Integrative System Biology Analyses Identify Seven MicroRNAs to Predict Heart Failure.
Henri CharrierMarie CuvelliezEmilie Dubois-DeruyPaul MulderVincent RichardChristophe BautersFlorence PinetPublished in: Non-coding RNA (2019)
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 provide molecular insights into 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 predicted that 13 miRNAs and 3 of these miRNAs would be validated to be associated with LVR in vivo: miR-21-5p, miR-23a-3p and miR-222-3p. The second approach predicted that 24 miRNAs among 1310 molecules and 6 of these miRNAs would be 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.
Keyphrases
- heart failure
- left ventricular
- acute heart failure
- coronary artery
- electronic health record
- cardiac resynchronization therapy
- ejection fraction
- newly diagnosed
- cell proliferation
- acute myocardial infarction
- prognostic factors
- pulmonary artery
- oxidative stress
- hypertrophic cardiomyopathy
- machine learning
- molecular docking
- patient reported outcomes
- chronic kidney disease
- single molecule
- transcatheter aortic valve replacement