High-Resolution Plasma Metabolomic Profiling to Identify Biomarkers for Tuberculosis Disease and Response to Therapy

摘要/摘要：结核病是世界头号传染病杀手，有150万人 2014年可归因于该疾病的死亡。由于缺乏生物学知识，存在着严重的知识鸿沟 与结核病发病、进展和消退相关的途径和预测性生物标记物。一种改进的诊断 结核病检测将对全球疾病控制和降低死亡率产生重大影响。不幸的是， 目前尚无有效的生物标记物可用于结核病的发病、进展和消退； 迫切需要生物标记物。目前的超高分辨率代谢组学(HRM)方法有相当大的 为结核病相关生物标志物的开发提供了希望。几项研究已经确定了区别于小的 活动性分枝杆菌携带者血液和其他生物样本中的分子代谢特征 结核病(Mtb)引起的结核病与未感染的对照组相比，但没有研究探索是否 代谢组学可以预测结核转归、结核分枝杆菌从痰中清除。此外，到目前为止的所有研究都使用了 低分辨率代谢组学方法。质谱计机器能力的进步，加上 最近先进的数据提取/分析方法大大增加了动态范围 HRM在生物样本中检测代谢物，目前已超过20,000种(&gt；100,000离子)。我们的 HRM处理方案提供了检测极低丰度代谢物的能力，包括结核分枝杆菌细胞 包膜糖脂，并探索人类代谢途径的调节。在一项初步研究中，我们成功地 鉴定61种血浆代谢物，区分成人活动性肺结核和家庭接触者 没有结核病。分化的物种包括特定的结核分枝杆菌衍生的细胞壁糖脂和内源性脂肪 调解人解决方案。我们最近的试验数据显示，特定的代谢物和人类的代谢途径， 包括那些涉及药物、氨基酸和脂类代谢的物质，都与 痰结核分枝杆菌培养随时间推移而清除。这一探索性建议的最终目标是获得新的数据 这可能会导致新的结核病生物标记物的开发。我们假设血浆HRM分析可以：1) 通过鉴定结核分枝杆菌衍生和内源性代谢物预测成功抗结核治疗的倾向 (生物标志物)和与痰结核分枝杆菌清除有关的人体代谢途径(病理生理学)；以及2) 成功地将活动性结核病患者与没有潜在结核病感染(LTBI)或结核病疾病的对照组区分开来。 为了验证这些假设，我们在这个探索性的R21项目中提出了以下具体目标： 具体目标1：确定血浆HRM分析是否可以识别结核分枝杆菌来源和内源性 预测结核分枝杆菌从痰中清除的代谢物(从阳性培养变为阴性培养)。 具体目标2：确定血浆HRM分析是否可以区分成人与药物 来自无LTBI的无症状对照的敏感或MDR-TB±HIV混合感染。

Summary/abstract: Tuberculosis (TB) is the number one infectious disease killer in the world with 1.5 million deaths attributable to the disease in 2014. A critical knowledge gap exists given the lack of biological pathways and predictive biomarkers related to TB onset, progression and resolution. An improved diagnostic test for TB would have a major impact on global control of the disease and reduce mortality. Unfortunately, there are no validated biomarkers for TB onset, progression and resolution; the development of a TB biomarker is urgently needed. Current ultra-high-resolution metabolomics (HRM) methods have considerable promise for the development of TB-associated biomarkers. Several studies have identified distinguishing small molecule metabolic profiles in blood and other bio samples in individuals with active Mycobacterium tuberculosis (Mtb)-induced TB disease compared to uninfected controls, but no studies have explored whether metabolomics is predictive of TB outcomes, Mtb clearance from sputum. Further, all studies to date have used low-resolution metabolomics methods. Advances in mass spectrometer machine capability, coupled with recent advanced data extraction/analysis methods has considerably increased the dynamic range of metabolite detection by HRM in biologic samples, which now exceeds 20,000 species (>100,000 ions). Our HRM processing scheme provides capability to detect very low abundance metabolites, including Mtb cell envelope glycolipids, and explore regulation of human metabolic pathways. In a pilot study, we successfully identified 61 plasma metabolites that differentiated adults with active pulmonary TB from household contacts without TB. Differentiating species included specific Mtb-derived cell wall glycolipids and endogenous lipid mediator resolvins. Our recent pilot data shows that specific metabolites and human metabolic pathways, including those involved in drug, amino acid, and lipid metabolism, are associated with the propensity for sputum Mtb culture clearance over time. The ultimate goal of this exploratory proposal is to obtain novel data that may lead to the development of new TB biomarkers. We hypothesize that plasma HRM analysis can: 1) predict the propensity for successful anti-TB treatment by identifying Mtb-derived and endogenous metabolites (biomarkers) and human metabolic pathways (pathophysiology) associated with sputum Mtb clearance; and 2) successfully differentiate patients with active TB from controls without latent TB infection (LTBI) or TB disease. To test these hypotheses, we propose the following Specific Aims in this exploratory R21 project: Specific Aim 1: To determine whether plasma HRM analysis can identify Mtb-derived and endogenous metabolites that predict clearance of Mtb from sputum (change from positive to negative culture). Specific Aim 2: To determine whether plasma HRM analysis can differentiate adults with drug- sensitive or MDR-TB ± HIV co-infection from asymptomatic controls without LTBI.