The intestinal microbiome is a co-determinant of the postprandial plasma glucose response

• DOI: 10.1371/journal.pone.0238648
• Publication Date: 2020-09-18T22:05:35Z
• Authors: Nadja B. Søndertoft; Josef K. Vogt; Manimozhiyan Arum...; Mette Kristensen; Rikke J. Gøbel; Yong Fan; Liwei Lyu; Martin I. Bahl; Carsten Eriksen; Lars Ängquist; Hanne Frøkiær; Tue H. Hansen; Susanne Brix; H. Bjørn Nielsen; Torben Hansen; Henrik Vestergaard; Ramneek Gupta; Tine R. Licht; Lotte Lauritzen; Oluf Pedersen
• Keywords: Blood Glucose; Male; 2. Zero hunger; 0301 basic medicine; Science; Q; R; Fasting; Middle Aged; Postprandial Period; Models, Biological; Gastrointestinal Microbiome; 3. Good health; 03 medical and health sciences; Medicine; Humans; Female; /dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_being; name=SDG 3 - Good Health and Well-being; Phenomics; Life Style; Algorithms; Research Article

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