Diabetes and Obesity Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States.
Front Endocrinol (Lausanne). 2021 Feb 15;11:583016. doi: 10.3389/fendo.2020.583016. eCollection 2020.
It has long been hoped that our understanding of the pathogenesis of diabetes would be helped by the use of mathematical modeling. In 1979 Richard Bergman and Claudio Cobelli worked together to find a "minimal model" based upon experimental data from Bergman's laboratory. Model was chosen as the simplest representation based upon physiology known at the time. The model itself is two quasi-linear differential equations; one representing insulin kinetics in plasma, and a second representing the effects of insulin and glucose itself on restoration of the glucose after perturbation by intravenous injection. Model would only be sufficient if it included a delay in insulin action; that is, insulin had to enter a remote compartment, which was interstitial fluid (ISF). Insulin suppressed endogenous glucose output (by liver) slowly. Delay proved to be due to initial suppression of lipolysis; resultant lowering of free fatty acids reduced liver glucose output. Modeling also demanded that normalization of glucose after injection included an effect of glucose itself on glucose disposal and endogenous glucose production - these effects were termed "glucose effectiveness." Insulin sensitivity was calculated from fitting the model to intravenous glucose tolerance test data; the resulting insulin sensitivity index, SI, was validated with the glucose clamp method in human subjects. Model allowed us to examine the relationship between insulin sensitivity and insulin secretion. Relationship was described by a rectangular hyperbola, such that Insulin Secretion x Insulin Sensitivity = Disposition Index (DI). Latter term represents ability of the pancreatic beta-cells to compensate for insulin resistance due to factors such as obesity, pregnancy, or puberty. DI has a genetic basis, and predicts the onset of Type 2 diabetes. An additional factor was clearance of insulin by the liver. Clearance varies significantly among animal or human populations; using the model, clearance was shown to be lower in African Americans than Whites (adults and children), and may be a factor accounting for greater diabetes prevalence in African Americans. The research outlined in the manuscript emphasizes the powerful approach by which hypothesis testing, experimental studies, and mathematical modeling can work together to explain the pathogenesis of metabolic disease.
长期以来,人们一直希望通过使用数学建模来帮助我们更好地理解糖尿病的发病机制。1979 年,Richard Bergman 和 Claudio Cobelli 合作,根据 Bergman 实验室的实验数据找到了一个“最小模型”。该模型是基于当时已知的生理学知识选择的最简单表示。该模型本身是两个准线性微分方程;一个代表血浆中胰岛素的动力学,另一个代表胰岛素和葡萄糖本身对静脉注射后葡萄糖恢复的影响。只有当模型包括胰岛素作用的延迟时,该模型才足够;也就是说,胰岛素必须进入一个远程隔室,即间质液 (ISF)。胰岛素缓慢抑制内源性葡萄糖输出(来自肝脏)。延迟被证明是由于最初抑制脂肪分解;由此降低的游离脂肪酸降低了肝脏葡萄糖输出。建模还要求在注射后使葡萄糖正常化包括葡萄糖本身对葡萄糖摄取和内源性葡萄糖产生的影响 - 这些影响被称为“葡萄糖效应”。通过将模型拟合到静脉葡萄糖耐量试验数据来计算胰岛素敏感性;所得胰岛素敏感性指数 SI 用人体葡萄糖钳夹法进行了验证。该模型使我们能够检查胰岛素敏感性和胰岛素分泌之间的关系。这种关系可以用矩形双曲线来描述,即胰岛素分泌 x 胰岛素敏感性=处置指数(DI)。后者代表了胰腺β细胞由于肥胖、妊娠或青春期等因素导致胰岛素抵抗时的补偿能力。DI 具有遗传基础,并预测 2 型糖尿病的发病。另一个因素是肝脏对胰岛素的清除。胰岛素在不同的动物或人群中的清除率差异很大;通过该模型,发现非裔美国人的清除率低于白种人(成年人和儿童),这可能是非裔美国人糖尿病患病率较高的一个因素。本文所述的研究强调了通过假设检验、实验研究和数学建模相结合来解释代谢疾病发病机制的有力方法。