Association of polymorphism of serotonin 2A receptor gene with suicidal ideation in major depressive disorder
Bibliographic record
Abstract
There is evidence indicating that density of 5-HT2A receptors is altered in brain regions of depressed suicide victims and in platelets of suicidal subjects with major depression or schizophrenia. Recent studies have also shown an association between the allele C of 102T/C polymorphism in the 5-HT2A receptor gene and schizophrenia. The present investigation tested the hypothesis that the observed changes in 5-HT2A receptor density in platelets of patients with major depression are a trait rather than state phenomenon and are associated with the 102 C allele in 5-HT2A receptor gene in a sample of 120 patients with major depression and a group of 131 control subjects comparable with respect to age, sex, and ethnic background. The allele and genotype frequencies of 102T/C polymorphism in 5-HT2A receptor gene were compared between patients and control subjects and between suicidal and non-suicidal patient groups. The major finding of this study was a significant association between the 102 C allele in 5-HT2A receptor gene and major depression, chi(2) = 4.5, df = 1, P = 0.03, particularly in patients with suicidal ideation, chi(2) = 8.5, df = 1, P < 0.005. Furthermore, we found that patients with a 102 C/C genotype had a significantly higher mean HAMD item 3 score (indication of suicidal ideation) than T/C or T/T genotype patients. Our results suggest that the 102T/C polymorphism in 5-HT2A receptor gene is primarily associated with suicidal ideation in patients with major depression. Am. J. Med. Genet. (Neuropsychiatr. Genet.) 96:56-60, 2000.
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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) | 0.001 | 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".