Insulin-modified Intravenous Glucose Tolerance Test Research Articles

Model-Based Assessment of Hepatic and Extrahepatic Insulin Clearance from Short Insulin-Modified IVGTT in Women with a History of Gestational Diabetes.

Insulin clearance is an integral component of insulin metabolism. Yet, little is known about separate contribution of hepatic and extrahepatic insulin clearance in type 2 diabetes and in high-risk populations, such as women who experienced gestational diabetes mellitus (pGDM). A model-based method was recently proposed to assess both contributions from 3-hour insulin-modified intravenous glucose tolerance test (IM-IVGTT); the aim of this study was to assess the reliability of short (1 hour) IM-IVGTT in the application of such model-based method and to evaluate the role of the two contributions in determining insulin clearance in pGDM. A total of 115 pGDM women and 41 who remained healthy during pregnancy (CNT) were analyzed early postpartum and underwent a 3-hour IMIVGTT. Peripheral insulin clearance (CLP), hepatic fractional extraction (FEL) and extrahepatic distribution volume (VP) were estimated by performing a best-fit procedure on insulin IMIVGTT data considering firstly the overall 3-hour duration and then limiting data to 1 hour. Results showed no significant difference in parameter values between the 3-hour and the 1-hour IM-IVGTT. Comparison between pGDM and CNT (1-hour) showed no significant difference in CLp (0.23 [0.29] vs. 0.27 [0.43] L·min-1; p=0.64), FEL (50.2 [15.1] vs. 50.9 [11.7] %; p=0.63) and VP (2.01 [2.99] vs. 2.70 [4.00] L; p=0.92). In conclusion, short IM-IVGTT provides a reliable assessment of hepatic and extrahepatic insulin clearance through such model-based method. Its application to the study of pGDM women showed no alteration in hepatic and extrahepatic contributions with respect to women who had a healthy pregnancy.Clinical Relevance- This study proves the reliability of short (1 hour) IM-IVGTT to assess hepatic and extrahepatic insulin clearance in women who experienced gestational diabetes.

The pathophysiology of glucose intolerance in newly diagnosed, untreated T2DM

AimsThe two predominant pathophysiological defects resulting in glucose intolerance are beta-cell dysfunction and insulin insensitivity. This study aimed to re-examine beta-cell function and insulin sensitivity across a continuum from normal glucose tolerance (NGT) to early type 2 diabetes (T2DM) employing highly specific insulin, C-peptide and intact proinsulin assays.Materials and methodsA total of 104 persons with NGT, 85 with impaired glucose tolerance (IGT) and 554 with newly diagnosed T2DM were investigated. Following an overnight fast, all underwent a 4-h standardised mixed meal tolerance test (MTT), and on a second day, a sub-group underwent a frequently sampled insulin-modified intravenous glucose tolerance test (FSIVGTT) over a 3-h period. The participants were stratified according to fasting glucose and BMI for analysis.ResultsThe MTT revealed that increasing FPG was accompanied by progressively elevated and delayed postprandial glucose peaks. In parallel, following an initial compensatory increase in fasting and postprandial insulin responses there followed a progressive demise in overall beta-cell secretory capacity. FSIVGTT demonstrated a major reduction in the early insulin response to IV glucose in persons with IGT accompanied by a dramatic fall in insulin sensitivity. Beyond pre-diabetes, ever-increasing fasting and postprandial hyperglycaemia resulted predominantly from a progressively decreasing beta-cell secretory function.ConclusionThis study utilising improved assay technology re-affirms that beta-cell dysfunction is evident throughout the spectrum of glucose intolerance, whereas the predominant fall in insulin sensitivity occurs early in its evolution.

Hyperinsulinemic Compensation for Insulin Resistance Occurs Independent of Elevated Glycemia in Male Dogs.

Insulin resistance engenders a compensatory increase in plasma insulin. Inadequate compensation is a primary element in the pathogenesis of type 2 diabetes. The signal that heralds developing insulin resistance and initiates hyperinsulinemic compensation is not known. It has often been assumed to be increased glucose. We tested this assumption by determining whether development of fasting and/or glucose-stimulated hyperinsulinemia with diet-induced insulin resistance occurs because of concomitant elevation of glycemia. Male dogs (n = 58) were fed a hypercaloric, fat-supplemented diet for 6 weeks. Dogs underwent magnetic resonance imaging to quantify total and regional (visceral, subcutaneous) adiposity as well as euglycemic hyperinsulinemic clamps. A subset of animals also underwent an insulin-modified intravenous glucose tolerance test to assess insulin sensitivity, acute insulin response (AIRg), and glucose effectiveness. Fat feeding caused modest weight gain, increased visceral and subcutaneous fat, and insulin resistance at both peripheral and hepatic levels. Hyperinsulinemic compensation was observed in fasting levels as well as increased AIRg. However, we observed absolutely no increase in carefully measured fasting, evening (6 to 8 pm) or nocturnal glycemia (2 to 4 am). Insulin resistance and hyperinsulinemia occurred despite no elevation in 24-hour glucose. Compensatory development of hyperinsulinemia during diet-induced insulin resistance occurs without elevated fasting or 24-hour glycemia. These data refute the idea that glucose itself is a requisite signal for β-cell upregulation. Alternative feedback mechanisms need to be identified.

Effects of energy source in milk replacer on glucose metabolism of neonatal dairy calves

Milk replacers (MR) formulated to contain more lactose than whole milk could potentially reduce insulin sensitivity in dairy calves. This study evaluated how partially replacing lactose in MR with fat on a weight/weight basis affects glucose-insulin kinetics in neonatal dairy calves fed high quantities of MR. Thirty-four Holstein bull calves were blocked by dam parity (1.6 ± 0.3) and randomly assigned to 1 of 2 treatments (n = 17): a high-lactose MR (HL; 46.1% lactose, 18.0% crude fat, and 23.9% crude protein on a dry matter basis) or a high fat MR (HF; 39.9% lactose, 24.6% crude fat, and 24.0% crude protein on a dry matter basis). Calves were individually housed and fed pooled colostrum at 1.5 h and 12 h postnatal at 18 and 9% of metabolic body weight (BW0.75), respectively. From 24 h postnatal until the end of the study (d 7), calves were transitioned to MR (prepared at 150 g/L) at 18% of BW0.75 twice daily at 0700 and 1900 h. On d 4, an insulin-modified intravenous glucose tolerance test was conducted 8 h after the morning meal by intravenous infusion of glucose (0.54 g/kg of BW0.75, min 0) and insulin (3.9 µg/kg of BW0.75, min 20). During postprandial sampling on d 6, abomasal emptying was assessed by dosing acetaminophen (0.13 g/kg of BW0.75) with MR and measuring its appearance within plasma. Sequential blood samples were collected and analyzed for plasma glucose, insulin, and acetaminophen concentrations. Calves were killed on d 7 and liver and pancreatic tissues were collected for histomorphological analysis. Partially replacing lactose in MR with fat increased body weight gain (679.6 vs. 462.0 ± 69.68 g/d) and gain:metabolizable energy intake (186.6 vs. 120.5 ± 20.21 g of body weight/Mcal) compared with feeding HL MR. Furthermore, abomasal emptying rate was reduced in calves fed HF MR. Calculated variables based on postprandial glucose and insulin concentrations, such as maximum concentration or area under the curve, were or tended to be lower in HF than in HL calves. Postprandial insulin sensitivity tended to be reduced in HL compared with HF, although insulin sensitivity estimated from the insulin-modified intravenous glucose tolerance test was not different. Calves fed HF MR showed enhanced glucose-stimulated insulin secretion. In conclusion, partially replacing lactose in MR with fat resulted in smaller fluctuations in postprandial glucose and insulin concentrations and tended to increase postprandial but not fasting insulin sensitivity in neonatal dairy calves.

Optimal Designs for Model-Based Assessment of Insulin Sensitivity and Glucose Effectiveness.

The integrated minimal model allows assessment of clinical diagnosis indices, for example, insulin sensitivity (SI ) and glucose effectiveness (SG ), from data of the insulin-modified intravenous glucose tolerance test (IVGTT), which is laborious with an intense sampling schedule, up to 32 samples. The aim of this study was to propose a more informative, although less laborious, IVGTT design to be used for model-based assessment of SI and SG . The IVGTT design was optimized simultaneously for all design variables: glucose and insulin infusion doses, time of glucose dose and start of insulin infusion, insulin infusion duration, sampling times, and number of samples. Design efficiency was used to compare among different designs. The simultaneously optimized designs showed a profound higher efficiency than both standard rich (32 samples) and sparse (10 samples) designs. The optimized designs, after removing replicate sample times, were 1.9 and 7.1 times more efficient than the standard rich and sparse designs, respectively. After including practical aspects of the designs, for example, sufficient duration between samples and avoidance of prolonged hypoglycemia, we propose 2 practical designs with fewer sampling times and lower input of glucose and insulin than standard designs, constrained to prevent hypoglycemia. The optimized practical rich design is equally efficient in assessing SI and SG as the rich standard design, but with half the number of the samples, while the optimized practical sparse design has 1 less sample and requires 4.6 times fewer individuals for equal certainty when assessing SI and SG than the sparse standard design.

Insulin clearance is altered in women with a history of gestational diabetes progressing to type 2 diabetes

Background and aimsInsulin clearance is a relevant process in glucose homeostasis. In this observational study, we aimed to assess insulin clearance (ClINS) in women with former gestational diabetes (fGDM) both early after delivery and after a follow-up. Methods and resultsWe analysed 59 fGDM women, and 16 women not developing GDM (CNT). All women underwent an oral glucose tolerance test (OGTT) yearly, and an insulin-modified intravenous glucose tolerance test (IVGTT) at baseline and at follow-up end (until 7 years). Both IVGTT and OGTT ClINS was assessed as insulin secretion to plasma insulin ratio. We also defined IVGTT first (0–10 min) and second phase (10–180 min) ClINS. We found that 14 fGDM women progressed to type 2 diabetes (PROG), whereas 45 women remained diabetes-free (NONPROG). At baseline, IVGTT ClINS showed alterations in PROG, especially in second phase (0.88 ± 0.10 l·min−1 in PROG, 0.60 ± 0.06 in NONPROG, 0.54 ± 0.07 in CNT, p ≤ 0.03). Differences in ClINS were not found from OGTT. Cox regression analysis showed second phase ClINS as significant type 2 diabetes predictor (hazard ratio = 1.90, 95% confidence interval 1.09–3.30, p = 0.02). ConclusionThis study showed that insulin clearance derived from an insulin-modified IVGTT is notably altered in women with history of GDM progressing towards type 2 diabetes.

Metabolic modeling using statistical and spreadsheet software: Application to the glucose minimal model

Kinetic non-linear metabolic models are used extensively in medical research and increasingly for clinical diagnostic purposes. An example of such a model is the Glucose Minimal Model by Bergman and colleagues [1]. This model is similar to pharmacokinetic/pharmacodynamic models in that like pharmacokinetic/pharmacodynamic models, it is based on a small number of fairly simple ordinary differential equations and it aims to determine how the changing concentration of one blood constituent influences the concentration of another constituent. Although such models may appear prima facie, to be relatively simple, they have gained a reputation of being difficult to fit to data, especially in a consistent and repeatable fashion. Consequently, researchers and clinicians have generally relied on dedicated software packages to do this type of modeling.This article describes the use of statistical and spreadsheet software for fitting the Glucose Minimal Model to data from an insulin modified intravenous glucose tolerance test (IM-IVGTT). A novel aspect of the modeling is that the differential equations that are normally used to describe insulin action and the disposition of plasma glucose are first solved and expressed in their explicit forms so as to facilitate the estimation of Glucose Minimal Model parameters using the nonlinear (nl) optimization procedure within statistical and spreadsheet software. The most important clinical parameter obtained from the Glucose Minimal Model is insulin sensitivity (SI). Using IM-IVGTT data from 42 horses in one experiment and 48 horses in a second experiment, we demonstrate that estimates of SI derived from the Glucose Minimal Model fitted to data using STATA and Excel, are highly concordant with SI estimates obtained using the industry standard software, MinMod Millennium. This work demonstrates that there is potential for statistical and spreadsheet software to be applied to a wide range of kinetic non-linear modeling problems.

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

BackgroundThis study aimed to design a simple surrogate marker (i.e., predictor) of the minimal model glucose effectiveness (SG), namely calculated SG (CSG), 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).MethodsCSG 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). CSG 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 SG.ResultsCSG was described as CSG=1.06×10−2+5.71×10−2×KG/Gpeak, KG being the mean slope (absolute value) of loge glucose in 10–25- and 25–50-minute intervals, and Gpeak being the maximum of the glucose curve. Good agreement between CSG and SG 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 SG and CSG values compared to the NONPROG subgroup (P<0.03).ConclusionCSG is a valid SG predictor. In the pGDM group, glucose effectiveness appeared to be impaired in women progressing to T2DM.

Former gestational diabetes: Mathematical modeling of intravenous glucose tolerance test for the assessment of insulin clearance and its determinants.

Women with a previous history of gestational diabetes mellitus (GDM) have increased risk of developing GDM in future pregnancies (i.e. recurrent GDM) and also Type 2 Diabetes (T2D). Insulin clearance represents one of the processes regulating glucose tolerance but has been scarcely investigated for its possible impairment in high-risk subjects. The aim of this study was to identify possible determinants of insulin clearance in women with a previous history of GDM. A detailed model-based analysis of a regular 3-hour, insulin-modified intravenous glucose tolerance test (IM-IVGTT) has been performed in women with a previous history of GDM (pGDM, n = 115) and in women who had a healthy pregnancy (CNT, n = 41) to assess total, first-phase and second-phase insulin clearance (ClINS-TOT, ClINS-FP and ClINS-SP) and other metabolic parameters (insulin sensitivity SI, glucose effectiveness SG, beta-cell function and disposition index DI). CLINS-SP was found increased in pGDM with respect to CNT and was found significantly inversely linearly correlated with SG (r = -0.20, p = 0.03, slope: -16.2, 95% CI -30.9 to -1.4, intercept: 1.1, 95% CI 0.7-1.4) and also with DI (r = -0.22, p = 0.02, slope: -10.0, 95% CI -18.5 to -1.6, intercept: 0.9, 95% CI 0.7-1.3). Disposition index, accounting for the combined contribution of insulin sensitivity and beta-cell function, and glucose effectiveness were identified as possible determinants of insulin clearance in women with a previous history of GDM. This may be of relevance for more accurate estimation and prevention of the risk for recurrent GDM and T2D.

Host-microbiome interactions in human type 2 diabetes following prebiotic fibre (galacto-oligosaccharide) intake.

Aberrant microbiota composition and function have been linked to several pathologies, including type 2 diabetes. In animal models, prebiotics induce favourable changes in the intestinal microbiota, intestinal permeability (IP) and endotoxaemia, which are linked to concurrent improvement in glucose tolerance. This is the first study to investigate the link between IP, glucose tolerance and intestinal bacteria in human type 2 diabetes. In all, twenty-nine men with well-controlled type 2 diabetes were randomised to a prebiotic (galacto-oligosaccharide mixture) or placebo (maltodextrin) supplement (5·5 g/d for 12 weeks). Intestinal microbial community structure, IP, endotoxaemia, inflammatory markers and glucose tolerance were assessed at baseline and post intervention. IP was estimated by the urinary recovery of oral 51Cr-EDTA and glucose tolerance by insulin-modified intravenous glucose tolerance test. Intestinal microbial community analysis was performed by high-throughput next-generation sequencing of 16S rRNA amplicons and quantitative PCR. Prebiotic fibre supplementation had no significant effects on clinical outcomes or bacterial abundances compared with placebo; however, changes in the bacterial family Veillonellaceae correlated inversely with changes in glucose response and IL-6 levels (r -0·90, P=0·042 for both) following prebiotic intake. The absence of significant changes to the microbial community structure at a prebiotic dosage/length of supplementation shown to be effective in healthy individuals is an important finding. We propose that concurrent metformin treatment and the high heterogeneity of human type 2 diabetes may have played a significant role. The current study does not provide evidence for the role of prebiotics in the treatment of type 2 diabetes.

Evaluation of an Insulin Sensitivity Index from the Short Intravenous Glucose Tolerance Test for Detecting Response to a Dietary Intervention

The aim of this analysis was to evaluate an insulin sensitivity index (Tura SI) from the short (50 min) insulin‐modified intravenous glucose tolerance test (IVGTT), compared with minimal model analysis of 180 min IVGTT data (MM SI). Subjects, a subset of a clinical trial sample (J Nutr 2012;142:717–723) who agreed to take part in a substudy, included men (n = 8) and women (n = 16), with mean (SD) age 48.9 (9.9) y and body mass index 30.8 (4.9) kg/m2. Participants consumed 0, 15, and 30 g/d high‐amylose resistant starch (RS) for 4 wk each in a double‐blind, randomized, crossover trial. MM SI was assessed after each condition with a 0.3 g/kg IV glucose bolus (t = 0 min) followed by regular human insulin (0.03 U/kg, t = 20 min). Plasma samples were collected at frequent intervals over 180 min. MM SI was calculated with MINMOD MILLENIUM v6.02. Tura SI was calculated as the fractional glucose disappearance rate/mean increment above baseline plasma insulin, both from 10–50 min. MM SI and Tura SI were 3.70 (2.85) and 3.24 (2.17) × 10−4 L/(min*mU), respectively. Median (interquartile limits) % changes from control at 15 g/d RS were 28.3 (−2.7, 85.3; p = 0.005) and 29.2 (−8.3, 74.4; p = 0.01), for MM SI and Tura SI, respectively; 30 g/d RS values were 16.1 (−9.8, 58.9; p = 0.03), and 19.3 (−12.8, 47.6; p = 0.03), for MM SI and Tura SI, respectively. The two indices were highly correlated during each condition: r = 0.957 (control), 0.920 (15 g/d), and 0.958 (30 g/d) (all p &lt;0.001). These results support the use of Tura SI as a less costly and time‐consuming method than MM SI for assessing changes in whole‐body insulin sensitivity.Support or Funding InformationIngredion, Westchester, IL

Human insulin dynamics in women: a physiologically based model.

Currently available models of insulin dynamics are mostly based on the classical compartmental structure and, thus, their physiological utility is limited. In this work, we describe the development of a physiologically based model and its application to data from 154 patients who underwent an insulin-modified intravenous glucose tolerance test (IM-IVGTT). To determine the time profile of endogenous insulin delivery without using C-peptide data and to evaluate the transcapillary transport of insulin, the hepatosplanchnic, renal, and peripheral beds were incorporated into the circulatory model as separate subsystems. Physiologically reasonable population mean estimates were obtained for all estimated model parameters, including plasma volume, interstitial volume of the peripheral circulation (mainly skeletal muscle), uptake clearance into the interstitial space, hepatic and renal clearance, as well as total insulin delivery into plasma. The results indicate that, at a population level, the proposed physiologically based model provides a useful description of insulin disposition, which allows for the assessment of muscle insulin uptake.

IMPACT OF DIETARY FATTY ACIDS ON LIPID PROFILE, INSULIN SENSITIVITY AND FUNCTIONALITY OF PANCREATIC β CELLS IN TYPE 2 DIABETIC SUBJECTS

the quality of fats could influence the metabolic control of patients with Type 2 Diabetes Mellitus (DM2). to determine the relationship between intake and quality of dietary fatty acids to lipid profile, metabolic control, functionality of pancreatic cells and insulin sensivity in subjects with DM2. we studied 54 subjects with DM2, anthropometric measurements were performed, body composition and dietary lipid intake, saturated fatty acids (SFA), trans, monounsaturated, polyunsaturated, omega 3, omega 6 and dietary cholesterol. Laboratory parameters related to their metabolic control were determined (fasting blood glucose, glycated hemoglobin, and lipid profile). The insulin secretion and insulin sensitivity was determined with the insulin-modified intravenous glucose tolerance test according to the Bergman's minimal model. 28 men and 26 women were studied (BMI of 29.5 ± 3.7 kg/m2; age 55.6 ± 6.8 y.), 48% had LDL-C < 100 mg/dL, 12.9% of men c-HDL > 40 mg/dL and 7.4% of women c-HDL > 50 mg/dL. 32% consumed > 10% of AGS and > 300 mg/day of dietary cholesterol. The SFA intake and percentage of calories from fat (G%) were significantly associated with insulin resistance and fasting plasma glucose concentration. The G% predicted 84% variability on c-VLDL. in patients with DM2 a greater intake of fat and saturated fatty acids it associated with greater fasting glycemia and insulin resistance.

Weight Loss Programs May Have Beneficial or Adverse Effects on Fat Mass and Insulin Sensitivity in Overweight and Obese Black Women.

ObjectiveWeight loss interventions have produced little change in insulin sensitivity in black women, but mean data may obscure metabolic benefit to some and adverse effects for others. Accordingly, we analyzed insulin sensitivity relative to fat mass change following a weight loss program.Design and MethodsFifty-four black women (BMI range 25.9 to 54.7 kg/m2) completed the 6-month program that included nutrition information and worksite exercise facilities. Fat mass was measured by dual-energy X-ray absorptiometry, and insulin sensitivity index (SI) was calculated from an insulin-modified intravenous glucose tolerance test using the minimal model.ResultsBaseline SI (range 0.74 to 7.58 l/mU−1•min−1) was inversely associated with fat mass (r = −0.516, p < 0.001), independent of age. On average, subjects lost fat mass (baseline 40.8 ± 12.4 to 39.4 ± 12.6 kg [mean ± SD], P < 0.01), but 17 women (32 %) actually gained fat mass. SI for the group was unchanged (baseline 3.3 ± 1.7 to 3.2 ± 1.6, P = 0.67). However, the tertile with greatest fat mass loss (−3.6 kg, range −10.7 to −1.7 kg) improved insulin sensitivity (SI +0.3 ± 1.2), whereas the tertile with net fat mass gain (+0.9 kg, range −0.1 to +3.8 kg) had reduced insulin sensitivity (SI −0.7 ± 1.3) from baseline values (P < 0.05 by ANOVA).ConclusionsBlack women in a weight loss program who lose fat mass may have improved insulin sensitivity, but fat mass gain with diminished sensitivity is common. Additional support for participants who fail to achieve fat mass loss early in an intervention may be required for success.

Increased De Novo Lipogenesis Is a Distinct Characteristic of Individuals With Nonalcoholic Fatty Liver Disease

There have been few studies of the role of de novo lipogenesis in the development of nonalcoholic fatty liver disease (NAFLD). We used isotope analyses to compare de novo lipogenesis and fatty acid flux between subjects with NAFLD and those without, matched for metabolic factors (controls). We studied subjects with metabolic syndrome and/or levels of alanine aminotransferase and aspartate aminotransferase >30 mU/L, using magnetic resonance spectroscopy to identify those with high levels (HighLF, n = 13) or low levels (LowLF, n = 11) of liver fat. Clinical and demographic information was collected from all participants, and insulin sensitivity was measured using the insulin-modified intravenous glucose tolerance test. Stable isotopes were administered and gas chromatography with mass spectrometry was used to analyze free (nonesterified) fatty acid (FFA) and triacylglycerol flux and lipogenesis. Subjects with HighLF (18.4% ± 3.6%) had higher plasma levels of FFAs during the nighttime and higher concentrations of insulin than subjects with LowLF (3.1% ± 2.7%; P = .04 and P < .001, respectively). No differences were observed between groups in adipose flux of FFAs (414 ± 195 μmol/min for HighLF vs 358 ± 105 μmol/min for LowLF; P = .41) or production of very-low-density lipoprotein triacylglycerol from FFAs (4.06 ± 2.57 μmol/min vs 4.34 ± 1.82 μmol/min; P = .77). In contrast, subjects with HighLF had more than 3-fold higher rates of de novo fatty acid synthesis than subjects with LowLF (2.57 ± 1.53 μmol/min vs 0.78 ± 0.42 μmol/min; P = .001). As a percentage of triacylglycerol palmitate, de novo lipogenesis was 2-fold higher in subjects with HighLF (23.2% ± 7.9% vs 10.1% ± 6.7%; P < .001); this level was independently associated with the level of intrahepatic triacylglycerol (r = 0.53; P = .007). By administering isotopes to subjects with NAFLD and control subjects, we confirmed that those with NAFLD have increased synthesis of fatty acids. Subjects with NAFLD also had higher nocturnal plasma levels of FFAs and did not suppress the contribution from de novo lipogenesis on fasting. These findings indicate that lipogenesis might be a therapeutic target for NAFLD.

A Comparison of Meal‐derived Indices for Predicting Glucose Tolerance

This investigation evaluated indices of insulin sensitivity and secretion from the liquid meal tolerance test (LMTT) as determinants of 2‐h glucose (G) values from an oral glucose tolerance test (OGTT). Subjects were 38 men and 31 women, 42% with pre‐diabetes, mean±SEM age 35.1±1.0 y and BMI 32.5±0.5 kg/m2. On separate days subjects completed a 75 g OGTT, a LMTT (Carnation Instant Breakfast®+ whole milk; 7 kcal/kg; 24% fat, 59% carbohydrate, and 17% protein) and an insulin‐modified intravenous glucose tolerance test (IVGTT). Multivariate linear regression was used to assess the variance in log‐transformed 2‐hour OGTT G values explained by indices of insulin (I) sensitivity ‐ Matsuda LMTT (MISI), Cobelli LMTT (CoSI) and IVGTT (Minmod SI) and I secretion ‐ LMTT 30 min ΔI/ΔG, 120 min AUC I/AUC G, Phi S and the acute insulin response to IV glucose (AIRG). The R2 value for the reference method (IVGTT SI and AIRG) was 0.199. R2 values for combinations of LMTT variables (all models P&lt;0.001) were: 0.178 (CoSI and ΔI/ΔG), 0.154 (MISI and ΔI/ΔG), 0.127 (CoSI and Phi S), 0.112 (CoSI and 120 min AUC I/AUC G) and 0.086 (MISI and AUC I/AUC G). These results suggest that CoSI and ΔI/ΔG performs well compared to the IVGTT reference method, and that use of MISI and ΔI/ΔG (from I and G at 0, 30, 60, 90, 120 min vs. 23 timepoints for CoSI) results in only minor loss of explanatory power.

Estimation of prehepatic insulin secretion: comparison between standardized C-peptide and insulin kinetic models

Our aim was to compare traditional C-peptide–based method and insulin-based method with standardized kinetic parameters in the estimation of prehepatic insulin secretion rate (ISR). One-hundred thirty-four subjects with varying degrees of glucose tolerance received an insulin-modified intravenous glucose tolerance test and a standard oral glucose tolerance test with measurement of plasma insulin and C-peptide. From the intravenous glucose tolerance test, we determined insulin kinetics parameters and selected standardized kinetic parameters based on mean values in a selected subgroup. We computed ISR from insulin concentration during the oral glucose tolerance test using these parameters and compared ISR with the standard C-peptide deconvolution approach. We then performed the same comparison in an independent data set (231 subjects). In the first data set, total ISRs from insulin and C-peptide were highly correlated (R2 = 0.75, P < .0001), although on average different (103 ± 6 vs 108 ± 3 nmol, P < .001). Good correlation was also found in the second data set (R2 = 0.54, P < .0001). The insulin method somewhat overestimated total ISR (85 ± 5 vs 67 ± 3 nmol, P = .002), in part because of differences in insulin assay. Similar results were obtained for fasting ISR. Despite the modest bias, the insulin and C-peptide methods were consistent in predicting differences between groups (eg, obese vs nonobese) and relationships with other physiological variables (eg, body mass index, insulin resistance). The insulin method estimated first-phase ISR peak similarly to the C-peptide method and better than the simple use of insulin concentration. The insulin-based ISR method compares favorably with the C-peptide approach. The method will be particularly useful in data sets lacking C-peptide to assess β-cell function through models requiring prehepatic secretion.

Validation of Insulin Sensitivity and Secretion Indices Derived from the Liquid Meal Tolerance Test

A liquid meal tolerance test (LMTT) has been proposed as a useful alternative to more labor-intensive methods of assessing insulin sensitivity and secretion. This substudy, conducted at the conclusion of a randomized, double-blind crossover trial, compared insulin sensitivity indices from a LMTT (Matsuda insulin sensitivity index [MISI] and LMTT disposition index [LMTT-DI]) with indices derived from minimal model analysis of results from the insulin-modified intravenous glucose tolerance test (IVGTT) (insulin sensitivity index [S(I)] and disposition index [DI]). Participants included men (n = 16) and women (n = 8) without diabetes but with increased abdominal adiposity (waist circumference ≥102 cm and ≥89 cm, respectively) and mean age of 48.9 years. The correlation between S(I) and the MISI was 0.776 (P < 0.0001). The respective associations between S(I) and MISI with waist circumference (r = -0.445 and -0.554, both P < 0.05) and body mass index were similar (r = -0.500 and -0.539, P < 0.05). The correlation between DI and LMTT-DI was 0.604 (P = 0.002). These results indicate that indices of insulin sensitivity and secretion derived from the LMTT correlate well with those from the insulin-modified IVGTT with minimal model analysis, suggesting that they may be useful for application in clinical and population studies of glucose homeostasis.

IVGTT glucose minimal model covariate selection by nonlinear mixed-effects approach

Population approaches, traditionally employed in pharmacokinetic-pharmacodynamic studies, have shown value also in the context of glucose-insulin metabolism models by providing more accurate individual parameters estimates and a compelling statistical framework for the analysis of between-subject variability (BSV). In this work, the advantages of population techniques are further explored by proposing integration of covariates in the intravenous glucose tolerance test (IVGTT) glucose minimal model analysis. A previously published dataset of 204 healthy subjects, who underwent insulin-modified IVGTTs, was analyzed in NONMEM, and relevant demographic information about each subject was employed to explain part of the BSV observed in parameter values. Demographic data included height, weight, sex, and age, but also basal glycemia and insulinemia, and information about amount and distribution of body fat. On the basis of nonlinear mixed-effects modeling, age, visceral abdominal fat, and basal insulinemia were significant predictors for SI (insulin sensitivity), whereas only age and basal insulinemia were significant for P2 (insulin action). The volume of distribution correlated with sex, age, percentage of total body fat, and basal glycemia, whereas no significant covariate was detected to explain variability in SG (glucose effectiveness). The introduction of covariates resulted in a significant shrinking of the unexplained BSV, especially for SI and P2 and considerably improved the model fit. These results offer a starting point for speculation about the physiological meaning of the relationships detected and pave the way for the design of less invasive and less expensive protocols for epidemiological studies of glucose-insulin metabolism.

Bayesian analysis of minimal model under the insulin-modified IVGTT

A Bayesian analysis of the minimal model was proposed where both glucose and insulin were analyzed simultaneously under the insulin-modified intravenous glucose tolerance test (IVGTT). The resulting model was implemented with a nonlinear mixed-effects modeling setup using ordinary differential equations (ODEs), which leads to precise estimation of population parameters by separating the inter- and intra-individual variability. The results indicated that the Bayesian method applied to the glucose-insulin minimal model provided a satisfactory solution with accurate parameter estimates which were numerically stable since the Bayesian method did not require approximation by linearization.