Host Metabolic Biosignatures for the Diagnosis of Lyme Disease

项目总结 莱姆病是美国最常见的媒介传播疾病，估计有30万例 每年都会发生。目前莱姆病的诊断是基于对移行性红斑(EM)皮肤的识别 临床症状一致的患者的皮损或两级血清(抗体检测)阳性检测 莱姆病发生地区的扁虱暴露。据估计，20%到30%的患者没有出现 EM，大多数患者都不记得被扁虱叮咬过。此外，血清学测试依赖于宿主。 早期莱姆病的体液免疫反应和缺乏敏感性(只有29%-40%的EM患者是 血清阳性)。血清反应性也可能在抗生素治疗和解决后持续数年 症状。这些局限性和早期诊断的需要促进了快速治疗干预提供了 开发新的莱姆病诊断测试的强有力的理由。我们已经承接了一部小说 应用血清代谢组学开发小分子生物标志物的方法 莱姆病早期诊断试验。这些努力的结果是公布了一个候选生物签名，它提供了 对早期莱姆病的敏感度为88%，对健康对照组的特异度为95%，对其他疾病的特异度为93% 疾病控制人口。这种方法也能够区分早期莱姆病和南方硬蜱 相关皮疹(STARI)，一种具有EM样皮肤损害和类似的非特异性症状的疾病 早期莱姆病，并对这两组患者进行正确分类，对莱姆病和 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，证明新陈代谢谱可以 鉴别早期LD与其他硬虱传播疾病，并区分不同表现 早期莱姆病(即早期局限性疾病与早期播散性疾病)。在这项建议下， 生物化学家、微生物学家、数学家、统计学家和传染病专家的专业知识 临床医生将联合起来进行研究，这将大大推进我们之前的努力。 具体地说，我们假设有可能创建一个准确的诊断新陈代谢图谱 区分早期莱姆病患者和非莱姆病患者，这可以应用于 临床实验室，重要的是，非莱姆病患者组是那些疑似莱姆病的人 疾病(接受医疗护理并接受莱姆病诊断测试的患者，但 未被诊断为莱姆病的人)，以及患有其他扁虱传播疾病的人。我们提议的努力 考虑到早期莱姆病和非莱姆病人群的不同症状。 将通过应用最先进的数学方法来促进诊断开发的目标 建模和特征良好的前瞻性和回溯性收集的血清。代谢物中最大的 将从结构上阐明早期莱姆病的鉴别价值，并将其表征为便于 多分析多反应监测方法作为莱姆病早期诊断平台的建立 诊断。与早期莱姆病相关的代谢途径将被阐明，以建立一个生物学的 支持代谢图谱作为早期莱姆病诊断方法的理论基础。

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.