Interaction between Methylation and CpG Single-Nucleotide Polymorphisms in the HTR2A Gene: Association Analysis with Suicide Attempt in Schizophrenia
Bibliographic record
Abstract
Dysfunctional mechanisms in the serotonergic system have been implicated in suicidal behavior among patients with schizophrenia. However, previous association analyses of major serotonin genes have provided inconsistent findings regarding their role in suicidal behavior. The goal of the current study was to identify single-nucleotide polymorphisms (SNP) within HTR2A that directly affect CpG methylation sites in schizophrenic patients with suicidal behavior. Furthermore, direct methylation analysis was performed using genomic DNA from peripheral leukocytes employing bisulfite pyrosequencing to assess the contributions of six CpG sites in HTR2A exon I in 67 schizophrenia patients assessed for lifetime suicide attempt. Potential methylation in 25 CpG SNPs across the entire HTR2A gene was analyzed considering their direct contribution to methylation. When we compared direct methylation between attempters and nonattempters, we found that only the polymorphic T102C (rs6313) was significantly different between the two groups (p = 0.02). Furthermore, in the potential methylation analysis, we found a nominal association with suicide attempt for six of the 25 SNPs analyzed, i.e. rs2770293 (p = 0.045), rs6313 (p = 0.033), rs17068986 (p = 0.029), rs4942578 (p = 0.024), rs1728872 (p = 0.014), and rs9534511 (p = 0.003). The results of this investigation provide preliminary evidence that the combined analysis of CpG SNPs and methylation may be useful for investigating the genetic and epigenetic factors involved in suicidal behavior.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".