Although several risk factors such as infarct size have been identified, the progression of heart failure (HF) remains difficult to predict in clinical practice. Using an experimental rat model of post-myocardial infarction (MI), we previously identified 45 proteins differentially modulated during HF by proteomic analysis. This study sought to identify microRNAs (miRNAs) able to regulate these proteins and to test their relevance as biomarkers for HF. In silico bioinformatical analysis selected 13 miRNAs related to the 45 proteins previously identified. These miRNAs were analyzed in the rat and in cohorts of patients phenotyped for left ventricular remodeling (LVR). We identified that 3 miRNAs, miR-21-5p, miR-23a-3p and miR-222-3p, and their target Mn superoxide dismutase (SOD2) were significantly increased in LV and plasma of HF-rats. We found by luciferase activity a direct interaction of miR-222-3p with 3'UTR of SOD2. Transfection of human cardiomyocytes with miR-222-3p mimic or inhibitor induced respectively a decrease and an increase of SOD2 expression. Circulating levels of the 3 miRNAs and their target SOD2 were associated with high LVR post-MI in REVE-2 patients. We demonstrated for the first time the potential of microRNAs regulating SOD2 as new circulating biomarkers of HF.

Long Intergenic noncoding RNA predicting CARdiac remodeling (LIPCAR) is a long noncoding RNA identified in plasma of patients after myocardial infarction (MI) to be associated with left ventricle remodeling (LVR). LIPCAR was also shown to be a predictor of early death in heart failure (HF) patients. However, no information regarding the expression of LIPCAR and its function in heart as well as the mechanisms involved in its transport to the circulation is known. The aims of this study are (1) to characterize the transporter of LIPCAR from heart to circulation; (2) to determine whether LIPCAR levels in plasma isolated-extracellular vesicles (EVs) reflect the alteration of its expression in total plasma and could be used as biomarkers of LVR post-MI.

Extracellular vesicles (EVs) are considered as transporters of biomarkers for the diagnosis of cardiac diseases, playing an important role in cell-to-cell communication during physiological and pathological processes. However, specific markers for the isolation and analysis of cardiac EVs are missing, imposing limitation on understanding their function in heart tissue. For this, we performed multiple proteomic approaches to compare EVs isolated from neonate rat cardiomyocytes and cardiac fibroblasts by ultracentrifugation, as well as EVs isolated from minced cardiac tissue and plasma by EVtrap. We identified Ldb3, a cytoskeletal protein which is essential in maintaining Z-disc structural integrity, as enriched in cardiac EVs. This result was validated using different EV isolation techniques showing Ldb3 in both large and small EVs. In parallel, we showed that Ldb3 is almost exclusively detected in the neonate rat heart when compared to other tissues, and specifically in cardiomyocytes compared to cardiac fibroblasts. Furthermore, Ldb3 levels, specifically higher molecular weight isoforms, were decreased in the left ventricle of ischemic heart failure patients compared to control groups, but not in the corresponding EVs. Our results suggest that Ldb3 could be a potential cardiomyocytes derived-EV marker and could be useful to identify cardiac EVs in physiological and pathological conditions.

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.