Dopamine Transporter Genotype and Stimulant Side Effect Factors in Youth Diagnosed with Attention-Deficit/Hyperactivity Disorder
Bibliographic record
Abstract
The dopamine transporter locus (DAT1) has been studied as a risk factor for attention-deficit/hyperactivity disorder (ADHD) and in pharmacogenetic studies of stimulant response. Several prospective studies have reported an association between the homozygous 9 repeat allele of the DAT1 3' untranslated region (UTR) variable number tandem repeat (VNTR) (DAT1 3') and decreased efficacy of methylphenidate (MPH). We hypothesized that children with the 9/9 genotype would display higher rates of specific stimulant side effects. Data on adverse events and DAT1 3' genotypes were combined from two, double-blind, placebo-controlled, crossover studies of MPH conducted in child psychiatric outpatient clinics in Montreal and Washington, D.C. There were 177 participants, 5-16 years old (mean age = 8.99, standard deviation [SD] = 2), with ADHD. Parents completed the Stimulant Side Effect Scale (SERS) after a week of placebo and a week of MPH treatment. Principal components analysis of the SERS resulted in three factors: Emotionality, Somatic Complaints, and Over-focused. Children with the 9/9 genotype displayed higher scores on the Emotionality factor during placebo than children with the 9/10 and the 10/10 genotype, and their Emotionality scores increased further during MPH treatment (F[2,151] = 3.24, p < 0.05). Children with the 10/10 genotype displayed a significant increase in Somatic Complaint factor scores during MPH treatment relative to the other genotype groups (F[2,150] = 3.4, p < 0.05). These data provide suggestive evidence that DAT1 variants are differentially associated with specific stimulant side effects. Children with the 9/10 genotype displayed less severe stimulant side-effect ratings than either of the homozygous groups, who each displayed increased susceptibility to different types of adverse events. Preliminary evidence suggests that pharmacogenetic analysis using DAT1 variants shows promise for identifying individuals at increased or decreased risk for poor tolerability.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".