A translational data integration platform for the stratification of patients based on clinical, laboratory and magnetic resonances imaging

转化生物医学研究依赖于多个数据集的整合，这些数据集共同代表了患者在健康和疾病状态之间过渡的复杂的大量特征。联合王国有几项举措，旨在纵向调查疾病的发作和进展，特别适合研究。英国生物银行（UKB）收集了超过50万名健康人的临床数据，旨在收集10万份大脑、心脏和腹部等身体各部位的磁共振图像扫描，以及参与者的骨组织结构和颈动脉超声信息。这些成像数据正在与遗传数据和来自详细受试者评估的详细临床信息以及相关的电子健康记录相结合。与主要健康的UKB队列相比，Barts心脏中心自2014年以来招募了14，000多名患者，以创建Barts BioResource（BBR），旨在为心血管研究创建丰富的信息资源，将组学，成像和EHR联系起来。为了加快使用这些前所未有的数据集的翻译研究，确保这些数据集的来源信息，收集它们的精确方法并将它们集成到一个主要的统一数据库系统中至关重要。UKB和BBR队列共同代表了健康和心血管疾病之间的全部谱。与此同时，欧盟委员会（EC）与欧洲制药工业协会（EFPIA）共同资助了eTRIKS项目（2012-2018），以部署可持续的开源数据和知识管理平台来支持转化研究：transSMART。该系统支持多种数据，并已成功应用于多个项目，（例如U-BIOPRED、MRC分层医学项目（PSORT、MATURA、RA-MAP、IMID-BIO、CLUSTER和MASTERPLANS））和英国以外的地区（例如AETIONOMY）。transSMART的新功能允许整合研究元数据;沿着各种分类和数值数据（如红细胞计数）以及OMICS数据（如基因表达、基因组拷贝数变异和小核苷酸多态性、肽和代谢物分析）。该工具transSMART允许编程数据访问，用于使用各种软件生成计算工作流。通过eTRIKS和AETIONOMY项目之间的合作，一个名为BrainMesh的新软件概念在加州大学（美国圣地亚哥）举行的transSMART基金会年会（2016年）上获得了最佳海报奖;该奖项被认为是围绕transSMART环境的有前途的未来技术。通过新开发的软件组件SmartR，BrainMesh与transSMART的新视觉分析功能一起，为transSMART增加了一个全新的动态视觉分析概念，例如允许以集成方式对临床和图像数据进行视觉分析。 在本提案中，我们的目标是将完整的UKB和BBR心血管MRI队列纳入专用（不同）transSMART环境中，在该环境中可以执行多个分析工作流程，以便对共享共同健康数据特征的患者进行分层，为这些队列以及希望使用该平台的未来项目中的数据挖掘和发现铺平道路。

Translational biomedicine studies depend on the integration of multiple datasets that, together, represent the complex plethora of features from patients transiting between health and disease states. The UK has several initiatives which aim to investigate disease onset and progression on a longitudinal basis which are particularly suited for research. The UK Biobank (UKB) has a clinical data collection comprised of more than 500,000 healthy individuals, with aims to collect 100,000 magnetic resonance image scans of various body parts such as brain, heart and abdomen, as well as information about the bone tissue structure and ultrasound of the carotid arteries from participants. This imaging data is being integrated with genetic data and detailed clinical information derived from detailed subject assessments and linked electronic health records. By comparison to the mainly healthy UKB cohort, the Barts Heart Centre has recruited over 14,000 patients since 2014 to create the Barts BioResource (BBR), which aims to create a rich information resource for cardiovascular research, linking omics, imaging and EHR. In order to speed-up translational research using these unprecedented datasets, it is of utmost importance to guarantee the information about the origin of these datasets, the precise methods that they were collected and integrate them in a major unified database system. The UKB and BBR cohorts collectively represent the full spectrum between health and cardiovascular disease. In parallel, the European Commission (EC) together with the European Association of Pharmaceutical Industries and Associations (EFPIA) funded the eTRIKS project (2012-2018) to deploy a sustainable open-source data and knowledge management platform to support translational research: tranSMART. This system supports a wide variety of data and has been successfully applied to various projects within (e.g. U-BIOPRED, MRC Stratified Medicine projects (PSORT, MATURA, RA-MAP, IMID-BIO, CLUSTER and MASTERPLANS)) and beyond the UK (e.g. AETIONOMY).The new capabilities of tranSMART allow the integration of study metadata; various categorical and numerical data (e.g. red-blood cells counts) along with OMICS data (e.g. gene expression, genomic copy number variation and small nucleotide polymorphisms, peptides & metabolite profiling). The tool tranSMART allows programmatic data access for the generation of computational workflows using a large variety of software. From the collaboration between the projects eTRIKS and AETIONOMY, a new software concept called BrainMesh raised and prized the best-poster award from the tranSMART Foundation Annual Meeting (2016) at the University of California (San Diego - US); featuring as promising future technology around the tranSMART environment. Together with the new visual analytical features of tranSMART, via the newly developed software component SmartR, BrainMesh adds a completely new dynamic visual analytics concept to tranSMART, such as allowing the visual analysis of clinical and image-derived data in a integrated fashion. In this proposal, we aim to include the complete UKB and BBR cardiovascular MRI cohorts into dedicated (distinct) tranSMART environments where multiple analytical workflows could be executed in order to stratify patients that share common health data features, paving the way for data mining and discovery in these cohorts and in future projects that desire to use the platform.