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.
Nutrients. 2023 Oct 15;15(20):4369. doi: 10.3390/nu15204369.
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.
近年来,全球 2 型糖尿病(T2DM)的患病率呈上升趋势,识别不同的血糖应答者可以帮助针对糖尿病前期和 T2DM 进行个体化治疗。基于常规食物的混合餐耐量试验(MMTT)有可能揭示餐后动态事件中的不同应答者。我们旨在根据高 T2DM 风险参与者的多次 MMTT 的餐后动态血糖数据拟合一个简单的数学模型,以识别应答簇,并研究其与 T2DM 风险因素和肠道微生物群的关系。该数据来自一项为期 12 周的多中心饮食干预试验,涉及高风险 T2DM 成年人,在地中海饮食背景下(MEDGICarb)比较高血糖指数与低血糖指数的食物。对 155 名参与者(81 名女性和 74 名男性)的 MMTT 进行基于模型的分析显示,存在两个不同的血浆葡萄糖应答簇,与基线肠道微生物群相关。与 HbA1c 和腰围呈负相关,与胰岛素敏感性呈正相关的簇 A,与簇 B 的特征相反。这些发现表明,使用常规食物的标准化早餐 MMTT 可以使用简单的机制模型有效地区分不同 T2DM 风险水平的非糖尿病个体。