Effects of DNA methylation and polygenic scores on self-reported suicidal ideation in psychoses: no evidence of epigenetic basis of polygenic risk
Bibliographic record
Abstract
INTRODUCTION: Schizophrenia is a significant clinical problem. Unfortunately, there are currently no biomarkers available for accurately identifying patients with schizophrenia who may be vulnerable to suicide. Because genetic and environmental factors play a role in suicide, we attempted to determine the role of DNA methylation and polygenic risk scores in the relationship to suicidal ideation. METHODS: Using a cross-sectional study design, 98 participants with schizophrenia spectrum disorders were interviewed, and suicidal ideation was assessed using the Beck Scale for suicidal ideation, and whole blood was collected for methylation analysis. RESULTS: Our analysis showed a correlation between cg21813303 methylation and suicidal ideation, but this association did not reach genome-wide significance. The polygenic risk scores for suicidality were not associated with schizophrenia severity, and no biological relationship was found between DNA methylation and polygenic risk scores. CONCLUSION: This pilot study indicates that it is unlikely that DNA methylation and polygenic scores can predict suicidal ideation in schizophrenia.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.003 | 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".