Evidence map›Paper›PMID 34016052›Full record

ArticleBMC microbiology2021

Comprehensive analysis of gut microbiota of a healthy population and covariates affecting microbial variation in two large Japanese cohorts.

Jonguk Park, Kumiko Kato, Haruka Murakami, Koji Hosomi, Kumpei Tanisawa, Takashi Nakagata, Harumi Ohno, Kana Konishi, Hitoshi Kawashima, Yi-An Chen and 6 more

Abstract read
In one paragraph

Article in BMC microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.

0numbers the graph read from it
0cells of the map it votes in
49citing 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

49 citing papers in PubMed.

  1. Trial
  2. Low Prevalence and Abundance ofMicroorganisms · 2026
    Article
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  8. Review
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  17. Anti-obesity peptides from food: Production, evaluation, sources, and commercialization.Comprehensive reviews in food science and food safety · 2025
    Review
  18. Review
  19. Article
  20. 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.

Jonguk Park *Laboratory of Bioinformatics, Artificial Intelligence Center for Health and Biomedical Research, National Institutes of Biomedical Innovation, Health and Nutrition, Osaka, 567-0085, Japan.
Kumiko Kato *Morinaga Milk Industry Co., Ltd., Next Generation Science Institute, Kanagawa, 252-8583, Japan.
Haruka MurakamiDepartment of Physical Activity Research, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, 162-8636, Japan.
Koji HosomiLaboratory of Vaccine Materials, Center for Vaccine and Adjuvant Research and Laboratory of Gut Environmental System, National Institutes of Biomedical Innovation, Health and Nutrition, Osaka, 567-0085, Japan.
Kumpei TanisawaDepartment of Physical Activity Research, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, 162-8636, Japan.
Takashi NakagataDepartment of Physical Activity Research, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, 162-8636, Japan.
Harumi OhnoDepartment of Physical Activity Research, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, 162-8636, Japan.
Kana KonishiDepartment of Physical Activity Research, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, 162-8636, Japan.
Hitoshi KawashimaLaboratory of Bioinformatics, Artificial Intelligence Center for Health and Biomedical Research, National Institutes of Biomedical Innovation, Health and Nutrition, Osaka, 567-0085, Japan.
Yi-An ChenLaboratory of Bioinformatics, Artificial Intelligence Center for Health and Biomedical Research, National Institutes of Biomedical Innovation, Health and Nutrition, Osaka, 567-0085, Japan.
Attayeb MohsenLaboratory of Bioinformatics, Artificial Intelligence Center for Health and Biomedical Research, National Institutes of Biomedical Innovation, Health and Nutrition, Osaka, 567-0085, Japan.
Jin-Zhong XiaoMorinaga Milk Industry Co., Ltd., Next Generation Science Institute, Kanagawa, 252-8583, Japan.
Toshitaka OdamakiMorinaga Milk Industry Co., Ltd., Next Generation Science Institute, Kanagawa, 252-8583, Japan. t-odamak@morinagamilk.co.jp.
Jun KunisawaLaboratory of Vaccine Materials, Center for Vaccine and Adjuvant Research and Laboratory of Gut Environmental System, National Institutes of Biomedical Innovation, Health and Nutrition, Osaka, 567-0085, Japan. kunisawa@nibiohn.go.jp.
Kenji MizuguchiLaboratory of Bioinformatics, Artificial Intelligence Center for Health and Biomedical Research, National Institutes of Biomedical Innovation, Health and Nutrition, Osaka, 567-0085, Japan. kenji@nibiohn.go.jp.
Motohiko MiyachiDepartment of Physical Activity Research, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, 162-8636, Japan. miyachi@nibiohn.go.jp.ORCID 0000-0002-1146-0905

Funding

Grant-in-Aid for Scientific Research (C) 6K00944Health and Labour Sciences Research Grant 201709002Bthe Japan Agency for Medical Research and Development JP20gm1010006h004the Japan Society for the Promotion of Science KAKENHI JP18H05280
6 · The paper itself

Abstract

backgroundInter-individual variations in gut microbiota composition are observed even among healthy populations. The gut microbiota may exhibit a unique composition depending on the country of origin and race of individuals. To comprehensively understand the link between healthy gut microbiota and host state, it is beneficial to conduct large-scale cohort studies. The aim of the present study was to elucidate the integrated and non-redundant factors associated with gut microbiota composition within the Japanese population by 16S rRNA sequencing of fecal samples and questionnaire-based covariate analysis.

resultsA total of 1596 healthy Japanese individuals participated in this study via two independent cohorts, NIBIOHN cohort (n = 954) and MORINAGA cohort (n = 642). Gut microbiota composition was described and the interaction of these microorganisms with metadata parameters such as anthropometric measurements, bowel habits, medical history, and lifestyle were obtained. Thirteen genera, including Alistipes, Anaerostipes, Bacteroides, Bifidobacterium, Blautia, Eubacterium halli group, Faecalibacterium, Fusicatenibacter, Lachnoclostridium, Parabacteroides, Prevotella_9, Roseburia, and Subdoligranulum were predominant among the two cohorts. On the basis of univariate analysis for overall microbiome variation, 18 matching variables exhibited significant association in both cohorts. A stepwise redundancy analysis revealed that there were four common covariates, Bristol Stool Scale (BSS) scores, gender, age, and defecation frequency, displaying non-redundant association with gut microbial variance.

conclusionsWe conducted a comprehensive analysis of gut microbiota in healthy Japanese individuals, based on two independent cohorts, and obtained reliable evidence that questionnaire-based covariates such as frequency of bowel movement and specific dietary habit affects the microbial composition of the gut. To our knowledge, this was the first study to investigate integrated and non-redundant factors associated with gut microbiota among Japanese populations.

Indexed as

Gastrointestinal MicrobiomeAdultAgedAged, 80 and overBacteriaCohort StudiesDefecationDNA, BacterialFecesFeeding BehaviorFemaleHealthy VolunteersHumansJapanMaleMiddle AgedDNA, BacterialRNA, Ribosomal, 16S16S rRNACovariatesGut microbiotaJapanese populationLarge cohort

Identifiers

PMID34016052
PMCPMC8139087

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Registered trials

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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.