Differential Responders to a Mixed Meal Tolerance Test Associated with Type 2 Diabetes Risk Factors and Gut Microbiota-Data from the MEDGI-Carb Randomized Controlled Trial.

Viktor Skantze, Therese Hjorth, Mikael Wallman, Carl Brunius, Johan Dicksved, Erik A Pelve, Anders Esberg, Marilena Vitale, Rosalba Giacco, Giuseppina Costabile, Robert E Bergia, Mats Jirstrand, Wayne W Campbell, Gabriele Riccardi, Rikard Landberg

Journal: Nutrients 2023;15(20):4369

PMID: 37892445

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Plain Language Summary

Type 2 diabetes (T2D) is a growing worldwide health problem. Increased blood sugars and a corresponding increase in the production of the hormone insulin, which functions to lower blood sugar are risk factors for T2D development. However, it has been shown that everyone has an individual response to the food and the production of differing levels of blood sugar and insulin when eating the same meals has been shown. This secondary analysis of a 12-week randomised control trial of 155 individuals aimed to determine relationships between gut microbiota composition and the glucose response to high and low glycaemic index Mediterranean diets. The results identified two distinct types of response amongst the participants. Cluster A individuals had a lower but more rapid glucose response following food and were deemed to have a better glucose control than cluster B individuals. The clusters also differed in the gut microbiota composition. Cluster A had a higher proportion of Clostridium sensu stricto 1 and a lower proportion of Blautia, than cluster B. It was concluded that the glucose response to a standardised meal can differ between individuals and are associated with differing gut microbiota and risk for T2D. This study could be used by healthcare professionals to understand that diet recommendations are not one size fits all and that the recommendation of certain diets may have differing success. Understanding and differentiating individuals and tailor making recommendations may be of benefit, however further understanding is required on different glucose responses following a meal.

Abstract

The global prevalence of type 2 diabetes mellitus (T2DM) has surged in recent decades, and the identification of differential glycemic responders can aid tailored treatment for the prevention of prediabetes and T2DM. A mixed meal tolerance test (MMTT) based on regular foods offers the potential to uncover differential responders in dynamical postprandial events. We aimed to fit a simple mathematical model on dynamic postprandial glucose data from repeated MMTTs among participants with elevated T2DM risk to identify response clusters and investigate their association with T2DM risk factors and gut microbiota. Data were used from a 12-week multi-center dietary intervention trial involving high-risk T2DM adults, comparing high- versus low-glycemic index foods within a Mediterranean diet context (MEDGICarb). Model-based analysis of MMTTs from 155 participants (81 females and 74 males) revealed two distinct plasma glucose response clusters that were associated with baseline gut microbiota. Cluster A, inversely associated with HbA1c and waist circumference and directly with insulin sensitivity, exhibited a contrasting profile to cluster B. Findings imply that a standardized breakfast MMTT using regular foods could effectively distinguish non-diabetic individuals at varying risk levels for T2DM using a simple mechanistic model.

Address: Fraunhofer-Chalmers Research Centre for Industrial Mathematics, 412 88 Gothenburg, Sweden.; Department of Life Sciences, Food and Nutrition Science, Chalmers University of Technology, 412 96 Gothenburg, Sweden.; Department of Life Sciences, Food and Nutrition Science, Chalmers University of Technology, 412 96 Gothenburg, Sweden.; Fraunhofer-Chalmers Research Centre for Industrial Mathematics, 412 88 Gothenburg, Sweden.; Department of Anatomy, Physiology and Biochemistry, Swedish University of Agricultural Sciences, 750 07 Uppsala, Sweden.; Department of Animal Nutrition and Management, Swedish University of Agricultural Sciences, 750 07 Uppsala, Sweden.; Department of Odontology, Umeå University, 901 87 Umeå, Sweden.; Diabetes, Nutrition and Metabolism Unit, Department of Clinical Medicine and Surgery, Federico II University, 80138 Naples, Italy.; Diabetes, Nutrition and Metabolism Unit, Department of Clinical Medicine and Surgery, Federico II University, 80138 Naples, Italy.; Institute of Food Sciences, National Research Council, 83100 Avellino, Italy.; Department of Nutrition Science, Purdue University, West Lafayette, IN 47907, USA.

DOI: 10.3390/nu15204369