Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education and Information Materials and Intelligent Sensing Laboratory of Anhui Province, Institutes of Physical Science and Information Technology, Anhui University, 111 Jiulong Road, Shushan District, Hefei, Anhui 230601, China.
Affiliated Wuhan Mental Health Center, Tongji Medical College, Huazhong University of Science and Technology, 93 Youyi Road, Qiaokou District, Wuhan, Hubei 430030, China.
Database (Oxford). 2022 Jul 2;2022. doi: 10.1093/database/baac049.
Bipolar disorder (BIP) is one of the most common hereditary psychiatric disorders worldwide. Elucidating the genetic basis of BIP will play a pivotal role in mechanistic delineation. Genome-wide association studies (GWAS) have successfully reported multiple susceptibility loci conferring BIP risk, thus providing insight into the effects of its underlying pathobiology. However, difficulties remain in the extrication of important and biologically relevant data from genetic discoveries related to psychiatric disorders such as BIP. There is an urgent need for an integrated and comprehensive online database with unified access to genetic and multi-omics data for in-depth data mining. Here, we developed the dbBIP, a database for BIP genetic research based on published data. The dbBIP consists of several modules, i.e.: (i) single nucleotide polymorphism (SNP) module, containing large-scale GWAS genetic summary statistics and functional annotation information relevant to risk variants; (ii) gene module, containing BIP-related candidate risk genes from various sources and (iii) analysis module, providing a simple and user-friendly interface to analyze one's own data. We also conducted extensive analyses, including functional SNP annotation, integration (including summary-data-based Mendelian randomization and transcriptome-wide association studies), co-expression, gene expression, tissue expression, protein-protein interaction and brain expression quantitative trait loci analyses, thus shedding light on the genetic causes of BIP. Finally, we developed a graphical browser with powerful search tools to facilitate data navigation and access. The dbBIP provides a comprehensive resource for BIP genetic research as well as an integrated analysis platform for researchers and can be accessed online at http://dbbip.xialab.info. Database URL: http://dbbip.xialab.info.
双相情感障碍 (BIP) 是全球最常见的遗传性精神疾病之一。阐明 BIP 的遗传基础将在机制阐述中发挥关键作用。全基因组关联研究 (GWAS) 已成功报道了多个赋予 BIP 风险的易感基因座，从而深入了解其潜在的病理生物学。然而，从与 BIP 等精神疾病相关的遗传发现中提取重要且与生物学相关的数据仍然存在困难。迫切需要一个集成的、全面的在线数据库，以便统一访问遗传和多组学数据，以进行深入的数据挖掘。在这里，我们基于已发表的数据开发了一个用于 BIP 遗传研究的数据库 dbBIP。dbBIP 由几个模块组成，即：(i)单核苷酸多态性 (SNP) 模块，包含大规模 GWAS 遗传汇总统计数据和与风险变异相关的功能注释信息；(ii)基因模块，包含来自不同来源的与 BIP 相关的候选风险基因；(iii)分析模块，提供一个简单易用的界面来分析自己的数据。我们还进行了广泛的分析，包括功能 SNP 注释、整合（包括基于汇总数据的孟德尔随机化和全转录组关联研究）、共表达、基因表达、组织表达、蛋白质-蛋白质相互作用和大脑表达数量性状基因座分析，从而揭示了 BIP 的遗传原因。最后，我们开发了一个带有强大搜索工具的图形浏览器，以方便数据导航和访问。dbBIP 为 BIP 遗传研究提供了一个全面的资源，以及一个集成的分析平台，供研究人员使用，可以在 http://dbbip.xialab.info 上在线访问。数据库网址：http://dbbip.xialab.info。
