Evidence map›Paper›PMID 39473051›Full record

Trial reportGut microbes

Exercise-changed gut mycobiome as a potential contributor to metabolic benefits in diabetes prevention: an integrative multi-omics study.

Yao Wang, Jiarui Chen, Yueqiong Ni, Yan Liu, Xiang Gao, Michael Andrew Tse, Gianni Panagiotou, Aimin Xu

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Gut microbes. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 2 pooled it
–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

11 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Article
  5. Review
  6. Review
  7. Review
  8. Illuminating diabetesWorld journal of diabetes · 2025
    Review
  9. Article
  10. The Gut Mycobiome for Precision Medicine.Journal of fungi (Basel, Switzerland) · 2025
    Review
  11. Review
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

8 authors.

Yao WangState Key Laboratory of Pharmaceutical Biotechnology, The University of Hong Kong, Hong Kong, China.ORCID 0000-0003-0010-2819
Jiarui ChenState Key Laboratory of Pharmaceutical Biotechnology, The University of Hong Kong, Hong Kong, China.ORCID 0000-0002-5533-8434
Yueqiong NiDepartment of Microbiome Dynamics, Leibniz Institute for Natural Product Research and Infection Biology, Hans Knoll Institute, Jena, Germany.ORCID 0000-0003-1285-7354
Yan LiuState Key Laboratory of Pharmaceutical Biotechnology, The University of Hong Kong, Hong Kong, China.ORCID 0000-0001-6358-4056
Xiang GaoState Key Laboratory of Pharmaceutical Biotechnology, The University of Hong Kong, Hong Kong, China.
Michael Andrew TseState Key Laboratory of Pharmaceutical Biotechnology, The University of Hong Kong, Hong Kong, China.
Gianni PanagiotouState Key Laboratory of Pharmaceutical Biotechnology, The University of Hong Kong, Hong Kong, China.ORCID 0000-0001-9393-124X
Aimin XuState Key Laboratory of Pharmaceutical Biotechnology, The University of Hong Kong, Hong Kong, China.ORCID 0000-0002-0668-033X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe importance of gut microbes in mediating the benefits of lifestyle intervention is increasingly recognized. However, compared to the bacterial microbiome, the role of intestinal fungi in exercise remains elusive. With our established randomized controlled trial of exercise intervention in Chinese males with prediabetes (

methodsClinical variations and biological samples were collected before and after training. Fecal fungal composition was analyzed using the internal transcribed spacer 2 (ITS2) sequencing and integrated with paired shotgun metagenomics, untargeted metabolomics, and Olink proteomics.

resultsTwelve weeks of exercise training profoundly promoted fungal ecological diversity and intrakingdom connection. We further identified exercise-responsive genera with potential metabolic benefits, including Verticillium, Sarocladium, and Ceratocystis. Using multi-omics approaches, we elucidated comprehensive associations between changes in gut mycobiome and exercise-shaped metabolic phenotypes, bacterial microbiome, and circulating metabolomics and proteomics profiles. Furthermore, a machine-learning algorithm built using baseline microbial signatures and clinical characteristics predicted exercise responsiveness in improvements of insulin sensitivity, with an area under the receiver operating characteristic (AUROC) of 0.91 (95% CI: 0.85-0.97) in the discovery cohort and of 0.79 (95% CI: 0.74-0.86) in the independent validation cohort (

conclusionsOur findings suggest that intense exercise training significantly remodels the human fungal microbiome composition. Changes in gut fungal composition are associated with the metabolic benefits of exercise, indicating gut mycobiome is a possible molecular transducer of exercise. Moreover, baseline gut fungal signatures predict exercise responsiveness for diabetes prevention, highlighting that targeting the gut mycobiome emerges as a prospective strategy in tailoring personalized training for diabetes prevention.

Indexed as

ExerciseFecesFungiGastrointestinal MicrobiomeMycobiomeAdultBacteriaDiabetes Mellitus, Type 2HumansMaleMetabolomicsMetagenomicsMiddle AgedMultiomicsPrediabetic StateProteomicsdiabetes preventionexercise trainingfungal microbiomeGut mycobiomeintervention responsivenessmulti-omicsrandomized controlled trial

Identifiers

PMID39473051
PMCPMC11533799

What OpenQuestion holds

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LicenceCC BY-NC
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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.