4.7 Article

Plasma microrna expression profile for reduced ejection fraction in dilated cardiomyopathy

Journal

SCIENTIFIC REPORTS
Volume 11, Issue 1, Pages -

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41598-021-87086-1

Keywords

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Funding

  1. European Regional Development Fund (ERDF) [PI-0048-2017]
  2. Plan Propio de INIBICA [PI-INBICA2019-13]
  3. Fundacion Publica Andaluza Progreso y Salud [PI 0136-2018]
  4. Spanish Society of Cardiology (SEC) for Basic Research [0011-2019]
  5. Fundacion Publica Andaluza Progreso y Salud para la Financiacion

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The study found that microRNA profiles can categorize DCM patients based on their EF, enabling the identification of high-risk individuals. A three-microRNA signature combined with clinical variables was identified as a potential novel prognostic biomarker with high clinical value for categorizing idiopathic DCM.
The left ventricular (LV) ejection fraction (EF) is key to prognosis in dilated cardiomyopathy (DCM). Circulating microRNAs have emerged as reliable biomarkers for heart diseases, included DCM. Clinicians need improved tools for greater clarification of DCM EF categorization, to identify high-risk patients. Thus, we investigated whether microRNA profiles can categorize DCM patients based on their EF. 179-differentially expressed circulating microRNAs were screened in two groups: (1) non-idiopathic DCM; (2) idiopathic DCM. Then, 26 microRNAs were identified and validated in the plasma of ischemic-DCM (n=60), idiopathic-DCM (n=55) and healthy individuals (n=44). We identified fourteen microRNAs associated with echocardiographic variables that differentiated idiopathic DCM according to the EF degree. A predictive model of a three-microRNA (miR-130b-3p, miR-150-5p and miR-210-3p) combined with clinical variables (left bundle branch block, left ventricle end-systolic dimension, lower systolic blood pressure and smoking habit) was obtained for idiopathic DCM with a severely reduced-EF. The receiver operating characteristic curve analysis supported the discriminative potential of the diagnosis. Bioinformatics analysis revealed that miR-150-5p and miR-210-3p target genes might interact with each other with a high connectivity degree. In conclusion, our results revealed a three-microRNA signature combined with clinical variables that highly discriminate idiopathic DCM categorization. This is a potential novel prognostic biomarker with high clinical value.

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