Nieuwboer et al. (2016)23 use summary statistics for educational achievement (EA)24 and both schizophrenia and bipolar disorder25 to determine if genetic correlations with EA are driven by variation specific to either disorder. EA is genetically correlated with schizophrenia (rg = .148, SE = .050, p = .003) and bipolar disorder (rg = .273, SE = .067, p < .001). Using a method called genome-wide inferred statistics (GWIS), they find that the correlation of EA with schizophrenia unique of bipolar is small (rg = .040, SE = .082, p = .627), whereas the genetic correlation between bipolar unique of schizophrenia and EA is far less attenuated (rg = .218, SE = .102, p = .032). We use Genomic SEM with the aim of replicating these results using a conceptually similar, but statistically distinct, framework. We present this example to demonstrate that Genomic SEM is not limited to factor analytic models, but can be used to construct and test an array of hypotheses using a general SEM approach.
