Effect of meal composition on postprandial glucagon-like peptide-1, insulin, glucagon, C-peptide, and glucose responses in overweight/obese subjects

Glucagon-like peptide-1 and interleukin-6 interaction in response to physical exercise: An in-silico model in the framework of immunometabolism

BACKGROUND AND OBJECTIVE

Glucagon-like peptide 1 (GLP-1) is classically identified as an incretin hormone, secreted in response to nutrient ingestion and able to enhance glucose-stimulated insulin secretion. However, other stimuli, such as physical exercise, may enhance GLP-1 plasma levels, and this exercise-induced GLP-1 secretion is mediated by interleukin-6 (IL-6), a cytokine secreted by contracting skeletal muscle. The aim of the study is to propose a mathematical model of IL-6-induced GLP-1 secretion and kinetics in response to physical exercise of moderate intensity.

METHODS

The model includes the GLP-1 subsystem (with two pools: gut and plasma) and the IL-6 subsystem (again with two pools: skeletal muscle and plasma); it provides a parameter of possible clinical relevance representing the sensitivity of GLP-1 to IL-6 (k0). The model was validated on mean IL-6 and GLP-1 data derived from the scientific literature and on a total of 100 virtual subjects.

RESULTS

Model validation provided mean residuals between 0.0051 and 0.5493 pg⋅mL-1 for IL-6 (in view of concentration values ranging from 0.8405 to 3.9718 pg⋅mL-1) and between 0.0133 and 4.1540 pmol⋅L-1 for GLP-1 (in view of concentration values ranging from 0.9387 to 17.9714 pmol⋅L-1); a positive significant linear correlation (r = 0.85, p<0.001) was found between k0 and the ratio between areas under GLP-1 and IL-6 curve, over the virtual subjects.

CONCLUSIONS

The model accurately captures IL-6-induced GLP-1 kinetics in response to physical exercise.

Dietary impact on fasting and stimulated GLP-1 secretion in different metabolic conditions - a narrative review

Glucagon-like peptide 1 (GLP-1), a gastrointestinal peptide and central mediator of glucose metabolism, is secreted by L cells in the intestine in response to food intake. Postprandial secretion of GLP-1 is triggered by nutrient-sensing via transporters and G-protein-coupled receptors (GPCRs). GLP-1 secretion may be lower in adults with obesity/overweight (OW) or type 2 diabetes mellitus (T2DM) than in those with normal glucose tolerance (NGT), but these findings are inconsistent. Because of the actions of GLP-1 on stimulating insulin secretion and promoting weight loss, GLP-1 and its analogs are used in pharmacologic preparations for the treatment of T2DM. However, physiologically stimulated GLP-1 secretion through the diet might be a preventive or synergistic method for improving glucose metabolism in individuals who are OW, or have impaired glucose tolerance (IGT) or T2DM. This narrative review focuses on fasting and postprandial GLP-1 secretion in individuals with different metabolic conditions and degrees of glucose intolerance. Further, the influence of relevant diet-related factors (e.g., specific diets, meal composition, and size, phytochemical content, and gut microbiome) that could affect fasting and postprandial GLP-1 secretion are discussed. Some studies showed diminished glucose- or meal-stimulated GLP-1 response in participants with T2DM, IGT, or OW compared with those with NGT, whereas other studies have reported an elevated or unchanged GLP-1 response in T2DM or IGT. Meal composition, especially the relationship between macronutrients and interventions targeting the microbiome can impact postprandial GLP-1 secretion, although it is not clear which macronutrients are strong stimulants of GLP-1. Moreover, glucose tolerance, antidiabetic treatment, grade of overweight/obesity, and sex were important factors influencing GLP-1 secretion. The results presented in this review highlight the potential of nutritional and physiologic stimulation of GLP-1 secretion. Further research on fasting and postprandial GLP-1 concentrations and the resulting metabolic consequences under different metabolic conditions is needed.

C-peptide determination in the diagnosis of type of diabetes and its management: A clinical perspective

Impaired beta-cell function is a recognized cornerstone of diabetes pathophysiology. Estimates of insulin secretory capacity are useful to inform clinical practice, helping to classify types of diabetes, complication risk stratification and to guide treatment decisions. Because C-peptide secretion mirrors beta-cell function, it has emerged as a valuable clinical biomarker, mainly in autoimmune diabetes and especially in adult-onset diabetes. Nonetheless, the lack of robust evidence about the clinical utility of C-peptide measurement in type 2 diabetes, where insulin resistance is a major confounder, limits its use in such cases. Furthermore, problems remain in the standardization of the assay for C-peptide, raising concerns about comparability of measurements between different laboratories. To approach the heterogeneity and complexity of diabetes, reliable, simple and inexpensive clinical markers are required that can inform clinicians about probable pathophysiology and disease progression, and so enable personalization of management and therapy. This review summarizes the current evidence base about the potential value of C-peptide in the management of the two most prevalent forms of diabetes (type 2 diabetes and autoimmune diabetes) to address how its measurement may assist daily clinical practice and to highlight current limitations and areas of uncertainties to be covered by future research.

Impact of Obesity on Postprandial Triglyceride Contribution to Glucose Homeostasis, Assessed with a Semimechanistic Model

The integrated glucose-insulin model is a semimechanistic model describing glucose and insulin after a glucose challenge. Similarly, a semiphysiologic model of the postprandial triglyceride (TG) response in chylomicrons and VLDL-V6 was recently published. We have developed the triglyceride-insulin-glucose-GLP-1 (TIGG) model by integrating these models and active GLP-1. The aim was to characterize, using the TIGG model, the postprandial response over 13 hours following a high-fat meal in 3 study populations based on body mass index categories: lean, obese, and very obese. Differential glucose and lipid regulation were observed between the lean population and obese or very obese populations. A population comparison revealed further that fasting glucose and insulin were elevated in obese and very obese when compared with lean; and euglycemia was achieved at different times postmeal between the obese and very obese populations. Postprandial insulin was incrementally elevated in the obese and very obese populations compared with lean. Postprandial chylomicrons TGs were similar across populations, whereas the postprandial TGs in VLDL-V6 were increased in the obese and very obese populations compared with lean. Postprandial active GLP-1 was diminished in the very obese population compared with lean or obese. The TIGG model described the response following a high-fat meal in individuals who are lean, obese, and very obese and provided insight into the possible regulation of glucose homeostasis in the extended period after the meal by utilizing lipids. The TIGG-model is the first model to integrate glucose and insulin regulation, incretin effect, and postprandial TGs response in chylomicrons and VLDL-V6.

Effect of Meal Texture on Postprandial Glucose Excursions and Gut Hormones After Roux-en-Y Gastric Bypass and Sleeve Gastrectomy

Background and aims

The metabolic consequences after Roux-en-Y gastric bypass (RYGB) and sleeve gastrectomy (SG) are often studied using a liquid mixed meal. However, liquid meals may not be representative of the patients’ everyday diet. We therefore examined postprandial glucose and gut hormone responses using mixed meals differing only with respect to meal texture.

Methods

Twelve RYGB-operated, 12 SG-operated, and 12 unoperated individuals (controls) were enrolled in the study. Participants were matched on age, sex, and body mass index. In randomized order, each participant underwent a liquid and a solid 4-h mixed meal test on separate days. The meals were isocaloric (309 kcal), and with identical macronutrient composition (47 E% carbohydrate, 18 E% protein, 32 E% fat, and 3 E% dietary fibers). The liquid meal was blended to create a smooth liquid texture while the other meal retained its solid components.

Results

Postprandial glucose concentrations (peak and incremental area under curve, iAUC) did not differ between the two meal textures in any group. In the control group, peak C-peptide was higher after the liquid meal compared with the solid meal (p = 0.04), whereas iAUCs of C-peptide were similar between the two meals in all groups. Peak of glucagon-like peptide-1 (GLP-1) was higher after the liquid meal compared with the solid meal in RYGB- and SG-operated individuals (RYGB p = 0.02; SG p &lt; 0.01), but iAUC of GLP-1 did not differ between meal textures within any group. Peak of glucose-dependent insulin tropic polypeptide (GIP) was higher after the liquid meal in the SG and control groups (SG p = 0.02; controls p &lt; 0.01), but iAUCs of GIP were equal between meals. There were no differences in total AUC of ghrelin between the liquid and solid meals within any of the groups.

Conclusion

A liquid and a solid meal with identical macronutrient composition result in similar postprandial glucose responses, both in operated and unoperated individuals. Small differences were observed for the postprandial peaks of C-peptide, GLP-1, and GIP concentrations. Overall, a liquid meal is suitable for evaluating glucose tolerance, β-cell function, and gut hormones responses, both after RYGB and SG and in unoperated individuals.

Clinical Trial Registration

[www.clinicaltrials.gov], identifier [NCT04082923].

The Effect of Dietary Interventions on Hypertriglyceridemia: From Public Health to Molecular Nutrition Evidence

Approximately 25–50% of the population worldwide exhibits serum triglycerides (TG) (≥150 mg/dL) which are associated with an increased level of highly atherogenic remnant-like particles, non-alcoholic fatty liver disease, and pancreatitis risk. High serum TG levels could be related to cardiovascular disease, which is the most prevalent cause of mortality in Western countries. The etiology of hypertriglyceridemia (HTG) is multifactorial and can be classified as primary and secondary causes. Among the primary causes are genetic disorders. On the other hand, secondary causes of HTG comprise lifestyle factors, medical conditions, and drugs. Among lifestyle changes, adequate diets and nutrition are the initial steps to treat and prevent serum lipid alterations. Dietary intervention for HTG is recommended in order to modify the amount of macronutrients. Macronutrient distribution changes such as fat or protein, low-carbohydrate diets, and caloric restriction seem to be effective strategies in reducing TG levels. Particularly, the Mediterranean diet is the dietary pattern with the most consistent evidence for efficacy in HTG while the use of omega-3 supplements consumption is the dietary component with the highest number of randomized clinical trials (RCT) carried out with effective results on reducing TG. The aim of this review was to provide a better comprehension between human nutrition and lipid metabolism.

A review of biosensor technology and algorithms for glucose monitoring

Diabetes mellitus (DM) has become a serious illness in the whole world. Until now, there is no effective cure for patients with DM. It is well known that the glucose level is one key factor to determine the progress of DM. It is also an important reference to carry out the accurate and timely treatment for patients with DM. In this article, the related biosensors technology that can be utilized to identify and predict glucose level are reviewed in detail, including the algorithms that can help to achieve numerical value of glucose level. Firstly, the biosensor technology based on the physiological fluids are illustrated, including blood, sweat, interstitial fluid, ocular fluid, and other available fluids. Secondly, the algorithms for achieving numerical value of glucose level are investigated, including the physiological model-based method and the machine learning-based method. Finally, the future development trend and challenges of glucose level monitoring are given and the conclusions are drawn.

Incretin drugs in diabetic kidney disease: biological mechanisms and clinical evidence

As the prevalence of diabetes continues to climb, the number of individuals living with diabetic complications will reach an unprecedented magnitude. The emergence of new glucose-lowering agents - sodium-glucose cotransporter 2 inhibitors and incretin therapies - has markedly changed the treatment landscape of type 2 diabetes mellitus. In addition to effectively lowering glucose, incretin drugs, which include glucagon-like peptide 1 receptor (GLP1R) agonists and dipeptidyl peptidase 4 (DPP4) inhibitors, can also reduce blood pressure, body weight, the risk of developing or worsening chronic kidney disease and/or atherosclerotic cardiovascular events, and the risk of death. Although kidney disease events have thus far been secondary outcomes in clinical trials, an ongoing phase III trial in patients with diabetic kidney disease will test the effect of a GLP1R agonist on a primary kidney disease outcome. Experimental data have identified the modulation of innate immunity and inflammation as plausible biological mechanisms underpinning the kidney-protective effects of incretin-based agents. These drugs block the mechanisms involved in the pathogenesis of kidney damage, including the activation of resident mononuclear phagocytes, tissue infiltration by non-resident inflammatory cells, and the production of pro-inflammatory cytokines and adhesion molecules. GLP1R agonists and DPP4 inhibitors might also attenuate oxidative stress, fibrosis and cellular apoptosis in the kidney.

Glucagon, insulin, adrenocorticotropic hormone, and cortisol in response to carbohydrates and fasting in healthy neonatal foals

Background

The endocrine pancreas and hypothalamic‐pituitary‐adrenal axis (HPAA) are central to energy homeostasis, but information on their dynamics in response to energy challenges in healthy newborn foals is lacking.

Objectives

To evaluate glucagon, insulin, ACTH, and cortisol response to fasting and carbohydrate administration in healthy foals.

Animals

Twenty‐two healthy Standardbred foals ≤4 days of age.

Methods

Foals were assigned to fasted (n = 6), IV glucose (IVGT; n = 5), PO glucose (OGT; n = 5), and PO lactose (OLT; n = 6) test groups. Blood samples were collected frequently for 210 minutes. Nursing was allowed from 180 to 210 minutes. Plasma glucagon, ACTH, serum insulin, and cortisol concentrations were measured using immunoassays.

Results

Plasma glucagon concentration decreased relative to baseline at 45, 90, and 180 minutes during the OLT (P = .03), but no differences occurred in other test groups. Nursing stimulated marked increases in plasma glucagon, serum insulin, and glucose concentrations in all test groups (P < .001). Plasma ACTH concentration increased relative to baseline at 180 minutes (P < .05) during fasting and OLT, but no differences occurred in other test groups. Serum cortisol concentration increased relative to baseline during OLT at 180 minutes (P = .04), but no differences occurred in other test groups. Nursing resulted in decreased plasma ACTH and serum cortisol concentrations in all test groups (P < .01).

Conclusions and Clinical Importance

The endocrine response to enterally and parenterally administered carbohydrates, including the major endocrine response to nursing, suggests that factors in milk other than carbohydrates are strong stimulators (directly or indirectly) of the endocrine pancreas and HPAA.

A word of caution against excessive protein intake

Dietary protein is crucial for human health because it provides essential amino acids for protein synthesis. In addition, dietary protein is more satiating than carbohydrate and fat. Accordingly, many people consider the protein content when purchasing food and beverages and report 'trying to eat more protein'. The global market for protein ingredients is projected to reach approximately US$90 billion by 2021, largely driven by the growing demand for protein-fortified food products. This Perspective serves as a caution against the trend of protein-enriched diets and provides an evidence-based counterpoint that underscores the potential adverse public health consequences of high protein intake.

Long-Term Glucose Forecasting Using a Physiological Model and Deconvolution of the Continuous Glucose Monitoring Signal

(1) Objective: Blood glucose forecasting in type 1 diabetes (T1D) management is a maturing field with numerous algorithms being published and a few of them having reached the commercialisation stage. However, accurate long-term glucose predictions (e.g., >60 min), which are usually needed in applications such as precision insulin dosing (e.g., an artificial pancreas), still remain a challenge. In this paper, we present a novel glucose forecasting algorithm that is well-suited for long-term prediction horizons. The proposed algorithm is currently being used as the core component of a modular safety system for an insulin dose recommender developed within the EU-funded PEPPER (Patient Empowerment through Predictive PERsonalised decision support) project. (2) Methods: The proposed blood glucose forecasting algorithm is based on a compartmental composite model of glucose-insulin dynamics, which uses a deconvolution technique applied to the continuous glucose monitoring (CGM) signal for state estimation. In addition to commonly employed inputs by glucose forecasting methods (i.e., CGM data, insulin, carbohydrates), the proposed algorithm allows the optional input of meal absorption information to enhance prediction accuracy. Clinical data corresponding to 10 adult subjects with T1D were used for evaluation purposes. In addition, in silico data obtained with a modified version of the UVa-Padova simulator was used to further evaluate the impact of accounting for meal absorption information on prediction accuracy. Finally, a comparison with two well-established glucose forecasting algorithms, the autoregressive exogenous (ARX) model and the latent variable-based statistical (LVX) model, was carried out. (3) Results: For prediction horizons beyond 60 min, the performance of the proposed physiological model-based (PM) algorithm is superior to that of the LVX and ARX algorithms. When comparing the performance of PM against the secondly ranked method (ARX) on a 120 min prediction horizon, the percentage improvement on prediction accuracy measured with the root mean square error, A-region of error grid analysis (EGA), and hypoglycaemia prediction calculated by the Matthews correlation coefficient, was 18.8 % , 17.9 % , and 80.9 % , respectively. Although showing a trend towards improvement, the addition of meal absorption information did not provide clinically significant improvements. (4) Conclusion: The proposed glucose forecasting algorithm is potentially well-suited for T1D management applications which require long-term glucose predictions.

Divided consumption of late-night-dinner improves glucose excursions in young healthy women: A randomized cross-over clinical trial

AIMS

Our aim was to explore the acute effect of the late-night-dinner and the divided-dinner on postprandial glucose levels in young healthy women.

METHODS

Fourteen women (22.6 ± 2.6 years, BMI 20.2 ± 1.5 kg/m²: mean ± SD) were randomly assigned to this crossover study. Each participant wore a continuous glucose monitor for 5 days and consumed identical test meals from the second to the fourth day at home. Each participant consumed the test meals of breakfast at 0800 h, lunch at 1300 h, and the half of the participants consumed dinner at 2100 h (D21) on the second day, 1800 h (D18) on the third day, and divided dinner (DD: vegetable and rice at 1800 h, and vegetable and the main dish at 2100 h) on the fourth day. The rest of the participants consumed DD on the second day, and D21 on the fourth day.

RESULTS

D21 demonstrated higher incremental glucose peak (IGP 2.74 ± 0.38 vs. 1.57 ± 0.23 mmol/L, p < .05, mean ± SEM) and incremental area under the curve for glucose (IAUC) 2300-0800 h (271 ± 63 vs. 111 ± 37 mmol/L × min, p < .05) than D18. On the other hand, DD ameliorated IGP (1.96 ± 0.29 mmol/L, p < .05), IAUC 2300-0800 h (80 ± 29 mmol/L × min, p < .001), and the mean amplitude of glycemic excursion (DD 2.34 ± 0.25 vs. D21 2.91 ± 0.28 mmol/L, p < .05) than D21.

CONCLUSIONS

Consuming late-night-dinner increased postprandial glucose levels, compared to DD, suggesting DD could be a practical strategy for reduction of postprandial glucose levels in young healthy women.

Effect of meal size and texture on gastric pouch emptying and glucagon-like peptide 1 after gastric bypass surgery

BACKGROUND

Roux-en-Y gastric bypass (RYGB) accelerates gastric pouch emptying, enhances postprandial glucagon-like peptide 1 (GLP-1) and insulin, and lowers glucose concentrations. To prevent discomfort and reactive hypoglycemia, it is recommended that post-RYGB patients eat small, frequent meals and avoid caloric drinks. However, the effect of meal size and texture on GLP-1 and metabolic response has not been studied.

OBJECTIVES

To demonstrate that frequent minimeals and solid meals (S) elicit less GLP-1 and insulin release and less reactive hypoglycemia and are better tolerated compared with a single isocaloric liquid meal (L).

SETTING

A university hospital.

METHODS

In this prospective study, 32 RYGB candidates were enrolled and randomized to L or S groups before gastric bypass. Each subject received an L or S 600-kcal single meal (SM) administered at hour 0 or three 200-kcal minimeals administered at hours 0, 2, and 4 on 2 separate days. Twenty-one patients were retested 1 year after RYGB. Blood and visual analogue scale measurements were collected up to 6 hours postprandially. Outcome measures included gastric pouch emptying, glucose, insulin, and GLP-1; hunger, fullness, and stomach discomfort were measured by visual analogue scale.

RESULTS

Twenty-one were patients retested after RYGB (L: n = 12; S: n = 9). Meal texture had a significant effect on peak GLP-1 (L-SM: 106.1 ± 67.2 versus S-SM: 45.3 ± 25.2 pM, P = .004), peak insulin, and postprandial glucose. Hypoglycemia was more frequent after the L-SM meal compared with the S-SM. Gastric pouch emptying was 2.4 times faster after RYGB but was not affected by texture.

CONCLUSIONS

Meal texture and size have significant impact on tolerance and metabolic response after RYGB.

Divided consumption of late-night-dinner improves glycemic excursions in patients with type 2 diabetes: A randomized cross-over clinical trial

AIMS

To explore the acute effect of late-night-dinner and divided dinner on postprandial glucose levels in patients with type 2 diabetes.

METHODS

Sixteen patients were randomly assigned to this cross-over study. Each patient wore a continuous glucose monitor for 5days and consumed identical test meals for 3days. Patients consumed the test meals of dinner at 2100h (D21) or divided dinner (vegetable and rice at 1800h and the vegetable and the main dish at 2100h) on the second or fourth day, and dinner at 1800h (D18) on the third day. The daily glucose parameters were compared within-patient for 3days.

RESULTS

D21 demonstrated significantly higher values of incremental area under the curve (IAUC) for glucose 2300 to 0800h (644±156vs. 147±63mmol/L×min, p<0.01, mean±standard error of the mean) and incremental glucose peak (IGP) after dinner (6.78±0.79 vs. 3.09±0.62mmol/L, p<0.01) compared to those of D18. Moreover, the mean amplitude of glycemic excursion (MAGE) of D21 tended to be higher than that of D18 (6.99±0.60 vs. 5.35±0.51mmol/L, p=0.077). However, the divided dinner significantly reduced IAUC 2300 to 0800h (142±60mmol/L×min, p<0.01), IGP after dinner (3.75±0.58mmol/L, p<0.01), and MAGE (5.33±0.41mmol/L, p<0.01) compared to those of D21.

CONCLUSION

Our findings demonstrated that consuming late-night-dinner led to postprandial hyperglycemia, and this postprandial hyperglycemia can be ameliorated by consuming a divided dinner.

Effect of meal composition on postprandial lipid concentrations and lipoprotein particle numbers: A randomized cross-over study

Background

It is unclear how high-protein (HP) and high-monounsaturated fat (HMF) meals affect postprandial blood lipids and lipoprotein particle numbers (LPN).

Purpose

To compare a HP versus a HMF meal on postprandial lipid and LPN responses.

Methods

Twenty-four participants (age: 36.3±15.0 years; body mass index: 23.6±2.0 kg/m²; 45.8% female) were fed a HP (31.9% energy from protein) and a HMF (35.2% fat and 20.7% monounsaturated fat) meal in a randomized cross-over trial design. Energy and carbohydrate content were the same across meals. Blood samples were drawn in the fasting state and 3 hour postprandial state, and assessed for lipids and LPN.

Results

Repeated measures analysis showed a significant (p<0.05) treatment by time interaction effect for triglycerides (TG), the primary variable, total high-density lipoprotein particles (T-HDLP) and T-HDLP minus large-buoyant high-density lipoprotein 2b (T-HDLP—LB-HDL2b). HP versus HMF condition led to significantly lower TG at 120 (geometric mean: 90.1 (95% confidence interval (CI): 76.4–106.3) vs. 146.5 (124.2–172.9) mg/dL) and 180 (101.4 (83.1–123.8) vs. 148.7 (121.9–181.4) mg/dL) min and higher T-HDLP at 120 (mean difference: 297.3 (95% CI: 48.6–545.9) nmol/L) and 180 (291.6 (15.8–567.5) nmol/L) min. The difference in T-HDLP by condition was due to the significantly higher small-dense HDLP (T-HDLP—LB-HDL2b) during HP versus HMF condition at 120 (mean difference: 452.6 (95% CI: 177.4–727.9) nmol/L) and 180 (496.8 (263.1–730.6) nmol/L) min. Area under the curve analysis showed that HP versus HMF condition led to significantly lower TG, non-HDLP, and very-low-density lipoprotein particles (VLDLP) responses but significantly less favorable responses in LB-HDL2b particles, T-HDLP—LB-HDL2b, and LB-HDL2b/T-HDLP ratio.

Conclusion

The HP meal led to lower TG, non-HDLP, and VLDLP but less favorable LB-HDL2b, small-dense HDLP, and LB-HDL2b/T-HDLP ratio responses versus a HMF meal. Further studies are needed to confirm these findings over multiple meals.