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.

项目摘要/摘要 尚不清楚为什么有些患者在适当治疗莱姆病后会恢复过期的健康前健康 而其他人则发展以发展后治疗后莱姆病（PTLD）。重要的事先发表， 初步数据表明，感染开始时临床，免疫和代谢因素的变异性 随着B. burgdorferi，包括PTLD在内的不同后治疗结果的发展。在这个 研究，我们将借鉴具有明确定义的PTLD的独特人群，没有病史的健康对照 莱姆病，莱姆病早期疾病的患者在纵向延伸至结束后1年 治疗。结合高级，创新的统计和实验室方法，这笔赠款的目的是 确定这些因素并研究它们与患者患者中的潜在症状表型的关系 PTLD。为了实现这一目标，我们将确定与治疗相关的临床上的风险因素 随着时间的流逝，莱姆病的结果。然后，这些因素将用于制定评估评分以识别 在临床环境中患PTLD的风险增加的患者（AIM 1）。纵向，多元，跨 此类域分析的目的是将发现直接转换为临床实践和研究 以前尚未进行PTLD的基本疾病途径。我们还将确定新颖的自动 通过蛋白质阵列与PTLD相关的抗体，并检查其与潜在的关系 临床表型（AIM 2）。虽然已经怀疑自身免疫过程是 PTLD，至少对于某些人来说，自适应免疫识别自我抗原才开始成为 描述。发现PTLD中自身抗体的发现可能揭示了以特定临床特征标记的患者子集， 例如主要的肌肉骨骼疼痛或神经系统症状，并确定疾病是 由自身免疫过程驱动。最后，我们将研究患者的纵向免疫代谢特征 使用新型的高维流式细胞术方法的不同临床结果，并假设 在体外对扰动途径的药理操作可能能够使PTLD相关 代谢签名（AIM 3）。免疫代谢在全球报告急性细胞的能力 环境表明，询问个体中免疫细胞代谢的未来会发展PTLD可能 提供对疾病机制的基本见解。总的来说，我们的研究代表了一种严格的方法 要发现与PTLD及其基础临床结果相关的决定因素 表型。该项目的长期目标是产生基本知识以告知发展 创新的治疗策略以及新的干预措施，以预防或减少通常重要的 PTLD的症状负担和功能影响。