Genetic Prediction of Smoking Cessation Medication Side Effects: A Genome‐Wide Investigation of Abnormal Dreams on Varenicline
Bibliographic record
Abstract
Varenicline, the most efficacious smoking cessation monotherapy, produces abnormal dreams. Although genetic contributions to varenicline‐associated nausea and cessation have been identified, the role of genetics in abnormal dreams is unknown. We conducted a genomewide association study (GWAS) of abnormal dreams in 188 European ancestry smokers treated with varenicline (NCT01314001). Additive genetic models examined the likelihood of experiencing abnormal dreams 2 weeks following varenicline initiation. For the top locus, we tested for selectivity to varenicline, effects on cessation, replication, and generalizability to African ancestry (AA) individuals. The top GWAS variant associated with abnormal dreams was rs901886, mapping to intron 2 of ICAM5 on chromosome 19. The prevalence of abnormal dreams in those with rs901886 CC, CT, and TT genotypes was 15%, 36%, and 62%, respectively (odds ratio = 2.94 for T vs. C, 95% confidence interval = 1.92–4.55, P = 2.03e−7; T allele frequency = 52%). This rs901886 association was selective to varenicline (P values > 0.05 on nicotine patch and placebo). There were also positive associations for rs901886 T (vs. C allele, P = 0.03) and for abnormal dreams (P = 0.06) with varenicline‐aided cessation. Neither rs901886 (P = 0.40) nor abnormal dreams (P = 0.24) were associated with adherence. A similar direction of effect of rs901886 on abnormal dreams was observed in a second varenicline trial (NCT01836276). In AA individuals (n = 137), rs901886 was not associated with abnormal dreams (P = 0.41), but there was an association for a variant located ~ 74.4 kb 5′ of ICAM5 (P = 2.56e−3). Variation in ICAM5 may influence abnormal dreams and cessation on varenicline. These findings provide additional support for genetically optimized smoking cessation approaches.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".