The shape of the glucose response curve during an oral glucose tolerance test heralds β-cell function in a large Chinese population

Silymarin Reduced Insulin Resistance in Non-Diabetic Women with Obesity

Silymarin has ameliorated obesity, type 2 diabetes (T2DM), and insulin resistance (IR) in combination with standard therapy, diet, or exercise in recent studies. Obesity and IR are the main risk factors for developing T2DM and other metabolic disorders. Today, there is a need for new strategies to target IR in patients with these metabolic diseases. In the present longitudinal study, a group of non-diabetic insulin-resistant women with type 1 and type 2 obesity were given silymarin for 12 weeks, with no change in habitual diet and physical activity. We used the Homeostatic Model Assessment for Insulin Resistance Index (HOMA-IR) to determine IR at baseline and after silymarin treatment (t = 12 weeks). We obtained five timepoint oral glucose tolerance tests, and other biochemical and clinical parameters were analyzed before and after treatment. Treatment with silymarin alone significantly reduced mean fasting plasma glucose (FPG) and HOMA-IR levels at 12 weeks compared to baseline values (p < 0.05). Mean fasting plasma insulin (FPI), total cholesterol, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), triglycerides (Tg), indirect bilirubin, and C-reactive protein (CRP) levels decreased compared to baseline values, although changes were non-significant. The overall results suggest that silymarin may offer a therapeutic alternative to improve IR in non-diabetic individuals with obesity. Further clinical trials are needed in this type of patient to strengthen the results of this study.

Sex Differences in Glucose Homeostasis

Sexual dimorphism has been demonstrated to have an effect on various physiological functions. In this regard, researchers have investigated its impact on glucose homeostasis in both preclinical and clinical studies. Sex differences mainly arise from physiological factors such as sex hormones, body fat and muscle distribution, and sex chromosomes. The sexual dimorphism has also been studied in the context of diabetes. Reflecting the prevalence of the disease among the population, studies focusing on the sex difference in type 1 diabetes (T1D) are not common as the ones in type 2 diabetes (T2D). T1D is reported as the only major specific autoimmune disease that exhibits a male predominance. Clinical studies have demonstrated that impaired fasting glucose is more frequent in men whereas women more commonly exhibit impaired glucose tolerance. Understanding the sex difference in glucose homeostasis becomes more attractive when focusing on the findings that highlight sexual dimorphism on the efficacy or adverse effect profile of antidiabetic medications. Thus, in this chapter, we aimed to discuss the impact of sex on the glucose homeostasis both in health and in diabetes.

Quantifying the contribution of triglycerides to metabolic resilience through the mixed meal model

Despite the pivotal role played by elevated circulating triglyceride levels in the pathophysiology of cardio-metabolic diseases many of the indices used to quantify metabolic health focus on deviations in glucose and insulin alone. We present the Mixed Meal Model, a computational model describing the systemic interplay between triglycerides, free fatty acids, glucose, and insulin. We show that the Mixed Meal Model can capture deviations in the post-meal excursions of plasma glucose, insulin, and triglyceride that are indicative of features of metabolic resilience; quantifying insulin resistance and liver fat; validated by comparison to gold-standard measures. We also demonstrate that the Mixed Meal Model is generalizable, applying it to meals with diverse macro-nutrient compositions. In this way, by coupling triglycerides to the glucose-insulin system the Mixed Meal Model provides a more holistic assessment of metabolic resilience from meal response data, quantifying pre-clinical metabolic deteriorations that drive disease development in overweight and obesity.

The characteristics of postprandial glycemic response patterns to white rice and glucose in healthy adults: Identifying subgroups by clustering analysis

OBJECTIVES

Large interpersonal variability in postprandial glycemic response (PGR) to white rice has been reported, and differences in the PGR patterns during the oral glucose tolerance test (OGTT) have been documented. However, there is scant study on the PGR patterns of white rice. We examined the typical PGR patterns of white rice and glucose and the association between them.

MATERIALS AND METHODS

We analyzed the data of 3-h PGRs to white rice (WR) and glucose (G) of 114 normoglycemic female subjects of similar age, weight status, and same ethnic group. Diverse glycemic parameters, based on the discrete blood glucose values, were calculated over 120 and 180 min. K-means clustering based on glycemic parameters calculated over 180 min was applied to identify subgroups and representative PGR patterns. Principal factor analysis based on the parameters used in the cluster analysis was applied to characterize PGR patterns. Simple correspondence analysis was performed on the clustering categories of WR and G.

RESULTS

More distinct differences were found in glycemic parameters calculated over 180 min compared with that calculated over 120 min, especially in the negative area under the curve and Nadir. We identified four distinct PGR patterns to WR (WR1, WR2, WR3, and WR4) and G (G1, G2, G3, and G4), respectively. There were significant differences among the patterns regard to postprandial hyperglycemia, hypoglycemic, and glycemic variability. The WR1 clusters had significantly lower glycemic index (59 ± 19), while no difference was found among the glycemic index based on the other three clusters. Each given G subgroup presented multiple patterns of PGR to WR, especially in the largest G subgroup (G1), and in subgroup with the greatest glycemic variability (G3).

CONCLUSION

Multiple subgroups could be classified based on the PGR patterns to white rice and glucose even in seemingly homogeneous subjects. Extending the monitoring time to 180 min was conducive to more effective discrimination of PGR patterns. It may not be reliable to extrapolate the patterns of PGR to rice from that to glucose, suggesting a need of combining OGTT and meal tolerance test for individualized glycemic management.

Incidence and status of insulin secretion in pregnant women with flat plasma glucose profiles during oral glucose tolerance test

OBJECTIVES

Flat shaped glucose curves (FC) during oral glucose tolerance test (OGTT) in pregnant women (PW) are a not uncommon finding. We aimed to define the FC incidence in a large PW cohort and to describe the status of insulin and C-peptide secretion in women with FC when compared with a well-matched control group.

METHODS

1050 PW performing OGTT for gestational diabetes screening were enrolled. An increase <6% in plasma glucose (PG) during OGTT defined a FC. Serum samples for measuring insulin and C-peptide were also obtained.

RESULTS

61 (5.8%) women showed a FC. 60 of them, paired to a group of 60 no-FC women matched for age, body mass index and gestational age, were further investigated. C-peptide and insulin concentrations were significantly lower (P<0.001) in FC in both 1-h and 2-h OGTT samples. When incremental area under the curves (AUC) normalized to PG were estimated, only AUC_insulin remained however significantly lower. The insulin sensitivity index was higher in FC.

CONCLUSIONS

PW with FC showed a hypersensitivity to insulin with normal β-cell function. Moreover, a delayed glucose absorption could be hypothesised because of the slight but continuously increasing shape of insulin curve found in FC group. Both phenomena could occur in parallel and contribute to FC.

The incessant increase curve during oral glucose tolerance tests in Chinese adults with type 2 diabetes and its association with gut hormone levels

Glucose curve shapes during oral glucose tolerance tests (OGTTs) are mainly classified as incessant increase, monophasic and biphasic. Youth with an incessant increase curve have worse β-cell function. The aim of this paper was to investigate the incessant increase curve in Chinese adults with type 2 diabetes (T2DM), and its association with β-cell function and gut hormone levels. Eighty-nine Chinese patients (59 males and 30 females) were included in this study with a mean age of 50.56 ± 16.00 years. They were all recently diagnosed with T2DM and underwent 180-min OGTTs. Data on demographics, β-cell function, and insulin sensitivity were also collected. Gut hormones, including glucagon-like peptide-1 (GLP-1), glucose-dependent insulinotropic polypeptide (GIP), and ghrelin, were also detected during the OGTT. A total of 39.3 % of subjects had an incessant increase in the glucose response curve, while 59.6 % had a monophasic curve. Because only one curve was classified as biphasic, patients with a biphasic curve were omitted from further research. Lower plasma C-peptide, HOMA2-β, area under the curve (AUC) of C-peptide, and ratio of AUC of insulin to AUC of glucose were found in patients with incessant increase curves compared to those with monophasic curves (P < 0.05). Higher glycated hemoglobin (HbA_1c) was found in subjects with an incessant increase curve (P < 0.05). Importantly, fasting plasma ghrelin was lower and incremental ghrelin at 120 min was higher in the incessant increase group (P < 0.05), irrespective of age, sex, body mass index (BMI), fasting glucose, and fasting insulin. Time to peak is also a parameter of the OGTT curve shape. In the late-peak group, GLP-1 at 120 min and the AUC of GLP-1 were elevated compared with those in the early-peak group (P < 0.05). In Chinese adults with T2DM, the incessant increase in OGTT shape indicated impaired insulin secretion. Lower fasting ghrelin and absence of ghrelin drops after glucose load may be associated with the incessant increase OGTT shape. In addition, compensatory elevated GLP-1 dose not prevent peak delay in the OGTT curve. Gut hormones may have an effect on OGTT shapes in T2DM adults.

Shape of the OGTT glucose response curve: relationship with β-cell function and differences by sex, race, and BMI in adults with early type 2 diabetes treated with metformin

INTRODUCTION

The shape of the glucose curve during an oral glucose tolerance test (OGTT) reflects β-cell function in populations without diabetes but has not been as well studied in those with diabetes. A monophasic shape has been associated with higher risk of diabetes, while a biphasic pattern has been associated with lower risk. We sought to determine if phenotypic or metabolic characteristics were associated with glucose response curve shape in adults with type 2 diabetes treated with metformin alone.

RESEARCH DESIGN AND METHODS

This is a cross-sectional analysis of 3108 metformin-treated adults with type 2 diabetes diagnosed <10 years who underwent 2-hour 75 g OGTT at baseline as part of the Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study (GRADE). Insulin sensitivity (homeostasis model of insulin sensitivity, HOMA2-S) and β-cell function (early, late, and total incremental insulin and C peptide responses adjusted for HOMA2-S) were calculated. Glucose curve shape was classified as monophasic, biphasic, or continuous rise.

RESULTS

The monophasic profile was the most common (67.8% monophasic, 5.5% biphasic, 26.7% continuous rise). The monophasic subgroup was younger, more likely male and white, and had higher body mass index (BMI), while the continuous rise subgroup was more likely female and African American/black. HOMA2-S and fasting glucose did not differ among the subgroups. The biphasic subgroup had the highest early, late, and total insulin and C peptide responses (all p<0.05 vs monophasic and continuous rise). Compared with the monophasic subgroup, the continuous rise subgroup had similar early insulin (p=0.3) and C peptide (p=0.6) responses but lower late insulin (p<0.001) and total insulin (p=0.008) and C peptide (p<0.001) responses.

CONCLUSIONS

Based on the large multiethnic GRADE cohort, sex, race, age, and BMI were found to be important determinants of the shape of the glucose response curve. A pattern of a continuously rising glucose at 2 hours reflected reduced β-cell function and may portend increased glycemic failure rates.

TRIAL REGISTRATION NUMBER

NCT01794143.

Both macronutrient food composition and fasting insulin resistance affect postprandial glycemic responses in senior subjects

INTRODUCTION

Postprandial hyperglycemia is a risk factor for type 2 diabetes. Insulin resistance (IR) might affect metabolic responses in non-fasting states. Dietary intake and food composition influence postprandial glucose homeostasis. The aims of this study were to evaluate the effects of different test foods varying in the macronutrient composition on postprandial glycemic responses and whether these outcomes are conditioned by the basal glycemic status in senior subjects.

METHODS

In a randomized, controlled crossover design, thirty-four adults consumed a test food, a high protein product (n = 19) or a high carbohydrate (CHO) product (n = 15), using the oral glucose tolerance test (OGTT) as a reference. Blood glucose and insulin were measured at fasting and at 15, 30, 45, 60, 90, and 120 min after starting the food intake. For each type of food, the incremental area under the curve (iAUC) for glucose and insulin was calculated. IR was measured using the Homeostatic Model Assessment of IR (HOMA-IR).

RESULTS

Consumption of a high protein product significantly lowered the peak and Δ blood glucose concentrations compared to the high CHO product (p < 0.001). Concerning the insulin response, no significant differences between both foods were observed. Fasting glucose was positively correlated with the glucose iAUC only for the high protein product. Positive associations of both fasting insulin and HOMA-IR with the insulin iAUC for all the cases were observed. Linear regression models showed significant positive associations between the glucose iAUC and fasting glucose after adjusting for age and sex. Regarding the insulin iAUC, positive associations were found with fasting insulin and HOMA-IR. Regression models also evidenced that both food test consumptions were able to decrease the glucose and insulin iAUC values when compared with the OGTT product.

CONCLUSION

Our research found that not only is the nutritional composition of foods important, but also the baseline glycemic state of individuals when assessing glycemic index estimations and addressing precision nutritional strategies to prevent and treat IR-associated disturbances.

Personalized computational model quantifies heterogeneity in postprandial responses to oral glucose challenge

Plasma glucose and insulin responses following an oral glucose challenge are representative of glucose tolerance and insulin resistance, key indicators of type 2 diabetes mellitus pathophysiology. A large heterogeneity in individuals' challenge test responses has been shown to underlie the effectiveness of lifestyle intervention. Currently, this heterogeneity is overlooked due to a lack of methods to quantify the interconnected dynamics in the glucose and insulin time-courses. Here, a physiology-based mathematical model of the human glucose-insulin system is personalized to elucidate the heterogeneity in individuals' responses using a large population of overweight/obese individuals (n = 738) from the DIOGenes study. The personalized models are derived from population level models through a systematic parameter selection pipeline that may be generalized to other biological systems. The resulting personalized models showed a 4-5 fold decrease in discrepancy between measurements and model simulation compared to population level. The estimated model parameters capture relevant features of individuals' metabolic health such as gastric emptying, endogenous insulin secretion and insulin dependent glucose disposal into tissues, with the latter also showing a significant association with the Insulinogenic index and the Matsuda insulin sensitivity index, respectively.

OGTT Glucose Response Curves, Insulin Sensitivity, and β-Cell Function in RISE: Comparison Between Youth and Adults at Randomization and in Response to Interventions to Preserve β-Cell Function

We examined the glucose response curves (biphasic [BPh], monophasic [MPh], incessant increase [IIn]) during an oral glucose tolerance test (OGTT) and their relationship to insulin sensitivity (IS) and β-cell function (βCF) in youth versus adults with impaired glucose tolerance or recently diagnosed type 2 diabetes.RESEARCH DESIGN AND METHODSThis was both a cross-sectional and a longitudinal evaluation of participants in the RISE study randomized to metformin alone for 12 months or glargine for 3 months followed by metformin for 9 months. At baseline/randomization, OGTTs (85 youth, 353 adults) were categorized as BPh, MPh, or IIn. The relationship of the glucose response curves to hyperglycemic clamp-measured IS and βCF at baseline and the change in glucose response curves 12 months after randomization were assessed.RESULTSAt randomization, the prevalence of the BPh curve was significantly higher in youth than adults (18.8% vs. 8.2%), with no differences in MPh or IIn. IS did not differ across glucose response curves in youth or adults. However, irrespective of curve type, youth had lower IS than adults (P < 0.05). βCF was lowest in IIn versus MPh and BPh in youth and adults (P < 0.05), yet compared with adults, youth had higher βCF in BPh and MPh (P < 0.005) but not IIn. At month 12, the change in glucose response curves did not differ between youth and adults, and there was no treatment effect.CONCLUSIONSDespite a twofold higher prevalence of the more favorable BPh curve in youth at randomization, RISE interventions did not result in beneficial changes in glucose response curves in youth compared with adults. Moreover, the typical β-cell hypersecretion in youth was not present in the IIn curve, emphasizing the severity of β-cell dysfunction in youth with this least favorable glucose response curve.

OGTT Glucose Response Curves, Insulin Sensitivity, and β-Cell Function in RISE: Comparison Between Youth and Adults at Randomization and in Response to Interventions to Preserve β-Cell Function

OBJECTIVE

We examined the glucose response curves (biphasic [BPh], monophasic [MPh], incessant increase [IIn]) during an oral glucose tolerance test (OGTT) and their relationship to insulin sensitivity (IS) and β-cell function (βCF) in youth versus adults with impaired glucose tolerance or recently diagnosed type 2 diabetes.RESEARCH DESIGN AND METHODSThis was both a cross-sectional and a longitudinal evaluation of participants in the RISE study randomized to metformin alone for 12 months or glargine for 3 months followed by metformin for 9 months. At baseline/randomization, OGTTs (85 youth, 353 adults) were categorized as BPh, MPh, or IIn. The relationship of the glucose response curves to hyperglycemic clamp-measured IS and βCF at baseline and the change in glucose response curves 12 months after randomization were assessed.RESULTSAt randomization, the prevalence of the BPh curve was significantly higher in youth than adults (18.8% vs. 8.2%), with no differences in MPh or IIn. IS did not differ across glucose response curves in youth or adults. However, irrespective of curve type, youth had lower IS than adults (P < 0.05). βCF was lowest in IIn versus MPh and BPh in youth and adults (P < 0.05), yet compared with adults, youth had higher βCF in BPh and MPh (P < 0.005) but not IIn. At month 12, the change in glucose response curves did not differ between youth and adults, and there was no treatment effect.CONCLUSIONSDespite a twofold higher prevalence of the more favorable BPh curve in youth at randomization, RISE interventions did not result in beneficial changes in glucose response curves in youth compared with adults. Moreover, the typical β-cell hypersecretion in youth was not present in the IIn curve, emphasizing the severity of β-cell dysfunction in youth with this least favorable glucose response curve.

The Oral Glucose Tolerance Test: 100 Years Later

For over 100 years, the oral glucose tolerance test (OGTT) has been the cornerstone for detecting prediabetes and type 2 diabetes (T2DM). In recent decades, controversies have arisen identifying internationally acceptable cut points using fasting plasma glucose (FPG), 2-h post-load glucose (2-h PG), and/or HbA1c for defining intermediate hyperglycemia (prediabetes). Despite this, there has been a steadfast global consensus of the 2-h PG for defining dysglycemic states during the OGTT. This article reviews the history of the OGTT and recent advances in its application, including the glucose challenge test and mathematical modeling for determining the shape of the glucose curve. Pitfalls of the FPG, 2-h PG during the OGTT, and HbA1c are considered as well. Finally, the associations between the 30-minute and 1-hour plasma glucose (1-h PG) levels derived from the OGTT and incidence of diabetes and its complications will be reviewed. The considerable evidence base supports modifying current screening and diagnostic recommendations with the use of the 1-h PG. Measurement of the 1-h PG level could increase the likelihood of identifying high-risk individuals when the pancreatic ß-cell function is substantially more intact with the added practical advantage of potentially replacing the conventional 2-h OGTT making it more acceptable in the clinical setting.