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.

项目总结/文摘