Diet-Associated Variability in the Elderly Gut Microbiome. (14th June 2022)

• Record Type: Journal Article
• Authors: Low, Dorrain; Tee, Kai Xuan; Meldrum, Oliver; D'Agostino, Giuseppe; Kim, Hye Jin; Kang, Alicia; Purbojati, Rikky; Chandrasekaran, Lakshmi; Drautz-Moses, Daniela; Yang, Yifan; Cheon, Bobby; Elizabeth, Aimee; Fong, Lai Guan; Wang, Yulan; Padmanabhan, Parasuraman; Schuster, Stephan; Pettersson, Sven; Chambers, John; Gulyas, Balazs
• Is Part Of: Current developments in nutrition. Volume 6(2022)Supplement 1
• Page Start: 1020
• Page End: 1020
• Publication Date: 2022-06-14
• Subjects: Nutrition -- Periodicals; Nutritional Physiological Phenomena; Nutrition; Periodicals; Periodicals; Fulltext; Internet Resources; Periodicals; 612.3
• DOI: 10.1093/cdn/nzac069.025
• Languages: English
• ISSNs: 2475-2991

Abstract

Abstract: Objectives: The gut microbiome adapts to diet variations, which contribute to interindividual variability in human host metabolism and environmental factors. Microbe-diet studies have largely focused on specific diets (e.g., high-fat Western, Mediterranean-style) in American and European populations, with limited studies on compositionally-different diets in Asian populations. This study aimed to understand how diet composition modulates the gut microbiome in a Singapore multi-ethnic population. Methods: We performed metagenomic sequencing of faecal samples from 118 healthy individuals (66 ± 5 years old), and estimated their food and nutrient intakes from 3-day food records (IRB-2018–01-011). Multivariate associations between microbial composition (species) and functional potentials (pathways, enzymes) with diet variables were analysed using linear mixed models with Benjamin-Hochberg correction, and adjusted for age, sex, BMI, physical activity, energy intake and medications. Permutational multivariate analysis of variance, based on Bray-Curtis dissimilarity metric, was applied to quantify variance within the microbiome that is explained by diet variables. Results: We found gut microbes (5 phyla, >100 species) significantly associated with one of four observed dietary patterns ( P < 0.05), various food groups and nutrients (q < 0.1). The microbiome was driven by intake and diversity of plant-based foods. Parabacteroides and Blautia species, and microbial metabolism of energy, carbohydrate and glycan were associated with increased intakes of white rice and noodles. Prevotella species were associated with increased intakes of legumes, wholegrains and plant protein. Lachnospira, Clostridiumand Fournierella species, and microbial lipid metabolism were associated with energy-dense diet. Lastly, Firmicutes, Eubacterium, Ruminococcus and Roseburia species as well as microbial regulation of amino acid metabolism were associated with high-fibre diet. Conclusions: This study provides new insights into gut microbial variations by distinct Asian dietary composition, supporting the feasibility of intervening habitual diets to reshape the gut microbiome for better health. Funding Sources: This project was funded by LKC, CONIC and ARISE, NTU, and NTU-CSIRO Precision Health and Technologies Seed Fund.