Metabolic factors that control the spectrum of human tuberculosis

由于缺乏有效的结核病疫苗，结核病控制依赖于对传染性病例的早期诊断和有效治疗，而标准诊断工具的敏感性和特异性相对较低，影响了这一点。由于结核病感染最常导致慢性无症状状态，因此，在一半以上人口感染结核病的高负担环境中，很难通过针对已感染但尚未患病的人进行疾病预防。实现高治愈率所需的长期治疗以及耐药菌的出现和传播进一步削弱了国家结核病控制规划的潜在影响。我们提出的计划回应了这些研究重点，并从我们自己的团队和其他人最近的一系列研究成果中发展出来，这些研究成果建议采用创新的跨学科方法来发现基本机制。我们提议的项目首先对诊断为活动性结核病的患者及其家庭接触者进行识别和纵向随访。对进展为活动性结核病（进展者）的患者进行疾病结局跟踪，包括复发，并对家庭接触者进行跟踪，以了解结核病感染和疾病的证据。这种设计和我们广泛的纵向随访能力将使我们能够通过仔细的临床和流行病学研究、人类基因组学（通过外显子组测序）、人类遗传学（通过外显子组芯片）、转录组学和代谢组学来识别和描述结核病指数病例及其暴露的家庭接触者。我们已经在人类受试者、生物信息学和代谢组学方面建立了核心，这些核心将并行工作，以确定靶标，包括连接人体代谢和免疫反应的途径、参与结核分枝杆菌反应的T细胞、耐药性病原体决定因素和临床结核表型病原体标记物。每个项目都包括在豚鼠模型中验证这些目标。基于我们的结果，我们将继续在动物模型中测试特定的干预措施，特别关注改变人体代谢和免疫反应的药物。

The absence of an effective vaccine for tuberculosis means that TB control relies on the early diagnosis and effective treatment of infectious cases, which is compromised by the relatively low sensitivity and specificity of standard diagnostic tools. Because TB infection most often results in a chronic asymptomatic state, prevention of disease by targeting those who are infected, but not yet ill, has been difficult to implement in high burden settings where more than half of the population is TB infected. The long duration of treatment necessary to achieve high cure rates and the emergence and spread of drug resistant organisms have further undermined the potential impact of national TB control programs. Our proposed plan responds to these research priorities and grows out of a series of recent research findings from our own groups and others that suggest an innovative interdisciplinary approach to the discovery of basic mechanisms through. Our proposed project begins with the identification and longitudinal follow-up of patients diagnosed with active TB and their household contacts. Patients that progress to active TB disease (progressors) are followed for disease outcomes, including relapse, and household contacts are followed for evidence of TB infection and disease. This design and our extensive longitudinal follow up capabilities will allow us to identify and characterize TB index cases and their exposed household contacts through careful clinical and epidemiologic studies, human genomics (by exome sequencing) human genetics (by exome chip), transcriptomics, and metabolomics. We have established Cores in Human subjects, Bio-informatics, and Metabolomics that will work in parallel to identify targets including pathways linking human metabolism and immune response, T cells involved in Mtb response, pathogen determinants of drug resistance and pathogen-shed markers of clinical TB phenotypes. Each project includes validation of these targets in the guinea pig model. Based on our results, we will then go on to test specific interventions in the animal model, focusing in particular on pharmacologic agents that alter human metabolic and immune responses.