Larger GWAS sample sizes can be obtained by examining phenotypes that are less stringently defined and therefore more likely available across genomic studies of other outcomes. For example, the ICC published a meta-analysis of genome-wide association data of 13 cohorts (N = 32,330) and four replication samples (N = 5627) of European ancestry (EA) assessed for cannabis use (i.e., having ever used cannabis in one’s lifetime)4. The ICC meta-analysis included data from previous GWAS of cannabis dependence6 described above. While no individual SNP reached genome-wide significance, gene-based tests identified four genes significantly associated with lifetime cannabis use: NCAM1 and CADM2 (genes involved in neural cell adhesion), short coiled-coil protein (SCOC), and a potassium sodium-activated channel gene (KCNT2). Furthermore, they demonstrated that all common SNPs explained 13–20% (p < 0.001) of the variance in lifetime cannabis use. While several large studies and consortia efforts to examine cannabis involvement are underway, this is currently the largest peer-reviewed meta-analysis of cannabis GWAS studies to date. A more recent and larger meta-analysis (N: 184,765), including data from the ICC (N: 35,297), 23andme (N: 22,683),
