Peripheral Circular RNA Expression Levels in Schizophrenia and Schizoaffective Disorder: Associations With Clinical Characteristics and Behavioral Phenotypes
Bibliographic record
Abstract
OBJECTIVE: Circular RNA (circRNA) molecules may play a significant role in the pathogenesis of psychiatric disorders by regulating synaptic gene expression. This study aimed to evaluate the relationship between the peripheral expression levels of three circRNA molecules (chr3_196488683, chr5_69175537, and hsa_circ_0084021) and clinical characteristics, specifically behavioral phenotypes related to self-harm and harm to others, in individuals diagnosed with schizophrenia and schizoaffective disorder. METHODS: The study included 104 patients aged 18–65 diagnosed with schizophrenia or schizoaffective disorder. RNA was isolated from peripheral blood, and circRNA molecules were identified using RNA sequencing techniques. Clinical status was assessed using the Positive and Negative Syndrome Scale, Clinical Global Impressions Scale, Global Assessment of Functioning, Calgary Depression Scale for Schizophrenia, Beck Anxiety Inventory, Beck Scale for Suicide Ideation, and Suicide Probability Scale. The relationship between concurrent circRNA levels and clinical features was investigated. RESULTS: A significant positive correlation was observed among the circRNAs (p<0.001). Apart from a weak positive correlation between chr3_196488683 and the Beck Anxiety Inventory score (r=0.213, p=0.03), no significant relationship was found between clinical scales and circRNAs. No significant difference was detected between groups regarding suicidal behavior. However, mean levels of all circRNAs were found to be statistically significantly higher in the group with self-injurious behavior (chr3_196488683, p=0.036; chr5_69175537, p=0.001; hsa_circ_0084021, p=0.045). Similarly, levels of chr3_196488683 and chr5_69175537 were significantly higher in the group with homicidal behavior (p<0.001). CONCLUSION: The findings suggest that peripheral circRNA levels may be associated with anxiety and behavioral risk profiles involving harm to self or others, indicating their potential value as biomarkers.
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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 | 0.000 |
| 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) | 0.002 | 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".