Association of the serotonin transporter and 5HT1Dβ receptor genes with extreme, persistent and pervasive aggressive behaviour in children
Bibliographic record
Abstract
There is an inverse correlation between central nervous system serotonergic activity and human aggression, and aggressive traits are at least partially heritable. The present study sought to investigate the relationship between childhood aggression and polymorphisms of two serotonin system genes: the 5HT1Dbeta receptor gene and the serotonin transporter (5HTT) gene. Fifty children with a minimum 2-year history of aggression and scores above the 90th percentile on the Aggression subscales of both the Child Behaviour Checklist and the Teacher's Report Form were included in the study. All probands and locally recruited ethnically matched controls were genotyped for the 5HT1Dbeta G861C, 5HTTLPR (promoter) and 5HTT variable number of tandem repeats (VNTR) polymorphisms. Chi-square tests revealed a significantly reduced frequency of the 5HTT VNTR 10R allele in children displaying the high-aggression phenotype compared with normal controls (P=0.039). After correction for multiple comparisons, this association reached the level of a trend but was no longer significant. Probands also demonstrated an increased 5HT1Dbeta 861C allele frequency, but this was not statistically significant (P=0.156). 5HTTLPR was not found to be significantly associated with aggression, but our data support previous findings of an association between this polymorphism and attention deficit hyperactivity disorder (P=0.025). While these preliminary findings should be interpreted cautiously, our data suggest that the 5HTT VNTR polymorphism is associated with measures of aggressive behaviour in a sample of children displaying extreme, persistent and pervasive aggression.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".