Unknown,Transcriptomics,Genomics,Proteomics

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Transcription profiling of mouse to predict left ventricle systolic dysfunction using gene expression profiling

ABSTRACT: We tested the hypothesis that a set of differentially expressed genes could be used to predict cardiovascular phenotype in mice after prolonged catecholamine stress. Experiment Overall Design: We observed that WT FVB and B2KO mice developed systolic dysfunction in response to continuous catecholamine infusion while WT C57 mice developed diastolic dysfunction. Using these mice as the derivation cohort, we identified a set of 83 genes whose differential expression correlated with left ventricle systolic dysfunction. The gene set was then used to accurately predict development of left ventricle systolic dysfunction in a separate group of mice (WT B6129SF2/J) after catecholamine stress.

ORGANISM(S): Mus musculus

SUBMITTER: Rani Agrawal

PROVIDER: E-GEOD-12413 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:To find which genes were significantly modulated by Valsartan in non-infarcted left ventricle, 4 weeks after coronary artery ligation, and to correlate emerging modulated pathways with histology and cardiac magnetic resonance (CMR) imaging. The goal was to validate the estimation of the systolic dysfunction and of the regions preserved by pharmacological treatment performed with a CMR index. Title of the associated submitted paper: Evaluation of left ventricle function by regional fractional area change (RFAC) in a mouse model of myocardial infarction secondary to Valsartan treatment. Abstract: Purpose: Left ventricle (LV) regional fractional area change (RFAC) measured by cardiac magnetic resonance (CMR) allows the non-invasive localization and quantification of the extent of myocardial infarction (MI), and could be applied to assess the effectiveness of pharmacological or regenerative therapies. Here we investigate the ability of RFAC to identify regional dysfunction and discriminate the effect of pharmacological treatment with valsartan, a selective antagonist of angiotensin II type 1 receptor, in a model of MI. Methods: C57BL/6N mice, undergoing coronary artery ligation, were divided into two groups: untreated (MI) or treated with Valsartan (MI+Val). Sham-operated mice were used as a control. Cardiac dimensions and function were assessed at baseline, 24 hours, 1 and 4 weeks post surgery by CMR and echocardiography. At sacrifice histology and whole-genome gene expression profiling were performed. Results: RFAC was able to detect significant differences between treatment groups whereas the global ejection fraction was not. RFAC showed greater loss of contractility in remote non-infarcted myocardium in MI group than in MI+Val group. Consistently, in the same region MI+Val mice showed reduced myocyte hypertrophy, fibroblast proliferation, and fibrosis and modulation of target genes; in addition, left atrium volumes, appendage length and duct contractility were preserved. Conclusion: In this study, RFAC effectively estimated the degree of systolic dysfunction and discriminated the regions preserved by pharmacological treatment. RFAC index is a promising tool to monitor changes in LV contractility and to assess the effectiveness of therapeutic regimens in clinical settings.

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Transcription profiling of mouse to predict left ventricle systolic dysfunction using gene expression profiling

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