Some limitations are noteworthy. First, despite aggregating across several large datasets, our meta-analytic sample was relatively underpowered to detect small effects and also, for analyses that would allow us to estimate genetic correlations between cannabis dependence and other traits (e.g. cigarettes per day (68) for which genomewide summary statistics are available. Such calculations typically rely on unrelated cases and controls and our study included two samples with complex pedigree structures. Second, we did not have adequate numbers of AA participants for a full examination of loci identified in Sherva et al (8). In EAs, the only SNP associated at genomewide significant levels in Sherva et al was rs77378271 (CSMD1). In the current study, rs77378271 shows some evidence for independent association with cannabis dependence in COGA-cc (p=5.3E-3); however, the meta-analytic p-value was not significant, with indication of heterogeneity across the samples included in the present meta-analysis. We anticipate that additional data on cannabis dependence in both EA and AA participants will be available in the future. Finally, the minor allele frequency for rs1409568 (and related genomewide significant SNPs) was <10% across cases and controls from each sample.
