Assessing the Effect of Incretin Hormones and Other Insulin Secretagogues on Pancreatic Beta-Cell Function: Review on Mathematical Modelling Approaches

Advances in small-molecule insulin secretagogues for diabetes treatment

Diabetes, a metabolic disease caused by abnormally high levels of blood glucose, has a high prevalence rate worldwide and causes a series of complications, including coronary heart disease, stroke, peripheral vascular disease, end-stage renal disease, and retinopathy. Small-molecule compounds have been developed as drugs for the treatment of diabetes because of their oral advantages. Insulin secretagogues are a class of small-molecule drugs used to treat diabetes, and include sulfonylureas, non-sulfonylureas, glucagon-like peptide-1 receptor agonists, dipeptidyl peptidase 4 inhibitors, and other novel small-molecule insulin secretagogues. However, many small-molecule compounds cause different side effects, posing huge challenges to drug monotherapy and drug selection. Therefore, the use of different small-molecule drugs must be improved. This article reviews the mechanism, advantages, limitations, and potential risks of small-molecule insulin secretagogues to provide future research directions on small-molecule drugs for the treatment of diabetes.

Acute Effects of Dietary Protein Consumption on the Postprandial Metabolic Response, Amino Acid Levels and Circulating MicroRNAs in Patients with Obesity and Insulin Resistance

The post-nutritional intervention modulation of miRNA expression has been previously investigated; however, post-acute dietary-ingestion-related miRNA expression dynamics in individuals with obesity and insulin resistance (IR) are unknown. We aimed to determine the acute effects of protein ingestion from different dietary sources on the postprandial metabolic response, amino acid levels, and circulating miRNA expression in adults with obesity and IR. This clinical trial included adults with obesity and IR who consumed (1) animal-source protein (AP; calcium caseinate) or (2) vegetable-source protein (VP; soy protein isolate). Glycaemic, insulinaemic, and glucagon responses, amino acid levels, and exosomal microRNAs isolated from plasma were analysed. Post-AP ingestion, the area under the curve (AUC) of insulin (p = 0.04) and the plasma concentrations of branched-chain (p = 0.007) and gluconeogenic (p = 0.01) amino acids increased. The effects of different types of proteins on the concentration of miRNAs were evaluated by measuring their plasma circulating levels. Compared with the baseline, the AP group presented increased circulating levels of miR-27a-3p, miR-29b-3p, and miR-122-5p (p < 0.05). Subsequent analysis over time at 0, 30, and 60 min revealed the same pattern and differences between treatments. We demonstrated that a single dose of dietary protein has acute effects on hormonal and metabolic regulation and increases exosomal miRNA expression in individuals with obesity and IR.

An extended minimal model of OGTT: estimation of α- and β-cell dysfunction, insulin resistance, and the incretin effect

Loss of insulin sensitivity, α- and β-cell dysfunction, and impairment in incretin effect have all been implicated in the pathophysiology of type 2 diabetes (T2D). Parsimonious mathematical models are useful in quantifying parameters related to the pathophysiology of T2D. Here, we extend the minimum model developed to describe the glucose-insulin-glucagon dynamics in the isoglycemic intravenous glucose infusion (IIGI) experiment to the oral glucose tolerance test (OGTT). The extended model describes glucose and hormone dynamics in OGTT including the contribution of the incretin hormones, glucose-dependent insulinotropic polypeptide (GIP), and glucagon-like peptide-1 (GLP-1), to insulin secretion. A new function describing glucose arrival from the gut is introduced. The model is fitted to OGTT data from eight individuals with T2D and eight weight-matched controls (CS) without diabetes to obtain parameters related to insulin sensitivity, β- and α-cell function. The parameters, i.e., measures of insulin sensitivity, a1, suppression of glucagon secretion, k1, magnitude of glucagon secretion, γ2, and incretin-dependent insulin secretion, γ3, were found to be different between CS and T2D with P values < 0.002, <0.017, <0.009, <0.004, respectively. A new rubric for estimating the incretin effect directly from modeling the OGTT is presented. The average incretin effect correlated well with the experimentally determined incretin effect with a Spearman rank test correlation coefficient of 0.67 (P < 0.012). The average incretin effect was found to be different between CS and T2D (P < 0.032). The developed model is shown to be effective in quantifying the factors relevant to T2D pathophysiology.NEW & NOTEWORTHY A new extended model of oral glucose tolerance test (OGTT) has been developed that includes glucagon dynamics and incretin contribution to insulin secretion. The model allows the estimation of parameters related to α- and β-cell dysfunction, insulin sensitivity, and incretin action. A new function describing the influx of glucose from the gut has been introduced. A new rubric for estimating the incretin effect directly from the OGTT experiment has been developed. The effect of glucose dose was also investigated.

Amino acid-stimulated insulin secretion: a path forward in type 2 diabetes

Qualitative and quantitatively appropriate insulin secretion is essential for optimal control of blood glucose. Beta-cells of the pancreas produce and secrete insulin in response to glucose and non-glucose stimuli including amino acids. In this manuscript, we review the literature on amino acid-stimulated insulin secretion in oral and intravenous in vivo studies, in addition to the in vitro literature, and describe areas of consensus and gaps in understanding. We find promising evidence that the synergism of amino acid-stimulated insulin secretion could be exploited to develop novel therapeutics, but that a systematic approach to investigating these lines of evidence is lacking. We highlight evidence that supports the relative preservation of amino acid-stimulated insulin secretion compared to glucose-stimulated insulin secretion in type 2 diabetes, and make the case for the therapeutic potential of amino acids. Finally, we make recommendations for research and describe the potential clinical utility of nutrient-based treatments for type 2 diabetes including remission services.

A pathway model of glucose-stimulated insulin secretion in the pancreatic β-cell

The pancreas plays a critical role in maintaining glucose homeostasis through the secretion of hormones from the islets of Langerhans. Glucose-stimulated insulin secretion (GSIS) by the pancreatic β-cell is the main mechanism for reducing elevated plasma glucose. Here we present a systematic modeling workflow for the development of kinetic pathway models using the Systems Biology Markup Language (SBML). Steps include retrieval of information from databases, curation of experimental and clinical data for model calibration and validation, integration of heterogeneous data including absolute and relative measurements, unit normalization, data normalization, and model annotation. An important factor was the reproducibility and exchangeability of the model, which allowed the use of various existing tools. The workflow was applied to construct a novel data-driven kinetic model of GSIS in the pancreatic β-cell based on experimental and clinical data from 39 studies spanning 50 years of pancreatic, islet, and β-cell research in humans, rats, mice, and cell lines. The model consists of detailed glycolysis and phenomenological equations for insulin secretion coupled to cellular energy state, ATP dynamics and (ATP/ADP ratio). Key findings of our work are that in GSIS there is a glucose-dependent increase in almost all intermediates of glycolysis. This increase in glycolytic metabolites is accompanied by an increase in energy metabolites, especially ATP and NADH. One of the few decreasing metabolites is ADP, which, in combination with the increase in ATP, results in a large increase in ATP/ADP ratios in the β-cell with increasing glucose. Insulin secretion is dependent on ATP/ADP, resulting in glucose-stimulated insulin secretion. The observed glucose-dependent increase in glycolytic intermediates and the resulting change in ATP/ADP ratios and insulin secretion is a robust phenomenon observed across data sets, experimental systems and species. Model predictions of the glucose-dependent response of glycolytic intermediates and biphasic insulin secretion are in good agreement with experimental measurements. Our model predicts that factors affecting ATP consumption, ATP formation, hexokinase, phosphofructokinase, and ATP/ADP-dependent insulin secretion have a major effect on GSIS. In conclusion, we have developed and applied a systematic modeling workflow for pathway models that allowed us to gain insight into key mechanisms in GSIS in the pancreatic β-cell.

Mathematical model of insulin kinetics accounting for the amino acids effect during a mixed meal tolerance test

Amino acids (AAs) are well known to be involved in the regulation of glucose metabolism and, in particular, of insulin secretion. However, the effects of different AAs on insulin release and kinetics have not been completely elucidated. The aim of this study was to propose a mathematical model that includes the effect of AAs on insulin kinetics during a mixed meal tolerance test. To this aim, five different models were proposed and compared. Validation was performed using average data, derived from the scientific literature, regarding subjects with normal glucose tolerance (CNT) and with type 2 diabetes (T2D). From the average data of the CNT and T2D people, data for two virtual populations (100 for each group) were generated for further model validation. Among the five proposed models, a simple model including one first-order differential equation showed the best results in terms of model performance (best compromise between model structure parsimony, estimated parameters plausibility, and data fit accuracy). With regard to the contribution of AAs to insulin appearance/disappearance (k_AA model parameter), model analysis of the average data from the literature yielded 0.0247 (confidence interval, CI: 0.0168 - 0.0325) and -0.0048 (CI: -0.0281 - 0.0185) μU·ml^-1/(μmol·l^-1·min), for CNT and T2D, respectively. This suggests a positive effect of AAs on insulin secretion in CNT, and negligible effect in T2D. In conclusion, a simple model, including single first-order differential equation, may help to describe the possible AAs effects on insulin kinetics during a physiological metabolic test, and provide parameters that can be assessed in the single individuals.