRNA contributing to the presence of CAD was estimated by univariate and multivariate logistic regression models. The area under the receiver operating characteristic curve (AUC) was used to evaluate diagnostic accuracy.

Results:: The expression levels of miR-24, miR-33a, miR-103a, and miR-122 in PBMCs were significantly increased in CAD patients compared with controls and were significantly correlated with blood lipids in both CAD patients and controls. The increased levels of miR-24 (adjusted OR = 1.32, 95% CI 1.07–1.62, P = 0.009), miR-33a (adjusted OR = 1.57, 95% CI 1.35–1.81, P < 0.001), miR-103a (adjusted OR = 1.01, 95% CI 1.01–1.02, P < 0.001), and miR-122 (adjusted OR = 1.03, 95% CI 1.01–1.04, P < 0.001) were associated with risk of CAD. We identified a miRNA panel (miR-24, miR-33, miR-103a, and miR-122) that provided a high diagnostic accuracy of CAD (AUC= 0.911, 95% CI 0.880–0.942).

Conclusion:: The increased expression levels of miR-24, miR-33a, miR-103a, and miR-122 in PBMCs are associated with risk of CAD. A panel of the four miRNAs has considerable clinical value in diagnosing stable CAD.

No MeSH data available.


Receiver operating characteristic (ROC) curve analysis for CAD diagnosis. Area under the curve (AUC) estimation for the microRNAs: (A) miR-24, (B) miR-33a, (C) miR-103a, and (D) miR-122.
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Figure 2: Receiver operating characteristic (ROC) curve analysis for CAD diagnosis. Area under the curve (AUC) estimation for the microRNAs: (A) miR-24, (B) miR-33a, (C) miR-103a, and (D) miR-122.

Mentions: The diagnostic accuracy of miR-24, miR-33a, miR-103a, and miR-122, measured by AUC, was 0.722 (cutoff value: 2.10), 0.799 (cutoff value: 9.91), 0.687 (cutoff value: 18.59), and 0.739 (cutoff value: 25.85), respectively (P < 0.05). The corresponding sensitivity and specificity was presented in Fig. 2. As compared with the other three miRNAs, miR-33a is a more valuable biomarker for diagnosis for CAD.


Potential Role of Lipometabolism-Related MicroRNAs in Peripheral Blood Mononuclear Cells as Biomarkers for Coronary Artery Disease
Receiver operating characteristic (ROC) curve analysis for CAD diagnosis. Area under the curve (AUC) estimation for the microRNAs: (A) miR-24, (B) miR-33a, (C) miR-103a, and (D) miR-122.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5392481&req=5

Figure 2: Receiver operating characteristic (ROC) curve analysis for CAD diagnosis. Area under the curve (AUC) estimation for the microRNAs: (A) miR-24, (B) miR-33a, (C) miR-103a, and (D) miR-122.
Mentions: The diagnostic accuracy of miR-24, miR-33a, miR-103a, and miR-122, measured by AUC, was 0.722 (cutoff value: 2.10), 0.799 (cutoff value: 9.91), 0.687 (cutoff value: 18.59), and 0.739 (cutoff value: 25.85), respectively (P < 0.05). The corresponding sensitivity and specificity was presented in Fig. 2. As compared with the other three miRNAs, miR-33a is a more valuable biomarker for diagnosis for CAD.

View Article: PubMed Central - PubMed

ABSTRACT

Aim:: To explore the relationship between lipometabolism-related microRNAs (miRNAs) in peripheral blood mononuclear cells (PBMCs) and the presence of coronary artery disease (CAD).

Methods:: In the present study, 161 stable CAD patients and 149 health controls were enrolled. The expression levels of seven miRNAs (miR-21, miR-24, miR-29a, miR-33a, miR-34a, miR-103a, and miR-122) in PBMCs were qualified by quantitative real-time polymerase chain reaction (qRT-PCR). The miRNA markers that showed significant difference between the two groups were used for further analysis. The risk of miRNA contributing to the presence of CAD was estimated by univariate and multivariate logistic regression models. The area under the receiver operating characteristic curve (AUC) was used to evaluate diagnostic accuracy.

Results:: The expression levels of miR-24, miR-33a, miR-103a, and miR-122 in PBMCs were significantly increased in CAD patients compared with controls and were significantly correlated with blood lipids in both CAD patients and controls. The increased levels of miR-24 (adjusted OR = 1.32, 95% CI 1.07&ndash;1.62, P = 0.009), miR-33a (adjusted OR = 1.57, 95% CI 1.35&ndash;1.81, P &lt; 0.001), miR-103a (adjusted OR = 1.01, 95% CI 1.01&ndash;1.02, P &lt; 0.001), and miR-122 (adjusted OR = 1.03, 95% CI 1.01&ndash;1.04, P &lt; 0.001) were associated with risk of CAD. We identified a miRNA panel (miR-24, miR-33, miR-103a, and miR-122) that provided a high diagnostic accuracy of CAD (AUC= 0.911, 95% CI 0.880&ndash;0.942).

Conclusion:: The increased expression levels of miR-24, miR-33a, miR-103a, and miR-122 in PBMCs are associated with risk of CAD. A panel of the four miRNAs has considerable clinical value in diagnosing stable CAD.

No MeSH data available.