Plasma miR-1, miR-208, miR-499 as potential predictive biomarkers for acute myocardial infarction: An independent study of Han population
Male
0301 basic medicine
China
Myocardial Infarction
Middle Aged
Sensitivity and Specificity
3. Good health
MicroRNAs
03 medical and health sciences
Asian People
Meta-Analysis as Topic
ROC Curve
Case-Control Studies
Acute Disease
Humans
Female
Biomarkers
Aged
DOI:
10.1016/j.exger.2015.10.011
Publication Date:
2015-10-25T19:18:21Z
AUTHORS (9)
ABSTRACT
It has been demonstrated that circulating muscle-enriched miR-1 and the cardiac-specific miR-208 and miR-499 might leak out of the necrotic myocardium and release into the circulation during the early stages of acute myocardial infarction (AMI). This study aims to investigate potential predictive value of the three miRNAs in AMI.Plasma samples were taken from 70 AMI patients and 72 healthy controls. The expression levels of target miRNAs were measured by qRT-PCR. Student's t test and χ(2) test were applied to test the significance of the differences between AMI patients and controls. Additionally, a meta-analysis about the prediction accuracy of the three miRNAs in AMI was performed to summarize all the results from available studies.The expression of plasma miR-1, miR-208 and miR-499 were all significantly elevated in AMI patients compared with controls. By receiver operating characteristic (ROC) curve analysis, plasma miR-1, miR-208 and miR-499 were demonstrated to be potential biomarkers for the prediction of AMI with AUC values of 0.81, 0.72, and 0.88, respectively. The meta-analysis consisted of nine studies for miR-1, eight studies for miR-208 and eight studies for miR-499. The summary estimates of miR-1, miR-208 and miR-499 were 0.73, 0.80 and 0.83 for sensitivity, 0.82, 0.95 and 0.90 for specificity, 0.84, 0.89 and 0.91 for AUC, respectively.In summary, we confirmed the predictive values of plasma miR-1, miR-208 and miR-499 in AMI. In contrast to miR-1, the cardiac-specific miR-208 and miR-499 were supposed to be more reliable as biomarkers in AMI screening and prediction.
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