Multiple tissue methylation analysis of HTR2A exon I in suicidal behavior
Bibliographic record
Abstract
OBJECTIVE: The main aim of the current study was to investigate epigenetic alterations in serotonin 2A receptor (HTR2A) exon I CpG sites as possible risk factors for suicidal behavior. We also aimed to analyze the epigenetic alterations in two different tissues as epigenetic mechanisms are tissue specific. These epigenetic changes may lead to a better prediction of suicidal behavior. METHODS: Direct CpG methylation analysis was carried out on genomic DNA from the saliva of 20 schizophrenia suicide attempters and 27 non-attempters, and from post-mortem brain tissues of nine suicide victims and 11 controls. We used bisulfite pyrosequencing to assess the contributions of six CpG sites including the rs6313 (C102T) site in the first exon of HTR2A in suicide attempters and suicide victims. RESULTS: DNA methylation analysis did not find a significant difference in CpG methylation between suicide attempters and non-attempters (P=0.759) or between suicide victims and controls (P=0.189). We found a strong positive correlation between CpG methylation levels in blood and saliva (r=0.547, P<0.001). DISCUSSION: DNA methylation analysis confirmed that the overall methylation level of HTR2A exon I was around 80% for DNA extracted from saliva and almost 30% in the frontal cortex DNA. The results of this investigation do not support the evidence that methylation analysis of the HTR2A may be useful for investigating the epigenetic factors involved in suicidal behavior.
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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 | 0.000 |
| 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) | 0.002 | 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".