Smoking in adult attention-deficit/hyperactivity disorder: Interaction between 15q13 nicotinic genes and Temperament Character Inventory scores
Bibliographic record
Abstract
Adults with ADHD smoke cigarettes at a higher rate than normal subjects. Nicotine has been shown to significantly improve clinical ADHD symptoms as measured by the Clinical Global Impression scale (CGI) as well as by measures of attention, vigour and arousal in ADHD subjects. In this study we hypothesized that the allele 113bp in D15S1360 marker at CHRNA7 and the 2 bp deletion allele at CHRFAM7A are associated with increased smoking in a sample of 90 DSM-IV patients affected by Adult ADHD. Temperament and Character Inventory (TCI) scores were included as covariates in the analysis to distinguish the contribution of personality traits from the contribution of the nicotinic genes under investigation. Smoking status was determined from the medical history questionnaire, and there were 35 current smokers and 55 non-smokers. Single marker associations and the CHRNA7-CHRFAM7A interaction were calculated by logistic regression, considering the 113 bp and the -2 bp deletion in a dominant model. No association of these genes with smoking was observed. Similarly, no significant interaction between the genes was observed in the logistic model. However, Persistence score of the TCI was significantly associated with smoking status. Further investigation on the hypothesis of the molecular interaction between CHRNA7 and CHRFAM7A genes is warranted.
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How this classification was reachedexpand
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 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".