Review article: bugs, inflammation and mood—a microbiota‐based approach to psychiatric symptoms in inflammatory bowel diseases
Bibliographic record
Abstract
BACKGROUND: Psychiatric co-morbidities including depression and anxiety are common in inflammatory bowel diseases (IBD). Emerging evidence suggests that interactions between the gut microbiota and brain may play a role in the pathogenesis of psychiatric symptoms in IBD. AIM: To review the literature on microbiota-brain-gut interactions in gut inflammation, psychosocial stress and mental disorders and to discuss the putative mediating role of gut microbiota in the development of psychiatric symptoms or co-morbidities in IBD. METHODS: A literature search was conducted on Ovid and Pubmed to select relevant animal and human studies reporting an association between IBD, mental disorders and gut microbiota. RESULTS: Gut microbial alterations are frequently reported in subjects with IBD and with mental disorders. Both have been associated with reduced faecal bacterial diversity, decreased taxa within the phylum Firmicutes and increased Gammaproteobacteria. In animal studies, microbial perturbations induce behavioural changes and modulate inflammation in mice. Anxiety- and depression-like behaviours in animals can be transferred via faecal microbiota. In humans, modulation of the gut microbiota with probiotics is associated with behavioural and mood changes. Recent data show correlations in changes of faecal and mucosal microbiota and psychological distress in patients with IBD independent of disease activity. CONCLUSION: Both IBD and mental disorders are associated with gut microbial alterations. Preclinical and preliminary human studies have shown a mediating role of the gut microbiota in intestinal inflammation and anxiety, depression and stress. Targeting the gut microbiota may represent a useful therapeutic approach for the treatment of psychiatric co-morbidities in IBD.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".