Abstract：
BACKGROUND: It is valuable to analyze the genome-wide association studies (GWAS) data for a complex disease phenotype in the context of the protein-protein interaction (PPI) network, as the related pathophysiology results from the function of interacting polyprotein pathways. The analysis may include the design and curation of a phenotype-specific GWAS meta-database incorporating genotypic and eQTL data linking to PPI and other biological datasets, and the development of systematic workflows for PPI network-based data integration toward protein and pathway prioritization. Here, we pursued this analysis for blood pressure (BP) regulation.
METHODS: The relational scheme of the implemented in Microsoft SQL Server BP-GWAS meta-database enabled the combined storage of: GWAS data and attributes mined from GWAS Catalog and the literature, Ensembl-defined SNP-transcript associations, and GTEx eQTL data. The BP-protein interactome was reconstructed from the PICKLE PPI meta-database, extending the GWAS-deduced network with the shortest paths connecting all GWAS-proteins into one component. The shortest-path intermediates were considered as BP-related. For protein prioritization, we combined a new integrated GWAS-based scoring scheme with two network-based criteria: one considering the protein role in the reconstructed by shortest-path (RbSP) interactome and one novel promoting the common neighbors of GWAS-prioritized proteins. Prioritized proteins were ranked by the number of satisfied criteria.
RESULTS: The meta-database includes 6687 variants linked with 1167 BP-associated protein-coding genes. The GWAS-deduced PPI network includes 1065 proteins, with 672 forming a connected component. The RbSP interactome contains 1443 additional, network-deduced proteins and indicated that essentially all BP-GWAS proteins are at most second neighbors. The prioritized BP-protein set was derived from the union of the most BP-significant by any of the GWAS-based or the network-based criteria. It included 335 proteins, with ~ 2/3 deduced from the BP PPI network extension and 126 prioritized by at least two criteria. ESR1 was the only protein satisfying all three criteria, followed in the top-10 by INSR, PTN11, CDK6, CSK, NOS3, SH2B3, ATP2B1, FES and FINC, satisfying two. Pathway analysis of the RbSP interactome revealed numerous bioprocesses, which are indeed functionally supported as BP-associated, extending our understanding about BP regulation.
CONCLUSIONS: The implemented workflow could be used for other multifactorial diseases.
METHODS: The relational scheme of the implemented in Microsoft SQL Server BP-GWAS meta-database enabled the combined storage of: GWAS data and attributes mined from GWAS Catalog and the literature, Ensembl-defined SNP-transcript associations, and GTEx eQTL data. The BP-protein interactome was reconstructed from the PICKLE PPI meta-database, extending the GWAS-deduced network with the shortest paths connecting all GWAS-proteins into one component. The shortest-path intermediates were considered as BP-related. For protein prioritization, we combined a new integrated GWAS-based scoring scheme with two network-based criteria: one considering the protein role in the reconstructed by shortest-path (RbSP) interactome and one novel promoting the common neighbors of GWAS-prioritized proteins. Prioritized proteins were ranked by the number of satisfied criteria.
RESULTS: The meta-database includes 6687 variants linked with 1167 BP-associated protein-coding genes. The GWAS-deduced PPI network includes 1065 proteins, with 672 forming a connected component. The RbSP interactome contains 1443 additional, network-deduced proteins and indicated that essentially all BP-GWAS proteins are at most second neighbors. The prioritized BP-protein set was derived from the union of the most BP-significant by any of the GWAS-based or the network-based criteria. It included 335 proteins, with ~ 2/3 deduced from the BP PPI network extension and 126 prioritized by at least two criteria. ESR1 was the only protein satisfying all three criteria, followed in the top-10 by INSR, PTN11, CDK6, CSK, NOS3, SH2B3, ATP2B1, FES and FINC, satisfying two. Pathway analysis of the RbSP interactome revealed numerous bioprocesses, which are indeed functionally supported as BP-associated, extending our understanding about BP regulation.
CONCLUSIONS: The implemented workflow could be used for other multifactorial diseases.
摘要：
背景：在蛋白质-蛋白质相互作用（PPI）网络的背景下，分析复杂疾病表型的全基因组关联研究（GWAS）数据是有价值的，因为相关的病理生理学是由相互作用的多蛋白途径的功能引起的。分析可能包括设计和管理表型特异性GWAS元数据库，其中包含与PPI和其他生物学数据集相关的基因型和eQTL数据。以及为基于PPI网络的数据集成开发系统的工作流程，以实现蛋白质和途径优先排序。这里,我们对血压（BP）调节进行了这项分析。
方法：在MicrosoftSQLServerBP-GWAS元数据库中实现的关系方案实现了组合存储：GWAS数据和从GWAS目录和文献中挖掘的属性，Ensembl定义的SNP转录本关联，和GTExeQTL数据。从PICKLEPPImeta数据库重建了BP蛋白相互作用组，扩展GWAS推导的网络，将所有GWAS蛋白连接到一个组件中的最短路径。最短路径中间体被认为是BP相关的。对于蛋白质优先排序，我们将一个新的基于GWAS的综合评分方案与两个基于网络的标准结合起来:一个标准考虑了蛋白质在通过最短路径(RbSP)相互作用的重建组中的作用,另一个新的标准是促进GWAS优先蛋白质的共同邻居.按满足的标准的数量对优先的蛋白质进行排序。
结果：元数据库包括与1167个BP相关蛋白编码基因相关的6687个变异体。GWAS推导的PPI网络包括1065种蛋白质，672形成一个连接的组件。RbSP相互作用组包含1443个额外的，网络推导的蛋白质，表明基本上所有的BP-GWAS蛋白最多是第二邻居。通过基于GWAS或基于网络的标准中的任一个,从最显著的BP的联合中导出优先的BP-蛋白质组。它包括335种蛋白质，从BPPPI网络扩展中推导出~2/3，至少有两个标准确定了126个优先级。ESR1是唯一满足所有三个标准的蛋白质，排在前十名的是INSR，PTN11,CDK6,CSK,NOS3，SH2B3，ATP2B1，FES和FINC，满足两个RbSP相互作用组的途径分析揭示了许多生物过程，实际上在功能上支持与BP相关的功能，扩展了我们对BP监管的理解。
结论：实施的工作流程可用于其他多因素疾病。
方法：在MicrosoftSQLServerBP-GWAS元数据库中实现的关系方案实现了组合存储：GWAS数据和从GWAS目录和文献中挖掘的属性，Ensembl定义的SNP转录本关联，和GTExeQTL数据。从PICKLEPPImeta数据库重建了BP蛋白相互作用组，扩展GWAS推导的网络，将所有GWAS蛋白连接到一个组件中的最短路径。最短路径中间体被认为是BP相关的。对于蛋白质优先排序，我们将一个新的基于GWAS的综合评分方案与两个基于网络的标准结合起来:一个标准考虑了蛋白质在通过最短路径(RbSP)相互作用的重建组中的作用,另一个新的标准是促进GWAS优先蛋白质的共同邻居.按满足的标准的数量对优先的蛋白质进行排序。
结果：元数据库包括与1167个BP相关蛋白编码基因相关的6687个变异体。GWAS推导的PPI网络包括1065种蛋白质，672形成一个连接的组件。RbSP相互作用组包含1443个额外的，网络推导的蛋白质，表明基本上所有的BP-GWAS蛋白最多是第二邻居。通过基于GWAS或基于网络的标准中的任一个,从最显著的BP的联合中导出优先的BP-蛋白质组。它包括335种蛋白质，从BPPPI网络扩展中推导出~2/3，至少有两个标准确定了126个优先级。ESR1是唯一满足所有三个标准的蛋白质，排在前十名的是INSR，PTN11,CDK6,CSK,NOS3，SH2B3，ATP2B1，FES和FINC，满足两个RbSP相互作用组的途径分析揭示了许多生物过程，实际上在功能上支持与BP相关的功能，扩展了我们对BP监管的理解。
结论：实施的工作流程可用于其他多因素疾病。
