Genetic Variants and Early Cigarette Smoking and Nicotine Dependence Phenotypes in Adolescents
Bibliographic record
Abstract
BACKGROUND: While the heritability of cigarette smoking and nicotine dependence (ND) is well-documented, the contribution of specific genetic variants to specific phenotypes has not been closely examined. The objectives of this study were to test the associations between 321 tagging single-nucleotide polymorphisms (SNPs) that capture common genetic variation in 24 genes, and early smoking and ND phenotypes in novice adolescent smokers, and to assess if genetic predictors differ across these phenotypes. METHODS: In a prospective study of 1294 adolescents aged 12-13 years recruited from ten Montreal-area secondary schools, 544 participants who had smoked at least once during the 7-8 year follow-up provided DNA. 321 single-nucleotide polymorphisms (SNPs) in 24 candidate genes were tested for an association with number of cigarettes smoked in the past 3 months, and with five ND phenotypes (a modified version of the Fagerstrom Tolerance Questionnaire, the ICD-10 and three clusters of ND symptoms representing withdrawal symptoms, use of nicotine for self-medication, and a general ND/craving symptom indicator). RESULTS: The pattern of SNP-gene associations differed across phenotypes. Sixteen SNPs in seven genes (ANKK1, CHRNA7, DDC, DRD2, COMT, OPRM1, SLC6A3 (also known as DAT1)) were associated with at least one phenotype with a p-value <0.01 using linear mixed models. After permutation and FDR adjustment, none of the associations remained statistically significant, although the p-values for the association between rs557748 in OPRM1 and the ND/craving and self-medication phenotypes were both 0.076. CONCLUSIONS: Because the genetic predictors differ, specific cigarette smoking and ND phenotypes should be distinguished in genetic studies in adolescents. Fifteen of the 16 top-ranked SNPs identified in this study were from loci involved in dopaminergic pathways (ANKK1/DRD2, DDC, COMT, OPRM1, and SLC6A3). IMPACT: Dopaminergic pathways may be salient during early smoking and the development of ND.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".