Peripheral cytokine and chemokine alterations in depression: a meta‐analysis of 82 studies
Bibliographic record
Abstract
Objective To conduct a systematic review and meta‐analysis of studies that measured cytokine and chemokine levels in individuals with major depressive disorder (MDD) compared to healthy controls (HCs). Method The PubMed/MEDLINE, EMBASE, and PsycINFO databases were searched up until May 30, 2016. Effect sizes were estimated with random‐effects models. Result Eighty‐two studies comprising 3212 participants with MDD and 2798 HCs met inclusion criteria. Peripheral levels of interleukin‐6 (IL‐6), tumor necrosis factor (TNF)‐alpha, IL‐10, the soluble IL‐2 receptor, C‐C chemokine ligand 2, IL‐13, IL‐18, IL‐12, the IL‐1 receptor antagonist, and the soluble TNF receptor 2 were elevated in patients with MDD compared to HCs, whereas interferon‐gamma levels were lower in MDD (Hedge's g = −0.477, P = 0.043). Levels of IL‐1β, IL‐2, IL‐4, IL‐8, the soluble IL‐6 receptor (sIL‐6R), IL‐5, CCL‐3, IL‐17, and transforming growth factor‐beta 1 were not significantly altered in individuals with MDD compared to HCs. Heterogeneity was large (I2: 51.6–97.7%), and sources of heterogeneity were explored (e.g., age, smoking status, and body mass index). Conclusion Our results further characterize a cytokine/chemokine profile associated with MDD. Future studies are warranted to further elucidate sources of heterogeneity, as well as biosignature cytokines secreted by other immune cells.
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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 | 0.017 | 0.027 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.047 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".