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Development and use of a novel model of hepatic insulin extraction during an oral test
Full text linkThe regulation of glucose metabolism, in healthy subjects, is based on a complex control system which aims to maintain plasma glucose concentrations within a narrow range (70÷180 mg/dl). Insulin, a hormone secreted by pancreatic beta-cells, is fundamental in maintaining glucose homeostasis, by reducing liver glucose production, while promoting its utilization by the insulin-dependent organs. The inability of beta-cells to adequately secrete insulin creates metabolic disorders which can result in glucose intolerance and even diabetes mellitus. There are two different kinds of diabetes: type 1 diabetes (T1DM), characterized by a total inability of pancreatic beta-cells to secrete insulin, and type 2 diabetes (T2DM), in which, because of insulin resistance, tissues are unable to appropriately utilize glucose, and insulin secretion is unable to compensate for this defect. Given the increasing prevalence of diabetes, a complete understanding of all the mechanisms involved in the glucose regulation system is essential.
The liver is a fundamental organ in glucose regulation, since it is also responsible for circulating insulin levels by extracting about 50% of insulin appearing in the portal circulation, with every passage through it. A quantitative estimation of hepatic insulin extraction (HE), both in basal and dynamic physiological conditions (such as after an oral glucose load) is therefore a key aspect for a systematic description of glucose metabolism. Since a direct measurement of HE is very invasive, requiring the insertion of catheters into the portal and hepatic veins, indirect methods employing mathematical models are used. Such models require measurement of plasma concentrations and knowledge of the kinetics of C-peptide, and insulin secretion and clearance. This is facilitated by the fact that insulin and C-peptide are secreted in a 1:1 ratio by the beta-cells, and that the liver extracts insulin, but not C-peptide.
The first model available in the literature for assessing HE was developed by Toffolo et al. and describes HE during an insulin modified intravenous glucose tolerance test (IM-IVGTT); this model estimates the insulin secretion rate (ISR) and the insulin delivery rate (IDR) from C-peptide and insulin concentrations, respectively. HE is subsequently derived from these two fluxes. More recently, Campioni et al. proposed a model to estimate HE after meal ingestion. In this case HE is described as a piecewise linear function, with a fixed number of breakpoints, which are the model parameters to be estimated. The main limitation of this approach is that, although allowing a reconstruction of the HE profile, it does not provide a mechanistic relationship between the involved variables, and thus the resulting model parameters do not have an easy physiological interpretation. Moreover, model structure makes the parameter identification vulnerable to noise, since the HE profile may vary rapidly to fit fluctuations in peripheral insulin concentrations.
The aim of this work is to overcome the disadvantages of the available HE description by proposing a new physiological model of insulin kinetics and extraction. The best model is selected from seven, including an increasing number of compartments and different mechanistic descriptions of HE, each taking into account the influence of one or more modifiers, such as plasma glucose and insulin concentrations. In fact, during an oral test, one observes that, while glucose and insulin concentrations rise, the HE time course decreases in the meantime. These models are tested against data of a frequently sampled mixed meal (21 plasma samples) measured in 204 healthy subjects. The best model was selected according to standard criteria (ability to describe the data, precision of parameter estimates, model parsimony). Such a model describes insulin kinetics with three compartments, and HE as a function of plasma glucose concentration. One of the peculiarities of this model is to provide an index of HE sensitivity to glucose (SGHE), besides total (HEtot) and basal (HEb) HE indexes, already adopted in the literature. Moreover, the new model performs well even in data sets with less frequent sampling (11 samples).
The new model was then applied to three further databases, involving subjects with different degrees of glucose tolerance, studied with a standard mixed meal or the oral glucose tolerance test (OGTT). The first data set is composed of 62 prediabetic subjects (including healthy, glucose intolerant subjects, and subjects with impaired fasting glucose), who underwent a triple tracer mixed meal and an OGTT. The model was able to describe data during both the tests, and HE indexes are shown to correlate with the degree of dysfunction in glucose metabolism. The second data set consists of 11 healthy and 14 T2DM subjects, matched for age, weight and body mass index (BMI), who underwent a mixed meal test with the triple tracer technique. Also in this case, the new model predicts the data, and the estimated HE indexes (HEb, HEtot, SGHE) differ significantly between the two groups. The last database is composed of 14 subjects with T2DM who were treated with vildagliptin or placebo before the meal; moreover, at t = 300 min, 0.02 unit/kg insulin was administered intravenously (over a 5-min period), thus allowing a better estimation of insulin kinetics. In this case the model was used in two different ways: at first, analyzing all the available plasma samples, then, neglecting the insulin infusion and just considering the former part of the test. Interestingly, the model provided a good correlation among the HE parameters in these two different occasions.
In summary, we have developed a model of insulin kinetics which contains a new physiological description of HE. This model allows a good prediction of the available data during meals and OGTT in all the spectrum of glucose tolerance (healthy, intolerant and T2DM), also providing a powerful new index of HE sensitivity to glucose
Hepatic insulin extraction as measured by a novel physiologic model is defective in prediabetes.
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