Molecular Phenotyping of Autoimmunity in Tribal Members: Aiding Precision Medicine and Tribal Student Training

项目摘要： 美国印第安人（AI）的预期寿命最短，地理不平等甚至更多 在农村县，如切罗基民族集水区的那些县。这些发现的原因 是多因素的，并受到许多慢性健康状况的不良结果的影响，如 风湿性疾病不幸的是，美国部落成员有一些风湿性疾病的发病率最高， 国家，包括疾病，如系统性红斑狼疮（SLE），类风湿性关节炎（RA）， 系统性硬化症为了帮助解决这些健康不平等问题，该项目旨在了解分子生物学。 俄克拉荷马州部落患者加速衰老的免疫表型和潜在机制， 为诊断和治疗提供信息。OMRF、OUHSC和切罗基民族一起聚集在一起， 风湿性疾病研究和基础设施，这是该项目成功的关键， 作为来自454名AI SLE患者、190名AI RA患者和300名AI RA患者的样本和相关临床数据的收集， 对照，以及数千名其他患者和其他种族/民族背景的对照。部落 风湿病诊所又招募了273名部落风湿病患者。联合调查结果， 数据包括：部落人群常见风湿性疾病的重叠特征（没有 符合标准分类标准），疾病特异性自身抗体标志物不存在于美国人中。 印度患者，以及高达41%的AI SLE患者， 自身抗体一些未知的SLE特异性针对线粒体或肌炎特异性 抗原基于这些结果，该应用程序汇集了三种尖端的科学方法， 精准医学/深度分子表型分析、大数据分析/可视化和分子机制 加速老化，以确定AI风湿病患者的失调途径。 我们将通过以下目标来解决相关假设：（1）进行全面的 自身免疫性疾病的血清学、基因表达和细胞学证据的分子表型评价- 与匹配的对照组相比，美国印第安人SLE或RA患者的相关变化， 独特而重要的疾病途径，这些途径在AI自身免疫中富集。(2)评估美国印第安人 风湿性自身免疫性疾病患者加速衰老的分子证据。我们的主要人员 指导20多名美国印第安学生获得高等学位和学术、医疗和部落服务 医生、医生助理和科学家等职业。该项目为部落提供额外培训， 学生，最初的三个已经确定。临床研究、数据管理、数据分析、 将向部落学生和研究人员提供临床免疫学和精准医学， 专注于识别分子信息，以选择和完善合理的，定向的治疗方法，以改善AI 风湿性疾病患者结局。

Project Summary: American Indians (AIs) have some of the shortest life-expectancies with geographic inequalities even more pronounced in rural counties like those in the Cherokee Nation catchment area. The causes for these findings are multi-factorial and are impacted by poorer outcomes in many chronic health conditions, such as the rheumatic diseases. Unfortunately, US tribal members have some of the highest rates of rheumatic disease in the nation, including diseases such as systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), and systemic sclerosis. To help address these health inequalities, this project seeks to understand the molecular immunologic phenotypes and potential mechanisms of accelerated aging in Oklahoma tribal patients to better inform diagnosis and treatments. Together, OMRF, OUHSC and the Cherokee Nation have assembled rheumatic disease research and infrastructure which are critical for the success of this proposed project, such as collections of samples and associated clinical data from 454 AI SLE patients, 190 AI RA patients and 300 AI controls, as well as thousands of additional patients and controls of other racial/ethnic backgrounds. Tribal NARCH rheumatology clinics have enrolled 273 additional tribal rheumatic disease patients. Joint findings to date include: it is common for tribal populations to have overlapping features of rheumatic disease (without meeting standard classification criteria), disease-specific autoantibody markers are not present in American Indian patients, and up to 41% of AI SLE patients have high concentrations of previously unidentified autoantibodies. Some unknown SLE specificities are directed against mitochondrial or myositis-specific antigens. Based upon these results, this application brings together three cutting-edge scientific approaches, precision medicine/deep molecular phenotyping, big data analytics/visualization and molecular mechanisms of accelerated aging, to identify dysregulated pathways in AI rheumatic disease patients. We will address the associated hypotheses through the following aims: (1) Perform a comprehensive molecular phenotypic evaluation of serologic, gene expression and cellular evidence of autoimmune disease- associated changes in American Indian patients with SLE or RA compared to matched controls to identify unique and important disease pathways which are enriched in AI autoimmunity. (2) Evaluate American Indian rheumatic autoimmune disease patients for molecular evidence of accelerated aging. Our key personnel have mentored over 20 American Indian students to advanced degrees and academic, medical and tribal service careers as physicians, physician assistants, and scientists. This project provides additional training to tribal students, with the initial three already identified. Training in clinical research, data management, data analytics, clinical immunology and precision medicine will be provided to the tribal students and investigators, which focuses on identifying molecular information to select and refine rational, directed therapies to improve AI rheumatic disease patient outcomes.