A novel mathematical model detecting early individual changes of insulin resistance.
A novel mathematical model detecting early individual changes of insulin resistance.
复制标题
一种检测胰岛素抵抗的早期个体变化的新颖数学模型。
DOI：
10.1089/dia.2013.0084
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发表时间：
2013
影响因子：
5.4
通讯作者：
Ament,Christoph
中科院分区：
文献类型：
--
作者：
Eberle,Claudia;Palinski,Wulf;Ament,Christoph
背景：胰岛素抵抗（IR）和高胰岛素血症以及肥胖在代谢综合征（MetS）、2型糖尿病（T2D）和相关心血管疾病中起关键作用。不幸的是，IR和高胰岛素血症通常诊断较晚（即，当MetS在临床上已经明显时）。IR的早期诊断将是期望的，以减少其临床后果，特别是考虑到肥胖和糖尿病状况的日益普遍。为此，我们开发了一个数学模型，能够检测IR的早期发作，通过小的变化，胰岛素敏感性，葡萄糖的有效性，和第一或第二阶段respons.Materials和Methods：小鼠模型提供了控制条件，研究各个阶段的IR。不同程度的高胆固醇血症，肥胖，IR，和动脉粥样硬化的低密度脂蛋白受体缺陷小鼠通过喂养他们的胆固醇或蔗糖丰富的饮食。通过口服葡萄糖耐量试验评估IR。对照组包括只喂食或转换回常规食物的动物。一个非线性的数学模型的顺序为5的改进Bergman的“最小模型”，然后应用到实验data.Results：不同的代谢星座一致对应于特定的和密切啮合的模型参数的变化。第二阶段葡萄糖敏感性降低的特征是早期葡萄糖耐量受损。后期表现出增加的第一阶段葡萄糖敏感性补偿降低胰岛素敏感性。最后，T2D与第一和第二阶段的敏感性接近zero.Conclusions：新的数学模型检测各种胰岛素敏感或抵抗的代谢阶段的IR。因此，它可以实现定量代谢风险评估，并可能是治疗价值的预期开始的治疗干预。
Background:Insulin resistance (IR) and hyperinsulinemia as well as obesity play a key role in the metabolic syndrome (MetS), type 2 diabetes (T2D), and associated cardiovascular disease. Unfortunately, IR and hyperinsulinemia are often diagnosed late (i.e., when the MetS is already clinically evident). An earlier diagnosis of IR would be desirable to reduce its clinical consequences, in particular in view of the increasing prevalence of obesity and diabetes conditions. For this purpose, we developed a mathematical model capable of detecting early onset of IR through small variations of insulin sensitivity, glucose effectiveness, and first- or second-phase responses.Materials and Methods:Murine models provide controlled conditions to study various stages of IR. Various degrees of hypercholesterolemia, obesity, IR, and atherosclerosis were induced in low-density lipoprotein receptor-deficient mice by feeding them cholesterol- or sucrose-rich diets. IR was assessed by oral glucose tolerance tests. Controls included animals fed exclusively, or switched back to, regular chow. A nonlinear mathematical model of the order of 5 was developed by refining Bergman's “Minimal Model” and then applied to experimental data.Results:Different metabolic constellations consistently corresponded to specific and close-meshed changes in model parameters. Reduced second-phase glucose sensitivity characterized an early impaired glucose tolerance. Later stages showed an increased first-phase glucose sensitivity compensating for decreased insulin sensitivity. Finally, T2D was associated with both first- and second-phase sensitivities close to zero.Conclusions:The new mathematical model detected various insulin-sensitive or -resistant metabolic stages of IR. It can therefore be implemented for quantitative metabolic risk assessment and may be of therapeutic value by anticipating the start of therapeutic interventions.