BBADIS-16-507-R1 1 Integrative network analysis reveals time-dependent molecular events underlying left ventricular remodeling in post-myocardial infarction patients

International audienceTo elucidate the time-resolved molecular events underlying the LV remodeling (LVR) process, we developed a large-scale network model that integrates the 24 molecular variables (plasma proteins and non-coding RNAs) collected in the REVE-2 study at four time points (baseline, 1month, 3months and 1year) after MI. The REVE-2 network model was built by extending the set of REVE-2 variables with their mechanistic context based on known molecular interactions (1310 nodes and 8639 edges). Changes in the molecular variables between the group of patients with high LVR (>20%) and low LVR (<20%) were used to identify active network modules within the clusters associated with progression of LVR, enabling assessment of time-resolved molecular changes. Although the majority of molecular changes occur at the baseline, two network modules specifically show an increasing number of active molecules throughout the post-MI follow up: one involved in muscle filament sliding, containing the major troponin forms and tropomyosin proteins, and the other associated with extracellular matrix disassembly, including matrix metalloproteinases, tissue inhibitors of metalloproteinases and laminin proteins. For the first time, integrative network analysis of molecular variables collected in REVE-2 patients with known molecular interactions allows insight into time-dependent mechanisms associated with LVR following MI, linking specific processes with LV structure alteration. In addition, the REVE-2 network model provides a shortlist of prioritized putative novel biomarker candidates for detection of LVR after MI event associated with a high risk of heart failure and is a valuable resource for further hypothesis generation

Clinical score building from high-throughput proteomic data

International audienc

Alterations in phenotype and gene expression of adult human aneurysmal smooth muscle cells by exogenous nitric oxide

International audienceAbdominal aortic aneurysms (AAA) are characterized by matrix remodeling, elastin degradation, absence of nitric oxide (NO) signaling, and inflammation, influencing smooth muscle cell (SMC) phenotype and gene expression. Little is known about the biomolecular release and intrinsic biomechanics of human AAA-SMCs. NO delivery could be an attractive therapeutic strategy to restore lost functionality of AAA-SMCs by inhibiting inflammation and cell stiffening. We aim to establish the differences in phenotype and gene expression of adult human AAA-SMCs from healthy SMCs. Based on our previous study which showed benefits of optimal NO dosage delivered via S-Nitrosoglutathione (GSNO) to healthy aortic SMCs, we tested whether such benefits would occur in AAA-SMCs. The mRNA expression of three genes involved in matrix degradation (ACE, ADAMTS5 and ADAMTS8) was significantly downregulated in AAA-SMCs. Total protein and glycosaminoglycans synthesis were higher in AAA-SMCs than healthy-SMCs (p < 0.05 for AAA-vs. healthy-SMC cultures) and was enhanced by GSNO and 3D cultures (p < 0.05 for 3D vs. 2D cultures; p < 0.05 for GSNO vs. non-GSNO cases). Elastin gene expression, synthesis and deposition, desmosine crosslinker levels, and lysyl oxidase (LOX) functional activity were lower, while cell proliferation, iNOS, LOX and fibrillin-1 gene expressions were higher in AAA-SMCs (p < 0.05 between respective cases), with differential benefits from GSNO exposure. GSNO and 3D cultures reduced MMPs −2, −9, and increased TIMP-1 release in AAA-SMC cultures (p < 0.05 for GSNO vs. non-GSNO cultures). AAA-SMCs were inherently stiffer and had smoother surface than healthy SMCs (p < 0.01 in both cases), but GSNO reduced stiffness (~25%; p < 0.01) and increased roughness (p < 0.05) of both cell types. In conclusion, exogenously-delivered NO offers an attractive strategy by providing therapeutic benefits to AAA-SMCs

Let-7f: A New Potential Circulating Biomarker Identified by miRNA Profiling of Cells Isolated from Human Abdominal Aortic Aneurysm

International audienceAbdominal aortic aneurysm (AAA) is a progressive vascular disease responsible for 1-4% of the deaths in elderly men. This study aimed to characterize specific microRNA (miRNA) expression in aneurysmal smooth muscle cells (SMCs) and macrophages in order to identify circulating miRNAs associated with AAA. We screened 850 miRNAs in aneurysmal SMCs, M1 and M2 macrophages, and in control SMCs isolated by micro-dissection from aortic biopsies using microarray analysis. In all, 92 miRNAs were detected and 10 miRNAs were selected for validation by qRT-PCR in isolated cells (n = 5), whole control and aneurysmal aorta biopsies (n = 13), and plasma from patients (n = 24) undergoing AAA (over 50 mm) repair matched to patients (n = 18) with peripheral arterial disease (PAD) with atherosclerosis but not AAA. Seven miRNAs were modulated similarly in all aneurysmal cells. The Let-7f was downregulated in aneurysmal cells compared to control SMCs with a significant lower expression in M1 compared to M2 macrophages (0.1 fold, p = 0.03), correlated with a significant downregulation in whole aneurysmal aorta compared to control aorta (0.2 fold, p = 0.03). Significant levels of circulating let-7f (p = 0.048) were found in AAA patients compared to PAD patients with no significant correlation with aortic diameter (R 2 = 0.03). Our study underlines the utility of profiling isolated aneurysmal cells to identify other miRNAs for which the modulation of expression might be masked when the whole aorta is used. The results highlight let-7f as a new potential biomarker for AAA

Prise en compte de la structure temporelle dans l'analyse de données protéomiques à haut débit

International audienceEach year, in France, over 100 000 people suffer from myocardial infarction (MI) which, for some of them, lead to a left ventricular remodeling (LVR) and heart failure (HF). Studies have shown that during a year following MI, LVR is a risk factor for HF and cardiovascular death. Finding biomarkers which can detect early stage of LVR or HF after a MI is a leading public health matter. We are aiming at selecting few proteins responsible for LVR and survival, using not only baseline measurements of over 5000 proteins on 2 cohorts of around 240 patients each, but also using three additional longitudinal measurements of these proteins available on one of the two cohorts. In a first time, we will present how we developped a prediction survival model by creating cluster of patients. In a second time, we will focus on the longitudinal dimension of the data and explore how this dimension could help selecting relevant proteins for predicting survival using only baseline measurment. To handle the longitudinal (and high) dimension of the data, clustering of longitudinal data will be studied in order to create groups of proteins that could be used in a selection model.Chaque année, en France, plus de 100 000 personnes déclarent un infarctus du myocarde (IM) qui, pour certains d'entre eux, conduit à un remodelage ventriculaire gauche (RVG) et à de l'insuffisance cardiaque (IC). De précédentes études ont montré que la présence d'un RVG suite à un infarctus était un facteur de risque d'IC et de décès pour causes cardiovasculaires. La rechercher de biomarqueurs permettant la prédiction du RVG ou de la survie à un stade précoce est donc un problème de santé publique. Notre but, ici, est de sélectionner un petit nombre de protéines liées au RVG ou à la survie en utilisant les mesures de plus de 5000 protéines sur deux cohortes d'environs 240 patients chacune disponibles au moment de l'infarctus, mais aussi à trois temps supplémentaires pour l'une des deux cohortes. Dans un premier temps, nous présenterons un modèle prédictif de la survie basé sur la création de clusters de patients. Puis, nous nous concentrerons sur la dimension longitudinale des données et explorerons comment cette dimension peut nous être utile dans la sélection de protéines pour la prédiction précoce de la survie des patients. Afin de modéliser la dimension longitudinale et la grande dimension des données un clustering longitudinal sera d'abord étudié afin de créer des groupes de protéines pouvant ensuite être utilisés dans un modèle de prédiction de la survie

Echocardiographic diastolic function evolution in patients with an anterior Q-wave myocardial infarction: insights from the REVE-2 study.

International audienceBackground: Myocardial fibrosis plays a key role in the development of adverse left ventricular remodeling after myocardial infarction (MI). This study aimed to determine whether the circulating levels of BNP, collagen peptides, and galectin-3 are associated with diastolic function evolution (both deterioration and improvement) at 1-year after an anterior MI.Methods: The REVE-2 is a prospective multicenter study including 246 patients with a first anterior Q-wave MI. Echocardiographic assessment was performed at hospital discharge and ±1-year after MI. BNP, Galectin-3 and collagen peptides were measured ±1-month after MI. Left ventricular diastolic dysfunction (DD) was defined according to the presence of at least 2 criteria of echocardiographic parameters: septal e’6 mg/l (Odds Ratio, OR=5.29; 95%CI=1.05-26.66; p=0.044), Galectin-3>13 μg/l (OR=5.99; 95%CI=1.18-30.45; p=0.031), and BNP>82 ng/l (OR=10.25; 95%CI=2.36-44.50; p=0.002) quantified at 1-month post-MI were independently associated with 1-year DD. Follow-up of the 137 patients with DD at baseline among the 159 patients showed that 36 patients (26%) had a normalized diastolic function at 1-year post-MI. Patients with a BNP>82 ng/l were less likely to improve diastolic function (OR=0.06; 95%CI=0.01-0.28; p=0.0003).Conclusions. The present study suggests that circulating levels of PIIINP, Galectin-3 and BNP may be independently associated with new-onset DD in post-MI patients

Proteomic signature for early diagnosis of left ventricular remodeling after myocardial infarction

International audienceHeart failure (HF) remains a main cause of mortality worldwide. The most common cause of HF is coronary artery disease and particularly myocardial infarction (MI). Left ventricular remodelling (LVR) is a progressive dilatation of the left ventricle that occurs in response to MI and is difficult to predict in clinical practice based on infarct size, infarct location or LV ejection fraction. Several studies have identified LVR as a powerful indicator of a high risk of HF or death after MI.The aim is to identify plasmatic proteins that could predict the occurrence and severity of LVR in order to prevent HF. The REVE and REVE-2 studies have included respectively, 215 and 246 patients with a first anterior MI. The patients have been followed-up with serial echocardiography during one year to quantify LVR. Plasma samples have been collected during hospitalization for both studies, and at 1, 3 and 12 months after MI for REVE-2, allowing to measure 5284 proteins thanks to a high throughput proteomic approach (SOMASCAN). Due to the high dimension of data (more variables than individuals), we used statistical methods performing variable selection to build a proteomic signature of LVR. We showed that REVE and REVE-2 studies share common statistical characteristics (distributions, correlations) allowing us to perform analysis on REVE-2 and use REVE for validation. We confirmed the difficulty to predict LVR using only clinical data, with prediction models explaining at the best 11% of LVR (R²=0,106). Using the proteomic data we explained 30% of LVR (R²=0,297) using a 22-proteins based score built with nested models. We confirmed that LVR is complex to predict even with a huge number of potential biomarkers to explore. Still, we enhanced the predictability of LVR and we intend to find a protein profile of LVR during the year after MI by studying data collected during this period

Transcriptomic and proteomic profiles of vascular cells involved in human abdominal aortic aneurysm

Diseases & disorder

Expression and implication of clusterin in left ventricular remodeling after myocardial infarction

International audienceBACKGROUND: Left ventricular remodeling (LVR) after myocardial infarction is associated with an increased risk of heart failure and death. In spite of a modern therapeutic approach, LVR remains relatively frequent and difficult to predict in clinical practice. Our aim was to identify new biomarkers of LVR and understand their involvement in its development.METHODS AND RESULTS:Proteomic analysis of plasma from the REVE-2 study (Remodelage Ventriculaire)-a study dedicated to the analysis of LVR which included 246 patients after a first anterior myocardial infarction-identified increased plasma levels of CLU (clusterin) in patients with high LVR. We used a rat model of myocardial infarction to analyze CLU expression in the LV and found a significant increase that was correlated with LVR parameters. We found increased CLU expression and secretion in primary cultures of rat neonate cardiomyocytes hypertrophied by isoproterenol. Silencing of CLU in hypertrophied neonate cardiomyocytes induced a significant decrease in cell size, ANP (atrial natriuretic peptide), and BNP (B-type natriuretic peptide) expression, associated with a decreased ERK (extracellular signal-regulated kinase) 1/2 activity, suggesting a prohypertrophic role of CLU. We then confirmed a significant increase of both intracellular p-CLU (precursor form of CLU) and m-CLU (mature form of CLU) in failing human hearts. Finally, the circulating levels of CLU (secreted form) were increased in patients with chronic heart failure who died from cardiovascular cause during a 3-year follow-up (n=99) compared with survivors (n=99).CONCLUSIONS: Our results show for the first time that plasma CLU levels are associated with LVR post-myocardial infarction, have in part a cardiac origin, and are a predictor of early death in heart failure patients