Evidence map›Paper›PMID 41056270›Full record

ArticlePloS one2025

Relationship between Gut microbiome and brain volumes among Japanese Men.

Sabrina Ahmed, Zhang Hexun, Yuichiro Yano, Yukiko Okami, Nazar Mohd Azahar, Keiko Kondo, Hisatomi Arima, Sayuki Torii, Mohammad Moniruzzaman, Gantsetseg Ganbaatar and 6 more

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. 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

16 authors.

Sabrina AhmedNCD Epidemiology Research Center (NERC), Shiga University of Medical Science, Otsu, Shiga, Japan.ORCID https://orcid.org/0000-0001-6256-1389
Zhang HexunDepartment of Surgery, Shiga University of Medical Science, Otsu, Shiga, Japan.
Yuichiro YanoNCD Epidemiology Research Center (NERC), Shiga University of Medical Science, Otsu, Shiga, Japan.
Yukiko OkamiNCD Epidemiology Research Center (NERC), Shiga University of Medical Science, Otsu, Shiga, Japan.
Nazar Mohd AzaharNCD Epidemiology Research Center (NERC), Shiga University of Medical Science, Otsu, Shiga, Japan.ORCID https://orcid.org/0000-0002-0412-4268
Keiko KondoNCD Epidemiology Research Center (NERC), Shiga University of Medical Science, Otsu, Shiga, Japan.
Hisatomi ArimaDepartment of Public Health and Preventive Medicine, Faculty of Medicine, Fukuoka University, Fukuoka, Japan.
Sayuki ToriiNCD Epidemiology Research Center (NERC), Shiga University of Medical Science, Otsu, Shiga, Japan.
Mohammad MoniruzzamanNCD Epidemiology Research Center (NERC), Shiga University of Medical Science, Otsu, Shiga, Japan.
Gantsetseg GanbaatarNCD Epidemiology Research Center (NERC), Shiga University of Medical Science, Otsu, Shiga, Japan.
Aya KadotaNCD Epidemiology Research Center (NERC), Shiga University of Medical Science, Otsu, Shiga, Japan.
Akira AndohDepartment of Internal Medicine, Shiga University of Medical Science, Otsu, Shiga, Japan.
Akihiko ShiinoMolecular Neuroscience Research Center, Shiga University of Medical Science, Otsu, Shiga, Japan.
Hirotsugu UeshimaNCD Epidemiology Research Center (NERC), Shiga University of Medical Science, Otsu, Shiga, Japan.
Katsuyuki MiuraNCD Epidemiology Research Center (NERC), Shiga University of Medical Science, Otsu, Shiga, Japan.
SESSA Research Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Evidence of preclinical interactions between the gut microbiome and brain health is accumulating. Studies of animal models and specific patient populations have suggested a relationship between gut microbiomes and brain volumes, but this association is understudied in apparently healthy humans. We conducted a population-based cross-sectional study of 623 Japanese men from the Shiga Epidemiological Study on Subclinical Atherosclerosis (SESSA). We performed 16S ribosomal RNA gene sequencing of stool samples collected during the follow-up stage (mean [SD] age, 68.0 [8.0] years; range, 46-83 years). All participants underwent brain magnetic resonance imaging and automated voxel-based morphometry. Principal coordinate analysis, linear discriminant, and multivariable linear regression analyses were performed. In multivariable linear regression analysis, after adjusting for age and total intracranial volume, only gray matter volume showed a positive association with alpha diversity (the Shannon index richness, q-value <0.01). However, no association was found after further adjustments for body mass index, physical activity, smoking, drinking, and hypertension. The weighted UniFrac distances (beta diversity) measured using principal coordinate analysis showed that lower and higher white and gray matter volumes formed distinct clusters (q < 0.01). In linear discriminant analysis and multivariable-adjusted linear regression analysis, several genera were significantly associated with gray and white matter volumes (q < 0.01); however, Lachnospiraceae, a butyrate-producing bacterium, was consistently related to a higher white matter volume in different statistical analysis models. Egarthellaceae, Bifidobacteraceae, and Selenomonadaceae showed a positive association with greater gray matter volume. Our findings support an association between gut microbiome diversity and brain volumes in middle-aged to older Japanese men. This study provides insight into the underlying effects of the gut microbiome on human brain volume.

Indexed as

BrainGastrointestinal MicrobiomeAgedAged, 80 and overCross-Sectional StudiesEast Asian PeopleGray MatterHumansJapanMagnetic Resonance ImagingMaleMiddle AgedOrgan SizeRNA, Ribosomal, 16SRNA, Ribosomal, 16S

Identifiers

PMID41056270
PMCPMC12503305

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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.