Introduction: Recent 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. Methodology: We 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. Results: There 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. Discussion: Here 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.

中文翻译：

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阐明情绪障碍和精神分裂症的联合遗传结构

简介：精神病学基因组学的最新进展使大规模的全基因组扫描成为可能，从而阐明了东亚和欧洲血统个体的情绪障碍和精神分裂症的遗传结构。对这些精神病性状的联合遗传结构进行研究使得能够确定这些精神病性病因的共同且不同的病因学机制。在这里，我们利用迄今为止在东亚和欧洲血统样本中进行的最大的精神分裂症和情绪障碍的GWAS来阐明构成这些精神障碍的基础遗传结构。方法：我们通过GWAS的多特征分析，对欧洲（EUR）和东亚（EAS）的重性抑郁症（MDD）和精神分裂症的先祖摘要统计数据进行了GWAS荟萃分析。下游通路 进行了eQTL，染色质相互作用分析以表征全基因组结果。此外，我们进行了遗传相关性和多基因风险预测分析，以进一步研究情绪障碍和精神分裂症的联合遗传结构。结果：308个位点与至少一个性状显着相关。具体而言，EUR-MDD中有98个独立基因座，MTAGx-EAS-MDD中有5个基因座，MTAGx-EUR-MDD有121个基因座，EAS-SZ有8个独立基因座，EUR-SZ有171个独立基因座，EURO-SZ有124个独立基因座。 MTAGx-EAS-SZ，以及159个独立的MTAGx-EUR-SZ基因座。共有61个基因座在各个性状上都是新颖的。SOAT1和FOXO3基因是基于全基因组关联。在脑组织中基因表达的eQTL分析中涉及114个基因。基因组分析显示，MDA牵涉的GABA阳性途径受到多种GABA-α受体基因以及负责胞吞作用和神经元运输的外围PLCL1和NISCH基因的驱动。跨祖先的遗传相关性确定，CONVERGE MDD表型通常具有较高的基于SNP的遗传力，并且很可能是由病例确定程序驱动的。最后，多基因风险评分建模表明，MTAGx程序可以有效地丰富EAS-MDD中的GWAS信号，从而可以在独立的病例对照样本中进行预测。讨论：在这里我们能够证明精神分裂症和MDD中的跨性状跨谱系研究方法不仅为这些疾病的遗传结构带来了新发现；我们能够在GABA途径中确定抑郁症的新生物学基础。本报告中的证据强调了在全基因组研究中同时考虑表型和祖先复杂性的重要性。