We note that the genetic correlation estimated by MiXeR was more modest than that estimated in the latent variable model. This difference may be explained by differences in methods; whereas Genomic SEM estimates genetic correlations between latent variables in a measurement model and thus only includes genetic effects that act homogeneously through the latent factor, MiXeR uses summary statistics, which include genetic effects that act through the latent factor as well as those that influence individual indicators (i.e., Q-SNPs). Use of summary statistics may therefore result in downward bias of genetic correlations. This may also suggest that the influential variants for addiction risk that are unshared with externalizing impact one or a few SUDs, rather than the broad addiction risk factor.
