Cardiorespiratory fitness as a predictor of intestinal microbial diversity and distinct metagenomic functions
Bibliographic record
Abstract
BACKGROUND: Reduced microbial diversity in human intestines has been implicated in various conditions such as diabetes, colorectal cancer, and inflammatory bowel disease. The role of physical fitness in the context of human intestinal microbiota is currently not known. We used high-throughput sequencing to analyze fecal microbiota of 39 healthy participants with similar age, BMI, and diets but with varying cardiorespiratory fitness levels. Fecal short-chain fatty acids were analyzed using gas chromatography. RESULTS: We showed that peak oxygen uptake (VO2peak), the gold standard measure of cardiorespiratory fitness, can account for more than 20 % of the variation in taxonomic richness, after accounting for all other factors, including diet. While VO2peak did not explain variation in beta diversity, it did play a significant role in explaining variation in the microbiomes' predicted metagenomic functions, aligning positively with genes related to bacterial chemotaxis, motility, and fatty acid biosynthesis. These predicted functions were supported by measured increases in production of fecal butyrate, a short-chain fatty acid associated with improved gut health, amongst physically fit participants. We also identified increased abundances of key butyrate-producing taxa (Clostridiales, Roseburia, Lachnospiraceae, and Erysipelotrichaceae) amongst these individuals, which likely contributed to the observed increases in butyrate levels. CONCLUSIONS: Results from this study show that cardiorespiratory fitness is correlated with increased microbial diversity in healthy humans and that the associated changes are anchored around a set of functional cores rather than specific taxa. The microbial profiles of fit individuals favor the production of butyrate. As increased microbiota diversity and butyrate production is associated with overall host health, our findings warrant the use of exercise prescription as an adjuvant therapy in combating dysbiosis-associated diseases.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".