Dairy Product Intake Alters the Correlations between Circulating Bile Acids and Short-Chain Fatty Acids with the Bacterial Taxa Roseburia, Faecalibacterium, Flavonifractor, and Verrucomicrobia
Bibliographic record
Abstract
INTRODUCTION: Type 2 diabetes (T2D) risk factors are associated with gut microbiota dysregulation that can alter circulating metabolite levels such as bile acids (BAs) and short-chain fatty acids (SCFAs). The objective was to investigate how the high dairy (HD) (≥4 servings/day) product intake compared to adequate dairy (AD) (≤2 servings/day) intake influences the correlations between Roseburia, Faecalibacterium, Flavonifractor, as well as Verrucomicrobia and circulating BAs and SCFAs in subjects at risk of T2D. METHODS: In a randomized crossover trial, 10 hyperinsulinemic adults were randomized to HD or AD for 6 weeks separated by a 6-week washout period. Gut microbiota were measured with 16S rRNA-based high-throughput sequencing. BA profiling in plasma was performed by high-performance liquid chromatography-tandem mass spectrometry. Serum SCFAs were determined using headspace gas chromatography. RESULTS: No significant differences were observed in mean circulating BA or SCFA levels between AD and HD consumption. Verrucomicrobia and Flavonifractor showed positive correlations with secondary BAs following HD and AD intake, respectively. Additionally, Flavonifractor correlated positively with acetic and propionic acids after HD intake. Roseburia correlated positively with primary BAs, propionate, and butyrate after HD intake. Faecalibacterium was positively correlated with cholic acid after AD intake and with hexanoic acid after HD intake. CONCLUSION: These findings suggest that HD intake may modulate microbiota-metabolite interactions without altering circulating metabolite concentrations, highlighting a potential role for dietary patterns in shaping gut-derived metabolic signals in individuals at risk of T2D.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".