Association study of the nicotinic acetylcholine receptor α4 subunit gene, <i>CHRNA4</i>, in attention‐deficit hyperactivity disorder
Bibliographic record
Abstract
Attention-deficit hyperactivity disorder (ADHD) is a common childhood-onset psychiatric condition with a strong genetic component. Evidence from pharmacological, clinical and animal studies has suggested that the nicotinic system could be involved in the disorder. Previous studies have implicated the nicotinic acetylcholine receptor alpha4 subunit gene, CHRNA4, in ADHD. Particularly, a polymorphism in the exon 2-intron 2 junction of CHRNA4 has been associated with severe inattention defined by latent class analysis. In the current study, we used the transmission disequilibrium test (TDT) to investigate four polymorphisms encompassing this region of CHRNA4 for association with ADHD in a sample of 264 nuclear families from Toronto. No significant evidence of biased transmission was observed for any of the marker alleles for ADHD defined as a categorical trait (all subtypes included), although one haplotype showed marginal evidence of under-transmission. No association was found with the ADHD predominantly inattentive subtype or with symptom dimension scores of inattention. On the contrary, nominally significant evidence of association of individual markers was obtained for the ADHD combined subtype and with teacher-rated hyperactivity-impulsivity scores, with the same haplotype being under-transmitted. Based on our results and others, CHRNA4 may be involved in ADHD; however, its role in ADHD symptomatology remains to be clarified.
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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 | 0.002 |
| 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 | 0.001 |
| 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".