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

项目摘要/摘要 在这里，我们提出了一个系统生物学核心(SBC)来加速自身免疫中的药物伙伴关系 和免疫介导性疾病(AMP AIM)。AMP AIM将使用高维分子和细胞 确定组织炎症和损伤的关键细胞状态、途径和分子成分的分析 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 自身免疫性和炎症性疾病中的炎症，包括银屑病谱系疾病(PSD)， 类风湿关节炎(RA)、系统性红斑狼疮(SLE)、干燥综合征(SS)及其他相关疾病 条件。AMP RA/SLE通过询问发炎的RA滑膜和SLE中的106个单个细胞启动了这一过程 使用多模式策略的肾炎组织样本；它定义了组织炎症中的关键细胞状态，包括 T辅助T细胞(TPH)，GZMK CD8 T细胞，HLA-DR THY1成纤维细胞，以及自身免疫- 相关B细胞(ABC)。现在，为了了解这些和新兴的细胞状态是如何发挥作用和相互作用的 导致疾病，因此必须获得关于患者样本数据的高维数据 疾病和疾病亚型。这些数据可以捕捉细胞的状态；空间定位 细胞状态、蛋白质和转录本；组织学特征；以及其他组织参数。一个强大而熟练的 能够定义分析此数据的策略、集成多个数据通道以及集成 来自不同疾病和组织的结果将是这一计划成功的关键。 我们建立在我们的经验基础上，领导系统生物学小组在加速药物 类风湿性关节炎和系统性红斑狼疮(AMP RA/SLE)的伙伴关系。我们已经建立了一支团队 擅长分析各种形态和计算生物学。我们有特定的经验和 炎症性疾病方面的专业知识。在此，我们建议： (1)开发分析高维细胞和分子数据的工具和技术。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，整合疾病的高维数据表现形式。 (2)实现整个网络的协作，促进系统级分析。我们设想这一点 是与网络集成的活动，我们将在其中设计并最终创建集成的 跨疾病的组织炎症模型，以定义驱动临床疾病的特征。这将是 需要开发新的统计和计算方法。它还需要紧凑的 网络内的协作，包括数据同步、存储、共享和临床数据 整合。此外，我们将通过提供咨询、技术支持和 高维数据分析方面的培训。 。

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. .