Influence of Gut Microbial Communities on Fasting and Postprandial Lipids and Circulating Metabolites: The PREDICT 1 Study. (29th May 2020)

• Record Type: Journal Article
• Authors: Berry, Sarah; Ordovas, Jose; Asnicar, Francesco; Valdes, Ana; Franks, Paul; Wolf, Jonathan; Hadjigeorgiou, George; Drew, David; Roy, Caroline Le; Leeming, Emily; Nguyen, Long; Chan, Andrew; Spector, Tim; Segata, Nicola
• Is Part Of: Current developments in nutrition. Volume 4(2020)Supplement 2
• Page Start: 1547
• Page End: 1547
• Publication Date: 2020-05-29
• Subjects: Nutrition -- Periodicals; Nutritional Physiological Phenomena; Nutrition; Periodicals; Periodicals; Fulltext; Internet Resources; Periodicals; 612.3
• DOI: 10.1093/cdn/nzaa062_004
• Languages: English
• ISSNs: 2475-2991

Abstract

Abstract: Objectives: The human gut microbiome plays a critical role in host glucose metabolism, but its connections to other key markers of cardiometabolic health in fasting and postprandial conditions is largely unknown. The PREDICT 1 study enrolled n = 1, 102 twins and unrelated healthy US/UK adults to explore the genetic, metabolic, microbial, and meal determinants of fasting metabolites and postprandial responses to foods. Methods: This multi-centre dietary study assessed fasting and postprandial (0-6h) circulating metabolites over a 13d study period incorporating standardized test meals of varying nutrient composition. Shotgun metagenomics was performed from samples collected at baseline (n = 1, 001 UK and 97 US). Metabolomics (NMR) was performed on clinic fasting and postprandial samples, blood glucose was continuously assessed, and blood triglycerides and C-peptide were serially measured. Results: Using machine learning models, we found the fasting metabolites most strongly associated with overall gut community structure were the inflammatory marker GlycA (r = 0.31), and HDL and VLDL particle diameter (HDL-D and VLDL-D; r = 0.3 and 0.28 respectively). Variance explained was slightly greater for postprandial HDL-D and VLDL-D (at 6h; r = 0.32 and 0.31, respectively) than fasting levels, whilst the other metabolites did not differ (e.g., GlycA r = 0.28). Lipid-mediated metabolites were more closely associated with the gut microbiome in both fasting and postprandial states compared with glycemic-mediated measurements. There were distinct microbial clusters that segregated both fasting and postprandial metabolites according to their known association with cardiometabolic disease; ApoA and HDL vs. ApoB, VLDL, IDL LDL, remnant C, GlycA, IL-6, blood pressure, glucose, insulin and HbA1c. We also identified differential abundance among several microbes associated with metabolic health, including Prevotella copri and Faecalibacterium prausnitzii . Results obtained in the UK cohort were validated in the US cohort. Conclusions: An individual's gut microbial composition is predictive of their cardiometabolic markers and personalized responses to food. Our data highlight the potential of the gut microbiome as a target amenable to modulation in personalized nutrition to ameliorate cardiometabolic risk. Funding Sources: Zoe Global Ltd., NIHR GSTT BRC, Wellcome Trust.