Nutritional strategies to attenuate postprandial glycemic response

Role of the intestinal microbiota in contributing to weight disorders and associated comorbidities

SUMMARYThe gut microbiota is a major factor contributing to the regulation of energy homeostasis and has been linked to both excessive body weight and accumulation of fat mass (i.e., overweight, obesity) or body weight loss, weakness, muscle atrophy, and fat depletion (i.e., cachexia). These syndromes are characterized by multiple metabolic dysfunctions including abnormal regulation of food reward and intake, energy storage, and low-grade inflammation. Given the increasing worldwide prevalence of obesity, cachexia, and associated metabolic disorders, novel therapeutic strategies are needed. Among the different mechanisms explaining how the gut microbiota is capable of influencing host metabolism and energy balance, numerous studies have investigated the complex interactions existing between nutrition, gut microbes, and their metabolites. In this review, we discuss how gut microbes and different microbiota-derived metabolites regulate host metabolism. We describe the role of the gut barrier function in the onset of inflammation in this context. We explore the importance of the gut-to-brain axis in the regulation of energy homeostasis and glucose metabolism but also the key role played by the liver. Finally, we present specific key examples of how using targeted approaches such as prebiotics and probiotics might affect specific metabolites, their signaling pathways, and their interactions with the host and reflect on the challenges to move from bench to bedside.

MTNR1B genotype and effects of carbohydrate quantity and dietary glycaemic index on glycaemic response to an oral glucose load: the OmniCarb trial

AIMS/HYPOTHESIS

A type 2 diabetes-risk-increasing variant, MTNR1B (melatonin receptor 1B) rs10830963, regulates the circadian function and may influence the variability in metabolic responses to dietary carbohydrates. We investigated whether the effects of carbohydrate quantity and dietary glycaemic index (GI) on glycaemic response during OGTTs varied by the risk G allele of MTNR1B-rs10830963.

METHODS

This study included participants (n=150) of a randomised crossover-controlled feeding trial of four diets with high/low GI levels and high/low carbohydrate content for 5 weeks. The MTNR1B-rs10830963 (C/G) variant was genotyped. Glucose response during 2 h OGTT was measured at baseline and the end of each diet intervention.

RESULTS

Among the four study diets, carrying the risk G allele (CG/GG vs CC genotype) of MTNR1B-rs10830963 was associated with the largest AUC of glucose during 2 h OGTT after consuming a high-carbohydrate/high-GI diet (β 134.32 [SE 45.69] mmol/l × min; p=0.004). The risk G-allele carriers showed greater increment of glucose during 0-60 min (β 1.26 [0.47] mmol/l; p=0.008) or 0-90 min (β 1.10 [0.50] mmol/l; p=0.028) after the high-carbohydrate/high-GI diet intervention, but not after consuming the other three diets. At high carbohydrate content, reducing GI levels decreased 60 min post-OGTT glucose (mean -0.67 [95% CI: -1.18, -0.17] mmol/l) and the increment of glucose during 0-60 min (mean -1.00 [95% CI: -1.67, -0.33] mmol/l) and 0-90 min, particularly in the risk G-allele carriers (pinteraction <0.05 for all).

CONCLUSIONS/INTERPRETATION

Our study shows that carrying the risk G allele of MTNR1B-rs10830963 is associated with greater glycaemic responses after consuming a diet with high carbohydrates and high GI levels. Reducing GI in a high-carbohydrate diet may decrease post-OGTT glucose concentrations among the risk G-allele carriers.

Synthesis, biological evaluation and action mechanism of 7H-[1,2,4] triazolo [3,4-b] [1,3,4] thiadiazine-phenylhydrazone derivatives as α-glucosidase inhibitors

In our work, several 7H-[1,2,4]triazolo[3,4-b][1,3,4]thiadiazine-phenylhydrazone derivatives as α-glucosidase inhibitors (α-GIs) were synthesized and characterized by 1H NMR, 13C NMR, and HRMS spectrum. Then, their bio-activity against the α-glucosidase (α-Glu) was further evaluated. Among them, almost all compounds displayed better bio-activity with IC50 from 31.23 ± 0.89 to 213.50 ± 4.19 μM than acarbose (IC50 = 700.20 ± 10.55 μM). In particular, compound 5o showed the best potency to inhibit α-Glu in a mixed manner. Moreover, the action mechanisms of 5o were further clarified including fluorescence quenching, circular dichroism spectra, three-dimensional fluorescence spectra, molecular docking, etc. All mechanism studies revealed that 5o could arouse the changed secondary structure of α-Glu to hinder enzyme catalytic activity. It was observed from an in vivo study that 5o of 20 mg/kg could significantly decrease by 24.45 % postprandial blood glucose in mice vs. the control. Meanwhile, 5o had low drug-drug interaction potential and was likely to be an orally active compound. Moreover, 5o was observed to be no obvious cytotoxicity to HEK-293 cells. In summary, compound 5o exhibited one potential to be further applied as an antidiabetic drug.

Carbohydrates for glycemic control: functional and microbiome aspects

PURPOSE OF REVIEW

Glycemia goals are used as indicators of control and progression in prediabetes and diabetes. Adopting healthy eating habits is essential. It is worth considering the quality of carbohydrates to help with dietary glycemic control. The present article aims to review recent meta-analyses published in the years 2021-2022 on the effects of dietary fiber and low glycemic index/load (LGI/LGL) foods on glycemic control and how gut microbiome modulation contributes to glycemic control.

RECENT FINDINGS

Data involving more than 320 studies were reviewed. The evidence allows us to infer that LGI/LGL foods, including dietary fiber intake, are associated with reduced fasting glycemia and insulinemia, postprandial glycemic response, HOMA-IR, and glycated hemoglobin, which are more evident in soluble dietary fiber. These results can be correlated with changes in the gut microbiome. However, the mechanistic roles of microbes or metabolites implicated in these observations continue to be explored. Some controversial data highlight the need for more homogeneity between studies.

SUMMARY

The properties of dietary fiber are reasonably well established for their glycemic homeostasis effects, including the fermentation aspects. Findings of gut microbiome correlations with glucose homeostasis can be incorporated into clinical nutrition practice. Target dietary fiber interventions on microbiome modulation can offer options to improve glucose control and contribute to personalized nutritional practices.

Thiazolidinedione-triazole conjugates: design, synthesis and probing of the α-amylase inhibitory potential

Aim: The primary objective of this investigation was the synthesis, spectral interpretation and evaluation of the α-amylase inhibition of rationally designed thiazolidinedione-triazole conjugates (7a-7aa). Materials & methods: The designed compounds were synthesized by stirring a mixture of thiazolidine-2,4-dione, propargyl bromide, cinnamaldehyde and azide derivatives in polyethylene glycol-400. The α-amylase inhibitory activity of the synthesized conjugates was examined by integrating in vitro and in silico studies. Results: The investigated derivatives exhibited promising α-amylase inhibitory activity, with IC50 values ranging between 0.028 and 0.088 μmol ml-1. Various computational approaches were employed to get detailed information about the inhibition mechanism. Conclusion: The thiazolidinedione-triazole conjugate 7p, with IC50 = 0.028 μmol ml-1, was identified as the best hit for inhibiting α-amylase.

High Fructose Causes More Prominent Liver Steatohepatitis with Leaky Gut Similar to High Glucose Administration in Mice and Attenuation by Lactiplantibacillus plantarum dfa1

High-sugar diet-induced prediabetes and obesity are a global current problem that can be the result of glucose or fructose. However, a head-to-head comparison between both sugars on health impact is still lacking, and Lactiplantibacillus plantarum dfa1 has never been tested, and has recently been isolated from healthy volunteers. The mice were administered with the high glucose or fructose preparation in standard mouse chaw with or without L. plantarum dfa1 gavage, on alternate days, and in vitro experiments were performed using enterocyte cell lines (Caco2) and hepatocytes (HepG2). After 12 weeks of experiments, both glucose and fructose induced a similar severity of obesity (weight gain, lipid profiles, and fat deposition at several sites) and prediabetes condition (fasting glucose, insulin, oral glucose tolerance test, and Homeostatic Model Assessment for Insulin Resistance (HOMA score)). However, fructose administration induced more severe liver damage (serum alanine transaminase, liver weight, histology score, fat components, and oxidative stress) than the glucose group, while glucose caused more prominent intestinal permeability damage (FITC-dextran assay) and serum cytokines (TNF-α, IL-6, and IL-10) compared to the fructose group. Interestingly, all of these parameters were attenuated by L. plantarum dfa1 administration. Because there was a subtle change in the analysis of the fecal microbiome of mice with glucose or fructose administration compared to control mice, the probiotics altered only some microbiome parameters (Chao1 and Lactobacilli abundance). For in vitro experiments, glucose induced more damage to high-dose lipopolysaccharide (LPS) (1 µg/mL) to enterocytes (Caco2 cell) than fructose, as indicated by transepithelial electrical resistance (TEER), supernatant cytokines (TNF-α and IL-8), and glycolysis capacity (by extracellular flux analysis). Meanwhile, both glucose and fructose similarly facilitated LPS injury in hepatocytes (HepG2 cell) as evaluated by supernatant cytokines (TNF-α, IL-6, and IL-10) and extracellular flux analysis. In conclusion, glucose possibly induced a more severe intestinal injury (perhaps due to LPS-glucose synergy) and fructose caused a more prominent liver injury (possibly due to liver fructose metabolism), despite a similar effect on obesity and prediabetes. Prevention of obesity and prediabetes with probiotics was encouraged.

Previous gut microbiota has an effect on postprandial insulin response after intervention with yacon syrup as a source of fructooligosaccharides: a randomized, crossover, double-blind clinical trial

OBJECTIVES

The use of prebiotics has an effect on postprandial glucose and insulin concentrations; however, the interaction between the previous profile of the intestinal microbiota and the effect of supplementation with prebiotics is not clear. Our objective was to evaluate the effect of previous intestinal microbiota profile on the postprandial insulin response to yacon syrup, used as a source of fructooligosaccharides (FOSs), in young women. The product presents high levels of FOS.

METHODS

In this double-blind, crossover, randomized clinical trial, 40 adult women were allocated to receive a breakfast containing 40 g of yacon syrup (14 g FOS, intervention A) or a breakfast containing 40 g of placebo (intervention B). On each intervention day, after 12 h of fasting, an aliquot of blood was collected for insulin analysis at 0, 15, 30, 45, 60, 90, and 120 min. The fecal sample was collected before the beginning of the interventions, and the DNA was extracted and quantified, with subsequent amplification of the 16S region, next-generation sequencing, and analysis of sequencing data.

RESULTS

The glucose and insulin concentrations were reduced after ingestion of yacon syrup compared with placebo, specifically at the 30 min to insulin. After the receiver operating characteristic analysis, six volunteers who did not respond to the yacon consumption intervention were identified. The abundance of the phylum Actinobacteria (P = 0.021) and the order Bifidobacteriales (P = 0.013) were positively associated with better insulin response. Other main phyla were not associated with intervention response.

CONCLUSIONS

The previous profile of the intestinal microbiota has an effect on the postprandial insulin response to FOSs, mainly in the phylum Actinobacteria and Bifidobacteriales order.