Association of the dopamine transporter gene and ADHD symptoms in a Canadian population‐based sample of same‐age twins
Bibliographic record
Abstract
Attention deficit hyperactivity disorder (ADHD) is the most prevalent psychiatric disorder emerging during childhood. Psychostimulant medications (e.g., methylphenidate) noticeably reduce ADHD symptoms in most children. Since methylphenidate inhibits dopamine transporter activity, the dopamine transporter gene (DAT1) was considered to be the prime candidate risk gene in ADHD. Several studies found evidence for an association between the 10-repeat allele of the variable number of tandem repeat (VNTR) located in the 3' untranslated region and ADHD and/or ADHD symptoms in clinical and population-based samples. However, this finding was not replicated in all samples. In this study, we investigated the association between the DAT1 gene and ADHD symptoms in a population-based twin sample from Québec (Canada). We used two polymorphisms, the VNTR and rs27072, the last providing the most significant results in a clinical sample from Toronto (Ontario, Canada). No association was noted between the VNTR and ADHD symptoms in children at 6 and 7 years of age, as reported by teachers. However, a significant association was found for the rs27072 polymorphism and symptoms of inattention and hyperactivity/impulsivity. These findings indicate that the DAT1 gene contributes to ADHD symptoms in this sample and further suggest that the VNTR may not be the optimal polymorphism for study in all populations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".