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

基于临床、实验室和磁共振成像的患者分层转化数据集成平台

• 批准号: MR/S003827/1
• 负责人: Adriano Barbosa Da Silva
• 金额: $ 38.17万
• 依托单位: Queen Mary University of London
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FS003827%2F1
• 关键词: translational; data; integration; platform; stratification

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.

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转变的复杂特征。英国有几项旨在纵向调查疾病发病和进展的举措，这些举措特别适合研究。英国生物银行（UKB）拥有超过50万名健康个体的临床数据收集，旨在收集参与者大脑、心脏和腹部等不同身体部位的1​​0万张磁共振图像扫描，以及有关骨组织结构和颈动脉超声的信息。该成像数据正在与遗传数据以及从详细的受试者评估和链接的电子健康记录中得出的详细临床信息相集成。与主要健康的 UKB 队列相比，Barts 心脏中心自 2014 年以来已招募了超过 14,000 名患者来创建 Barts BioResource (BBR)，旨在为心血管研究创建丰富的信息资源，将组学、影像学和 EHR 连接起来。为了加速利用这些前所未有的数据集的转化研究，最重要的是保证这些数据集的来源、收集数据的精确方法以及将它们集成到一个主要的统一数据库系统中的信息。 UKB 和 BBR 队列共同代表了健康和心血管疾病之间的全部范围。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 年），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：tranSMART。该系统支持多种数据，并已成功应用于英国境内（例如 U-BIOPRED、MRC 分层医学项目（PSORT、MATURA、RA-MAP、IMID-BIO、CLUSTER 和 MASTERPLANS））和英国境外（例如 AETIONOMY）的各种项目。tranSMART 的新功能允许整合研究元数据；各种分类和数值数据（例如红细胞计数）以及组学数据（例如基因表达、基因组拷贝数变异和小核苷酸多态性、肽和代谢物分析）。 tranSMART 工具允许使用多种软件以编程方式访问数据以生成计算工作流程。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）举办的 tranSMART 基金会年会（2016 年）中获得了最佳海报奖；围绕 tranSMART 环境，该技术被认为是有前景的未来技术。结合 tranSMART 的新视觉分析功能，通过新开发的软件组件 SmartR，BrainMesh 为 tranSMART 添加了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衍生数据进行视觉分析。 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）的 tranSMART 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，为这些队列中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。

项目成果

Data and knowledge management in translational research: implementation of the eTRIKS platform for the IMI OncoTrack consortium.

转化研究中的数据和知识管理：为 IMI OncoTrack 联盟实施 eTRIKS 平台。

• DOI: 10.1186/s12859-019-2748-y
• 发表时间: 2019
• 期刊: BMC bioinformatics
• 影响因子: 3
• 作者: Gu W

Presenting and sharing clinical data using the eTRIKS Standards Master Tree for tranSMART.

使用Etriks标准介绍和共享临床数据，用于Transmart。

• DOI: 10.1093/bioinformatics/bty809
• 发表时间: 2019-05-01
• 期刊: Bioinformatics (Oxford, England)
• 作者: Barbosa-Silva A;Bratfalean D;Gu W;Satagopam V;Houston P;Becnel LB;Eifes S;Richard F;Tielmann A;Herzinger S;Rege K;Balling R;Peeters P;Schneider R
• 通讯作者: Schneider R