Brain-derived neurotrophic factor and inflammatory markers in patients with early- vs. late-stage bipolar disorder
Bibliographic record
Abstract
Bipolar I disorder (BD) has a poorer longer-term outcome than previously thought, with persistent cognitive impairment and functional decline. The neurobiological underpinnings that might underlie these changes remain unknown. Changes in brain-derived neurotrophic factor (BDNF) levels and cytokines are potential candidates. The aim of this study was to examine both cytokine and BDNF levels and their relationship in BD patients in the early and late stages of the disorder. We measured serum BDNF, TNF-alpha, IL-6 and IL-10 levels in a total of 60 patients with BD I and we compared those in early stages of illness with those in late stages of illness and also compared both groups with 60 matched healthy controls. BDNF was decreased only in those patients in the late stage of bipolar disorder. Moreover, BDNF levels were negatively correlated with length of illness. In contrast, all interleukins and TNF-alpha were increased in the early stages of BD, compared to controls. While TNF-alpha and IL-6 continued to be significantly higher than controls at late stages of BD, IL-10 did not. When levels were compared between patients at early and late stages of illness, there was a significant decrease in BDNF and IL-6 in the later stage of BD compared to the early stage. Inversely, TNF-alpha showed a significant increase at the later stage. Failure of inflammatory defences in the late stage of the disorder may account for reduction in BDNF and continued elevations in cytokines; thus these may have the potential to serve as markers of illness progression in BD.
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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 | 0.001 |
| 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) | 0.001 | 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".