Integrative analysis of high dimensional tissue molecular data to define key biological systems in autoimmune diseases (SBC)

项目概要/摘要 在这里，我们提出了一个系统生物学核心（SBC），以加速自身免疫药物的合作伙伴关系。 免疫介导疾病（AMP AIM）AMP AIM将使用高维分子和细胞 用于确定组织炎症和损伤的关键细胞状态、途径和分子组分的测定 通过检查病人的组织和血液样本最终，我们试图定义组织的成分 自身免疫性和炎性疾病中的炎症，包括银屑病谱系疾病（PSD）， 类风湿性关节炎（RA）、系统性红斑狼疮（SLE）、舍格伦综合征（SS）和其他相关疾病 条件AMP RA/SLE通过查询炎症RA滑膜和SLE中的106个单细胞启动了这一过程 肾炎组织样本使用多模式策略;它定义了组织炎症中的关键细胞状态，包括 T外周辅助性T细胞（Tph）、GZMK + CD8 + T细胞、HLA-DR + THY1+成纤维细胞和自身免疫性- 相关B细胞（ABC）。现在，为了理解这些和新兴的细胞状态如何发挥作用和相互作用， 导致疾病，因此必须获得一系列患者样本数据的高维数据 疾病和疾病亚表型。这些数据可以捕获细胞状态; 细胞状态、蛋白质和转录物;组织学特征;以及其他组织参数。一个强大而熟练的 一个能够定义策略来分析这些数据、集成多种数据形式并集成 来自各种疾病和组织的结果对于该计划的成功至关重要。 我们凭借在加速药物领域领导系统生物学小组的经验， 风湿性关节炎和系统性红斑狼疮（AMP RA/SLE）。我们建立了一个团队 擅长分析不同的模态和计算生物学。我们有具体的经验， 炎症性疾病的专业知识。在此，我们建议： (1)开发工具和技术来分析高维细胞和分子数据。这包括 优化现有的生物信息学和计算工具。它还包括开发新的 计算和统计方法来整合疾病的高维数据表现。 (2)支持整个网络的协作并促进系统级分析。我们设想， 是与网络的集成活动，我们将设计并最终创建一个集成的 跨疾病的组织炎症模型，以定义驱动临床疾病的特征。这将 需要开发新的统计和计算方法。这也将要求严格 网络内的协作，包括数据同步、存储、共享和临床数据 一体化此外，我们还将通过提供咨询、技术支持和 培训高维数据分析。 .

PROJECT SUMMARY/ABSTRACT Here we propose a Systems Biology Core (SBC) for the Accelerating Medicines Partnerships in Autoimmune and Immune-Mediated Diseases (AMP AIM). The AMP AIM will use high dimensional molecular and cellular assays to define the key cell states, pathways, and molecular components of tissue inflammation and damage by examining patient tissue and blood samples. Ultimately, we seek to define the components of tissue inflammation in autoimmune and inflammatory diseases including psoriatic spectrum diseases (PSD), rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), Sjogren’s syndrome (SS), and other related conditions. AMP RA/SLE initiated this process by querying 106 single cells in inflamed RA synovial and SLE nephritis tissue samples using multimodal strategies; it defined key cell states in tissue inflammation, including T peripheral helper T cells (Tph), GZMK+ CD8+ T cells, HLA-DR+THY1+ fibroblasts, and autoimmune- associated B cells (ABCs). Now, to understand how these and emerging cell-states function and interact to cause disease, it will be essential to obtain high dimensional data on patient sample data across a spectrum of diseases and disease sub-phenotypes. These data may capture the cellular states; the spatial localization of cell states, proteins and transcripts; histological features; and other tissue parameters. A powerful and skilled team that is able to define strategies to analyze this data, integrate multiple modalities of data, and integrate results from across a diverse set of diseases and tissues will be essential to the success of this program. We build from our experience leading the Systems Biology Group within the Accelerating Medicines Partnerships Rheumatoid Arthritis and Systemic Lupus Erythematosus (AMP RA/SLE). We have built a team that is skilled at analysis of diverse modalities and computational biology. We have specific experience and expertise in inflammatory diseases. Here we propose to: (1) Develop Tools and Technology to analyze high dimensional cellular and molecular data. This includes optimizing existing bioinformatics and computational tools. It also includes developing new computational and statistical methods to integrate high dimensional data manifestation of disease. (2) Enable collaboration throughout the network and facilitate systems level analysis. We envision that this is an integrated activity with the network, where we will devise and ultimately create an integrated model of tissue inflammation across diseases to define features that drive clinical disease. This will require the development of new statistical and computational methods. It will also require tight collaboration within the network including data synchronization, storage, sharing, and clinical data integration. In addition, we will engage the network by offering consultation, technical support and training in high dimensional data analysis. .