Dataset Information

The Gut Microbiome and Abiotic Factors as Potential Determinants of Postprandial Glucose Responses: A Single-Arm Meal Study.

ABSTRACT: The gut microbiome has combined with other person-specific information, such as blood parameters, dietary habits, anthropometrics, and physical activity been found to predict personalized postprandial glucose responses (PPGRs) to various foods. Yet, the contributions of specific microbiome taxa, measures of fermentation, and abiotic factors in the colon to glycemic control remain elusive. We tested whether PPGRs 60 min after a standardized breakfast was associated with gut microbial ?-diversity (primary outcome) and explored whether postprandial responses of glucose and insulin were associated with specific microbiome taxa, colonic fermentation as reflected by fecal short-chain fatty acids (SCFAs), and breath hydrogen and methane exhalation, as well as abiotic factors including fecal pH, fecal water content, fecal energy density, intestinal transit time (ITT), and stool consistency. A single-arm meal trial was conducted. A total of 31 healthy (24 female and seven male) subjects consumed a standardized evening meal and a subsequent standardized breakfast (1,499 kJ) where blood was collected for analysis of postprandial glucose and insulin responses. PPGRs to the same breakfast varied across the healthy subjects. The largest inter-individual variability in PPGRs was observed 60 min after the meal but was not associated with gut microbial ?-diversity. In addition, no significant associations were observed between postprandial responses and specific taxa of the gut microbiome, measures of colonic fermentation, ITT, or other abiotic factors. However, fasting glucose concentrations were negatively associated with ITT, and fasting insulin was positively associated with fasting breath hydrogen. In conclusion, the gut microbiome, measures of colonic fermentation, and abiotic factors were not shown to be significantly associated with variability in postprandial responses, suggesting that contributions of the gut microbiome, colonic fermentation, and abiotic factors to PPGRs may be subtle in healthy adults.

SUBMITTER: Nestel N

PROVIDER: S-EPMC7874175 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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The Gut Microbiome and Abiotic Factors as Potential Determinants of Postprandial Glucose Responses: A Single-Arm Meal Study.

Nestel Nathalie N Hvass Josephine D JD Bahl Martin I MI Hansen Lars H LH Krych Lukasz L Nielsen Dennis S DS Dragsted Lars Ove LO Roager Henrik M HM

Frontiers in nutrition 20210114

The gut microbiome has combined with other person-specific information, such as blood parameters, dietary habits, anthropometrics, and physical activity been found to predict personalized postprandial glucose responses (PPGRs) to various foods. Yet, the contributions of specific microbiome taxa, measures of fermentation, and abiotic factors in the colon to glycemic control remain elusive. We tested whether PPGRs 60 min after a standardized breakfast was associated with gut microbial α-diversity ...[more]

PMID: 33585532

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Project description:BackgroundHigh postprandial glucose excursions may increase risk for disease. Individuals have widely varying glucose responses to different meals, and precision nutrition approaches often seek to personalize diets to minimize postprandial glycemic responses as measured by continuous glucose monitors (CGMs). However, it is unknown whether different CGM devices result in concordant meal rankings according to postprandial glycemic excursions.ObjectiveWe explored whether meal rankings according to postprandial glycemic excursions differ between 2 simultaneously worn CGMs.MethodsWe collected 27,489 simultaneous measurements from Dexcom G4 Platinum and Abbott Freestyle Libre Pro CGMs during 28 inpatient days in 16 adults without diabetes. Simultaneous glucose measurements obtained for 2 h following 760 ad libitum meals were used to compare within-subject meal rankings between the CGM devices according to their incremental glucose response.ResultsPostprandial responses to ad libitum meals were highly variable, with the Abbott and Dexcom systems resulting in within-subject incremental mean ± SD glucose CVs of 91.7 ± 1.9% and 94.2 ± 2.7%, respectively. Within-subject meal rankings for incremental glycemic responses were relatively discordant between CGMs, with a mean Kendall rank correlation coefficient of 0.43 ± 0.05. Meals in the bottom compared with those in the top half of incremental glycemic responses ranked by Abbott resulted in 50 ± 10% (P = 0.0002) less glycemic reduction as measured by Dexcom, and vice versa. The missing glycemic reduction by eating meals ranked according to the discordant CGM was inversely correlated with each subject's Kendall rank correlation coefficient (r = -0.95; P < 0.0001).ConclusionsPrecision nutrition approaches that use CGMs to personalize meal recommendations for minimizing glycemic excursions may be premature given the discordance of within-subject meal rankings between simultaneous CGM devices. More research is needed to clarify the source of this imprecision. This trial was registered at clinicaltrials.gov as NCT03407053.

Project description:BackgroundDyslipidemia is a feature of impaired metabolic health in conjunction with impaired glucose metabolism and central obesity. However, the contribution of factors to postprandial lipemia in healthy but metabolically at-risk adults is not well understood. We investigated the collective contribution of several physiologic and lifestyle factors to postprandial triglyceride (TG) response to a high-fat meal in healthy, overweight and obese adults.MethodsOverweight and obese adults (n = 35) underwent a high-fat meal challenge with blood sampled at fasting and hourly in the 4-hour postprandial period after a breakfast containing 50 g fat. Incremental area under the curve (iAUC) and postprandial magnitude for TG were calculated and data analyzed using a linear model with physiologic and lifestyle characteristics as explanatory variables. Model reduction was used to assess which explanatory variables contributed most to the postprandial TG response.ResultsTG responses to a high-fat meal were variable between individuals, with approximately 57 % of participants exceeded the nonfasting threshold for hypertriglyceridemia. Visceral adiposity was the strongest predictor of TG iAUC (β = 0.53, p = 0.01), followed by aerobic exercise frequency (β = 0.31, p = 0.05), insulin resistance based on HOMA-IR (β = 0.30, p = 0.04), and relative exercise intensity at which substrate utilization crossover occurred (β = 0.05, p = 0.04). For postprandial TG magnitude, visceral adiposity was a strong predictor (β = 0.43, p < 0.001) followed by aerobic exercise frequency (β = 0.23, p = 0.01), and exercise intensity for substrate utilization crossover (β = 0.53, p = 0.01).ConclusionsPostprandial TG responses to a high-fat meal was partially explained by several physiologic and lifestyle characteristics, including visceral adiposity, insulin resistance, aerobic exercise frequency, and relative substrate utilization crossover during exercise.Trial registrationClinicalTrials.gov, NCT04128839 , Registered 16 October 2019 - Retrospectively registered.

Project description:Elevated postprandial plasma glucose is a risk factor for development of type 2 diabetes and cardiovascular disease. We hypothesized that the inter-individual postprandial plasma glucose response varies partly depending on the intestinal microbiome composition and function. We analyzed data from Danish adults (n = 106), who were self-reported healthy and attended the baseline visit of two previously reported randomized controlled cross-over trials within the Gut, Grain and Greens project. Plasma glucose concentrations at five time points were measured before and during three hours after a standardized breakfast. Based on these data, we devised machine learning algorithms integrating bio-clinical, as well as shotgun-sequencing-derived taxa and functional potentials of the intestinal microbiome to predict individual postprandial glucose excursions. In this post hoc study, we found microbial and clinical features, which predicted up to 48% of the inter-individual variance of postprandial plasma glucose responses (Pearson correlation coefficient of measured vs. predicted values, R = 0.69, 95% CI: 0.45 to 0.84, p<0.001). The features were age, fasting serum triglycerides, systolic blood pressure, BMI, fasting total serum cholesterol, abundance of Bifidobacterium genus, richness of metagenomics species and abundance of a metagenomic species annotated to Clostridiales at order level. A model based only on microbial features predicted up to 14% of the variance in postprandial plasma glucose excursions (R = 0.37, 95% CI: 0.02 to 0.64, p = 0.04). Adding fasting glycaemic measures to the model including microbial and bio-clinical features increased the predictive power to R = 0.78 (95% CI: 0.59 to 0.89, p<0.001), explaining more than 60% of the inter-individual variance of postprandial plasma glucose concentrations. The outcome of the study points to a potential role of the taxa and functional potentials of the intestinal microbiome. If validated in larger studies our findings may be included in future algorithms attempting to develop personalized nutrition, especially for prediction of individual blood glucose excursions in dys-glycaemic individuals.

Project description:BackgroundMycoprotein is a high-fibre food previously shown to reduce postprandial glucose concentrations when ingested within a mixed-meal. We applied a dual stable isotope tracer approach to determine whether this is due to a reduced rate of appearance of glucose, in participants of ranging BMI.MethodsTwenty-four adults (F = 8, BMI 30 ± 6 kg·m-2) attended 2 trials in a double-blind, randomised, cross-over design. Participants ingested two energy and macronutrient matched milk-based drinks (enriched with 1000 mg [U-13C6] glucose in a subset of 12 participants), containing 50 g glucose and either 0 (CON) or 20 g (MYC) mycoprotein. A primed continuous intravenous infusion of D-[6,6-2H2] glucose determined plasma glucose kinetics over 6 h. Postprandial time-course, and AUC, of glucose and insulin concentration, rate of disappearance (RdT) and appearance of exogenous (RaEx), endogenous (EGP), and total (RaT) plasma glucose were assessed using two- and one-way ANOVA.ResultsDrink ingestion increased blood glucose and serum insulin concentrations (P < 0.05) and were comparable between conditions (P > 0.05). Both RaT and RdT were higher with MYC compared with CON over 6 h (mean 6 h glucose appearance and disappearance increased by 5 and 9%, respectively, P < 0.05). RaEx was not affected by MYC ingestion over 6 h (P > 0.05). The mean contribution of EGP to total glucose appearance was 15% greater with MYC, with a trend towards significance (P = 0.05). There was no relationship between BMI and the response to MYC ingestion for any of the variables (P < 0.05).ConclusionThe ingestion of mycoprotein within a mixed-meal impacted postprandial glucose kinetics, but not blood glucose or serum insulin concentrations, in individuals of ranging BMI.Clinical trial registry number and websiteThis trial was registered at clinicaltrials.gov as NCT04084639 and can be accessed at https://clinicaltrials.gov/ct2/show/NCT04084639 .

Dataset Information

The Gut Microbiome and Abiotic Factors as Potential Determinants of Postprandial Glucose Responses: A Single-Arm Meal Study.

Publications

The Gut Microbiome and Abiotic Factors as Potential Determinants of Postprandial Glucose Responses: A Single-Arm Meal Study.

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