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Identification of a miRNA Based-Signature Associated with Acute Coronary Syndrome: Evidence from the FLORINF Study.

ABSTRACT: BACKGROUND:The discovery of novel biomarkers that improve risk prediction models of acute coronary syndrome (ACS) is needed to better identify and stratify very high-risk patients. MicroRNAs (miRNAs) are essential non-coding modulators of gene expression. Circulating miRNAs 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 aims of the present study were: i) to assess the changes in circulating miRNAs levels associated with ACS and ii) to evaluate the incremental value of adding circulating miRNAs to a clinical predictive risk model. METHODS AND RESULTS:The study population included ACS patients (n = 99) and control subjects (n = 103) at high to very high cardiovascular risk but without known coronary event. Based on a miRNA profiling in a matched derivation case (n = -6) control (n = 6) cohort, 21 miRNAs were selected for validation. Comparing ACS cases versus controls, seven miRNAs were significantly differentially expressed. Multivariate logistic regression analyses demonstrated that among the seven miRNAs tested, five were independently associated with the occurrence of ACS. A receiver operating characteristic curve analysis revealed that the addition of miR-122 + miR-150 + miR-195 + miR-16 to the clinical model provided the best performance with an increased area under the curve (AUC) from 0.882 to 0.924 (95% CI 0.885-0.933, p = 0.003). CONCLUSIONS:Our study identified a powerful signature of circulating miRNAs providing additive value to traditional risk markers for ACS.

SUBMITTER: Elbaz M

PROVIDER: S-EPMC7356017 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Identification of a miRNA Based-Signature Associated with Acute Coronary Syndrome: Evidence from the FLORINF Study.

Elbaz Meyer M Faccini Julien J Laperche Clémence C Grousset Elisa E Roncalli Jérôme J Ruidavets Jean-Bernard JB Vindis Cécile C

Journal of clinical medicine 20200601 6

<h4>Background</h4>The discovery of novel biomarkers that improve risk prediction models of acute coronary syndrome (ACS) is needed to better identify and stratify very high-risk patients. MicroRNAs (miRNAs) are essential non-coding modulators of gene expression. Circulating miRNAs 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 aims of the pr ...[more]

PMID: 32492915

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Project description:BackgroundWith the development of biological technology, biomarkers for the prevention and diagnosis of acute coronary syndrome (ACS) have become increasingly evident. However, the study of novel circular RNAs (circRNAs) in ACS is still in progress. This study aimed to investigate whether the regulation of circRNA-miRNA networks is involved in ACS pathogenesis.MethodsWe used microarray analysis to detect significantly expressed circRNAs and miRNAs in the peripheral blood of patients in the control group (CG) and ACS groups, including an unstable angina pectoris (UAP) group and an acute myocardial infarction (AMI) group. A circRNA-miRNA interaction network analysis was carried out with open-source bioinformatics. The gene ontology (GO), pathway, and disease enrichment analyses for differentially expressed circRNAs were further analysed with hierarchical clustering.ResultsA total of 266 circRNAs (121 upregulated and 145 downregulated, P < 0.05, fold change FC ≥2) and 3 miRNAs (1 upregulated and 2 downregulated, P < 0.05, FC ≥ 1.2) were differentially expressed in the ACS groups compared with those in the CG. In addition, among these expressed circRNAs and miRNAs, a single circRNA could bind to more than 1-100 miRNAs, and vice versa. Next, an AMI-UAP network, an AMI-CG network, a UAP-CG network, and an AMI-CG-UAP network were constructed. The top 30 enriched GO terms among the three groups were emphasized as differentially expressed. Disease enrichment analysis showed that these differentially expressed circRNAs are involved in the pathogenesis of cardiovascular diseases. KEGG pathway analysis was performed to identify pathways associated with circRNAs targeting mRNAs.ConclusionCircRNAs are closely related to the pathological process of ACS via a mechanism that may be related to the up- or down-regulation of circRNAs and miRNAs and circRNA-miRNA coexpression. The metabolic pathways, signalling pathways, and diseases affected by these circRNAs can be predicted by enrichment analysis.

Project description:ObjectivesTo evaluate whether radiomics signature of pericoronary adipose tissue (PCAT) based on coronary computed tomography angiography (CCTA) could improve the prediction of future acute coronary syndrome (ACS) within 3 years.MethodsWe designed a retrospective case-control study that patients with ACS (n = 90) were well matched to patients with no cardiac events (n = 1496) during 3 years follow-up, then which were randomly divided into training and test datasets with a ratio of 3:1. A total of 107 radiomics features were extracted from PCAT surrounding lesions and 14 conventional plaque characteristics were analyzed. Radiomics score, plaque score, and integrated score were respectively calculated via a linear combination of the selected features, and their performance was evaluated with discrimination, calibration, and clinical application.ResultsRadiomics score achieved superior performance in identifying patients with future ACS within 3 years in both training and test datasets (AUC = 0.826, 0.811) compared with plaque score (AUC = 0.699, 0.640), with a significant difference of AUC between two scores in the training dataset (p = 0.009); while the improvement of integrated score discriminating capability (AUC = 0.838, 0.826) was non-significant. The calibration curves of three predictive models demonstrated a good fitness respectively (all p > 0.05). Decision curve analysis suggested that integrated score added more clinical benefit than plaque score. Stratified analysis revealed that the performance of three predictive models was not affected by tube voltage, CT version, different sites of hospital.ConclusionCCTA-based radiomics signature of PCAT could have the potential to predict the occurrence of subsequent ACS. Radiomics-based integrated score significantly outperformed plaque score in identifying future ACS within 3 years.Key points• Plaque score based on conventional plaque characteristics had certain limitations in the prediction of ACS. • Radiomics signature of PCAT surrounding plaques could have the potential to improve the predictive ability of subsequent ACS. • Radiomics-based integrated score significantly outperformed plaque score in the identification of future ACS within 3 years.

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Identification of a miRNA Based-Signature Associated with Acute Coronary Syndrome: Evidence from the FLORINF Study.

Publications

Identification of a miRNA Based-Signature Associated with Acute Coronary Syndrome: Evidence from the FLORINF Study.

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