DIET AND INSULIN SENSITIVITY: STATISTICAL METHODS

饮食和胰岛素敏感性：统计方法

• 批准号: 8788350
• 负责人: VINCENT JAMES CAREY
• 金额: $ 22.14万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8788350
• 关键词: Address; Adopted; Affect; African American; Algorithms; Ally; Area Under Curve; Baltimore; Bayesian Analysis; Bayesian Method; Biological Assay; Blood Circulation; Blood Pressure; Body Size; Body Weight; Boston; C-Peptide; Carbohydrates; Cardiovascular Diseases; Characteristics; Clinical Trials; Collection; Complex; Databases; Diabetes Mellitus; Diet; Differential Equation; Drug Formulations; Ensure; Epidemic; Etiology; Euglycemic Clamping; Fostering; Future; Glucose; Glucose Clamp; Glycemic Index; HDL-triglyceride; Harvest; Health; High Density Lipoprotein Cholesterol; Hour; Individual; Insulin; Investigation; LDL Cholesterol Lipoproteins; Link; Measurement; Measures; Metabolic; Metabolic Diseases; Metabolism; Methods; Modeling; Monte Carlo Method; National Heart, Lung, and Blood Institute; Nature; Non-Insulin-Dependent Diabetes Mellitus; Nutritional; OGTT; Obesity; Oral; Outcome; Overweight; Participant; Persons; Plasma; Procedures; Process; Protocols documentation; Public Health; Publishing; Randomized; Reporting; Research; Research Design; Research Personnel; Research Support; Risk Factors; Sampling; Series; Software Tools; Solutions; Statistical Methods; System; Techniques; Test Result; Testing; Time; Time Series Analysis; Uncertainty; Woman; Work; analytical method; base; cardiovascular disorder risk; clinical epidemiology; cohort; data reduction; design; diabetes risk; dietary control; disorder risk; feeding; flexibility; glucose metabolism; glucose production; high risk; improved; indexing; insulin sensitivity; interest; intravenous glucose tolerance test; novel strategies; nutritional epidemiology; sound; tool

DESCRIPTION: Assessment of determinants of insulin sensitivity is a basic objective of research into diabetes and cardiovascular disease risk. Trade-offs between invasiveness and indirectness of insulin sensitivity (SI) measurement are a challenge for nutritional epidemiology and clinical trials. While the glucose clamp is highly accurate, it is too invasive and expensive t use in large studies. The oral glucose tolerance test (OGTT) is much more practical but requires complex modeling with numerous assumptions to yield commonly used estimates of insulin sensitivity. Various OGTT SI algorithms based on compartmental models and associated differential equations have been published, but there are indications that widely cited methods cannot be used effectively in the context of ongoing or incipient metabolic disease. The NHLBI OMNI-Carb study was a controlled feeding study of 163 overweight or obese participants at elevated risk for diabetes or CVD in Baltimore and Boston. All participants received a random sequence of four five-week diets in a crossover factorial design with high or low glycemic index and high or low carbohydrate defining the main experimental factors; a two-hour, seven sample OGTT protocol was performed at baseline and at the end of each diet period. Full OGTT series on all diets were obtained for 135 participants. Application of the oral minimal model based estimation (Della Man et al AJP 2004) indicated that estimation of SI was numerically unstable on a nontrivial fraction of participants in the sense that estimates were dependent on convergence of solution processes that were sensitive to arbitrarily chosen starting values; convergence to biologically plausible solutions was also not achievable for a nontrivial fraction of series. The proposed project will use new procedures for assessing "practical" nonidentifiability of key parameters of the minimal model, and will apply newly developed Bayesian inference techniques to properly quantify uncertainty in inference on SI. We will also create and illustrate analytical methods that employ newly developed concepts in multivariate time series analysis to more powerfully discriminate features of OGTT series that correlate with exposures or health conditions. This work will help fully harvest existing and new OGTT databases and will facilitate harmonization of the growing body of research results that use OGTT to address the consequences of obesity, diabetes and cardiovascular disease epidemics by providing transparent computational solutions and more flexible and accessible analytic frameworks.

描述：评估胰岛素敏感性的决定因素是研究糖尿病和心血管疾病风险的基本目标。胰岛素敏感性（SI）测量的侵入性和间接性之间的权衡是营养流行病学和临床试验的挑战。虽然葡萄糖夹非常准确，但在大型研究中它过于侵入性且昂贵。口服葡萄糖耐量测试（OGTT）更加实用，但需要具有许多假设的复杂建模，以产生胰岛素敏感性的常用估计值。已经发布了基于隔室模型和相关微分方程的各种OGTT SI算法，但有迹象表明，在正在进行的或初期的代谢疾病的背景下，广泛引用的方法不能有效地使用。 NHLBI OMNI-CARB研究是对巴尔的摩和波士顿糖尿病风险或CVD风险升高的163名超重或肥胖参与者的对照喂养研究。所有参与者在具有高或低血糖指数和高或低碳水化合物的跨界阶乘设计中均随机序列的四个五周饮食，定义了主要的实验因素；在基线和每个饮食期结束时，进行了两个小时的七个样本OGTT方案。为135名参与者获得了所有饮食的完整OGTT系列。基于口服最小模型的估计的应用（Della Man等人AJP 2004）表明，Si的估计在数值上是不稳定的，因为估计值取决于对任意选择的起始值敏感的解决方案过程的收敛性。对于串联的非平凡部分，与生物学上合理的溶液的收敛性也无法实现。拟议的项目将使用新的程序来评估最小模型的关键参数的“实际”非识别性，并将应用新开发的贝叶斯推理技术来正确量化SI推断的不确定性。我们还将创建和说明在多元时间序列分析中采用新开发的概念的分析方法，以更有强大地区分与暴露或健康状况相关的OGTT系列的特征。这项工作将有助于充分收获现有和新的OGTT数据库，并有助于通过使用OGTT来解决肥胖，糖尿病和心血管疾病流行病的后果，通过提供透明的计算解决方案以及更灵活，更可访问的分析框架来解决研究结果的统一。