IIT Home Page CNR Home Page

Differential Regulation of MicroRNAs in End-Stage Failing Hearts Is Associated with Left Ventricular Assist Device Unloading

Mechanical unloading by left ventricular assist devices (LVADs) in advanced heart failure (HF), in addition to improving symptoms and end-organ perfusion, is supposed to stimulate cellular and molecular responses which can reverse maladaptive cardiac remodeling. As microRNAs (miRNAs) are key regulators in remodeling processes, a comparative miRNA profiling in transplanted hearts of HF patients with/without LVAD assistance could aid to comprehend underlying molecular mechanisms. Next generation sequencing (NGS) was used to analyze miRNA differential expression in left ventricles of HF patients who underwent heart transplantation directly (n=9) or following a period of LVAD support (n=8). After data validation by quantitative real-time PCR, association with functional clinical parameters was investigated. Bioinformatics’ tools were then used for prediction of putative targets of modulated miRNAs and relative pathway enrichment. The analysis revealed 13 upregulated and 10 downregulated miRNAs in failing hearts subjected to LVAD assistance. In particular, the expression level of some of them (miR-338-3p, miR-142-5p and -3p, miR-216a-5p, miR-223-3p, miR-27a-5p, and miR-378g) showed correlation with off-pump cardiac index values. Predicted targets of these miRNAs were involved in focal adhesion/integrin pathway and in actin cytoskeleton regulation. The identified miRNAs might contribute to molecular regulation of reverse remodeling and heart recovery mechanisms.


BioMed Research International, 2015

Autori esterni: Cristina Barsanti (IFC-CNR), Maria Giovanna Trivella (IFC-CNR), Mario Baumgart (FLI-Jena), Marco Groth (FLI-Jena), Raffaele Caruso (IFC-CNR), Alessandro Verde (CVD-Niguarda, Milano), Luca Botta (CVD-Niguarda, Milano), Lorena Cozzi (IFC-CNR), Letizia Pitto (IFC-CNR)
Autori IIT:

Mariama El Baroudi

Foto di Mariama El Baroudi

Tipo: Articoli su riviste ISI
Area di disciplina: Computer Science & Engineering

Attività: Biologia computazionale