Investigation of the Gut Microbiome in Patients with Schizophrenia and Clozapine-Induced Weight Gain: Protocol and Clinical Characteristics of First Patient Cohorts
Bibliographic record
Abstract
BACKGROUND: Emerging evidence suggests an important role of the human gut microbiome in psychiatry and neurodevelopmental disorders. An increasing body of literature based on animal studies has reported that the gut microbiome influences brain development and behavior by interacting with the gut-brain axis. Furthermore, as the gut microbiome has an important role in metabolism and is known to interact with pharmaceuticals, recent evidence suggests a role for the microbiome in antipsychotic-induced metabolic side effects in animals and humans. PURPOSE: Here we present the protocol for a two-phase study investigating the gut microbiome in healthy controls and in patients with schizophrenia treated with antipsychotics. METHODS: Phase I of our study involves humans exclusively. We recruit 25 patients who are chronically treated with clozapine and compare them with 25 healthy controls matched for age, sex, BMI, and smoking status. A second cohort consists of 25 patients newly starting on clozapine, and a third cohort includes 25 antipsychotic-naive patients. The patients in the second cohort and third cohort are prospectively assessed for up to 6 and 12 weeks, respectively. Phase II of this study will incorporate microbiota humanized mouse models to examine the influence of human fecal transplant on metabolic parameters and the gut-brain axis. Progress and Future Directions: We are underway with the first participants enrolled in all phase I treatment cohorts. This study will contribute to elucidating the role of the gut microbiome in schizophrenia and metabolic side effects. In addition, its results may help to explore potential therapeutic targets for antipsychotic-induced metabolic side effects.
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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 | 0.000 | 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) | 0.000 | 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".