Elevation of cerebrospinal fluid interleukin-1β in bipolar disorder
Bibliographic record
Abstract
BACKGROUND: In recent years, a role for the immune system in the pathogenesis of psychiatric diseases has gained increased attention. Although bipolar disorder appears to be associated with altered serum cytokine levels, a putative immunological contribution to its pathophysiology remains to be established. Hitherto, no direct analyses of cerebrospinal fluid (CSF) cytokines in patients with bipolar disorder have been performed. METHODS: We analyzed CSF cytokine concentrations in euthymic patients with diagnosed bipolar disorder type I (n = 15) or type II (n = 15) and healthy volunteers (n = 30) using an immunoassay-based protein array multiplex system. RESULTS: The mean interleukin (IL)-1ß level (4.2 pg/mL, standard error of the mean [SEM] 0.5) was higher and the IL-6 level (1.5 pg/mL, SEM 0.2) was lower in euthymic bipolar patients than in healthy volunteers (0.8 pg/mL, SEM 0.04, and 2.6 pg/mL, SEM 0.2, respectively). Patients with 1 or more manic/hypomanic episodes during the last year showed significantly higher levels of IL-1ß (6.2 pg/mL, SEM 0.8; n = 9) than patients without a recent manic/hypomanic episode (3.1 pg/mL, SEM 1.0; n = 10). LIMITATIONS: All patients were in an euthymic state at the time of sampling. Owing to the large variety of drugs prescribed to patients in the present study, influence of medication on the cytokine profile cannot be ruled out. CONCLUSION: Our findings show an altered brain cytokine profile associated with the manifestation of recent manic/hypomanic episodes in patients with bipolar disorder. Although the causality remains to be established, these findings may suggest a pathophysiological role for IL-1ß in bipolar disorder.
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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 | 0.001 | 0.001 |
| 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".