Evidence for association of vasopressin receptor 1A promoter region repeat with childhood onset aggression
Bibliographic record
Abstract
OBJECTIVE: Childhood onset aggression can cause major suffering to affected families and is associated with many negative outcomes in the child's later life, including poor academic performance, adolescent delinquency, drug abuse, depression and antisocial personality disorder. Currently available prevention and intervention strategies have limited efficacy, but a better understanding of underlying genetic and neurobiological factors can lead to more effective prevention and treatment strategies, through genetic screening programs and novel therapies. METHOD: This study examined the RS1 (n = 299 aggression, n = 192 controls) and RS3 (n = 291 aggression, n = 189 controls) microsatellite repeats within the promoter region of the vasopressin receptor 1A gene (AVPR1A) and their association with extreme childhood aggression, as assessed by the Child Behavior Checklist (CBCL), as well as the Teacher Report Form (TRF) and Youth Self Report (YSR). Binary logistic regression was used to model the relationship between microsatellite length and childhood aggression. Age and sex were used as covariates. RESULTS: Logistic regression revealed a nominally significant association between one specific RS3 repeat and non-aggressive status. No association was found for any of the RS1 repeats. In a separate model, grouping repeats into short and long, carriers of long RS3 repeats were nominally significantly associated with non-aggressive status. CONCLUSIONS: These findings suggest a role for AVPR1A and its RS3 microsatellite in extreme childhood aggression and could lead to a better understanding of the biological pathways of aggressive behavior. However, independent replication and further research into the functionality of studied genetic variants is required.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".