A high-protein breakfast induces greater insulin and glucose-dependent insulinotropic peptide responses to a subsequent lunch meal in individuals with type 2 diabetes

Postprandial glycemic response to a high-protein diabetes-specific nutritional shake compared to isocaloric instant oatmeal in people with type 2 diabetes: a randomized, controlled, crossover trial

Introduction

Minimizing postprandial glucose response is an important goal for overall diabetes management. Diabetes-specific nutritional shakes (DSNS) have been clinically shown to minimize postprandial glucose response in people with type 2 diabetes (T2DM) compared to high-glycemic foods. However, it is unknown how a high-protein, low-fat DSNS impacts the GLP-1 response.

Methods

We tested the postprandial glucose, insulin, and GLP-1 response to a high-protein, low-fat diabetes-specific nutritional shake (DSNS-HP) compared to isocaloric instant oatmeal (IOM) in a randomized, controlled, crossover study in adults with T2DM (n = 24). Participants were randomly selected to receive IOM or DSNS-HP on two test days. Glucose, insulin, and total GLP-1 concentration were measured at baseline and 15, 30, 45, 60, 90, 120, 180, and 240 min postprandially.

Results

Compared to IOM, the glucose-positive area under the curve (pAUC) was significantly lower (P = .021). DSNS-HP significantly increased GLP-1 pAUC response by 213% (P <.001) with a corresponding increase in insulin pAUC (P = .033) compared to IOM.

Discussion

A high-protein, low-fat DSNS leads to favorable changes in GLP-1 response and is a suitable option to minimize blood glucose response in people with type 2 diabetes.

Effect of gut hormones on bone metabolism and their possible mechanisms in the treatment of osteoporosis

Bone is a highly dynamic organ that changes with the daily circadian rhythm. During the day, bone resorption is suppressed due to eating, while it increases at night. This circadian rhythm of the skeleton is regulated by gut hormones. Until now, gut hormones that have been found to affect skeletal homeostasis include glucagon-like peptide-1 (GLP-1), glucagon-like peptide-2 (GLP-2), glucose-dependent insulinotropic polypeptide (GIP), and peptide YY (PYY), which exerts its effects by binding to its cognate receptors (GLP-1R, GLP-2R, GIPR, and Y1R). Several studies have shown that GLP-1, GLP-2, and GIP all inhibit bone resorption, while GIP also promotes bone formation. Notably, PYY has a strong bone resorption-promoting effect. In addition, gut microbiota (GM) plays an important role in maintaining bone homeostasis. This review outlines the roles of GLP-1, GLP-2, GIP, and PYY in bone metabolism and discusses the roles of gut hormones and the GM in regulating bone homeostasis and their potential mechanisms.

Protein and Leucine Intake at Main Meals in Elderly People with Type 2 Diabetes

Background: The recommended protein intake for the elderly is 25–30 g at main meals, with at least 2500–2800 mg of leucine at each meal. There is still little evidence regarding the amount and distribution of protein and leucine intake with meals in the elderly with type 2 diabetes (T2D). In this cross-sectional study, we evaluated protein and leucine intake at each meal in elderly patients with T2D. Methods: A total of 138 patients (91 men and 47 women) with T2D, aged 65 years or older, were included. Participants performed three 24-h dietary recalls for the evaluation of their dietary habits and protein and leucine intake at meals. Results: The average protein intake was 0.9 ± 0.2 g/kg body weight/day, and only 23% of patients complied with the recommendations. The average protein intake was 6.9 g at breakfast, 29 g at lunch, and 21 g at dinner. None of the patients reached the recommended protein intake at breakfast; 59% of patients complied with the recommendations at lunch; and 32% at dinner. The average leucine intake was 579 mg at breakfast, 2195 g at lunch, and 1583 mg at dinner. The recommended leucine intake was not reached by any patient at breakfast, by 29% of patients at lunch, and by 13% at dinner. Conclusions: Our data show that, in elderly patients with T2D, the average protein intake is low, particularly at breakfast and dinner, and that leucine intake is remarkably lower than the recommended levels. These data raise the need to implement nutritional strategies capable of increasing protein and leucine intake in the elderly with T2D.

Novel trends and concepts in the nutritional management of glycemia in type 2 diabetes mellitus-beyond dietary patterns: a narrative review

A variety of eating patterns are recommended by international guidelines to help people with type 2 diabetes mellitus (T2DM) achieve general health and glycemia goals. Apart from eating patterns, there is evidence that other approaches related to the everyday application of dietary advice, such as meal frequency, breakfast consumption, daily carbohydrate distribution, and order of food consumption during meals, have significant effects on glycemia management. The aims of this review were to examine published diabetes nutrition guidelines concerning specific recommendations with regard to the above approaches, as well as to review evidence from studies that have investigated their effect on glycemia in T2DM. The data suggest that eating breakfast regularly, consuming most carbohydrates at lunch, avoiding large dinners late at night, and applying the carbohydrate-last meal pattern are effective practices towards better nutritional management of T2DM.

The association of energy and macronutrient intake at dinner vs breakfast with the incidence of type 2 diabetes mellitus in a cohort study: The China Health and Nutrition Survey, 1997-2011

BACKGROUND

This study aims to investigate the association of energy and macronutrient intake at dinner vs breakfast with the incidence of type 2 diabetes mellitus (T2DM).

METHODS

A total of 11 153 adults, including 811 with T2DM, completed a questionnaire about energy and macronutrient intake in the China Health and Nutrition Survey (1997-2011). The differences (Δ) in energy and macronutrient intake between dinner and breakfast (Δ = dinner - breakfast) were categorized into quintiles. Cox proportional hazards regression models were performed to explore the association between Δ and the risk of T2DM and to investigate the change of the risk when 5% total energy or energy provided by macronutrients at dinner was substituted with total energy or energy provided by macronutrients at breakfast by isocaloric substitution models.

RESULTS

After adjustment for potential confounders, compared with participants in the lowest quintile, participants in the highest quintile were more likely to develop T2DM (hazard ratio [HR]_Δenergy 1.46, 95% CI 1.13-1.87; HR_Δfat 1.85, 95% CI 1.43-2.41; HR_Δprotein 1.37, 95% CI 1.06-1.78). Isocalorically replacing 5% energy at dinner with energy at breakfast was associated with a 7% lower T2DM risk. Replacing 5% energy provided by fat at dinner with energy provided by carbohydrate, protein, and fat at breakfast was associated with a 9%, 5%, and 7% lower T2DM risk, respectively. Replacing 5% energy provided by protein at dinner with energy provided by carbohydrate or protein at breakfast was associated with a 5% lower T2DM risk.

CONCLUSIONS

Higher intake of energy, protein, and fat at dinner than at breakfast increased the risk of T2DM.

Alliances of the gut and bone axis

Gut hormones secreted from enteroendocrine cells following nutrient ingestion modulate metabolic processes including glucose homeostasis and food intake, and several of these gut hormones are involved in the regulation of the energy demanding process of bone remodelling. Here, we review the gut hormones considered or known to be involved in the gut-bone crosstalk and their role in orchestrating adaptions of bone formation and resorption as demonstrated in cellular and physiological experiments and clinical trials. Understanding the physiology and pathophysiology of the gut-bone axis may identify adverse effects of investigational drugs aimed to treat metabolic diseases such as type 2 diabetes and obesity and new therapeutic candidates for the treatment of bone diseases.

Role of High Energy Breakfast "Big Breakfast Diet" in Clock Gene Regulation of Postprandial Hyperglycemia and Weight Loss in Type 2 Diabetes

Postprandial hyperglycemia (PPHG) is strongly linked with the future development of cardiovascular complications in type 2 diabetes (T2D). Hence, reducing postprandial glycemic excursions is essential in T2D treatment to slow progressive deficiency of β-cell function and prevent cardiovascular complications. Most of the metabolic processes involved in PPHG, i.e., β-cell secretory function, GLP-1 secretion, insulin sensitivity, muscular glucose uptake, and hepatic glucose production, are controlled by the circadian clock and display daily oscillation. Consequently, postprandial glycemia displays diurnal variation with a higher glycemic response after meals with the same carbohydrate content, consumed at dusk compared to the morning. T2D and meal timing schedule not synchronized with the circadian clock (i.e., skipping breakfast) are associated with disrupted clock gene expression and is linked to PPHG. In contrast, greater intake in the morning (i.e., high energy breakfast) than in the evening has a resetting effect on clock gene oscillations and beneficial effects on weight loss, appetite, and reduction of PPHG, independently of total energy intake. Therefore, resetting clock gene expression through a diet intervention consisting of meal timing aligned to the circadian clock, i.e., shifting most calories and carbohydrates to the early hours of the day, is a promising therapeutic approach to improve PPHG in T2D. This review will focus on recent studies, showing how a high-energy breakfast diet (Bdiet) has resetting and synchronizing actions on circadian clock genes expression, improving glucose metabolism, postprandial glycemic excursions along with weight loss in T2D.

Nocturnal whey protein ingestion impairs post-prandial glucose tolerance at breakfast

Poor post-prandial glucose control is a risk factor for multiple health conditions. The second-meal effect refers to the progressively improved glycaemic control with repeated feedings, an effect which is achievable with protein ingestion at the initial eating occasion. The most pronounced glycaemic response each day therefore typically occurs following breakfast, so the present study investigated whether ingesting protein during the night could improve glucose control at the first meal of the day. In a randomised crossover design, fifteen adults (seven males, eight females; age, 22 (sd 3) years; BMI, 24·0 (sd 2·8) kg/m2; fasting blood glucose, 4·9 (sd 0·5) mmol/l) woke at 04.00 (sd 1) hours to ingest 300 ml water with or without 63 g whey protein. Participants then completed a mixed-macronutrient meal tolerance test (1 g carbohydrate/kg body mass, 2356 (sd 435) kJ), 5 h 39 min following the nocturnal feeding. Nocturnal protein ingestion increased the glycaemic response (incremental AUC) to breakfast by 43·5 (sd 55·5) mmol × 120 min/l (P = 0·009, d = 0·94). Consistent with this effect, individual peak blood glucose concentrations were 0·6 (sd 1·0) mmol/l higher following breakfast when protein had been ingested (P = 0·049, d = 0·50). Immediately prior to breakfast, rates of lipid oxidation were 0·02 (sd 0·03) g/min higher (P = 0·045) in the protein condition, followed by an elevated post-prandial energy expenditure (0·38 (sd 0·50) kJ/min, P = 0·018). Post-prandial appetite and energy intake were similar between conditions. The present study reveals a paradoxical second-meal phenomenon whereby nocturnal whey protein feeding impaired subsequent glucose tolerance, whilst increasing post-prandial energy expenditure.

The effect of a split portion of flaxseed on 24-h blood glucose response

Purpose

Flaxseed can be effective at lowering and stabilising blood glucose responses. The aim of this study was to determine whether flaxseed could lower blood glucose response more effectively when consumed as a single portion of 30 g, or a split portion consumed three times per day (10 g flaxseed per portion).

Methods

The study was a randomised, repeated measures, cross-over design. Fifteen healthy participants consumed either (1) three flaxseed muffins containing a total of 30 g of flaxseed once in the morning, (2) three flaxseed muffins consumed at three different timepoints across the day (10 g flaxseed per muffin) or (3) three control muffins consumed at three different timepoints across the day (0 g flaxseed). The 24-h blood glucose response was measured using a continuous glucose monitor.

Results

The results of this study demonstrated that flaxseed muffins given three times a day were effective at lowering and maintaining blood glucose levels over 24 h, compared to the control muffins and that both flaxseed treatments resulting in a lower blood glucose iAUC during the night.

Conclusion

The results of this study indicated that adding flaxseed to a daily diet produced a lower glucose profile over 24 h in a free-living context compared to the control muffins.

Association between breakfast skipping and postprandial hyperglycaemia after lunch in healthy young individuals

Breakfast skipping has become an increasing trend in the modern lifestyle and may play a role in obesity and type 2 diabetes. In our previous studies in healthy young individuals, a single incident of breakfast skipping increased the overall 24-h blood glucose and elevated the postprandial glycaemic response after lunch; however, it was difficult to determine whether this response was due to breakfast omission or the extra energy (i.e. lunch plus breakfast contents). The present study aimed to assess the postprandial glycaemic response and to measure their hormone levels when healthy young individuals had identical lunch and dinner, and the 24-h average blood glucose as a secondary outcome. Nine healthy young men (19−24 years) participated in two-meal trials: with breakfast (three-meal condition) or without breakfast (breakfast skipping condition). During the meals, each individual’s blood glucose was continuously monitored. Skipping breakfast resulted in a significantly higher (P &lt; 0·001) glycaemic response after lunch as compared with the glycaemic response after an identical lunch when breakfast was consumed. Despite the difference in the total energy intake, the 24-h average blood glucose was similar between the two-meal conditions (P = 0·179). Plasma NEFA level was significantly higher (P &lt; 0·05) after lunch when breakfast was omitted, and NEFA level positively correlated with the postprandial glycaemic response (r 0·631, P &lt; 0·01). In conclusion, a single incident of breakfast skipping increases postprandial hyperglycaemia, and associated impaired insulin response, after lunch. The present study showed that skipping breakfast influences glucose regulation even in healthy young individuals.

A carbohydrate-reduced high-protein diet acutely decreases postprandial and diurnal glucose excursions in type 2 diabetes patients

The aim of the study was to assess whether a simple substitution of carbohydrate in the conventionally recommended diet with protein and fat would result in a clinically meaningful reduction in postprandial hyperglycaemia in subjects with type 2 diabetes mellitus (T2DM). In all, sixteen subjects with T2DM treated with metformin only, fourteen male, with a median age of 65 (43-70) years, HbA1c of 6·5 % (47 mmol/l) (5·5-8·3 % (37-67 mmol/l)) and a BMI of 30 (sd 4·4) kg/m2 participated in the randomised, cross-over study. A carbohydrate-reduced high-protein (CRHP) diet was compared with an iso-energetic conventional diabetes (CD) diet. Macronutrient contents of the CRHP/CD diets consisted of 31/54 % energy from carbohydrate, 29/16 % energy from protein and 40/30 % energy from fat, respectively. Each diet was consumed on 2 consecutive days in a randomised order. Postprandial glycaemia, pancreatic and gut hormones, as well as satiety, were evaluated at breakfast and lunch. Compared with the CD diet, the CRHP diet reduced postprandial AUC of glucose by 14 %, insulin by 22 % and glucose-dependent insulinotropic polypeptide by 17 % (all P<0·001), respectively. Correspondingly, glucagon AUC increased by 33 % (P<0·001), cholecystokinin by 24 % (P=0·004) and satiety scores by 7 % (P=0·035), respectively. A moderate reduction in carbohydrate with an increase in fat and protein in the diet, compared with an energy-matched CD diet, greatly reduced postprandial glucose excursions and resulted in increased satiety in patients with well-controlled T2DM.

High fructose consumption with a high-protein meal is associated with decreased glycemia and increased thermogenesis but reduced fat oxidation: A randomized controlled trial

OBJECTIVES

Fructose is often recommended due to its ability to lower glycemic response and its increased thermogenic effect. Additionally, proteins can reduce the glycemic response of carbohydrate-rich foods and have a high diet-induced thermogenesis (DIT). The aim of this study was to investigate whether the inclusion of fructose in a high-protein meal would demonstrate metabolic advantages.

METHODS

Nineteen Asian women (body mass index 17-28 kg/m²) consumed a low-glycemic index (GI; fructose) or high GI (glucose), high-protein breakfast followed by a standardized lunch in a randomized crossover design. Simultaneously, 8-h continuous glucose monitoring provided incremental area under the curve (iAUC) and 4-h indirect calorimetry provided DIT and respiratory quotient (RQ).

RESULTS

The low GI diet resulted in a lower glucose iAUC (135 ± 25 versus 212 ± 23 mmol/L, P < 0.05) following breakfast, but no second-meal effect after the standardized lunch (217 ± 37 versus 228 ± 27 mmol/L, P < 0.05) compared with the high GI diet. Furthermore, 4-h DIT was greater (40.6 ± 2.3 versus 34.9 ± 1.8 kcal, P < 0.05) and RQ was increased after the fructose high-protein breakfast (0.047 ± 0.009 versus 0.028 ± 0.009, P < 0.05) compared with the glucose meal.

CONCLUSIONS

Fructose is an effective sweetener in reducing glycemia and increasing DIT in the presence of a high-protein diet. However, the reduced fat oxidation after high fructose consumption might present a risk for increased lipogenesis.

Macronutrient Composition and Food Form Affect Glucose and Insulin Responses in Humans

Glycaemic index (GI) is used as an indicator to guide consumers in making healthier food choices. We compared the GI, insulin index (II), and the area under the curve for blood glucose and insulin as glucose (GR) and insulin responses (IR) of a newly developed liquid nutritional formula with one commercially available liquid product with different types of carbohydrates. We then evaluated the glucose and insulin responses of two test foods with comparable energy density and protein percentage but presented in different food forms (liquid vs. solid). Fourteen healthy women participated in the study. GI, II, GR, and IR were assessed after (independent) consumption of two liquid products and a solid breakfast meal. The two liquid foods showed comparable GI, whilst the liquid form appeared to produce lower median GI (25 vs. 54), and II (52 vs. 98) values compared to the solid breakfast (p < 0.02). The median GR and IR for solid breakfast were respectively 44% and 45% higher compared to the liquid product (p < 0.02). Liquid formulas with different carbohydrate qualities produced comparable glucose responses, while foods with comparable energy density and protein percentage but different food form elicited differential effects on GI, II, GR, and IR. Nutrient quality and food form need to be taken into consideration when developing low GI products to manage glycaemic responses.

Effect of prior meal macronutrient composition on postprandial glycemic responses and glycemic index and glycemic load value determinations

Background: The potential impact of prior meal composition on the postprandial glycemic response and glycemic index (GI) and glycemic load (GL) value determinations remains unclear.Objective: We determined the effect of meals that varied in macronutrient composition on the glycemic response and determination of GI and GL values of a subsequent standard test food.Design: Twenty healthy participants underwent 6 test sessions within 12 wk. The subjects received each of 3 isocaloric breakfast meals (i.e., high carbohydrate, high fat, or high protein) on separate days in a random order, which was followed by a standard set of challenges (i.e., white bread and a glucose drink) that were tested on separate days in a random order 4 h thereafter. Each challenge provided 50 g available carbohydrate. Arterialized venous blood was sampled throughout the 2-h postchallenge period. GI, GL, and insulin index (II) values were calculated with the use of the incremental area under the curve (AUCi) method, and serum lipids were determined with the use of standard assays.Results: The consumption of the high-protein breakfast before the white-bread challenge attenuated the rise in the postprandial serum glucose response (P < 0.0001) and resulted in lower glucose AUCi (P < 0.0001), GI (P = 0.0096), and GL (P = 0.0101) values than did the high-carbohydrate and high-fat breakfasts. The high-protein breakfast resulted in a lower insulin AUCi (P = 0.0146) for white bread than did the high-fat breakfast and a lower II value (P = 0.0285) than did the high-carbohydrate breakfast. The 3 breakfasts resulted in similar serum lipid responses to the white-bread challenge.Conclusions: These data indicate that the macronutrient composition of the prior meal influences the glycemic response and the determination of GI and GL values for white bread. Future studies are needed to determine whether the background food macronutrient composition influences mean dietary GI and GL values that are calculated for eating patterns, which may alter the interpretation of the associations between these values and chronic disease risk. This trial was registered at clinicaltrials.gov as NCT01023646.

Educational nutrition messaging at breakfast reduces snack intake and influences snack preferences in adult men and women

Breakfast skipping is associated with increased risk of weight gain and obesity in young adults, possibly due to increased snacking later in the day. Recent research suggests that providing and animal versus a plant source of protein at breakfast can reduce snack intake later in the day. In addition, providing nutrition information via a nutrition label, front-of-pack information, or via text messaging has been shown to help individuals make healthier food choices. The objective of this study was to determine if educational nutrition messaging and protein source influenced snack intake 2 h following the breakfast meal. Participants (n = 33) were randomly assigned to one of two groups: educational nutrition messaging (EM; n = 16) or no messaging (NM; n = 17) group. The study was conducted using a randomized, cross-over design in which each participant received each of two breakfast beverages, whey protein- (WP) and pea protein (PP)- based. Appetite was assessed at 0, 15, 30, 60, 90, and 120 min after each test breakfast using visual analog scales. Participants were then provided with a selection of healthy and unhealthy snacks for 60 min. There was no effect of protein source on appetite or snack intake. However, participants presented with EM had reduced snack intake over the snacking period compared to NM (P = 0.058) and, of the snacks consumed, the EM group consumed a higher percentage of healthy versus unhealthy snacks compared to NM (P < 0.0001), resulting in lower calorie intake. Taken together these data suggest that protein source, as part of a higher protein breakfast, does not affect appetite response or snack intake, but EM may help play a role in reducing snack intake between meals.

Dietary habits, physical activity and diabetes perception among patients with type 2 diabetes mellitus in Tabuk City, Saudi Arabia

Background

Medical nutritional therapy is an important aspect of diabetes care, there is an increasing awareness of breakfast skipping, late dinner and meal contents on diabetes control.

Aim

To assess dietary habits, physical activity and diabetes perception among patients with type 2 diabetes.

Methods

This case-control study was conducted among patients with diabetes mellitus at the diabetes center in Tabuk City, Saudi Arabia during the period from March through June 2017. One hundred patients with type 2 diabetes and 150 control subjects were interviewed to collect demographic data regarding, breakfast skipping, late dinner intake, and fruit, vegetables, sweet food, and fast food consumption. Diabetic patients’ perception of their disease was also assessed. (If diabetes is serious, it can be prevented and reversible). Data were analyzed by SPSS version 20 using Chi-square and independent-samples t-test.

Results

In the present study, body mass index (BMI) (p<0.001), fast food consumption (p<0.001), fruit consumption (p=0.004), and breakfast skipping (p<0.001) were higher among patients with diabetes compared to controls. No differences were found regarding the level of exercise, smoking, late dinner intake and diabetes perception. A significant statistical difference was observed between poor and accepted control regarding sweet food intake (p=0.046) and exercise (p=0.017).

Conclusion

Patients with type 2 diabetes had higher BMI, and were more likely to skip breakfast, consume less fast food and more fruits than control subjects. More physical activity and less sweet food consumption was observed among patients with accepted glycemic control.

High-energy breakfast based on whey protein reduces body weight, postprandial glycemia and HbA1C in Type 2 diabetes

Acute studies show that addition of whey protein at breakfast has a glucose-lowering effect through increased incretin and insulin secretion. However, whether this is a long-term effect in Type 2 diabetes is unknown. Fifty-six Type 2 diabetes participants aged 58.9±4.5 years, BMI 32.1±0.9 kg/m² and HbA_1C 7.8±0.1% (61.6±0.79 mmol/mol) were randomized to one of 3 isocaloric diets with similar lunch and dinner, but different breakfast: 1) 42 g total protein, 28 g whey (WBdiet, n=19); 2) 42 g various protein sources (PBdiet, n=19); or 3) high-carbohydrate breakfast, 17 g protein from various sources (CBdiet, n=18). Body weight and HbA_1C were examined after 12 weeks. All participants underwent three all-day meal challenges for postprandial glycemia, insulin, C-peptide, intact glucagon-like peptide 1 (iGLP-1), ghrelin and hunger and satiety scores. Overall postprandial AUC_glucose was reduced by 12% in PBdiet and by 19% in WBdiet, compared with CBdiet (P<.0001). Compared with PBdiet and CBdiet, WBdiet led to a greater postprandial overall AUC for insulin, C-peptide, iGLP-1 and satiety scores, while postprandial overall AUC for ghrelin and hunger scores were reduced (P<.0001). After 12 weeks, HbA_1C was reduced after WBdiet by 0.89±0.05% (11.5±0.6 mmol/mol), after PBdiet by 0.6±0.04% (7.1±0.31 mmol/mol) and after CBdiet by 0.36±0.04% (2.9±0.31 mmol/mol) (P<.0001). Furthermore, the participants on WBdiet lost 7.6±0.3 kg, PBdiet 6.1±0.3 kg and CBdiet 3.5±0.3 kg (P<.0001). Whey protein-based breakfast is an important adjuvant in the management of Type 2 diabetes.

Effects of Higher Dietary Protein and Fiber Intakes at Breakfast on Postprandial Glucose, Insulin, and 24-h Interstitial Glucose in Overweight Adults

Dietary protein and fiber independently influence insulin-mediated glucose control. However, potential additive effects are not well-known. Men and women (n = 20; age: 26 ± 5 years; body mass index: 26.1 ± 0.2 kg/m²; mean ± standard deviation) consumed normal protein and fiber (NPNF; NP = 12.5 g, NF = 2 g), normal protein and high fiber (NPHF; NP = 12.5 g, HF = 8 g), high protein and normal fiber (HPNF; HP = 25 g, NF = 2 g), or high protein and fiber (HPHF; HP = 25 g, HF = 8 g) breakfast treatments during four 2-week interventions in a randomized crossover fashion. On the last day of each intervention, meal tolerance tests were completed to assess postprandial (every 60 min for 240 min) serum glucose and insulin concentrations. Continuous glucose monitoring was used to measure 24-h interstitial glucose during five days of the second week of each intervention. Repeated-measures ANOVA was applied for data analyses. The HPHF treatment did not affect postprandial glucose and insulin responses or 24-h glucose total area under the curve (AUC). Higher fiber intake reduced 240-min insulin AUC. Doubling the amount of protein from 12.5 g to 25 g/meal and quadrupling fiber from 2 to 8 g/meal at breakfast was not an effective strategy for modulating insulin-mediated glucose responses in these young, overweight adults.

New Approaches to Feline Diabetes Mellitus: Glucagon-like peptide-1 analogs

CLINICAL RELEVANCE

Incretin-based therapies are revolutionizing the field of human diabetes mellitus (DM) by replacing insulin therapy with safer and more convenient long-acting drugs.

MECHANISM OF ACTION

Incretin hormones (glucagon-like peptide-1 [GLP-1] and glucose-dependent insulinotropic peptide [GIP]) are secreted from the intestinal tract in response to the presence of food in the intestinal lumen. GLP-1 delays gastric emptying and increases satiety. In the pancreas, GLP-1 augments insulin secretion and suppresses glucagon secretion during hyperglycemia in a glucose-dependent manner. It also protects beta cells from oxidative and toxic injury and promotes expansion of beta cell mass.

ADVANTAGES

Clinical data have revealed that GLP-1 analog drugs are as effective as insulin in improving glycemic control while reducing body weight in people suffering from type 2 DM. Furthermore, the incidence of hypoglycemia is low with these drugs because of their glucose-dependent mechanism of action. Another significant advantage of these drugs is their duration of action. While insulin injections are administered at least once daily, long-acting GLP-1 analogs have been developed as once-a-week injections and could potentially be administered even less frequently than that in diabetic cats.

OUTLINE

This article reviews the physiology of incretin hormones, and the pharmacology and use of GLP-1 analogs, with emphasis on recent research in cats. Further therapies that are based on incretin hormones, such as DPP-4 inhibitors, are also briefly discussed, as are some other treatment modalities that are currently under investigation.

Breakfast Macronutrient Composition Influences Thermic Effect of Feeding and Fat Oxidation in Young Women Who Habitually Skip Breakfast

The purpose of this study was to determine if breakfast macronutrient composition improved thermic effect of feeding (TEF) and appetite after a one-week adaptation in young women who habitually skip breakfast. A randomized, controlled study was conducted in females (24.1 ± 2 years), who skip breakfast (≥5 times/week). Participants were placed into one of three groups for eight days (n = 8 per group): breakfast skipping (SKP; no breakfast), carbohydrate (CHO; 351 kcal; 59 g CHO, 10 g PRO, 8 g fat) or protein (PRO; 350 kcal; 39 g CHO, 30 g PRO, 8 g fat). On days 1 (D1) and 8 (D8), TEF, substrate oxidation, appetite and blood glucose were measured. PRO had higher (p < 0.05) TEF compared to SKP and CHO on D1 and D8, with PRO having 29% higher TEF than CHO on D8. On D1, PRO had 30.6% higher fat oxidation than CHO and on D8, PRO had 40.6% higher fat oxidation than CHO. SKP had higher (p < 0.05) fat oxidation on D1 and D8 compared to PRO and CHO. There was an interaction (p < 0.0001) of time and breakfast on appetite response. In addition, CHO had a significant increase (p < 0.05) in PP hunger response on D8 vs. D1. CHO and PRO had similar PP (postprandial) glucose responses on D1 and D8. Consumption of PRO breakfast for 8 days increased TEF compared to CHO and SKP, while consumption of CHO for one week increased PP hunger response.

Co-Ingestion of Whey Protein with a Carbohydrate-Rich Breakfast Does Not Affect Glycemia, Insulinemia or Subjective Appetite Following a Subsequent Meal in Healthy Males

We aimed to assess postprandial metabolic and appetite responses to a mixed-macronutrient lunch following prior addition of whey protein to a carbohydrate-rich breakfast. Ten healthy males (age: 24 ± 1 years; body mass index (BMI): 24.5 ± 0.7 kg/m²) completed three trials in a non-isocaloric, crossover design. A carbohydrate-rich breakfast (93 g carbohydrate; 1799 kJ) was consumed with (CHO + WP) or without (CHO) 20 g whey protein isolate (373 kJ), or breakfast was omitted (NB). At 180 min, participants consumed a mixed-macronutrient lunch meal. Venous blood was sampled at 15 min intervals following each meal and every 30 min thereafter, while subjective appetite sensations were collected every 30 min throughout. Post-breakfast insulinemia was greater after CHO + WP (time-averaged area under the curve (AUC_{0–180 min}): 193.1 ± 26.3 pmol/L), compared to CHO (154.7 ± 18.5 pmol/L) and NB (46.1 ± 8.0 pmol/L; p < 0.05), with no difference in post-breakfast (0–180 min) glycemia (CHO + WP, 3.8 ± 0.2 mmol/L; CHO, 4.2 ± 0.2 mmol/L; NB, 4.2 ± 0.1 mmol/L; p = 0.247). There were no post-lunch (0–180 min) effects of condition on glycemia (p = 0.492), insulinemia (p = 0.338) or subjective appetite (p > 0.05). Adding whey protein to a carbohydrate-rich breakfast enhanced the acute postprandial insulin response, without influencing metabolic or appetite responses following a subsequent mixed-macronutrient meal.

Effects of Dietary Protein Source and Quantity during Weight Loss on Appetite, Energy Expenditure, and Cardio-Metabolic Responses

Higher protein meals increase satiety and the thermic effect of feeding (TEF) in acute settings, but it is unclear whether these effects remain after a person becomes acclimated to energy restriction or a given protein intake. This study assessed the effects of predominant protein source (omnivorous, beef/pork vs. lacto-ovo vegetarian, soy/legume) and quantity (10%, 20%, or 30% of energy from protein) on appetite, energy expenditure, and cardio-metabolic indices during energy restriction (ER) in overweight and obese adults. Subjects were randomly assigned to one protein source and then consumed diets with different quantities of protein (4 weeks each) in a randomized crossover manner. Perceived appetite ratings (free-living and in-lab), TEF, and fasting cardio-metabolic indices were assessed at the end of each 4-week period. Protein source and quantity did not affect TEF, hunger, or desire to eat, other than a modestly higher daily composite fullness rating with 30% vs. 10% protein diet (p = 0.03). While the 20% and 30% protein diets reduced cholesterol, triacylglycerol, and APO-B vs. 10% protein (p < 0.05), protein source did not affect cardio-metabolic indices. In conclusion, diets varying in protein quantity with either beef/pork or soy/legume as the predominant source have minimal effects on appetite control, energy expenditure and cardio-metabolic risk factors during ER-induced weight loss.

Mixed meal ingestion diminishes glucose excursion in comparison with glucose ingestion via several adaptive mechanisms in people with and without type 2 diabetes

AIMS

To study the integrative impact of macronutrients on postprandial glycaemia, β-cell function, glucagon and incretin hormones in humans.

METHODS

Macronutrients were ingested alone (glucose 330 kcal, protein 110 kcal or fat 110 kcal) or together (550 kcal) by healthy subjects (n = 18) and by subjects with drug-naïve type 2 diabetes (T2D; n = 18). β-cell function and insulin clearance were estimated by modelling glucose, insulin and C-peptide data. Secretion of glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-1) were measured, and paracetamol was administered to estimate gastric emptying.

RESULTS

In both groups, the mixed-meal challenge diminished glucose excursion compared with glucose challenge alone, and insulin levels, but not C-peptide levels, rose more than after the mixed meal than after glucose alone. β-cell function was augmented, insulin clearance was reduced and glucagon levels were higher after the mixed meal compared with glucose alone. GLP-1 and GIP levels increased after all challenges and GIP secretion was markedly higher after the mixed meal than after glucose alone. The appearance of paracetamol was delayed after the mixed-meal challenge compared with glucose alone.

CONCLUSIONS

Adding protein and fat macronutrients to glucose in a mixed meal diminished glucose excursion. This occurred in association with increased β-cell function, reduced insulin clearance, delayed gastric emptying and augmented glucagon and GIP secretion. This suggests that the macronutrient composition regulates glycaemia through both islet and extra-islet mechanisms in both healthy subjects and in subjects with T2D.

Modification of a traditional breakfast leads to increased satiety along with attenuated plasma increments of glucose, C-peptide, insulin, and glucose-dependent insulinotropic polypeptide in humans

Our hypothesis was that carbohydrate, fat, and protein contents of meals affect satiety, glucose homeostasis, and hormone secretion. The objectives of this crossover trial were to examine satiety, glycemic-insulinemic response, and plasma peptide levels in response to 2 different recommended diabetes diets with equivalent energy content. One traditional reference breakfast and one test breakfast, with lower carbohydrate and higher fat and protein content, were randomly administered to healthy volunteers (8 men, 12 women). Blood samples were collected, and satiety was scored on a visual analog scale before and 3 hours after meals. Plasma glucose was measured, and levels of C-peptide, ghrelin, glucagon, glucagon-like peptide-1, glucose-dependent insulinotropic polypeptide (GIP), insulin, plasminogen activator inhibitor-1, and adipokines were analyzed by Luminex. Greater satiety, visual analog scale, and total and delta area under the curve (P < .001), and lower glucose postprandial peak (max) and change from baseline (dmax; P < .001) were observed after test meal compared with reference meal. Postprandial increments of C-peptide, insulin, and GIP were suppressed after test meal compared with reference meal (total delta area under the curve [P = .03, .006, and .004], delta area under the curve [P = .006, .003, and .02], max [P = .01, .007, and .002], and dmax [P = .004, .008, and .007], respectively). Concentrations of other peptides were similar between meals. A lower carbohydrate and higher fat and protein content provides greater satiety and attenuation of C-peptide, glucose, insulin, and GIP responses compared with the reference breakfast but does not affect adipokines, ghrelin, glucagon, glucagon-like peptide-1, and plasminogen activator inhibitor-1.