Blood microbiota and metabolomic signature of major depression before and after antidepressant treatment: a prospective case–control study
Bibliographic record
Abstract
Background: The microbiota interacts with the brain through the gut-brain axis, and a distinct dysbiosis may lead to major depressive episodes. Bacteria can pass through the gut barrier and be found in the blood. Using a multiomic approach, we investigated whether a distinct blood microbiome and metabolome was associated with major depressive episodes, and how it was modulated by treatment. Methods: In this case-control multiomic study, we analyzed the blood microbiome composition, inferred bacterial functions and metabolomic profile of 56 patients experiencing a current major depressive episode and 56 matched healthy controls, before and after treatment, using 16S rDNA sequencing and liquid chromatography coupled to tandem mass spectrometry. Results: The baseline blood microbiome in patients with a major depressive episode was distinct from that of healthy controls (patients with a major depressive episode had a higher proportion of Janthinobacterium and lower levels of Neisseria) and changed after antidepressant treatment. Predicted microbiome functions confirmed by metabolomic profiling showed that patients who were experiencing a major depressive episode had alterations in the cyanoamino acid pathway at baseline. High baseline levels of Firmicutes and low proportions of Bosea and Tetrasphaera were associated with response to antidepressant treatment. Based on inferred baseline metagenomic profiles, bacterial pathways that were significantly associated with treatment response were related to xenobiotics, amino acids, and lipid and carbohydrate metabolism, including tryptophan and drug metabolism. Metabolomic analyses showed that plasma tryptophan levels are independently associated with response to antidepressant treatment. Limitations: Our study has some limitations, including a lack of information on blood microbiome origin and the lack of a validation cohort to confirm our results. Conclusion: Patients with depression have a distinct blood microbiome and metabolomic signature that changes after treatment. Dysbiosis could be a new therapeutic target and prognostic tool for the treatment of patients who are experiencing a major depressive episode.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".