Charrier, H.; Cuvelliez, M.; Dubois-Deruy, E.; Mulder, P.; Richard, V.; Bauters, C.; Pinet, F. Integrative System Biology Analyses Identify Seven MicroRNAs to Predict Heart Failure. Non-Coding RNA2019, 5, 22.
Charrier, H.; Cuvelliez, M.; Dubois-Deruy, E.; Mulder, P.; Richard, V.; Bauters, C.; Pinet, F. Integrative System Biology Analyses Identify Seven MicroRNAs to Predict Heart Failure. Non-Coding RNA 2019, 5, 22.
Heart failure (HF) has several etiologies including myocardial infarction (MI) and left ventricular remodeling (LVR), but its progression remains difficult to predict in clinical practice. Systems biology analyses of LVR after MI predict molecular insights of this event such as modulation of microRNA (miRNA) that could be used as a signature of HF progression. To define a miRNA signature of LVR after MI, we use 2 systems biology approaches integrating either proteomic data generated from LV of post-MI rat induced by left coronary artery ligation or multi-omics data (proteins and non-coding RNAs) generated from plasma of post-MI patients from the REVE-2 study. The first approach predicts 13 miRNAs and 3 of these miRNAs were validated to be associated with LVR in vivo: miR-21-5p, miR-23a-3p and miR-222-3p. The second approach predicts 24 miRNAs among 1310 molecules and 6 of these miRNAs were selected to be associated with LVR in silico: miR-17-5p, miR-21-5p, miR-26b-5p, miR-222-3p, miR-335-5p and miR-375. We identified a signature of 7 microRNAs associated with LVR after MI that support the interest of integrative systems biology analyses to define a miRNA signature of HF progression.
biomarkers; miRNAs; heart failure; system biology
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