Genome‐wide association meta‐analysis of age at first cannabis use
Bibliographic record
Abstract
Abstract Background and aims Cannabis is one of the most commonly used substances among adolescents and young adults. Earlier age at cannabis initiation is linked to adverse life outcomes, including multi‐substance use and dependence. This study estimated the heritability of age at first cannabis use and identified associations with genetic variants. Methods A twin‐based heritability analysis using 8055 twins from three cohorts was performed. We then carried out a genome‐wide association meta‐analysis of age at first cannabis use in a discovery sample of 24 953 individuals from nine European, North American and Australian cohorts, and a replication sample of 3735 individuals. Results The twin‐based heritability for age at first cannabis use was 38% [95% confidence interval (CI) = 19–60%]. Shared and unique environmental factors explained 39% (95% CI = 20–56%) and 22% (95% CI = 16–29%). The genome‐wide association meta‐analysis identified five single nucleotide polymorphisms (SNPs) on chromosome 16 within the calcium‐transporting ATPase gene (ATP2C2) at P < 5E‐08. All five SNPs are in high linkage disequilibrium (LD) (r2 > 0.8), with the strongest association at the intronic variant rs1574587 (P = 4.09E‐09). Gene‐based tests of association identified the ATP2C2 gene on 16q24.1 (P = 1.33e‐06). Although the five SNPs and ATP2C2 did not replicate, ATP2C2 has been associated with cocaine dependence in a previous study. ATP2B2, which is a member of the same calcium signalling pathway, has been associated previously with opioid dependence. SNP‐based heritability for age at first cannabis use was non‐significant. Conclusion Age at cannabis initiation appears to be moderately heritable in western countries, and individual differences in onset can be explained by separate but correlated genetic liabilities. The significant association between age of initiation and ATP2C2 is consistent with the role of calcium signalling mechanisms in substance use disorders.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.024 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".