Support for association between ADHD and two candidate genes: <i>NET1</i> and <i>DRD1</i>
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Attention deficit hyperactivity disorder (ADHD) is a common, multifactorial disorder with significant genetic contribution. Multiple candidate genes have been studied in ADHD, including the norepinephrine transporter (NET1) and dopamine D1 receptor (DRD1). NET1 is implicated in ADHD because of the efficacy of atomoxetine, a selective noradrenergic reuptake inhibitor, in the treatment of ADHD. DRD1 is primarily implicated through mouse models of ADHD. DNA from 163 ADHD probands, 192 parents, and 129 healthy controls was used to investigate possible associations between ADHD and polymorphisms in 12 previously studied candidate genes (5-HT1B, 5-HT2A, 5-HT2C, ADRA2A, CHRNA4, COMT, DAT1, DRD1, DRD4, DRD5, NET1, and SNAP-25). Analyses included case-control and family-based methods, and dimensional measures of behavior, cognition, and anatomic brain magnetic resonance imaging (MRI). Of the 12 genes examined, two showed a significant association with ADHD. Transmission disequilibrium test (TDT) analysis revealed significant association of two NET1 single nucleotide polymorphisms (SNPs) with ADHD (P < or = 0.009); case-control analysis revealed significant association of two DRD1 SNPs with ADHD (P < or = 0.008). No behavioral, cognitive, or brain MRI volume measurement significantly differed across NET1 or DRD1 genotypes at an alpha of 0.01. This study provides support for an association between ADHD and polymorphisms in both NET1 and DRD1; polymorphisms in ten other candidate genes were not associated with ADHD. Because family-based and case-control methods gave divergent results, both should be used in genetic studies of ADHD.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it