Predictive Inflammation-related microRNAs for Cardiovascular Events Following Early-Onset Coronary Artery Disease – DocWire News

Posted: Published on December 5th, 2020

This post was added by Alex Diaz-Granados

This article was originally published here

Arch Med Res. 2020 Nov 28:S0188-4409(19)31128-2. doi: 10.1016/j.arcmed.2020.10.004. Online ahead of print.

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.

PMID:33261889 | DOI:10.1016/j.arcmed.2020.10.004

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