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Int J Obes (Lond). 2017 Jul;41(7):1099-1105. doi: 10.1038/ijo.2017.66. Epub 2017 Mar 13.

Gut microbiome diversity and high-fibre intake are related to lower long-term weight gain.

Author information

1
Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
2
Academic Rheumatology, University of Nottingham, Nottingham, UK.

Abstract

BACKGROUND:

Cross-sectional studies suggest that the microbes in the human gut have a role in obesity by influencing the human body's ability to extract and store calories. The aim of this study was to assess if there is a correlation between change in body weight over time and gut microbiome composition.

METHODS:

We analysed 16S ribosomal RNA gene sequence data derived from the faecal samples of 1632 healthy females from TwinsUK to investigate the association between gut microbiome measured cross-sectionally and longitudinal weight gain (adjusted for caloric intake and baseline body mass index). Dietary fibre intake was investigated as a possible modifier.

RESULTS:

Less than half of the variation in long-term weight change was found to be heritable (h2=0.41 (0.31, 0.47)). Gut microbiota diversity was negatively associated with long-term weight gain, whereas it was positively correlated with fibre intake. Nine bacterial operational taxonomic units (OTUs) were significantly associated with weight gain after adjusting for covariates, family relatedness and multiple testing (false discovery rate <0.05). OTUs associated with lower long-term weight gain included those assigned to Ruminococcaceae (associated in mice with improved energy metabolism) and Lachnospiraceae. A Bacterioides species OTU was associated with increased risk of weight gain but this appears to be driven by its correlation with lower levels of diversity.

CONCLUSIONS:

High gut microbiome diversity, high-fibre intake and OTUs implicated in animal models of improved energy metabolism are all correlated with lower term weight gain in humans independently of calorie intake and other confounders.

PMID:
28286339
PMCID:
PMC5500185
[Available on 2017-09-13]
DOI:
10.1038/ijo.2017.66
[Indexed for MEDLINE]
Free PMC Article

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