From a translational perspective, this work illustrates that data from large GWAS and a pleiotropic framework can provide important insights into the relationships between various diseases. Complementary to recently developed polygenic pleiotropic methods 19–22, the analytic framework used in this manuscript is useful for detecting non-polygenic pleiotropy and can be integrated with other biomarkers to test biologically driven hypotheses. The combination of genetic, molecular, and neuroimaging measures may be additionally helpful for detecting and quantifying the biochemical effects of therapeutic interventions.
