Cited by 237Gut microbiota and healthOral microbiology and periodontitis researchAdipokines, Inflammation, and Metabolic Diseases

The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index; none of the 59 sources its claims cite is checked for support yet.

Six-Week Endurance Exercise Alters Gut Metagenome That Is not Reflected in Systemic Metabolism in Over-weight Women

Open access

Abstract

Previously sedentary overweight women (n=19) underwent a six-week endurance exercise intervention, but two were excluded due to antibiotic therapy. The gut microbiota composition and functions were analyzed by 16S rRNA gene amplicon sequencing and metagenomics. Body composition was analyzed with DXA X-ray densitometer and serum metabolomics with NMR metabolomics. Total energy and energy-yielding nutrient intakes were analyzed from food records using Micro-Nutrica software. Serum clinical variables were determined with KONELAB instrument. Soluble Vascular Adhesion Protein 1 (VAP-1) was measured with ELISA and its’ enzymatic activity as produced hydrogen peroxide. The exercise intervention was effective, as maximal power and maximum rate of oxygen consumption increased while android fat mass decreased. No changes in diet were observed. Metagenomic analysis revealed taxonomic shifts including an increase in Akkermansia and a decrease in Proteobacteria. These changes were independent of age, weight, fat % as well as energy and fibre intake. Training slightly increased Jaccard distance of genus level β-diversity. Training did not alter the enriched metagenomic pathways, which, according to Bray Curtis dissimilarity analysis, may have been due to that only half of the subjects’ microbiomes responded considerably to exercise. Nevertheless, training decreased the abundance of several genes including those related to fructose and amino acid metabolism. These metagenomic changes, however, were not translated into major systemic metabolic changes as only two metabolites, phospholipids and cholesterol in large VLDL particles, decreased after exercise. Training also decreased the amine oxidase activity of pro-inflammatory VAP-1, whereas no changes in CRP were detected. All clinical blood variables were within normal range, yet exercise slightly increased glucose and decreased LDL and HDL. In conclusion, exercise training modified the gut microbiome without greatly affecting systemic metabolites or body composition. Based on our data and existing literature, we propose that especially Akkermansia and Proteobacteria are exercise-responsive taxa. Our results warrant the need for further studies in larger cohorts to determine whether exercise types other than endurance exercise also modify the gut metagenome.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

Six weeks of supervised endurance exercise in previously sedentary overweight women improved fitness and modestly shifted gut metagenome composition, including increased *Akkermansia* and decreased Proteobacteria, without major changes in systemic metabolism or body composition. The authors propose *Akkermansia* and Proteobacteria as exercise-responsive taxa but call for larger/longer trials.

Key findings

  • Exercise was effective: VO2max increased from 29.8 ± 5.2 to 32.5 ± 5.4 ml·min⁻¹·kg⁻¹ and maximal power from 182.9 ± 36.0 to 202.6 ± 36.4 W (both p < 0.001); submaximal blood lactate decreased from 3.0 ± 0.8 to 2.3 ± 0.7 mmol·L⁻¹ (p < 0.001). Android fat mass decreased from 3.87 ± 1.42 to 3.75 ± 1.39 kg (p = 0.005), with no significant weight, BMI, total fat, or diet changes except a slight increase in starch energy percentage (20.7 ± 6.3 to 22.8 ± 3.4, p = 0.033).
  • Metagenomic analysis showed increased genus-level Jaccard β-diversity (0.449 to 0.465, p = 0.014), increased Verrucomicrobia (p = 0.038), Verrucomicrobiaceae (p = 0.038), Bifidobacteriaceae (p = 0.015), *Akkermansia* (p = 0.038), *Dorea* (p = 0.028), and *Anaerofilum* (p = 0.037), and decreased Proteobacteria (p = 0.039), unidentified Porphyromonadaceae (p = 0.016), *Odoribacter* (p = 0.033), unidentified Desulfovibrionaceae (p = 0.037), and unidentified Enterobacteriaceae (p = 0.036). Only Proteobacteria, Verrucomicrobia, Verrucomicrobiaceae, and *Akkermansia* changed independently of age, weight, fat %, android fat %, energy, sucrose, or fiber intake.
  • No major KEGG pathway enrichment changes were detected; several individual genes decreased, including those related to fructose/mannose metabolism, amino acid metabolism, and B-vitamin synthesis. Systemic metabolomics showed only decreased phospholipids and cholesterol in large VLDL particles (p < 0.05 for both). VAP-1 enzymatic activity decreased (p = 0.011) without change in VAP-1 protein or CRP, and TLR5 mRNA increased (p = 0.029).

Methods

  • Design: six-week supervised endurance cycling intervention in previously sedentary overweight women (BMI >27.5 kg/m²), with a preceding six-week non-training control period; subjects served as their own controls. Three sessions/week progressed from 40 to 60 min, with low-intensity and moderate-intensity interval cycling.
  • Sample: 19 women underwent the intervention; 2 were excluded from final analyses due to antibiotic therapy, leaving n = 17 for physical performance, body composition, and clinical variables; n = 15 for metagenome analyses after 2 additional samples clustered differently; n = 14 completed food diaries at all time points.
  • Measurements/analysis: 16S rRNA gene V4 amplicon sequencing and shotgun metagenomics; DXA for body composition; NMR metabolomics; KONELAB clinical assays; VAP-1 ELISA and amine oxidase activity; whole-blood TLR4/TLR5 qPCR. Statistics included repeated-measures ANOVA with Bonferroni post-hoc, Wilcoxon signed-rank tests with Benjamini-Hochberg correction, QIIME, Microbiome Analyst, Spearman correlations, and general linear models.

Limitations

  • Stated: the cohort was small and the authors state that larger and longer exercise trials are needed; only approximately half of subjects’ microbiomes responded considerably to exercise, and inter-individual variation was large; food records are prone to under-reporting and social-desirability/social-approval bias; the mechanism by which exercise regulates VAP-1 activity without changing protein concentration could not be determined.
  • Evident from the text: the study included only overweight women and only endurance exercise, so findings may not generalize to men, other BMI groups, or other exercise types; metagenome analyses were reduced to n = 15, and diet analyses to n = 14, further limiting power; the absence of major systemic metabolic changes may partly reflect heterogeneous individual responses rather than true lack of effect.

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Integrity signals

Registry

Crossref · 10.3389/fmicb.2018.02323

Cites

55 of 55 references verified0 citation errors · 0 not checkable

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Claims the paper makes

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Show all 116 claims

  • Probably not a substantial claim. 67
  • It may state two separate claims as one. 22
80 of 80
  • The paper relies on this without support.

    Dietary composition affects the gut microbiota.

    “As dietary composition affects the gut microbiota, the total daily energy and the intake of energy-yielding nutrients, were analyzed from the 3-days food records.”
  • The paper relies on this without support.

    Starch is broken down into glucose moieties.

    “as starch is broken down into glucose moieties”
  • The paper relies on this without support.

    Fructose absorption mainly occurs in the small intestine.

    “that mainly occurs in the small intestine”
  • The paper relies on this without support.

    No studies in humans have reported associations between Proteobacteria and exercise or physical fitness that would support the responsiveness of this taxon to exercise training.

    “However, to our knowledge, no studies in humans have reported associations between Proteobacteria and exercise or physical fitness that would support the responsiveness of this taxon to exercise training.”
4 of 4

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Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Post-exercise weight differs between text and table

    Minor

    The prose gives a post-exercise mean weight of 89.1 ± 15.2 kg, but Table 2 gives 89.3 ± 15.6 kg for the same time point.

  • Age exception for adjusted taxonomic changes is reversed

    Minor

    The text says these changes depend on all listed variables except age. Yet Bifidobacteriaceae loses significance after age adjustment (0.015 to 0.198); the table also reports significant age-adjusted p-values for the two unidentified taxa (0.038 and 0.027).

  • Phylum-level changes are both denied and reported

    Minor

    The results say there were no differences in phylum-level abundances, then report significant decreases in Proteobacteria and increases in Verrucomicrobia, both at the phylum level.

  • No-change-in-diet statement overlooks starch energy percentage

    Minor

    The abstract states that no dietary changes were observed, whereas the results report a significant increase in the percentage of energy derived from starch after exercise.

  • Claim of independent taxonomic responses conflicts with adjusted results

    Minor

    The claim of independence from the listed variables is not supported for every named taxon. Table 5 reports Proteobacteria p-values of 0.078 and 0.073 when adjusted for changes in energy and sucrose, respectively, and a Verrucomicrobia p-value of 0.054 when adjusted for the pre-exercise fiber value.

  • Heading says body-composition associations disappear despite reported correlations

    Minor

    The section heading says the associations disappear after exercise, but the section reports significant post-exercise correlations with waist circumference, weight, and android fat mass.

  • Figure 4 panel for Bray-Curtis analysis is mislabeled

    Minor

    The results direct readers to Figure 4B for the Bray-Curtis analysis, while the figure caption identifies panel B as Correspondence analysis and panel C as Bray-Curtis analysis.

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Metadata

Authors
Munukka, E., Ahtiainen, J. P., Puigbó, P., Jalkanen, S., Pahkala, K., Keskitalo, A., Kujala, U. M., Pietilä, S., Hollmén, M., Elo, L., Huovinen, P., D'Auria, G., & Pekkala, S.
Affiliations
  • University of Turku (FI)
  • University of Jyväskylä (FI)
Corresponding author
Pekkala, Satu
Venue
Frontiers in Microbiology
Published
2018-10-03
Volume
9
Pages
2323-2323
ISSN
1664-302X (ISSN-L)
OpenAlex
W2895626130
Cited by
237
References
55
Citations by year
2026: 31 · 2025: 30 · 2024: 33 · 2023: 26 · 2022: 43 · 2021: 33 · 2020: 26 · 2019: 14
FWCI
6.49
Type
journal article
Language
en
Open access
Locations
  • Frontiers in Microbiology (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Jyväskylä University Digital Archive (University of Jyväskylä) (submittedVersion, cc-by)
  • UTUPub (University of Turku) (submittedVersion)
  • UTUPub (University of Turku) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
Juho Vainion Säätiö
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
  • Health Sciences › Dentistry › Periodontics › Oral microbiology and periodontitis research
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Adipokines, Inflammation, and Metabolic Diseases
Keywords
endurance exercise, gut microbiota, gut metagenome, overweight women, Akkermansia, Proteobacteria, serum metabolomics, VAP-1, amine oxidase activity, hydrogen peroxide, body composition, fat mass, fructose metabolism, amino acid metabolism, lipid metabolism, VLDL cholesterol, phospholipids

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