Imaging Biomarkers for Evaluating Mitochondrial Function in Diabetes

描述（由申请人提供）：候选人以前的研究经验集中在研究医学成像的基础物理和技术进步，特别是MRI物理。由于糖尿病的患病率和自身候选人家庭的痛苦不断增加，他对应用他的技术技能研究2型糖尿病（T2 DM）的发病机制产生了兴趣。该提案的总体目标是扩大候选人在代谢生物学和临床医学领域的培训和实践经验，使他能够使用成像方法研究胰岛素抵抗和糖尿病背景下线粒体功能障碍的过程。培训的重点如下。胰岛素是葡萄糖代谢的重要调节剂，其通过刺激从血液中摄取葡萄糖并促进其作为糖原储存在肝脏和肌肉中来影响肝脏、肌肉和脂肪组织。当胰岛素水平正常时，葡萄糖摄取异常低，这是一种称为胰岛素抵抗（IR）的疾病。骨骼肌中胰岛素抵抗增加在瘦型和肥胖型糖尿病受试者中都是常见的。糖尿病中增加的葡萄糖水平导致线粒体中产生活性氧，这可能损害线粒体在胰岛素抵抗中产生足够能量的能力。胰岛素抵抗在骨骼肌代谢中的作用在糖尿病研究中引起了强烈的兴趣，研究人员正在研究一个整体的理论框架来理解这一过程。这种类型的计算机建模将受益于直接从活体受试者的组织获得的细胞内代谢数据。非侵入性成像技术可以在一系列生理条件下测量代谢过程，从而改进模型。这些数据将补充从切除的组织样本中获得的更具侵入性的分析信息，包括透射电子显微镜和台式生化测定。磷-31核磁共振波谱可用于证明胰岛素抵抗受试者的代谢受损。然而，所使用的方法需要进行校准和优化，以提供高度准确的生理模型的信息。此外，正电子发射断层扫描已被广泛用于测量骨骼肌中的葡萄糖利用率和组织血流量。拟议项目的总体目标是开发这些成像方法，以测量骨骼肌中作为代谢重要中介的各种化学物质的浓度，测量重要反应进展的速率，测量肌肉血流量和测量葡萄糖利用率，同时严格控制血糖水平以开发和完善分子和生物化学机制的计算机模型导致糖尿病患者骨骼肌的胰岛素抵抗。希望这些工具将导致对糖尿病发病的更好理解，并允许开发可以减轻与糖尿病相关的胰岛素抵抗状况的疗法。

DESCRIPTION (provided by applicant): The candidate's previous research experience has focused on studying the basic physics and technological advances of medical imaging, particularly MRI physics. Due to the increasing prevalence of diabetes and afflictions in the own candidate's family, he has become interested in applying his technical skills to investigate the pathogenesis of type 2 diabetes mellitus (T2DM). The overall goal of this proposal is to expand the candidate's training and practical experience in areas of metabolic biology and clinical medicine to position him for a research career using imaging methods to study the processes involved in mitochondrial dysfunction in the setting of insulin resistance and diabetes. The focus of this training is described below. Insulin is an important regulator of glucose metabolism that affects liver, muscle and fat tissue by stimulating glucose uptake from blood and promoting its storage as glycogen in liver and muscle. Abnormally low uptake of glucose, when there are normal insulin levels, is a condition known as insulin resistance (IR). Increased insulin resistance in skeletal muscle is common in both lean and obese diabetic subjects. The increased glucose levels in diabetes lead to production of reactive oxygen species in mitochondria, which probably impairs the ability of mitochondria to produce adequate energy in insulin resistance. The action of insulin resistance in skeletal muscle metabolism is of intense interest in diabetes research and investigators are working on an overall theoretical framework to understand the processes. This type of computer modeling would benefit from intracellular metabolic data acquired directly from the tissues of livings subjects. Noninvasive imaging technologies can measure metabolic processes under a range of physiological conditions, allowing refinement of the models. These data would supplement information obtained from more invasive analyses from excised tissue samples, including transmission electron microscopy and bench top biochemical assays. Phosphorus-31 nuclear magnetic resonance spectroscopy can be used to demonstrate impaired metabolism in subjects with insulin resistance. However the methods used need to be calibrated and optimized to supply highly accurate information for physiological models. Also, positron emission tomography has been used extensively to measure glucose utilization and tissue blood flow in skeletal muscle. The overall goals of the proposed project are to develop these imaging methods to measure the concentrations of various chemicals in skeletal muscle that are important intermediaries of metabolism, measure the rate at which important reactions progress, measure muscle blood flow and measure glucose utilization rate, while the blood glucose level is being strictly controlled in order to develop and refine computer models of molecular and biochemical mechanisms that contribute to insulin resistance in the skeletal muscle of diabetic patients. It is hoped that these tools will lead to improved understanding of the onset of diabetes and allow development of therapies that can alleviate the insulin resistant condition associated with diabetes.