From a genetic perspective, the single SNP analyses did not reveal any genome wide significant signals. This is likely because our sample is underpowered, even with a quantitative trait, to detect single variants of modest effect size. Using GWAPower (Feng et al., 2011), we estimated power available in our dataset to identify SNPs of varying effect size. Power was 80% when an effect size of 0.01 (1%) was anticipated (with covariates explaining about 20% of the variance, and Type 1 error set at 5 × 10−8). Increasing efforts to amass larger samples with comparable cannabis-related data would afford greater power to detect variants of more modest effect size via meta- and mega-analyses. However, few current studies have DSM-5 criteria data. In this regard, factor scores (or symptom counts) such as ours may prove to be useful phenotypes as they can accommodate DSM-IV and DSM-5 based assessments of vulnerability to cannabis use disorders.
