Literature DB >> 24462065

Relation of reduced expression of MiR-150 in platelets to atrial fibrillation in patients with chronic systolic heart failure.

Yaron Goren1, Eti Meiri1, Christopher Hogan1, Heather Mitchell1, Danit Lebanony1, Nabia Salman2, Jorge E Schliamser2, Offer Amir3.   

Abstract

Atrial fibrillation (AF) is associated with poor prognosis in patients with heart failure (HF). Although platelets play an important role in rendering a prothrombotic state in AF, the exact mechanism by which the effect is mediated is still debated. MicroRNAs (miRNAs), which have been shown to be involved in a variety of cardiovascular conditions, are abundant in platelets and in a cell-free form in the circulation. In the present study, we performed a genome-wide screen for miRNA expression in platelets of patients with systolic HF and in controls without cardiac disease, in pursuit of specific miRNAs that are associated with the presence of AF. MiRNA expression was measured in platelets from 50 patients with systolic HF and 50 controls, of which, samples from 41 patients with HF and 35 controls were used in the final analysis because of a quality control process. MiR-150 expression was 3.2-fold lower (p = 0.0003) in platelets of patients with HF with AF relative to those without AF. A similar effect was seen in serum samples from the same patients, in which miR-150 levels were 1.5-fold lower (p = 0.004) in patients with HF with AF. Furthermore, the serum levels of miR-150 were correlated to platelet levels in patients with AF (r = 0.65, p = 0.0087). In conclusion, miR-150 expression levels in platelets of patients with systolic HF with AF are significantly reduced and correlated to the cell-free circulating levels of this miRNA.
Copyright © 2014 Elsevier Inc. All rights reserved.

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Year:  2013        PMID: 24462065     DOI: 10.1016/j.amjcard.2013.11.060

Source DB:  PubMed          Journal:  Am J Cardiol        ISSN: 0002-9149            Impact factor:   2.778


  45 in total

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Review 10.  New biomarkers from multiomics approaches: improving risk prediction of atrial fibrillation.

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