The Gut–Brain Axis in Schizophrenia: A Systems-Level Understanding of Psychiatric Illness
Bibliographic record
Abstract
Schizophrenia is a complex psychiatric disorder traditionally linked to neurotransmitter dysregulation, particularly within dopamine and glutamate pathways. However, recent evidence implicates the gut–brain axis as a potential contributor to its pathophysiology. This perspective article proposes a systems-level understanding of schizophrenia that incorporates the role of gut microbial dysbiosis specifically, reductions in short-chain fatty acid (SCFA)-producing taxa, and elevations in pro-inflammatory microbes. These imbalances may compromise gut barrier integrity, stimulate systemic inflammation, and disrupt neurochemical signaling in the brain. We synthesize findings from animal models, clinical cohorts, and microbial intervention trials, highlighting mechanisms such as SCFA regulation, altered tryptophan–kynurenine metabolism, and microbial impacts on neurotransmitters. We also explore microbiome-targeted interventions like probiotics, prebiotics, dietary strategies, and fecal microbiota transplantation (FMT) and their potential as adjunctive therapies. While challenges remain in causality and translation, integrating gut–brain axis insights may support more personalized and biologically informed models of schizophrenia care.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".