AIM-for-RA

RA 的 AIM

• 批准号: 10595666
• 负责人: Jennifer Howitt Anolik
• 金额: $ 160万
• 依托单位: UNIVERSITY OF ROCHESTER
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-03-22 至 2026-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10595666
• 关键词: 3-Dimensional; Address; Affect; Algorithms; Architecture; Area; Arthritis; Artificial Intelligence; Autoantibodies; Autoimmune; B-Lymphocytes; Binding; Biological; Biological Markers; Biological Response Modifier Therapy; Biopsy; Cell Communication; Cells; Characteristics; Classification; Clinical; Clinical Research; Clinical Trials; Complement; Data; Diagnosis; Disease; Disease Outcome; Disease remission; Disease-Modifying Second-Line Drugs; Dissection; Dissociation; Drug Targeting; Early treatment; Enrollment; Ensure; Environmental Exposure; Evolution; Failure; Fibroblasts; Flare; Funding; Generations; Goals; Heterogeneity; Histology; Image; Immune; Immune system; In Situ; Individual; Inflammation; Inflammatory; Knowledge; Longitudinal Studies; Measurement; Mediator; Methotrexate; Molecular; Molecular Analysis; Onset of illness; Oranges; Outcome; Pain; Pathogenesis; Pathogenicity; Pathologic Processes; Pathway interactions; Patient Care; Patient Recruitments; Patients; Pattern; Phenotype; Population; Positioning Attribute; Precision therapeutics; Preparation; Prevention strategy; Process; Protocols documentation; Psoriatic Arthritis; Research Personnel; Rheumatoid Arthritis; Risk; Role; Sampling; Science; Selection for Treatments; Seminal; Site; Specimen; Synovial Cell; Synovial Fluid; Synovial Membrane; Synovitis; Systemic Lupus Erythematosus; Technology; Tissue Sample; Tissues; Treatment Failure; Treatment outcome; United States National Institutes of Health; Variant; adverse outcome; biobank; bone cell; clinical phenotype; cohort; design; disability; disorder prevention; effector T cell; epigenetic regulation; follow-up; high dimensionality; improved; individualized medicine; innovation; joint inflammation; joint injury; monocyte; multimodal data; multimodality; novel; patient retention; personalized therapeutic; phenotypic data; pre-clinical; prevent; prognostic; programs; reconstruction; response; small molecule; standard of care; tissue reconstruction; transcriptomics; translational applications; treatment response; treatment strategy

Rheumatoid arthritis (RA) affects approximately 1% of the population and is characterized by inflammation and joint damage, often leading to considerable disability and pain in both early and established stages. Key areas of unmet need in the field include the: 1) highly heterogeneous and unpredictable disease course, 2) rarity of lasting remissions, 3) failure of currently available treatments to achieve low disease activity and/or limit progressive joint damage in many patients, and 4) lack of robust biomarkers necessary to personalize appropriate treatment strategies. We propose that cellular and molecular variation in synovial tissue underlies this heterogeneity and that understanding the basis for this will improve the prediction of disease course and provide a rationale for the timely selection of precision treatment strategies with higher rates of sustained RA control. Through sustained collaborative global team-science, the AIM-for-RA Team has already developed state-of- the-art protocols that deconstructed RA synovial biopsy tissues - an innovation that profoundly advanced knowledge in cells and pathways involved in RA pathogenesis, identified novel treatment targets, identified disease biomarkers, and opened new opportunities in disease prevention. However, it remains unclear how molecular interactions in the synovium relate to the evolution of defined clinical outcomes, from the at-risk preclinical period to arthritis onset, and then through to synovitis outcome. Therefore, AIM-for-RA Disease Team (DT) aims to relate disease-relevant synovial cellular pathways and dynamic crosstalk to environmental exposures, disease outcomes and treatment response, thereby reconstructing the disease pathogenesis trajectory. In a DMARD-naïve RA cross- sectional synovial biopsy-based study of 50 RA patients across 9 sites using harmonized protocols and integrated technologies, Aim 1 will deliver high-quality multimodal clinical phenotype and histology data, along with synovial tissue and other biosamples, to evaluate how synovial cellular and molecular pathways relate to disease onset. With longitudinal follow-up and repeat biopsy of these individuals after methotrexate monotherapy, Aim 2 will address whether synovial signatures and multi-modal data predict first-line methotrexate response, or failure in patients with early previously untreated disease. Finally, in Aim 3, in patients with methotrexate inadequate response we will address whether distinct synovial cellular or molecular features predict a positive response to biologic therapies directly targeting these features. The outcomes of this program will have potential for rapid translational application to improve treatment outcomes at all RA disease stages. Collectively, the collaborative, global AIM-for-RA Team that has made seminal observations regarding RA disease pathogenesis is ideally suited to inform the key questions and meet major unmet needs in the field.

风湿性关节炎（RA）影响约1%的人口，其特征在于： 炎症和关节损伤，往往导致相当大的残疾和疼痛，在早期和 建立阶段。外地未满足需求的主要领域包括：1）高度异质性， 不可预测的病程，2）罕见的持久缓解，3）目前可用的治疗失败 以在许多患者中实现低疾病活动性和/或限制进行性关节损伤，以及4）缺乏 个性化适当的治疗策略所需的强大生物标志物。我们建议 滑膜组织中的细胞和分子变异是这种异质性的基础， 这一基础将改善对疾病进程的预测，并为及时 选择精确的治疗策略，以更高的持续性RA控制率。通过 持续合作的全球团队科学，AIM-for-RA团队已经开发出 解构RA滑膜活检组织的最新方案-这一创新深刻地 在RA发病机制中涉及的细胞和途径方面的先进知识，确定了新的治疗方法 研究人员发现了新的靶点，确定了疾病的生物标志物，并为疾病预防开辟了新的机会。然而，在这方面， 目前尚不清楚滑膜中的分子相互作用如何与定义的 临床结局，从临床前风险期到关节炎发作，然后到滑膜炎 结果。因此，AIM-for-RA疾病团队（DT）旨在将疾病相关的滑膜细胞与 环境暴露、疾病结果和治疗的途径和动态串扰 反应，从而重建疾病的发病机制轨迹。在DMARD初治RA交叉试验中， 采用统一方案，对9个研究中心的50名RA患者进行了基于关节滑膜切片活检的研究， 集成技术，Aim 1将提供高质量的多模式临床表型和组织学 数据，沿着滑膜组织和其他生物样品，以评估滑膜细胞和分子 与疾病发作有关的途径。通过对这些个体的纵向随访和重复活检 在甲氨蝶呤单药治疗后，目标2将讨论滑膜特征和多模式 数据预测一线甲氨蝶呤反应，或早期未经治疗的患者失败 疾病最后，在目标3中，在甲氨蝶呤反应不足的患者中，我们将讨论 不同的滑膜细胞或分子特征直接预测对生物疗法的积极反应 针对这些特点。该计划的成果将有可能迅速转化为 应用于改善所有RA疾病阶段的治疗结果。集体的，协作的， 全球AIM for RA团队已对RA疾病发病机制进行了开创性观察， 非常适合为关键问题提供信息和满足外地未满足的主要需求。