Combining a diet rich in fermentable carbohydrates with metformin improves glycaemic control and reshapes the gut microbiota in people with prediabetes
Chu et al.
The finding, in our words
In adults with prediabetes, a moderate FODMAP diet combined with metformin lowered postprandial glycaemia measured by continuous glucose monitoring, increased GLP-1, and altered gut microbiota compared with a low FODMAP diet plus metformin; higher baseline Dorea formicigenerans predicted gastrointestinal intolerance to metformin. These results support personalising nutrition and metformin to improve tolerability and glycaemic outcomes in decentralised diabetes prevention.
A paraphrase to the Library’s standard, never the abstract. The source is one link away and is always the authority.
In adults with prediabetes and obesity, gut microbiome diversity correlated with body composition but not with continuous glucose monitoring-derived glycaemic variability. Dietary composition showed the strongest microbiome associations, suggesting that microbiome-informed nutrition strategies may be more relevant than glycaemic-driven approaches in this population.
Continuous glucose monitoring of 55 participants showed considerable interindividual variation in postprandial glycaemic responses to carbohydrate meals, with rice producing the highest overall responses. Potato-spikers were more insulin resistant with lower beta cell function, grape-spikers were more insulin sensitive, and mitigators were less effective in insulin-resistant individuals. Multi-omics profiling revealed signatures linking glycaemic responses to triglycerides, metabolites and microbiome pathways.
The Human Phenotype Project enrolled 28,000 participants in a deep-phenotyping cohort that combines blood and microbiome sampling with continuous glucose and sleep monitoring. An AI model trained on dietary and glucose data predicted disease onset more accurately than existing methods, showing how integrating continuous digital signals with multi-omic data can support personalised risk assessment for decentralised diagnostics.
Reicher et al., Nature medicine (paywalled) · source ↗
In n-of-1 dietary trials, a personal gut microbial carb-sensitivity score derived from stool metagenomics correlated with glycaemic phenotypes during high-carbohydrate but not low-carbohydrate intake, and this association was validated in an independent cohort, supporting precision nutrition approaches that integrate stool microbiome signatures with continuous glucose monitoring for individualised dietary advice.
In pregnant women with diet-treated gestational diabetes and healthy controls, incorporating gut microbiome features alongside continuous glucose monitoring, diet, and clinical variables improved the prediction of postprandial glycaemic responses over carbohydrate counting alone, though the incremental contribution of the microbiota was modest.
Popova et al., NPJ biofilms and microbiomes · source ↗