Decoding the Inflammatory Signature of the Major Depressive Episode: Insights from Peripheral Immunophenotyping in Active and Remitted Condition
Bibliographic record
Abstract
Abstract Although the immune system's role in the pathogenesis and persistence of depression is increasingly recognized, there is a lack of comprehensive understanding regarding the involvement of innate and adaptive immune cells. This study aims to bridge this knowledge gap by providing a deepening assessment of immunological profiles integrated into clinical and biochemical parameters in individuals with Major Depressive Episode (MDE). This multicenter case-control sex and age-matched study recruiting 121 participants divided into patients with active and remitted MDE and healthy controls (HC). Biochemical parameters, humoral responses (pro- and anti-inflammatory), and specific innate and adaptive immune cell populations were measured. Patients with MDE showed monocytosis, increased high-sensitivity C-reactive protein and Erythrocyte Sedimentation Rate levels, and an altered proportion of specific monocyte subsets. CD4 lymphocytes exhibited increased activation and exhaustion and a higher frequency of CD4 + CD25 + FOXP3 + regulatory T cells. Additionally, patients with MDE showed increased plasma levels of sTREM2, IL-17 and IL-6. This profile denoted an immune dysregulation and inflammation in MDE. Boruta analyses identified markers with significant discriminative potential for distinguishing between patients with MDE and HC. Cluster analysis revealed that patients with MDE exhibited at least three different patterns of immune system activation, suggesting a different stage of inflammation or possible differences in the underlying mechanism involved. Our findings give a deeper understanding of the role of inflammation and its mediators in MDE, illuminating the way for novel therapeutic strategies tailored to specific subgroups of patients.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".