The Effects of Probiotics on Symptoms of Depression: Protocol for a Double-Blind Randomized Placebo-Controlled Trial
Bibliographic record
Abstract
BACKGROUND: A growing body of evidence has linked mental health outcomes to the gut microbiome. This has led to the investigation of the GI tract as a target for novel treatments and interventions for depression, including probiotic supplementation. Our recent pilot study provided the first evidence of probiotics improving symptoms of depression in treatment-naive depressed patients. To further support and expand upon this evidence, data from the pilot study were used to plan a 16-week, double-blind, randomized, placebo-controlled trial to assess the effects of probiotics on depression. Here, we report the protocol for this trial. METHODS: Participants diagnosed with depression will orally consume a probiotic supplement containing Lactobacillus helveticus and Bifidobacterium longum or placebo once daily. Participants will undergo assessments measuring clinical outcomes using a battery of validated clinical scales and questionnaires. Sleep architecture and quality will be measured using polysomnography. Neuroimaging data will be collected using magnetic resonance imaging to examine functional and structural neurophysiological changes. Molecular data will be collected from blood, stool, and urine samples to examine cytokine levels and explore potential genes and proteins that may predict outcomes in depression. RESULTS: We expect results to replicate and expand on our pilot data demonstrating that probiotics may be effective in alleviating symptoms of depression, and to find biomarkers that will predict these outcomes. CONCLUSIONS: The findings from this study will add to the growing body of research in this emerging field, which eventually may provide evidence for probiotics having a role in alleviating symptoms of depression.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".