The relative abundance of fecal bacterial species belonging to the Firmicutes and Bacteroidetes phyla is related to plasma levels of bile acids in young adults
Bibliographic record
Abstract
BACKGROUND: Gut bacteria play a crucial role in the metabolism of bile acids (BA). Whether an association exists between the fecal microbiota composition and circulating BA levels in humans is poorly understood. Here, we investigated the relationship between fecal microbiota diversity and composition with plasma levels of BA in young adults. METHODS: Fecal microbiota diversity/composition was analyzed with 16S rRNA sequencing in 80 young adults (74% women; 21.9 ± 2.2 years old). Plasma levels of BA were measured using liquid chromatography-tandem mass spectrometry. PERMANOVA and Spearman correlation analyses were used to investigate the association between fecal microbiota parameters and plasma levels of BA. RESULTS: Fecal microbiota beta (P = 0.025) and alpha diversity indexes of evenness (rho = 0.237, P = 0.033), Shannon (rho = 0.313, P = 0.004), and inverse Simpson (rho = 0.283, P = 0.010) were positively associated with plasma levels of the secondary BA glycolithocholic acid (GLCA). The relative abundance of genera belonging to the Firmicutes and Bacteroidetes phyla was positively correlated with plasma levels of GLCA (all rho ≥ 0.225, P ≤ 0.049). However, the relative abundance of species from Firmicutes and Bacteroidetes phyla were negatively correlated with plasma levels of primary and secondary BA (all rho ≤ - 0.220, P ≤ 0.045), except for the relative abundance of Bacteroides vulgatus, Alistipes onderdonkii, and Bacteroides xylanisolvens species (Bacteroidetes phylum) that were positively correlated with the plasma levels of GLCA. CONCLUSIONS: The relative abundance of specific fecal bacteria species is associated with plasma levels of BA in young adults. However, further investigations are required to validate whether the composition of the gut microbiota can regulate the plasma concentrations of BA in humans.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".