available microarray data even after imputation. An additional limitation is that we did not do formal Mendelian randomisation65 analysis. To do this analysis, we would have needed to remove sample overlap between our cannabis use disorder GWAS and the other GWASs of interest, which would have greatly decreased our statistical power. However, after doing latent causal variable analyses,34 an approach related to mendelian randomisation that can account for sample overlap among the input GWAS, there was no significant evidence of causal relationships between liability to cannabis use disorder and to any of the top genetically correlated traits: educational attainment, age at first birth, Townsend Deprivation Index, smoking initiation, or ADHD (appendix p 16). Overall, estimates of genetic overlap might also be sensitive to sample characteristics, such as older volunteers in the UK Biobank cohort66 and some younger registry-based cohorts in our GWAS. In addition, imbalance between cases and controls could have affected our findings, although we did not observe substantial genetic heterogeneity (appendix pp 23–24).
