Advancing Diagnostics of Infectious Uveitis with MetagenomicAnalysis

项目总结 葡萄膜炎是一种威胁视力的眼内炎症，影响到年轻的工作年龄的人，导致 重大的社会经济影响。它通常是由感染或免疫介导性疾病引起的。而当 疱疹病毒和弓形虫是感染性葡萄膜炎和许多其他感染性病原体的主要原因。 也可能涉及病毒、细菌、真菌和寄生虫。临床诊断常常因以下原因而复杂化 不同感染原因引起的病例检查结果重叠，也与 对那些由自身免疫性疾病和创伤引起的人进行了观察。正因为如此，互补 实验室检查对于病原学诊断和适当的临床处理是必不可少的。实验室 检查依赖于多种免疫学测试和病原体靶向的单链聚合酶链式反应 (聚合酶链式反应)检测。这种方法大大增加了诊断的时间，通常由于有限的原因而无法实现 可以安全获取的眼内液体的量，在许多情况下是不能透露的。因此，患者 可以使用不是为个人量身定做的一刀切的治疗试验进行数周或数月的治疗 而且并不是对每个人都有效。元基因组下一代测序(MNGS)在无偏倚中的应用 检测临床标本中的每一种病原体是一种新兴的诊断方式，它有可能 显著提高感染性葡萄膜炎的诊断率。到目前为止，还缺乏这样一种方法，即 对于独特的眼内液，彻底执行适当的分析和临床验证步骤 从葡萄膜炎患者的眼睛中检测出的矩阵。这里提出的研究旨在填补这一空白，并承担 开发和系统验证可转化为临床的无偏mNGS测试的挑战 应用于葡萄膜炎诊断和识别目前漏诊的新病因。首先，我们将 彻底建立检测葡萄膜炎病原体的mngs试验的分析性能特征 从玻璃标本中提取。这将通过使用含有不同水平宿主DNA的对照玻璃体来完成 背景中添加了参考病原体面板，该面板将用于模拟重要的 分析性能的决定因素。然后，我们将与患者一起挑战这种优化的mNGS检测 用于确定相关临床表现特征的样本，以充分验证此测试是否适用于临床 使用。使用存储在我们的生物储存库中的样本和将收集的其他样本的组合 对于一项前瞻性的盲法挑战研究，我们将使用不同的方法来确定检测的诊断准确性 样本类型(如房水与玻璃体)，其量化能力，并将定义临床阈值 报告检测到的病原体。这项建议将导致开发一种经过系统验证和 感染性葡萄膜炎的创新一体化诊断方法有望大幅提高诊断水平 在仍未诊断的病例中产生并有助于阐明新的感染性葡萄膜炎病因， 有可能极大地改变对患有这种衰弱疾病的患者的管理。

PROJECT SUMMARY Uveitis is a sight-threatening intraocular inflammation that affects young working-age individuals, resulting in significant socioeconomic impacts. It is most often caused by infections or immune-mediated diseases. While herpesviruses and Toxoplasma gondii are the leading causes of infectious uveitis, many other infectious agents can be also involved, including viruses, bacteria, fungi and parasites. Clinical diagnosis is often complicated by overlapping findings upon examination among cases caused by different infectious etiologies, and also with observations made for those caused by autoimmune diseases and trauma. Because of that, complementary laboratory tests are essential for the etiological diagnosis and proper clinical management. The laboratory workup relies on multiple immunological tests and pathogen-targeted singleplex polymerase chain reaction (PCR) assays. This approach increases significantly the time to diagnosis, is often prohibitive due to the limited amount of intraocular fluid that can be safely obtained, and in many cases is unrevealing. As a result, patients can be treated for weeks or months using one-size-fits-all therapeutic trials that are not tailored for an individual and do not work for everyone. The use of metagenomic next-generation sequencing (mNGS) for unbiased detection of every pathogen in a clinical specimen is an emerging diagnostic modality that has the potential to significantly improve diagnostic yields in infectious uveitis. To date, there is a lack of an approach in which the appropriate steps for analytical and clinical validations are thoroughly performed for the unique intraocular fluid matrices tested from uveitic eyes. The studies proposed here are intended to fill this void and take on the challenge of developing and systematically validating an unbiased mNGS test that can be translated into clinical application for uveitis diagnosis and identification of new etiologies that currently escape diagnosis. First, we will thoroughly establish the analytical performance characteristics of a mNGS test for detection of uveitis pathogens from vitreous specimens. This will be done by using control vitreous containing varying levels of host DNA background spiked with a reference pathogen panel that will be used to model the effects of important determinants of analytical performance. Then, we will challenge this optimized mNGS assay with patient specimens for determination of relevant clinical performance characteristics to fully validate this test for clinical use. Using a combination of specimens stored in our biorepository and additional ones that will be collected prospectively for a blinded challenge study, we will determine the diagnostic accuracy of the assay using different sample types (e.g., aqueous vs. vitreous), its quantification capabilities, and will define clinical thresholds for reporting of detected pathogens. This proposal will result in the development of a systematically validated and innovative all-in-one diagnostic assay for infectious uveitis that is expected to substantially improve diagnostic yields and help to illuminate novel infectious uveitis etiologies in cases that remain undiagnosed, with great potential to for significantly changing the management of patients suffering from this debilitating disease.