Host Metabolic Biosignatures for the Diagnosis of Lyme Disease

项目摘要 莱姆病是美国最常报告的病媒传播疾病，估计有30万例 每年发生。目前莱姆病的诊断是基于对游走性红斑（EM）皮肤的识别 具有一致临床体征的患者出现病变或阳性两级血清学（抗体检测）检测， 在莱姆病发生的地区接触蜱虫。据估计，20%至30%的患者不存在 EM，大多数患者不记得蜱虫叮咬。此外，血清学试验依赖于宿主 体液免疫反应和缺乏敏感性的早期莱姆病（只有29-40%的EM患者是 血清阳性）。血清学反应性也可能在抗生素治疗和缓解后持续数年。 症状这些局限性和对早期诊断的需要，以促进快速治疗干预， 为开发新的莱姆病诊断测试提供了强有力的理由。我们写了一部小说 一种应用血清代谢组学开发小分子生物特征的方法， 早期莱姆病的诊断测试。这些努力产生了一个已发表的候选生物签名， 早期莱姆病的敏感性为88%，健康对照的特异性为95%，其他疾病的特异性为93%。 疾病控制人口。这种方法也能够区分早期莱姆病和南方蜱 相关皮疹疾病（STARI），一种具有EM样皮肤病变和类似非特异性症状的疾病， 早期莱姆病，并正确分类这两个患者组，莱姆病的准确率为98%， STARI的准确率为89%。我们的初步数据现在提供了强有力的证据，表明代谢谱可以 区分早期LD与其他蜱传播疾病，并区分各种表现， 早期莱姆病（即，早期局限性与早期播散性疾病）。根据这项建议， 生物化学家、微生物学家、数学家、统计学家和传染病专家 临床医生将联合起来进行研究，这将大大推进我们以前的努力。 具体地说，我们假设有可能建立一个诊断代谢谱， 将早期莱姆病患者与非莱姆病患者区分开来，并且可以应用于 重要的是，非莱姆病患者组是那些怀疑患有莱姆病的个体 疾病（接受医疗护理并接受莱姆病诊断检测的患者，但 未被诊断患有莱姆病），以及患有其他蜱传播疾病的人。我们的努力 考虑到早期莱姆病和非莱姆病人群的异质性症状。 诊断发展的目标将通过应用最先进的数学 建模和良好表征的前瞻性和回顾性收集的血清。梅特涅与最伟大的 早期莱姆病的鉴别价值将在结构上阐明和表征，以促进 作为早期莱姆病平台的多分析物多反应监测测定的实施 诊断.与早期莱姆病相关的代谢途径将被阐明，以建立一个生物学模型。 支持代谢谱作为早期莱姆病诊断方法的基本原理。

PROJECT SUMMARY Lyme disease is the most frequently reported vector-borne disease in the U.S., with 300,000 cases estimated to occur annually. Current diagnosis of Lyme disease is based on recognition of an erythema migrans (EM) skin lesion or positive two-tiered serological (antibody detection) testing in a patient with consistent clinical signs and tick exposure in areas where Lyme disease occurs. It is estimated that 20 to 30% of patients do not present with an EM, and the majority of patients do not recall a tick bite. Moreover, serologic tests are dependent on the host humoral immune response and lack sensitivity in early Lyme disease (only 29-40% of patients with EM are seropositive). Serological reactivity also may persist for years following antibiotic treatment and resolution of symptoms. These limitations and the need for early diagnosis to facilitate rapid therapeutic intervention provide strong rationale for the development of new Lyme disease diagnostic tests. We have undertaken a novel approach of applying serum metabolomics to develop small molecule biosignatures that can be exploited as a diagnostic test for early Lyme disease. These efforts resulted in a published candidate biosignature that provided a sensitivity of 88% for early Lyme disease with a specificity of 95% for healthy controls and 93% for other disease control populations. This approach was also able to differentiate early Lyme disease from Southern Tick Associated Rash Illness (STARI), an illness with an EM-like skin lesion and similar non-specific symptoms of early Lyme disease, and correctly classified these two patient groups with 98% accuracy for Lyme disease and 89% accuracy for STARI. Our preliminary data now provides strong evidence that metabolic profiles can differentiate early LD from other tick transmitted diseases and distinguish between the various manifestations of early Lyme disease (i.e., early localized versus early disseminated disease). Under this proposal, the expertise of biochemists, microbiologists, mathematicians, statisticians and infectious disease clinicians will be combined to perform studies that will significantly advance our previous efforts. Specifically, we hypothesize that it is possible to create a diagnostic metabolic profile that accurately distinguishes early Lyme disease patients from non-Lyme disease patients, and that can be applied in a clinical laboratory, Importantly the non-Lyme disease patient group are those individuals suspected of Lyme disease (patients who present for medical care and who undergo diagnostic testing for Lyme disease, but are not diagnosed with Lyme disease), as well as those with other tick transmitted diseases. Our proposed efforts take into account the heterogeneous symptoms of early Lyme disease and the non-Lyme disease populations. The goal of diagnostic development will be facilitated through the application of state-of-the-art mathematical modeling and well-characterized prospectively and retrospectively collected sera. Metabolites with the greatest discriminatory value for early Lyme disease will be structurally elucidated and characterized to facilitate implementation of a multianalyte multiple reaction monitoring assay as a platform for early Lyme disease diagnosis. Metabolic pathways associated with early Lyme disease will be elucidated to establish a biological rationale that support metabolic profiling as a diagnostic method for early Lyme disease.