DAT1 polymorphism associated with poor decision‐making in males with antisocial personality disorder and high psychopathic traits
Bibliographic record
Abstract
Studies suggest that abnormalities of the dopaminergic system underlie decision-making deficits, a hallmark of antisocial personality disorder (ASPD) and psychopathy. The dopamine transporter gene (DAT1) is of particular interest due to a polymorphism that controls dopamine transporter (DAT) activity. However, the association between DAT1 genotypes and decision-making in ASPD has never been studied. The current study investigated the effect of DAT1 genotype on decision-making, as measured by the Iowa Gambling Task (IGT), in ASPD and healthy controls. A total of 17 participants with ASPD and 16 healthy control participants without ASPD were sampled. The Hare Psychopathy Checklist-Revised and the IGT were administered to all participants. All participants provided blood samples for genotyping. Data revealed a novel interaction effect between DAT1 genotype and diagnosis, whereby ASPD participants with low DAT activity genotypes performed significantly worse on the IGT and selected from disadvantageous decks more often, whereas the low DAT activity genotype in the healthy control group was associated with better performance on the IGT, and they selected from disadvantageous decks less often. We demonstrate, for the first time, that low DAT activity genotypes in ASPD with high psychopathic traits contribute to poor decision-making.
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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) | 0.003 | 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".