Wu Yong, Yao Yong-Gang, Luo Xiong-Jian
Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Kunming, China.
Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China.
Schizophr Bull. 2017 Mar 1;43(2):459-471. doi: 10.1093/schbul/sbw102.
Schizophrenia (SZ) is a debilitating brain disorder with a complex genetic architecture. Genetic studies, especially recent genome-wide association studies (GWAS), have identified multiple variants (loci) conferring risk to SZ. However, how to efficiently extract meaningful biological information from bulk genetic findings of SZ remains a major challenge. There is a pressing need to integrate multiple layers of data from various sources, eg, genetic findings from GWAS, copy number variations (CNVs), association and linkage studies, gene expression, protein-protein interaction (PPI), co-expression, expression quantitative trait loci (eQTL), and Encyclopedia of DNA Elements (ENCODE) data, to provide a comprehensive resource to facilitate the translation of genetic findings into SZ molecular diagnosis and mechanism study. Here we developed the SZDB database (http://www.szdb.org/), a comprehensive resource for SZ research. SZ genetic data, gene expression data, network-based data, brain eQTL data, and SNP function annotation information were systematically extracted, curated and deposited in SZDB. In-depth analyses and systematic integration were performed to identify top prioritized SZ genes and enriched pathways. Multiple types of data from various layers of SZ research were systematically integrated and deposited in SZDB. In-depth data analyses and integration identified top prioritized SZ genes and enriched pathways. We further showed that genes implicated in SZ are highly co-expressed in human brain and proteins encoded by the prioritized SZ risk genes are significantly interacted. The user-friendly SZDB provides high-confidence candidate variants and genes for further functional characterization. More important, SZDB provides convenient online tools for data search and browse, data integration, and customized data analyses.
精神分裂症(SZ)是一种具有复杂遗传结构的使人衰弱的脑部疾病。遗传研究,尤其是最近的全基因组关联研究(GWAS),已经鉴定出多个赋予SZ患病风险的变异(位点)。然而,如何从SZ的大量遗传研究结果中有效地提取有意义的生物学信息仍然是一个重大挑战。迫切需要整合来自各种来源的多层数据,例如GWAS的遗传研究结果、拷贝数变异(CNV)、关联和连锁研究、基因表达、蛋白质-蛋白质相互作用(PPI)、共表达、表达定量性状位点(eQTL)以及DNA元件百科全书(ENCODE)数据,以提供一个全面的资源,促进将遗传研究结果转化为SZ分子诊断和机制研究。在这里,我们开发了SZDB数据库(http://www.szdb.org/),这是一个用于SZ研究的综合资源。我们系统地提取、整理并将SZ遗传数据、基因表达数据、基于网络的数据、脑eQTL数据以及SNP功能注释信息存放在SZDB中。进行了深入分析和系统整合,以确定最优先的SZ基因和富集的通路。来自SZ研究各层面的多种类型数据被系统地整合并存放在SZDB中。深入的数据分析和整合确定了最优先的SZ基因和富集的通路。我们进一步表明,与SZ相关的基因在人类大脑中高度共表达,并且优先的SZ风险基因编码的蛋白质之间存在显著相互作用。用户友好的SZDB提供了高可信度的候选变异和基因,用于进一步的功能表征。更重要的是,SZDB提供了方便的在线工具,用于数据搜索和浏览、数据整合以及定制数据分析。