Abstract
Background and Aims : The discovery of novel biomarkers that improve risk prediction models of acute coronary syndrome (ACS) is essential to better identify and stratify very high-risk patients. MicroRNAs (miRNAs) are essential non-coding modulators of gene expression. Circulating miRNAs have recently emerged as important regulators and fine-tuners of physiological and pathological cardiovascular processes; therefore, specific miRNAs expression profiles may represent new risk biomarkers. The aim of the present study was i) to assess changes in circulating miRNAs levels associated with recent acute coronary syndrome (ACS) and ii) to evaluate the incremental value of adding circulating miRNAs to a clinical predictive risk model.Methods: The study population included ACS patients (n=99) and control subjects (n=103) with high cardiovascular risk but without any previous myocardial infarction or coronary event. Based on a miRNA profiling in a matched derivation case-control cohort, 21 miRNAs were selected for validation.Results: Comparing ACS cases versus controls, 7 miRNAs were significantly differentially expressed. Multivariate logistic regression analyses demonstrated that among the 7 miRNAs tested, 5 were independently associated with the risk of ACS. A receiver operating characteristic (ROC) curve analysis revealed that the combination of miR-122+miR-150+miR-195+miR-16 to the clinical model provides the best performance with an increased AUC from 0.882 to 0.924 (95% CI 0.885-0.933, p = 0.003).Conclusions: In conclusion, our study identified a powerful signature of circulating miRNAs providing additive value to traditional risk markers for ACS prediction. Background and Aims : The discovery of novel biomarkers that improve risk prediction models of acute coronary syndrome (ACS) is essential to better identify and stratify very high-risk patients. MicroRNAs (miRNAs) are essential non-coding modulators of gene expression. Circulating miRNAs have recently emerged as important regulators and fine-tuners of physiological and pathological cardiovascular processes; therefore, specific miRNAs expression profiles may represent new risk biomarkers. The aim of the present study was i) to assess changes in circulating miRNAs levels associated with recent acute coronary syndrome (ACS) and ii) to evaluate the incremental value of adding circulating miRNAs to a clinical predictive risk model. Methods: The study population included ACS patients (n=99) and control subjects (n=103) with high cardiovascular risk but without any previous myocardial infarction or coronary event. Based on a miRNA profiling in a matched derivation case-control cohort, 21 miRNAs were selected for validation. Results: Comparing ACS cases versus controls, 7 miRNAs were significantly differentially expressed. Multivariate logistic regression analyses demonstrated that among the 7 miRNAs tested, 5 were independently associated with the risk of ACS. A receiver operating characteristic (ROC) curve analysis revealed that the combination of miR-122+miR-150+miR-195+miR-16 to the clinical model provides the best performance with an increased AUC from 0.882 to 0.924 (95% CI 0.885-0.933, p = 0.003). Conclusions: In conclusion, our study identified a powerful signature of circulating miRNAs providing additive value to traditional risk markers for ACS prediction.
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