Pathogenesis of Primary Biliary Cholangitis

项目摘要/摘要 这项建议的主要目标是进行第一个初级胆汁的多组学翻译研究 胆管炎(PBC)，从而确定在这一罕见的、 自身免疫性肝病。迫切需要更好地了解PBC的发病机制 护理和开发新的有效疗法。全面评估免疫力和免疫系统的作用 目前，建设和平委员会缺乏环境影响。这种评价将为以下工作提供关键知识 利用该领域在药理上改变免疫系统能力方面的最新进展，从而提供 给PBC患者带来了新的希望。在理解基因组方面做出了重大贡献 在PBC自身免疫发展的基础上，我们提出了一种新的、面向患者的、多学科的 组学方法。在这一新的应用中，我们将破译外周细胞免疫和非细胞免疫 循环因素参与了PBC的发病。我们假设多种经济分析整合在一起 细胞和非细胞因素将确定驱动PBC发病的系统水平的途径。为了测试 在这一假设下，我们开发了一个结合了机器学习和量子理论的创新平台 结合临床特征确定PBC的组学特征的统计机制 将揭示驱动疾病发病机制的生物途径。 为了对PBC进行这种多学科的研究，我们组建了一支世界级的、多学科的团队 协同PBC生物学和组学规模分析方面的专业知识以及梅奥诊所和 哥伦比亚大学。通过一个新的，手头收集的来自300个深度不同的生物标本- 表型PBC患者和300名配对良好的对照，我们的研究已经在进行中，初步 展示可测量的免疫组、甲基组、炎性蛋白、暴露组和代谢组的数据 PBC患者与对照组之间的差异。在目标1中，我们彻底评估了外周免疫 组成(免疫组)和激活状态(甲基组、转录组、炎症蛋白)使用 基于质量细胞分析(CyTOF)、测序和邻近延伸的方法。在目标2中，我们执行一个 外源化学物质“暴露组”和内源性代谢物“代谢组”的前沿研究 使用超高分辨率质谱仪发现PBC代谢的病原性改变。我们 此外，还开发了一种量化血液中肝脏特异性无细胞DNA的方法，以此作为衡量疾病严重程度的指标。在AIM 3，我们集成了特定于基因组的签名(目标1和2)，使用一种新的方法来识别和优先排序PBC- 用于进一步生物学研究的相关特征。然后我们推断出与临床相关的PBC亚群 通过对患者进行相似度网络融合分析。总而言之，使用最先进的、多学科的 分析，我们将发现驱动PBC发病的系统级网络，刺激新的发展 旨在阐明PBC病理生物学和确定新疗法的假设和研究。

PROJECT SUMMARY/ABSTRACT The major goal of this proposal is to conduct the first multi-omics translational study of Primary Biliary Cholangitis (PBC), thereby identifying the systems-level networks driving pathological processes in this rare, autoimmune liver disease. Improved understanding of PBC pathogenesis is urgently needed to inform tailored care and the development of new effective therapies. Comprehensive assessments of immunity and the role of environmental influence in PBC are currently lacking. Such evaluations would provide critical knowledge to leverage recent advances in the field’s ability to pharmacologically alter the immune system, thereby providing new hope to PBC patients. Having made significant contributions to the understanding of the genomic architecture underlying development of autoimmunity in PBC, we propose a novel, patient-oriented, multi- omics approach. In this new application, we will decipher how peripheral cellular immunity and non-cellular circulating factors contribute to PBC pathogenesis. We hypothesize that multi-omic analyses integrating cellular and non-cellular factors will identify systems-level pathways driving PBC pathogenesis. To test this hypothesis, we develop an innovative platform that combines aspects of machine learning and quantum statistical mechanics to identify omics-based signatures of PBC that when integrated with clinical features will unveil biological pathways driving disease pathogenesis. To perform this multi-omic study of PBC, we have assembled a world-class, multi-disciplinary team synergizing expertise in PBC biology and omics-scale analytics as well as resources across Mayo Clinic and Columbia University. With a new, in-hand collection of diverse biological specimens from 300 deeply- phenotyped PBC patients and 300 well-matched controls, our studies are already underway with preliminary data demonstrating measureable immunome, methylome, inflammatory protein, exposome, and metabolome differences between PBC patients and controls. In Aim 1, we thoroughly evaluate peripheral immune composition (the immunome) and activation state (methylome, transcriptome, inflammatory proteins) using mass-cytometry (CyTOF), sequencing- and proximity extension-based methods. In Aim 2, we perform a cutting-edge study of exogenous chemicals “the exposome” and endogenous metabolites “the metabolome” using ultrahigh resolution mass spectroscopy to discover pathogenic alterations in metabolism in PBC. We also develop an assay to quantify liver-specific cell-free DNA in blood as a measure of disease severity. In Aim 3, we integrate omic-specific signatures (Aims 1 and 2) using a novel approach to identify and prioritize PBC- associated features for further biological investigation. We then infer clinically-relevant subgroups of PBC patients by performing similarity network fusion analysis. In summary, using state-of-the-art, multi-omic analyses, we will discover systems-level networks driving PBC pathogenesis, spurring development of new hypotheses and studies designed to elucidate PBC pathobiology and identify novel therapies.