Elucidating the Joint Genetic Architecture of Mood Disorder and Schizophrenia

IntroductionRecent advances in psychiatric genomics have enabled large-scale genome-wide scans that elucidated genetic architecture both in mood disorder and schizophrenia across individuals of East Asian and European descent. Investigating joint genetic architecture of these psychiatric traits enables the identification of common and diverging etiological mechanisms underlying these psychiatric illnesses. Here, we leverage on the largest GWAS of schizophrenia and mood disorder conducted to date in East Asian and European descent samples to elucidate the joint genetic architecture that underlie these psychiatric disorders. MethodologyWe carried out GWAS meta-analysis on both European (EUR) and East Asian (EAS) Ancestry summary statistics for Major Depressive Disorder (MDD) and Schizophrenia via Multi-Trait Analysis of GWAS. Downstream pathway, eQTL, chromatin interaction analysis were carried out to characterize genome-wide results. In addition we carried out genetic correlations and polygenic risk prediction analysis to further study the joint genetic architectures of mood disorder and schizophrenia. ResultsThere were 308 loci that was significantly associated with at least one trait. Specifically, there were 98 independent loci in EUR-MDD, 5 loci for MTAGx-EAS-MDD, 121 loci for MTAGx-EUR-MDD, 8 independent loci for EAS-SZ, 171 independent loci for EUR-SZ, 124 independent loci for MTAGx-EAS-SZ, and 159 independent loci for MTAGx-EUR-SZ. In all, 61 loci were novel across traits. SOAT1 and FOXO3 genes were implicated based on genome-wide associations. 114 gene(s) were implicated in eQTL analysis of gene expression in brain tissue. Gene-set analysis show support for GABA-egic pathways implicated in MDD, driven by several GABA-alpha receptor genes as well as more peripheral PLCL1 and NISCH genes that are responsible for endocytosis and neuronal trafficking. Cross-Ancestry genetic correlations ascertained that the CONVERGE MDD phenotype generally holds higher SNP based heritability and is likely driven by case-ascertainment procedures. Finally, polygenic risk score modelling indicates that MTAGx procedures were effective in enriching GWAS signals in the EAS-MDD for prediction in an independent case-control sample. DiscussionHere we are able to demonstrate that cross-trait cross-ancestry approaches in schizophrenia and MDD not only yields new discoveries to the genetic architecture of these illnesses; we were able to identify new biological underpinnings within the GABA pathways for depressive disorders. The evidence in the current report underscores the importance of taking into consideration both phenotype and ancestry complexities in genome-wide studies.