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Predictive Inflammation-Related Micrornas for Cardiovascular Events Following Early-Onset Coronary Artery Disease Publisher Pubmed



Ziaee S1 ; Hosseindokht M1 ; Cheraghi S1 ; Pourgholi L1 ; Ahmadi A2 ; Sadeghian S3 ; Abbasi SH3 ; Davarpasand T3 ; Boroumand M4
Authors
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Authors Affiliations
  1. 1. Department of Molecular Pathology, Tehran Heart Center, Tehran University of Medical Sciences, Tehran, Iran
  2. 2. Faculty of Science, Department of Biology, Persian Gulf University, Bushehr, Iran
  3. 3. Cardiovascular Research Department, Tehran Heart Center, Tehran University of Medical Sciences, Tehran, Iran
  4. 4. Department of Pathology and Laboratory Medicine, Tehran Heart Center, Tehran University of Medical Sciences, Tehran, Iran

Source: Archives of Medical Research Published:2021


Abstract

Background: Early-onset coronary artery disease (EOCAD) increases the risk of major cardiac adverse events (MACE) at the level of safety/effectiveness-related events. Since adverse events affect the quality of life of young patients with EOCAD, MACE prediction is of great importance for improving medical decision-making. Aims of the Study: We sought to determine whether the most important inflammation-related microRNAs in atherogenesis could predict MACE among patients with EOCAD. Methods: This nested case-control study recruited 143 young patients (males ≤45 and females ≤55 years old), selected from a cohort of patients with premature coronary atherosclerosis at a median follow-up period of 64.1 months. Total RNAs were extracted from their peripheral blood mononuclear cells. The expression levels of 18 miRNAs, which are involved in inflammation and atherogenesis, were analyzed via quantitative reverse transcription PCR. Results: A scoring model based on the upregulation of miR-146a_1 and miR-342_1, along with a history of myocardial infarction and the chronic usage of antithrombotic drugs, was able to predict MI/death at the level of safety-related events (higher vs lower risk scores: sHR: 4.61, 95% CI: 1.57–13.57, and p = 0.005). Another prediction model based on the downregulation of miR-145_1, age, and a history of unstable angina was also able to predict revascularization at the level of effectiveness-related events (higher vs lower risk scores: sHR: 2.90, 95% CI: 1.49–5.66, and p = 0.002). Conclusions: Our results highlighted the role of miRNAs in adverse cardiac events and suggest that miR-146a_1, miR-342_1, and miR-145_1 may be useful biomarkers in predictive and preventive cardiology. © 2020 IMSS