Association of Complement and Coagulation Pathway Proteins With Treatment Response in First-Episode Psychosis: A Longitudinal Analysis of the OPTiMiSE Clinical Trial
Bibliographic record
Abstract
BACKGROUND AND HYPOTHESIS: Treatment response to specific antipsychotic medications is difficult to predict on clinical grounds alone. The current study hypothesizes that the baseline complement pathway activity predicts the treatment response and investigates the relationship between baseline plasma biomarkers with treatment response to antipsychotic medications. STUDY DESIGN: Baseline plasma samples were collected from first episode of psychosis patients (n = 243) from a multi-center clinical trial. The participants were treated with amisulpride for 4 weeks. Levels of complement and coagulation proteins at baseline were measured using both data-dependent and data-independent mass spectrometry approaches. The primary outcome was remission status at 4 weeks and the secondary outcomes included change in psychotic and functional symptoms over the period of treatment. In addition, immunoassays were performed at baseline for complement C1R, as well as for activation markers C4a and sC5b-9. STUDY RESULTS: The plasma level of complement variant C4A was significantly associated with remission at 4 weeks. Moreover, higher levels of several complement and coagulation pathway proteins were associated with a reduction in psychotic symptoms and an improvement in functioning. Immunoassays showed an association of baseline levels of C1R and C4a as well as complement activation marker sC5b-9 levels with treatment response. CONCLUSION: The results demonstrated that the response to antipsychotic treatment might be related to pre-treatment levels of plasma complement and coagulation pathway proteins. This is consistent with independent evidence associating immune dysfunction with the pathophysiology of psychosis. Moreover, these results inform the development of novel therapeutic approaches that target the complement system for psychosis.
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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 | 0.010 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".