Determinants of Post-Treatment Phenotypes in Lyme Disease

莱姆病治疗后表型的决定因素

• 批准号: 10738012
• 负责人: John Aucott
• 金额: $ 63.51万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-01 至 2028-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10738012
• 关键词: Acute; Address; Aftercare; Antibiotic Therapy; Anxiety; Autoantibodies; Autoantigens; Autoimmune Process; Biology; Blood Pressure; Borrelia burgdorferi; Cellular Metabolic Process; Clinical; Coculture Techniques; Complex; Data; Development; Disease; Disease Pathway; Environment; Enzyme-Linked Immunosorbent Assay; Etiology; Event; FDA approved; Flow Cytometry; Functional disorder; Future; Goals; Grant; Health; Human; Immune; Immunologics; Immunology; Immunoprecipitation; In Vitro; Individual; Infection; Intervention; Knowledge; Laboratories; Longitudinal Studies; Lyme Disease; Mental Depression; Metabolic; Metabolic Pathway; Methods; Modeling; Modernization; Molecular; Musculoskeletal Pain; Neurologic Symptoms; Outcome; Participant; Pathogenesis; Pathway interactions; Patients; Peripheral Blood Mononuclear Cell; Persons; Phenotype; Physiologic pulse; Process; Prospective, cohort study; Protein Array; Protein Microchips; Psychosocial Factor; Publishing; Quality of life; Recording of previous events; Reporting; Research; Risk; Risk Assessment; Risk Factors; Sampling; Sampling Studies; Scientific Advances and Accomplishments; Series; Serology; Serum; Signs and Symptoms; Sorting; Standardization; Stressful Event; Subgroup; Symptoms; Syndrome; Testing; Therapeutic; Time; Translations; Treatment outcome; United States; Universities; Vector-transmitted infectious disease; Work; acute infection; biobank; candidate identification; clinical care; clinical phenotype; clinical practice; clinically relevant; cohort; cytokine; high dimensionality; innovation; insight; machine learning algorithm; novel; pain symptom; participant enrollment; patient population; patient subsets; pharmacologic; prevent; preventive intervention; profiles in patients; recruit; sex; therapeutic target; transcriptome sequencing; translational research program

PROJECT SUMMARY/ABSTRACT It is unknown why some patients regain their pre-morbid health following appropriate treatment for Lyme disease while others progress to develop post-treatment Lyme disease (PTLD). Significant prior published and preliminary data suggest that variability in clinical, immunologic, and metabolic factors at the onset of infection with B. burgdorferi contribute to the development of divergent post-treatment outcomes, including PTLD. In this study, we will draw upon unique cohorts of patients with well-defined PTLD, healthy controls without a history of Lyme disease, and patients with early Lyme disease followed longitudinally up to 1 year after the end of treatment. Combining advanced, innovative statistical and laboratory methods, the objective of this grant is to identify these factors and examine how they relate to underlying symptom phenotypes among patients with PTLD. To accomplish this goal, we will identify clinically-relevant risk factors associated with post-treatment outcomes in Lyme disease over time. These factors will then be used to develop an assessment score to identify patients at increased risk of developing PTLD in the clinical setting (AIM 1). A longitudinal, multivariate, cross- domain analysis of this sort with the goal of direct translation of findings to clinical practice and the study of fundamental disease pathways in PTLD has not previously been performed. We will also identify novel auto- antibodies that are associated with PTLD through protein array, and examine their relationship with underlying clinical phenotypes (AIM 2). While an autoimmune process has been suspected to underlie the pathogenesis of PTLD, at least for some individuals, adaptive immune recognition of self-antigens is only beginning to be described. Discovery of autoantibodies in PTLD may reveal patient subsets marked by specific clinical features, such as predominant musculoskeletal pain or neurologic symptoms, and identify individuals whose disease is driven by an autoimmune process. Finally, we will study the longitudinal immunometabolic profile of patients with differing clinical outcomes using a novel, high-dimensional flow cytometry approach, and hypothesize that pharmacologic manipulation of perturbed pathways in vitro may be able to normalize a PTLD-associated metabolic signature (AIM 3). The ability of immunometabolism to globally report on the acute cellular environment suggests that interrogating immune cell metabolism in individuals develop PTLD in the future could provide fundamental insights into disease mechanism. Collectively, our studies represent a rigorous approach towards uncovering determinants that are associated with the outcome of PTLD and its underlying clinical phenotypes. The long-term goal of this project is to generate fundamental knowledge to inform the development of innovative therapeutic strategies as well as novel interventions to prevent or reduce the often significant symptom burden and functional impact of PTLD.

项目概要/摘要 目前尚不清楚为什么一些莱姆病患者在接受适当的治疗后恢复了病前的健康状况 而另一些人则发展为治疗后莱姆病（PTLD）。先前发表的重要内容和 初步数据表明，感染开始时临床、免疫和代谢因素的变异性 伯氏疏螺旋体会导致不同的治疗后结果的发展，包括 PTLD。在这个 研究中，我们将利用具有明确 PTLD 的独特患者队列和无 PTLD 病史的健康对照 莱姆病和早期莱姆病患者在治疗结束后纵向随访长达 1 年 治疗。结合先进、创新的统计和实验室方法，这笔赠款的目的是 识别这些因素并检查它们与患者潜在症状表型的关系 PTLD。为了实现这一目标，我们将确定与治疗后相关的临床相关风险因素 随着时间的推移，莱姆病的结果。然后，这些因素将用于制定评估分数，以确定 临床环境中发生 PTLD 风险增加的患者 (AIM 1)。纵向、多元、交叉 此类领域分析的目的是将研究结果直接转化为临床实践和研究 此前尚未对 PTLD 的基本疾病途径进行过研究。我们还将确定新颖的自动 通过蛋白质芯片检测与 PTLD 相关的抗体，并检查它们与潜在的关系 临床表型（AIM 2）。虽然自身免疫过程被怀疑是其发病机制的基础 PTLD，至少对于某些个体来说，自身抗原的适应性免疫识别才刚刚开始 描述的。 PTLD 中自身抗体的发现可能揭示具有特定临床特征的患者亚群， 例如主要的肌肉骨骼疼痛或神经系统症状，并确定患有该疾病的个体 由自身免疫过程驱动。最后，我们将研究患有以下疾病的患者的纵向免疫代谢特征： 使用新颖的高维流式细胞术方法观察不同的临床结果，并假设 体外对扰动途径进行药理学操作可能能够使 PTLD 相关的正常化 代谢特征（AIM 3）。免疫代谢全局报告急性细胞疾病的能力 环境表明，询问未来患有 PTLD 的个体的免疫细胞代谢可能会 为疾病机制提供基本见解。总的来说，我们的研究代表了一种严格的方法 旨在揭示与 PTLD 结局及其潜在临床相关的决定因素 表型。该项目的长期目标是生成基础知识来为开发提供信息 创新的治疗策略以及新颖的干预措施，以预防或减少通常显着的 PTLD 的症状负担和功能影响。