Assessment of Metabolic Phenotypes in Patients with Non-ischemic Dilated Cardiomyopathy Undergoing Cardiac Resynchronization Therapy

Studies of myocardial metabolism have reported that contractile performance at a given myocardial oxygen consumption (MVO2) can be lower when the heart is oxidizing fatty acids rather than glucose or lactate. The objective of this study is to assess the prognostic value of myocardial metabolic phenotypes in identifying non-responders among non-ischemic dilated cardiomyopathy (NIDCM) patients undergoing cardiac resynchronization therapy (CRT). Arterial and coronary sinus plasma concentrations of oxygen, glucose, lactate, pyruvate, free fatty acids (FFA), and 22 amino acids were obtained from 19 male and 2 female patients (mean age 56 ± 16) with NIDCM undergoing CRT. Metabolite fluxes/MVO2 and extraction fractions were calculated. Flux balance analysis (FBA) was performed with MetaFluxNet 1.8 on a metabolic network of the cardiac mitochondria (189 reactions, 230 metabolites) reconstructed from mitochondrial proteomic data (615 proteins) from human heart tissue. Non-responders based on left ventricular ejection fraction (LVEF) demonstrated a greater mean FFA extraction fraction (35% ± 17%) than responders [18 ± 10%, p = 0.0098, area under the estimated ROC curve (AUC) was 0.8238, S.E. 0.1115]. Calculated adenosine triphosphate (ATP)/MVO2 using FBA correlated with change in New York Heart Association (NYHA) class (rho = 0.63, p = 0.0298; AUC = 0.8381, S.E. 0.1316). Non-responders based on both LVEF and NYHA demonstrated a greater mean FFA uptake/MVO2 (0.115 ± 0.112) than responders (0.034 ± 0.030, p = 0.0171; AUC = 0.8593, S.E. 0.0965). Myocardial FFA flux and calculated maximal ATP synthesis flux using FBA may be helpful as biomarkers in identifying non-responders among NIDCM patients undergoing CRT

Imaging and Modeling of Myocardial Metabolism

Current imaging methods have focused on evaluation of myocardial anatomy and function. However, since myocardial metabolism and function are interrelated, metabolic myocardial imaging techniques, such as positron emission tomography, single photon emission tomography, and magnetic resonance spectroscopy present novel opportunities for probing myocardial pathology and developing new therapeutic approaches. Potential clinical applications of metabolic imaging include hypertensive and ischemic heart disease, heart failure, cardiac transplantation, as well as cardiomyopathies. Furthermore, response to therapeutic intervention can be monitored using metabolic imaging. Analysis of metabolic data in the past has been limited, focusing primarily on isolated metabolites. Models of myocardial metabolism, however, such as the oxygen transport and cellular energetics model and constraint-based metabolic network modeling, offer opportunities for evaluation interactions between greater numbers of metabolites in the heart. In this review, the roles of metabolic myocardial imaging and analysis of metabolic data using modeling methods for expanding our understanding of cardiac pathology are discussed