Abstract P077: Midlife Physical Activity Is Associated With Gut Microbial Species And Metabolic Pathways: Coronary Artery Risk Development In Young Adults Study
Bibliographic record
Abstract
Background: Behavioral factors for cardiometabolic outcomes have been shown to influence the composition and function of the gut microbiota, which has been associated with cardiometabolic outcomes. Observational studies have documented associations between physical activity and gut microbial composition using 16S rRNA sequencing data, but there is a paucity of data on functional measures, which can be generated from whole-metagenomics sequencing (WMS). Methods: Data are from 480 CARDIA participants who attended the Year 30 follow-up exam (2015-2016, ages 48-60, 47:53 Black:White race, 47:53 male:female gender). Physical activity (exercise units) was estimated from reported frequency and duration of 13 activity types of at least moderate intensity during the previous year. Species, metabolic pathways, and enzyme families were assigned using standard reference databases. Multivariate measures of beta-diversity (between-person) was assessed with principal coordinates analysis (PCoA) and tested with PERMANOVA. Multivariable-adjusted linear regression was used to test associations between distinct microbial features and physical activity, adjusting for false discovery rate (FDR). Results: Sequence data mapped to 105 species 1,307 enzyme families, and 318 metabolic pathways. Beta-diversity of species, but not for enzyme families or metabolic pathways, was significantly differentiated according to physical activity. In analysis of distinct microbial features, 7 species, 15 enzyme families, and 3 metabolic pathways were significantly associated with physical activity at an FDR-adjusted p-value of 0.10 (Table). Conclusion: These findings support associations between gut microbial features and physical activity in a middle-aged, bi-race population-based cohort. Although temporality cannot be established from these cross-sectional analyses, our results are consistent with data suggesting that physical activity may influence composition and function of the gut microbiota.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".