Mechanisms of Metabolic Dysfunction in Heart Disease

心脏病代谢功能障碍的机制

• 批准号: 7754077
• 负责人: DANIEL A BEARD
• 金额: $ 34.2万
• 依托单位: MEDICAL COLLEGE OF WISCONSIN
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-01-01 至 2012-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7754077
• 关键词: ATP Synthesis Pathway; Accounting; Acetoacetates; Acetyl Coenzyme A; Acute; Affect; Biochemical Pathway; Biological Models; Blood; Brain Hypoxia-Ischemia; Carbohydrates; Cardiac; Cardiomyopathies; Cells; Citric Acid Cycle; Computer Simulation; Data; Data Analyses; Development; Disease; Disease model; Electrophysiology (science); Energy Metabolism; Engineering; Enzymes; Equilibrium; Exercise; Fatty Acids; Fatty acid glycerol esters; Functional disorder; Genetic Models; Glucose; Glycolysis; Goals; Heart; Heart Diseases; Heart failure; Heterogeneity; Hormonal; Hydroxybutyrates; Hypertension; Intervention; Ischemia; Ketone Bodies; Kinetics; Lead; Measurement; Measures; Metabolic; Metabolism; Mitochondria; Modeling; Molecular; Muscle Cells; Myocardial; Myocardium; Myopathy; Network-based; Organ; Organelles; Outcome; Oxidative Phosphorylation; Oxygen; PDH kinase; Pathway interactions; Phosphoric Monoester Hydrolases; Physiological; Protocols documentation; Pyruvate; Pyruvates; Rattus; Recovery; Source; Starvation; Stress; Suspension substance; Suspensions; System; Tars; Therapeutic; Therapeutic Effect; Time; Tissues; Translating; Validation; Work; base; case control; dehydrogenation; design; enzyme activity; fatty acid oxidation; fatty acid transport; flexibility; glycogenolysis; improved; improved functioning; in vivo; model development; models and simulation; myocardial hypoxia; oxidation; oxygen transport; pressure; reconstitution; research study; respiratory; response; simulation; tool

DESCRIPTION (provided by applicant): This proposed project is focused on determining how molecular-level changes in mitochondrial enzymes and transporters that occur in heart disease affect overall cardiac function and determining how therapies may be targeted at the molecular level to improve function at the whole-organ level. The proposed strategy is to first characterize the mitochondrial metabolic network based on quenched kinetic measurements in suspensions of isolated mitochondria. Studies will be carried out using mitochondria obtained from both normal healthy hearts and hearts obtained from a genetic model of hypertension and cardiomyopathy. Large-scale metabolic kinetic measurements will be used to parameterize and validate detailed metabolic models for both the healthy and diseased states. The developed mitochondrial models will be integrated into cell-level models of cardiac energy metabolism, and the cell-level models into a spatially distributed simulation of cardiac oxygen transport that effectively captures spatial gradients and heterogeneity in oxygenation of the myocardium. The resulting tissue-level model will be used for a number of applications: (1) to analyze data on substrate utilization in healthy and diseased states to determine if and how physiological control mechanisms fail in the setting of altered metabolic enzyme activity and expression in the diseased heart. The aim here will be to understand mechanisms leading to reduced capacity to oxidize both fatty acids and carbohydrates, and associated reduction in energetic state, in heart disease; (2) to evaluate metabolic effects of therapeutic strategies tied to metabolic function. We will determine if the model can predict the action of several specific metabolic interventions. The aim here is to develop a powerful platform for an engineering-based approach to under- standing and treating the metabolic effects of heart disease. These analyses may lead to identification of tar- gets or strategies for improving metabolic therapy; and (3) to evaluate if and how regulatory mechanisms respond differently to acute ischemia and recovery in the normal and disease cases. To realize these applications, we must first develop a rigorous simulation platform, integrated from the bottom-up. Specifically, we will start by obtaining kinetic data to identify the organelle-level model from ex vivo experiments (Aim 1). Here we propose to obtain (and make available) time-course kinetic data on 43 metabolic intermediates in response to protocols designed to probe the TCA cycle and 2-oxidation pathways. These data will be used in Aim 2 for model development, parameterization, and validation. Development and application of tissue-level modeling and simulation tools are pursued in Aim 3.

描述（由申请人提供）：该拟议项目的重点是确定心脏病中发生的线粒体酶和转运蛋白的分子水平变化如何影响整体心脏功能，并确定如何在分子水平上靶向治疗以改善整体功能-器官水平。所提出的策略是首先根据分离线粒体悬浮液中的猝灭动力学测量来表征线粒体代谢网络。研究将使用从正常健康心脏和从高血压和心肌病遗传模型获得的心脏获得的线粒体进行。大规模代谢动力学测量将用于参数化和验证健康和疾病状态的详细代谢模型。开发的线粒体模型将集成到心脏能量代谢的细胞级模型中，并将细胞级模型集成到心脏氧运输的空间分布模拟中，有效捕获心肌氧合的空间梯度和异质性。由此产生的组织水平模型将用于许多应用：（1）分析健康和患病状态下底物利用的数据，以确定生理控制机制在改变代谢酶活性和表达的情况下是否以及如何失效。患病的心脏。这里的目的是了解导致心脏病中脂肪酸和碳水化合物氧化能力降低以及能量状态相关降低的机制； (2)评估与代谢功能相关的治疗策略的代谢效果。我们将确定该模型是否可以预测几种特定代谢干预措施的作用。这里的目的是开发一个强大的平台，用于基于工程的方法来理解和治疗心脏病的代谢影响。这些分析可能有助于确定改善代谢治疗的目标或策略； (3) 评估正常和疾病情况下调节机制是否以及如何对急性缺血和恢复做出不同的反应。要实现这些应用，首先必须开发一个严格的仿真平台，自下而上地集成。具体来说，我们将首先获取动力学数据，以从离体实验中识别细胞器水平模型（目标 1）。在这里，我们建议获取（并提供）43 种代谢中间体的时程动力学数据，以响应旨在探测 TCA 循环和 2-氧化途径的方案。这些数据将在目标 2 中用于模型开发、参数化和验证。目标 3 致力于组织级建模和模拟工具的开发和应用。