Psychotic Disorders and exosomes: An overview of current evidence and future directions
Bibliographic record
Abstract
Due to its reliance on heterogeneous symptomatology, the accurate diagnosis of psychotic disorders remains a challenging task in clinical practice. Precise and early diagnosis of psychotic disorders facilitates early intervention, which has been shown to have substantial benefits for long-term outcomes. Still, the lack of specific biomarkers is an important limitation in early diagnosis and intervention. Exosomes, which act as messengers between cells, including brain cells, contain a vast array of molecules that hold promise for unveiling disorder-specific abnormalities. In this review, we discuss recent evidence highlighting the potential of circulating exosomes and brain-derived exosomes as valuable tools for the identification of accessible, non-invasive, and blood-based biomarkers of psychotic symptomatology and risk. We discuss current limitations in biomarker discovery studies focusing on exosomes. To enhance diagnosis specificity and treatment response, we also provide guidance for future investigations that need to target biomarkers of risk and relapse, as well as consider duration of untreated psychosis, biological sex, and other factors in the multifactorial biosignature of psychosis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".