The role of oxytocin and oxytocin receptor gene variants in childhood‐onset aggression
Bibliographic record
Abstract
Aggressive antisocial behaviours are the most common reasons why adolescents are referred to mental health clinics. Antisocial behaviours are costly in social and financial terms. The aetiology of aggressive behaviours is unknown but growing evidence suggests it is heritable, and certain genetic variants have been implicated as contributing factors. The purpose of this study was to determine whether genes regulating the hormone oxytocin (OXT) were associated with aggressive antisocial behaviour. The case-control study sample consisted of 160 cases of children displaying extreme, persistent and pervasive aggressive behaviour. This case sample was compared with 160 adult controls. We used polymerase chain reaction (PCR) to determine the genotype for three oxytocin gene (OXT) single nucleotide polymorphisms (SNPs): rs3761248, rs4813625 and rs877172; and five oxytocin receptor gene (OXTR) SNPs: rs6770632, rs11476, rs1042778, rs237902 and rs53576. Genotypic analyses were performed using stata, while differences in haplotypic and allelic frequencies were analysed using Unphased. We also performed within-case analyses (n = 236 aggressive cases) examining genotypic and allelic associations with callous-unemotional (CU) scores (as measured by the psychopathic screening device). OXTR SNPs rs6770632 and rs1042778 may be associated with extreme, persistent and pervasive aggressive behaviours in females and males, respectively. These and haplotype results suggest gender-specific effects of SNPs. No significant differences were detected with respect to CU behaviours. These results may help to elucidate the biochemical pathways associated with aggressive behaviours, which may aid in the development of novel medications.
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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 | 0.003 |
| 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 | 0.001 |
| 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".