Glucose effectiveness and insulin sensitivity measurements derived from the non-insulin-assisted minimal model and the clamp techniques are concordant

Dynamical modeling the effect of glucagon-like peptide on glucose-insulin regulatory system based on mice experimental observation

As an emerging global epidemic, type 2 diabetes mellitus (T2DM) represents one of the leading causes of morbidity and mortality worldwide. Existing evidences demonstrated that glucagon-like peptide-1 (GLP-1) modulate the glucose regulatory system by enhancing the β-cell function. However, the detailed process of GLP-1 in glycaemic regulator for T2DM remains to be clarified. Thus, in this study, we propose an Institute of Cancer Research (ICR) mice high fat and cholesterol dietary experimental data-driven mathematical model to investigate the secretory effect of GLP-1 on the dynamics of glucose-insulin regulatory system. Specifically, we develop a mathematical model of GLP-1 dynamics as part of the interaction model of β-cell, insulin, and glucose dynamics. The parameter estimation and data fitting are in agreement with the data in mice experiments In addition, uncertainty quantification is performed to explore the possible factors that influence the pathways leading to the pathological state. Model analyses reveal that the high fat or high cholesterol diet stimulated GLP-1 plays an important role in the dynamics of glucose, insulin and β cells in short-term. These results show that enhanced GLP-1 may mitigate the dysregulation of glucose-insulin regulatory system via promoting the β cells function and stimulating secretion of insulin, which offers an in-depth insights into the mechanistic of hyperglycemia from dynamical approach and provide the theoretical basis for GLP-1 served as a potential clinical targeted drug for treatment of T2DM.

An Analysis of Glucose Effectiveness in Subjects With or Without Type 2 Diabetes via Hierarchical Modeling

Glucose effectiveness, defined as the ability of glucose itself to increase glucose utilization and inhibit hepatic glucose production, is an important mechanism maintaining normoglycemia. We conducted a minimal modeling analysis of glucose effectiveness at zero insulin (GEZI) using intravenous glucose tolerance test data from subjects with type 2 diabetes (T2D, n=154) and non-diabetic (ND) subjects (n=343). A hierarchical statistical analysis was performed, which provided a formal mechanism for pooling the data from all study subjects, to yield a single composite population model that quantifies the role of subject specific characteristics such as weight, height, age, sex, and glucose tolerance. Based on the resulting composite population model, GEZI was reduced from 0.021 min-1 (standard error - 0.00078 min-1) in the ND population to 0.011 min-1 (standard error - 0.00045 min-1) in T2D. The resulting model was also employed to calculate the proportion of the non-insulin-dependent net glucose uptake in each subject receiving an intravenous glucose load. Based on individual parameter estimates, the fraction of total glucose disposal independent of insulin was 72.8% ± 12.0% in the 238 ND subjects over the course of the experiment, indicating the major contribution to the whole-body glucose clearance under non-diabetic conditions. This fraction was significantly reduced to 48.8% ± 16.9% in the 30 T2D subjects, although still accounting for approximately half of the total in the T2D population based on our modeling analysis. Given the potential application of glucose effectiveness as a predictor of glucose intolerance and as a potential therapeutic target for treating diabetes, more investigations of glucose effectiveness in other disease conditions can be conducted using the hierarchical modeling framework reported herein.

Estimated insulin sensitivity in Type 1 diabetes adults using clinical and research biomarkers

AIMS

Insulin resistance in people with type 1 diabetes (T1D) is associated with increased risk of chronic complications and death. The gold standard to quantify insulin sensitivity, a euglycaemic hyperinsulinaemic clamp, is not applicable to clinical practice. We have employed clamp studies to develop a panel of formulae to estimate insulin sensitivity in adults with T1D for use in clinical practice and trials.

METHODS

Clamps were conducted in 28 adults with T1D, who were also characterised with 38 clinical and research biomarkers. Exhaustive search analysis was used to derive equations correlating with clamp-quantified glucose disposal rate (GDR), GDR/plasma insulin (M/I) and log₁₀M/I.

RESULTS

Measured insulin sensitivity correlated with BMI, WHR, HDL-C, adipokines and inflammation markers on univariate analysis. Exhaustive search analysis derived three formulae correlating with clamp-derived GDR and logM/I (p < 0.0001), accounting for ≈62% of their variability. A formula using gender, age, HDL-C, pulse pressure and WHR performed as well as those containing inflammation and adipokine measures.

CONCLUSIONS

The performance of formulae using routinely available parameters with/without research biomarkers in clinical studies and trials, particularly related to future complications, relevant lifestyle interventions, insulin delivery modes and insulin sensitisers is merited.

Glucose Effectiveness from Short Insulin-Modified IVGTT and Its Application to the Study of Women with Previous Gestational Diabetes Mellitus

BACKGROUND

This study aimed to design a simple surrogate marker (i.e., predictor) of the minimal model glucose effectiveness (S_G), namely calculated S_G (CS_G), from a short insulin-modified intravenous glucose tolerance test (IM-IVGTT), and then to apply it to study women with previous gestational diabetes mellitus (pGDM).

METHODS

CS_G was designed using the stepwise model selection approach on a population of subjects (n=181) ranging from normal tolerance to type 2 diabetes mellitus (T2DM). CS_G was then tested on a population of women with pGDM (n=57). Each subject underwent a 3-hour IM-IVGTT; women with pGDM were observed early postpartum and after a follow-up period of up to 7 years and classified as progressors (PROG) or non-progressors (NONPROG) to T2DM. The minimal model analysis provided a reference S_G.

RESULTS

CS_G was described as CS_G=1.06×10⁻²+5.71×10⁻²×K_G/G_peak, K_G being the mean slope (absolute value) of loge glucose in 10-25- and 25-50-minute intervals, and G_peak being the maximum of the glucose curve. Good agreement between CS_G and S_G in the general population and in the pGDM group, both at baseline and follow-up (even in PROG and NONPROG subgroups), was shown by the Bland-Altman plots (<5% observations outside limits of agreement), and by the test for equivalence (equivalence margin not higher than one standard deviation). At baseline, the PROG subgroup showed significantly lower S_G and CS_G values compared to the NONPROG subgroup (P<0.03).

CONCLUSION

CS_G is a valid S_G predictor. In the pGDM group, glucose effectiveness appeared to be impaired in women progressing to T2DM.

Glucose effectiveness and its components in relation to body mass index

BACKGROUND

Obesity is known to induce a deterioration of insulin sensitivity (S_I ), one of the insulin-dependent components of glucose tolerance. However, few studies investigated whether obesity affects also the insulin-independent component, that is glucose effectiveness (S_G ). This cross-sectional study aimed to analyse S_G and its components in different body mass index (BMI) categories.

MATERIALS AND METHODS

Three groups of subjects spanning different BMI (kg m^-2 ) categories underwent a 3-h frequently sampled intravenous glucose tolerance test: Lean (LE; 18.5 ≤ BMI < 25, n = 73), Overweight (OW; 25 ≤ BMI < 30, n = 90), and Obese (OB; BMI ≥ 30, n = 41). OB has been further divided into two subgroups, namely Obese I (OB-I; 30 ≤ BMI < 35, n = 27) and Morbidly Obese (OB-M; BMI ≥ 35, n = 14). Minimal model analysis provided S_G and its components at zero (GEZI) and at basal (BIE) insulin.

RESULTS

Values for S_G were 1.98 ± 1.30 × 10^-2 ·min^-1 in all subjects grouped and 2.38 ± 1.23, 1.84 ± 0.82, 1.59 ± 0.61 10^-2 ·min^-1 in LE, OW and OB, respectively. In all subjects grouped, a significant inverse linear correlation was found between the log-transformed values of S_G and BMI (r = -0.3, P < 0.0001). S_G was significantly reduced in OW and OB with respect to LE (P < 0.001) but no significant difference was detected between OB and OW (P = 0.35) and between OB-I and OB-M (P = 0.25). Similar results were found for GEZI. BIE was not significantly different among NW, OW and OB (P = 0.11) and between OB-I and OB-M (P ≥ 0.07).

CONCLUSIONS

S_G and its major component GEZI deteriorate in overweight individuals compared to those in the normal BMI range, without further deterioration when BMI increases above 30 kg m^-2 .

Assessing the predictive accuracy of oral glucose effectiveness index using a calibration model

PURPOSE

Current reference methods for measuring glucose effectiveness (GE) are the somatostatin pancreatic glucose clamp and minimal model analysis of frequently sampled intravenous glucose tolerance test (FSIVGTT), both of which are laborious and not feasible in large epidemiological studies. Consequently, surrogate indices derived from an oral glucose tolerance test (OGTT) to measure GE (oGE) have been proposed and used in many studies. However, the predictive accuracy of these surrogates has not been formally validated. In this study, we used a calibration model analysis to evaluate the accuracy of surrogate indices to predict GE from the reference FSIVGTT (Sg_MM).

METHODS

Subjects (n = 123, mean age 48 ± 11 years; BMI 35.9 ± 7.3 kg/m²) with varying glucose tolerance (NGT, n = 37; IFG/IGT, n = 78; and T2DM, n = 8) underwent FSIVGTT and OGTT on two separate days. Predictive accuracy was assessed by both root mean squared error (RMSE) of prediction and leave-one-out cross-validation-type RMSE of prediction (CVPE).

RESULTS

As expected, insulin sensitivity, Sg_MM, and oGE were reduced in subjects with T2DM and IFG/IGT when compared with NGT. Simple linear regression analyses revealed a modest but significant relationship between oGE and Sg_MM (r = 0.25, p < 0.001). However, using calibration model, measured Sg_MM and predicted Sg_MM derived from oGE were modestly correlated (r = 0.21, p < 0.05) with the best fit line suggesting poor predictive accuracy. There were no significant differences in CVPE and RMSE among the surrogates, suggesting similar predictive ability.

CONCLUSIONS

Although OGTT-derived surrogate indices of GE are convenient and feasible, they have limited ability to robustly predict GE.

Glucose effectiveness is a critical pathogenic factor leading to glucose intolerance and type 2 diabetes: An ignored hypothesis

BACKGROUND

Although the ability of glucose to mediate its own in vivo metabolism is long documented, the quantitative measurement of whole body glucose-mediated glucose disposal at basal insulin levels (glucose effectiveness [GE]), followed the introduction of the Minimal Model intravenous glucose tolerance test technique.

METHODS

A literature review, combined with our own studies, of the role of GE in glucose metabolism in normal and "at risk" individuals, was undertaken to determine GE's contribution to glucose homeostasis.

RESULTS

GE accounts for ~45% to 65% of glucose disposal in man. A negative association between GE and insulin meditated glucose disposal (Si), is present in normal subjects without a family history of type 2 diabetes mellitus but is absent in normoglycaemic "at risk" relatives with a positive family history of diabetes mellitus. Intracellular GE disposal is mediated by mass action of glucose through the skeletal muscle membrane via facilitated Glut 4 transporters. However, GE is frequently forgotten as a significant contributor to the development of glucose intolerance in "at risk" individuals. Only limited studies have examined the role of a lower GE in such normoglycemic subjects with preexisting mild insulin resistance and β-cell dysfunction. These studies demonstrate that in "at risk" individuals, an initial low GE is a key contributor and predictor of future glucose intolerance, whereas an initial raised GE is protective against future glucose intolerance.

CONCLUSION

In "at risk" individuals, a low GE and genetically determined vulnerable β-cell function are more critical determinants of future glucose intolerance than their preexisting insulin-resistant state.