Linkage disequilibrium analysis of the dopamine beta-hydroxylase gene in persistent attention deficit hyperactivity disorder
Bibliographic record
Abstract
Numerous family, twin and adoption studies have reported a strong genetic component for attention deficit hyperactivity disorder (ADHD). In addition, an extensive amount of literature has implicated abnormalities of the dopaminergic system. In view of this evidence, genes that influence dopaminergic transmission have become prime candidates for molecular genetic investigations of ADHD. There are currently three studies (Daly et al., 1999; Roman et al., 2002; Wigg et al., 2002) that have found an association between the dopamine beta-hydroxylase gene (DBH) TaqI 2 allele and childhood ADHD. As such, we tested for association of the DBH TaqI 2 allele in two independent samples of patients with the persistent variant of ADHD. These consisted of 97 nuclear families, and 112 adult cases with controls carefully matched according to gender, age and ethnicity. Transmission Disequilibrium Test analysis revealed weak over-transmission of the 2 allele (35 transmissions versus 27 non-transmissions; chi2 = 1.03, 1 degree of freedom, P=0.31). The case-control sample did not support previous findings since the 2 allele was more frequent in our control sample (137 versus 116; chi2 = 3.63, 1 degree of freedom, P=0.057). Taken together, these results do not provide support for a role of the DBH TaqI marker in our persistent ADHD samples.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".