Metabolome-associated psychological comorbidities improvement in irritable bowel syndrome patients receiving a probiotic
Bibliographic record
Abstract
Our recent randomized, placebo-controlled study in Irritable Bowel Syndrome (IBS) patients with diarrhea or alternating bowel habits showed that the probiotic Bifidobacterium longum (BL) NCC3001 improves depression scores and decreases brain emotional reactivity. However, the involved metabolic pathways remain unclear. This analysis aimed to investigate the biochemical pathways underlying the beneficial effects of BL NCC3001 using metabolomic profiling. Patients received probiotic (1x 1010CFU, n=16) or placebo (n=19) daily for 6 weeks. Anxiety and depression were measured using the Hospital Anxiety and Depression Scale. Brain activity in response to negative emotional stimuli was assessed by functional Magnetic Resonance Imaging. Probiotic fecal abundance was quantified by qPCR. Quantitative measurement of specific panels of plasma host-microbial metabolites was performed by mass spectrometry-based metabolomics. Probiotic abundance in feces was associated with improvements in anxiety and depression scores, and a decrease in amygdala activation. The probiotic treatment increased the levels of butyric acid, tryptophan, N-acetyl tryptophan, glycine-conjugated bile acids, and free fatty acids. Butyric acid concentration correlated with lower anxiety and depression scores, and decreased amygdala activation. Furthermore, butyric acid concentration correlated with the probiotic abundance in feces. In patients with non-constipation IBS, improvements in psychological comorbidities and brain emotional reactivity were associated with an increased abundance of BL NCC3001 in feces and specific plasma metabolites, mainly butyric acid. These findings suggest the importance of a probiotic to thrive in the gut and highlight butyric acid as a potential biochemical marker linking microbial metabolism with beneficial effects on the gut-brain axis.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".