MULTI-TISSUE MULTI-TRACER METABOLIC PHENOTYPING OF DIABETES WITH PRE-CLINICAL PET

描述（由申请人提供）：2型糖尿病（T2D）是全身性代谢紊乱的结果，主要特征为外周组织（如肝脏、肌肉和脂肪组织）中胰岛素作用受损。鉴于健康中底物代谢的高度相互关联和协调的性质及其在T2D中的失败，目前的研究需要一种整合的体内"系统生物学"策略来研究肥胖和糖尿病中胰岛素抵抗病因学中的体内多组织代谢改变。临床前PET的独特之处在于多个组织处于视场（FOV）中。这种实现提供了通过多示踪剂实验结合示踪剂动力学的数学模型进行非侵入性多组织定量成像和代谢表型分析的机会。考虑到这一点，并考虑到我们在定量啮齿动物心肌底物代谢方面的经验，我们假设采用类似的方法将提供肝脏、肌肉和脂肪组织中底物代谢的定量测量。本提案中考虑的代谢示踪剂包括用于FA氧化和甘油三酯合成（储存）的[11 C]棕榈酸盐，用于脂肪酸氧化的18 FTHA;用于葡萄糖氧化和糖原合成的[11 C]葡萄糖，用于葡萄糖利用的18 FDG，以及作为脂肪生成潜在成像标记物的[11 C]乳酸盐。鉴于肝脏的双输入函数，在特定目标1中，我们将验证和优化一种算法，以在肝脏底物代谢的多示踪剂成像中重建肝脏双输入函数。有了肝脏双输入功能，在特定目标2中，我们通过增强代谢反应动态范围的干预措施，构建并验证了18 FDG、[11 C]葡萄糖、[11 C]乳酸盐、[11 C]棕榈酸盐、[11 C]乙酸盐和18 FTHA代谢的房室模型。在构建和验证了本提案中示踪剂的房室模型后，我们通过进行多组织多示踪剂时程代谢表型分析来评估和表征T2D发病机制中的代谢紊乱。体内代谢表型分析将与表达阵列分析相结合，以将基因组学改变与代谢紊乱相关联。我们预计，拟议工作的成功完成将提供一个整合的体内代谢表型分析平台，将转基因/基因敲除动物疾病模型中的基因组改变与T2D研究中的多组织代谢紊乱联系起来。此外，拟议的工作将有助于描述T2D和心血管疾病之间的相互作用，以及提案中强调的其他问题。同样重要的是，我们预计从这项工作中获得的策略和见解将转化为临床应用。 公共卫生相关性：2型糖尿病（T2D）是一种复杂的疾病，影响全球超过1.5亿人，预计未来几年这些数字将大幅增加。最近的流行病学和实验证据表明，肥胖和T2D的病因之间存在密切联系，从而混淆了T2D的暗淡前景。肥胖和T2D的共同特征是胰岛素抵抗。在胰岛素抵抗的情况下，包括肝脏、肌肉和脂肪组织在内的多个组织不能调节葡萄糖和脂肪酸代谢。鉴于这种协调的失败，在调节代谢，需要新的策略来表征底物代谢非侵入性的多个系统。我们建议开发和验证一种综合策略，使用多种代谢示踪剂结合临床前正电子发射断层扫描（PET）在多组织中进行代谢成像。临床前PET的独特之处在于多个组织处于视场（FOV）中。这种认识提供了机会，执行非侵入性多组织定量成像，以评估代谢，通过多示踪剂实验结合数学模型来量化代谢。我们将在本提案中考虑的示踪剂包括参与脂肪酸代谢、葡萄糖代谢和乳酸代谢的示踪剂。我们预计，所提出的策略将有助于描述T2D的进展，研究糖尿病和心血管疾病之间的相互作用-糖尿病患者死亡的主要原因-以及提案中强调的其他疾病和病症。

DESCRIPTION (provided by applicant): Type 2 Diabetes (T2D) is a result of systemic disturbances in metabolism characterized mainly by impaired insulin action in peripheral tissues such as liver, muscle, and adipose tissue. In light of the highly interconnected and coordinated nature of substrate metabolism in health, and its failure in T2D, current research necessitates an integrated in-vivo "systems biology" strategy to investigate in-vivo multi-tissue metabolic alterations in the etiology of insulin resistance in obesity and diabetes. Pre-clinical PET is unique in that multiple tissues are in the field-of-view (FOV). This realization affords the opportunity to perform non-invasive multi-tissue quantitative imaging and metabolic phenotyping through multi-tracer experiments coupled with mathematical models of tracer kinetics. With that in mind and given our experience in quantifying myocardial substrate metabolism in rodents, we hypothesize that employing a similar approach will provide quantitative measures of substrate metabolism in liver, muscle, and adipose tissue. The metabolic tracers considered in this proposal include [11C]Palmitate for FA oxidation and triglycerides synthesis (storage), 18FTHA for fatty acid oxidation; [11C]Glucose for glucose oxidation and glycogen synthesis, 18FDG for glucose utilization, and [11C]Lactate as a potential imaging marker for gluconeogenesis. Given the dual-input function to the liver, in Specific Aim 1 we will validate and optimize an algorithm to reconstruct the liver dual-input function in multi- tracer imaging of hepatic substrate metabolism. With the liver dual input function at hand, in Specific Aim 2 we construct and validate compartmental models of 18FDG, [11C]Glucose, [11C]Lactate, [11C]Palmitate, [11C]Acetate, and 18FTHA metabolism through interventions that enhance the dynamic range of metabolic response. Having constructed and validated compartmental models for the tracers in this proposal, we assess and characterize metabolic disturbances in the pathogenesis of T2D by performing multi-tissue multi-tracer time-course metabolic phenotyping. In-vivo metabolic phenotyping will be coupled with expression array analysis to correlate genomics alterations to metabolic disturbances. We anticipate that successful completion of the proposed work will provide an integrated in-vivo metabolic phenotyping platform linking genomic alterations in transgenetic/knockout animal models of disease to multi-tissue metabolic disturbances in the study of T2D. In addition, the proposed work will facilitate characterization of the interplay between T2D and cardiovascular disease, among others highlighted in the proposal. Equally important, we anticipate that strategy and insights derived from this work will be translated to clinical applications. PUBLIC HEALTH RELEVANCE: Type 2 Diabetes (T2D) is a complex disease affecting more than 150 million people worldwide, and a large increase in these numbers is expected within the coming years. Recent epidemiological and experimental evidence suggests that there is a close link between the etiology of obesity and T2D, thus confounding the bleak outlook for T2D. A common feature to both obesity and T2D is insulin resistance. In the setting of insulin resistance, multiple-tissues including liver, muscle, and adipose tissue, fail to regulate glucose and fatty acid metabolism. Given this coordinated failure in regulating metabolism, new strategies are needed to characterize substrate metabolism non-invasively in multiple systems. We propose to develop and validate an integrated strategy to perform metabolic imaging in multi-tissues using multiple metabolic tracers in conjunction with pre-clinical Positron Emission Tomography (PET). Pre-clinical PET is unique in that multiple tissues are in the field-of-view (FOV). This realization affords the opportunity to perform non-invasive multi-tissue quantitative imaging to assess metabolism through multi-tracer experiments coupled with mathematical models to quantify metabolism. The tracers we will consider in this proposal include tracers involved in fatty acid metabolism, glucose metabolism, and lactate metabolism. We anticipate that the proposed strategy will aid in characterizing the progression of T2D, the study of the interplay between diabetes and cardiovascular disease-a leading cause of death among diabetic patients-as well as other diseases and conditions highlighted in the proposal.