Evidence map›Paper›PMID 37016727›Full record

ArticleObesity (Silver Spring, Md.)2023

The gut microbiome and regional fat distribution: Findings from the Baltimore Longitudinal Study of Aging.

Curtis Tilves, Toshiko Tanaka, Moira K Differding, Adam P Spira, Chee W Chia, Luigi Ferrucci, Noel T Mueller

Open access · bronzeAbstract read
In one paragraph

Article in Obesity (Silver Spring, Md.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.2field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 14 citations in OpenAlex.

  1. The Gut Microbiome-Endocrine Axis in Obesity: Mechanisms and Therapeutics.Journal of gastroenterology and hepatology · 2026
    Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 1 country.

Curtis TilvesDepartment of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA.ORCID 0000-0003-0281-5986
Toshiko TanakaIntramural Research Program, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA.
Moira K DifferdingDepartment of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA.
Adam P SpiraDepartment of Mental Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA.
Chee W ChiaIntramural Research Program, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA.
Luigi FerrucciIntramural Research Program, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA.
Noel T MuellerDepartment of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA.
Johns Hopkins University · USNational Institutes of Health · US

Funding

The Baltimore Longitudinal Study Of AgingZIAAG000015 · NIA · NATIONAL INSTITUTE ON AGING · PI SIMONSICK, ELEANOR MARIE · 2009 to 2025
$116.9M
CARDIOVASCULAR EPIDEMIOLOGY INSTITUTIONAL TRAININGT32HL007024 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI Elizabeth Selvin · 1985 to 2026
$17.5M
Microbiome Projects in the Baltimore Longitudinal Study of AgingZIAAG000997 · NIA · NATIONAL INSTITUTE ON AGING · PI FERRUCCI, LUIGI · 2015 to 2025
$3.8M
Poor Sleep Altered Circadian Rhythms and Alzheimers DiseaseR01AG050507 · NIA · JOHNS HOPKINS UNIVERSITY · PI SPIRA, ADAM PETER · 2015 to 2019
$2.5M
The Effects of Diet on the Gut Microbiome and Short Chain Fatty AcidsK01HL141589 · NHLBI · UNIVERSITY OF COLORADO DENVER · PI MUELLER, NOEL T · 2018 to 2022
$845k
NHLBI NIH HHS K01 HL141589NHLBI NIH HHS T32 HL007024NIA NIH HHS R01 AG050507
6 · The paper itself

Abstract

objectiveThe 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.

methodsA 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.

resultsTrunk 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.

conclusionsMicrobiome 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.

Indexed as

Gastrointestinal MicrobiomeAbsorptiometry, PhotonAgingBaltimoreBody Mass IndexCross-Sectional StudiesEubacterialesFemaleHumansLongitudinal StudiesMale

Identifiers

PMID37016727
PMCPMC10191998
OpenAlexW4362602048

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.