Literature DB >> 18769631

Metabolite profiling of blood from individuals undergoing planned myocardial infarction reveals early markers of myocardial injury.

Gregory D Lewis1, Ru Wei, Emerson Liu, Elaine Yang, Xu Shi, Maryann Martinovic, Laurie Farrell, Aarti Asnani, Marcoli Cyrille, Arvind Ramanathan, Oded Shaham, Gabriel Berriz, Patricia A Lowry, Igor F Palacios, Murat Taşan, Frederick P Roth, Jiangyong Min, Christian Baumgartner, Hasmik Keshishian, Terri Addona, Vamsi K Mootha, Anthony Rosenzweig, Steven A Carr, Michael A Fifer, Marc S Sabatine, Robert E Gerszten.   

Abstract

Emerging metabolomic tools have created the opportunity to establish metabolic signatures of myocardial injury. We applied a mass spectrometry-based metabolite profiling platform to 36 patients undergoing alcohol septal ablation treatment for hypertrophic obstructive cardiomyopathy, a human model of planned myocardial infarction (PMI). Serial blood samples were obtained before and at various intervals after PMI, with patients undergoing elective diagnostic coronary angiography and patients with spontaneous myocardial infarction (SMI) serving as negative and positive controls, respectively. We identified changes in circulating levels of metabolites participating in pyrimidine metabolism, the tricarboxylic acid cycle and its upstream contributors, and the pentose phosphate pathway. Alterations in levels of multiple metabolites were detected as early as 10 minutes after PMI in an initial derivation group and were validated in a second, independent group of PMI patients. A PMI-derived metabolic signature consisting of aconitic acid, hypoxanthine, trimethylamine N-oxide, and threonine differentiated patients with SMI from those undergoing diagnostic coronary angiography with high accuracy, and coronary sinus sampling distinguished cardiac-derived from peripheral metabolic changes. Our results identify a role for metabolic profiling in the early detection of myocardial injury and suggest that similar approaches may be used for detection or prediction of other disease states.

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Year:  2008        PMID: 18769631      PMCID: PMC2525696          DOI: 10.1172/JCI35111

Source DB:  PubMed          Journal:  J Clin Invest        ISSN: 0021-9738            Impact factor:   14.808


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