Defining how the spectrum of latency affects reactivation of TB

描述（由申请人提供）：人类结核分枝杆菌感染的结果在临床上被定义为“活动性”或“潜伏性”。这些临床定义不足以描述M的连续体。肺结核感染。“活动性”结核病的实际表现从轻微到严重的肺部疾病，包括空洞性结核病，以及肺外或播散性疾病不等。几条证据支持潜伏感染也是一系列感染结果，从亚临床疾病到“休眠感染”再到完全清除的感染。潜伏期谱的概念具有实际意义：我们假设只有一小部分潜伏感染者最有可能发生反应性结核病，并确定我们认为潜伏期谱“较高”的人，使人们能够将干预措施瞄准最受益的人。在这个建议中，我们将探讨的概念，频谱的延迟和影响使用系统生物学方法的重新激活。我们建议整合来自人类、非人类灵长类动物和计算系统的数据，以提供一种全面的延迟和重新激活方法。我们将使用免疫学方法和最先进的成像技术来确定感染M的人类和非人灵长类动物的潜伏期谱。结核从非人类灵长类动物中，我们将更进一步，获得肉芽肿，以详细研究潜伏期和再激活期间的光谱。这些肉芽肿将用于免疫学、微生物学和病理学研究，以确定哪些最有可能再活化以及维持亚临床感染的相关因素。除了大大增加我们对“潜伏”结核病和导致结核病复发的因素的了解外，所有人类和非人类灵长类动物的数据都将被纳入下一代结核病多尺度数学模型。这将提供计算平台，用于对导致延迟谱和重新激活风险的因素进行复杂分析。最终，这些模型，从人类和一个非常相关的动物模型的数据，可以用来测试我们的假设，即一个人的位置上的潜伏期影响的风险重新激活。该项目汇集了一个经验丰富的免疫学家，微生物学家和计算科学家团队，他们多年来一直专注于结核病的研究。 公共卫生相关性：结核分枝杆菌，结核病的病原体，可以引起临床上明显的疾病（TB）或更常见的临床上沉默的感染（潜伏性TB），可以重新激活，以及引起TB。据估计，全世界有17亿人患有潜伏性结核病感染。在这里，我们将来自人类和动物模型的数据与计算和数学模型相结合，采用全面的系统生物学方法，以更好地了解潜伏性结核病和导致再激活的因素。

DESCRIPTION (provided by applicant): Outcome of Mycobacterium tuberculosis infection in humans is clinically defined as "active" or "latent". These clinical definitions are inadequate to describe the continuum of M. tuberculosis infection. The actual presentation of "active" tuberculosis varies from mild to severe pulmonary disease, including cavitary tuberculosis, and to extrapulmonary or disseminated disease. Several lines of evidence support that latent infection is also a spectrum of infection outcomes, from subclinical disease to "dormant infection" to completely cleared infection. The concept of a latency spectrum has practical implications: we hypothesize that only a small percentage of latently infected persons is most likely to reactive TB, and identifying those persons, who we believe are "higher" on the latency spectrum, allows one to target interventions to those who most will benefit. In this proposal, we will explore the concept of the spectrum of latency and implications for reactivation using a systems biology approach. We propose to integrate data from humans, non-human primates, and computational systems to provide a comprehensive approach to latency and reactivation. We will use immunologic methods and state-of-the-art imaging technology to define the spectrum of latency in humans and non-human primates infected with M. tuberculosis. From non-human primates, we will go one step further and obtain granulomas for detailed study of the spectrum of latency, as well as during reactivation. These granulomas will be used in immunologic, microbiologic and pathologic studies to identify which are most likely to reactivate and the factors involved in maintaining a subclinical infection. In addition to vastly increasing our understanding of "latent" TB and the factors that contribute to reactivation, all of the human and non-human primate data will be incorporated into next generation multi-scale mathematical models of tuberculosis. This will provide the computational platform for sophisticated analysis of factors that contribute to the spectrum of latency and the risk of reactivation. Ultimately these models, informed by data from humans and a very relevant animal model, can be used to test our hypothesis that the position of an individual on the spectrum of latency influences the risk of reactivation. This project brings together an experienced team of immunologists, microbiologists, and computational scientists who have focused on the study of tuberculosis for many years. PUBLIC HEALTH RELEVANCE: Mycobacterium tuberculosis, the causative agent of tuberculosis, can cause clinically apparent disease (TB) or more commonly a clinically silent infection (latent TB) that can reactivate to cause TB as well. It is estimated that 1.7 billion people worldwide have latent TB infection. Here we integrate data from humans and animal models with computational and mathematical models in a comprehensive systems biology approach to a better understanding of latent TB and the factors that lead to reactivation.