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The gut microbiome and regional fat distribution: Findings from the Baltimore Longitudinal Study of Aging.
Obesity 2023 April 5
OBJECTIVE: The aim of this study was to examine associations of gut microbiome diversity and composition with directly measured regional fat distribution, including central fat, in a large community-based cohort.
METHODS: A cross-sectional investigation was conducted in the Baltimore Longitudinal Study of Aging (N = 815, 55.2% female, 65.9% White). The fecal microbiome was assessed using whole-genome shotgun metagenomic sequencing, and trunk and leg fat was measured using dual x-ray absorptiometry. Multivariable-adjusted associations of regional fat measures, BMI, or waist circumference with microbiome alpha diversity metrics, microbiome beta diversity metrics, and species differential abundance (verified using two compositional statistical approaches) were examined.
RESULTS: Trunk fat, leg fat, BMI, and waist circumference all significantly explained similar amounts of variance in microbiome structure. Differential abundance testing identified 11 bacterial species significantly associated with at least one measure of body composition or anthropometry. Ruminococcus gnavus was strongly and consistently associated with trunk fat mass, which is congruent with prior literature.
CONCLUSIONS: Microbiome diversity and composition, in particular higher abundance of Ruminococcus gnavus, were associated with greater trunk fat, in addition to other measures of obesity. Longitudinal studies are needed to replicate these findings, and if replicated, randomized trials are needed to determine whether interventions targeting microbiome features such as abundance of Ruminococcus gnavus can lead to reductions in trunk fat and its metabolic sequelae.
METHODS: A cross-sectional investigation was conducted in the Baltimore Longitudinal Study of Aging (N = 815, 55.2% female, 65.9% White). The fecal microbiome was assessed using whole-genome shotgun metagenomic sequencing, and trunk and leg fat was measured using dual x-ray absorptiometry. Multivariable-adjusted associations of regional fat measures, BMI, or waist circumference with microbiome alpha diversity metrics, microbiome beta diversity metrics, and species differential abundance (verified using two compositional statistical approaches) were examined.
RESULTS: Trunk fat, leg fat, BMI, and waist circumference all significantly explained similar amounts of variance in microbiome structure. Differential abundance testing identified 11 bacterial species significantly associated with at least one measure of body composition or anthropometry. Ruminococcus gnavus was strongly and consistently associated with trunk fat mass, which is congruent with prior literature.
CONCLUSIONS: Microbiome diversity and composition, in particular higher abundance of Ruminococcus gnavus, were associated with greater trunk fat, in addition to other measures of obesity. Longitudinal studies are needed to replicate these findings, and if replicated, randomized trials are needed to determine whether interventions targeting microbiome features such as abundance of Ruminococcus gnavus can lead to reductions in trunk fat and its metabolic sequelae.
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