Genetics & Clinical Cohorts

为实现到2035年将结核病死亡人数减少95%的目标，世卫组织终结结核病战略指出， 需要新的工具，如疫苗、药物和治疗制度，以及护理点检测。新的工具来 消除结核病依赖于对结核病的新知识。我们利用基因组技术 结核病的病原体和宿主基因组变异，以促进我们对结核病的基本认识， 需要推动新疫苗和药物设计的创新，以控制结核病的流行。 我们将利用来自越南和乌干达的广泛的临床、流行病学和遗传学队列， 在过去的20年里，已经完成了一些研究，以发现结核病的遗传决定因素，进展和 人类和结核分枝杆菌的结果。我们的目标是1/确定活动性肺结核的遗传决定因素 2/确定人类和结核分枝杆菌中与细菌感染相关的遗传决定因素 疾病负担和不良的疾病结局3/确定与传播相关的细菌变体，使用 传播的进化和流行病学特征。在目标1和2中，我们将利用配对主机， 病原体基因组数据集从一个大的队列肺结核患者，并分析宿主和病原体 单独和组合的基因组数据。在这些目标中，我们将研究宿主和病原体基因 与结核病和临床终点相关的变异，以及与“中间表型”相关的变异， 宿主对细菌复制的控制、细菌在宿主中的存活和细菌清除。在目标3中，我们将使用 细菌基因组序列，以确定Mtb基因变异有助于疾病传播1/ 询问进化的基因组信号，2/利用低收入家庭的流行病学数据， 结核病传播率高。核心A遗传学的目标是将基因发现交付给3个项目， 分析，而在3个项目中使用体外和体内模型确定的功能候选人将 在我们的临床队列中进行评估，以弥合结核病模型和人类 结核病。通过人类和细菌的基因组学，核心A的鉴定结果将是关键 Mtb感染的反应机制、Mtb传播性、TB易感性和疾病结果。这 研究将通过推进我们对结核病的基本理解而产生影响，这对推动 为未来控制结核病流行进行创新。

To achieve a 95% reduction of TB deaths by 2035 the WHO END-TB strategy states that critical introduction of new tools, such as a vaccine, drugs and treatment regimes, and a point-of-care test are required. New tools to eliminate TB are reliant on new knowledge of TB. Here we are utilizing genomic technology to interrogate pathogen and host genomic variation in TB to advance our fundamental understanding of TB which is critically required to drive innovation for the design of new vaccines and drugs to control the TB epidemic. We will utilize our extensive clinical, epidemiological and genetic cohorts from Vietnam and Uganda which have been complied over the last 2 decades, to discover genetic determinants of TB disease, progression and outcome in humans and M.tuberculosis. We aim to 1/ identify genetic determinants of active pulmonary TB disease in humans and M.tb, 2/ identify genetic determinants in humans and M.tb associated with bacterial burden and poor disease outcome 3/ identify bacterial variants associated with transmission, using evolutionary and epidemiological signatures of transmission. In aims 1 and 2 we will utilize a paired host and pathogen genomic dataset from a large cohort of pulmonary TB patients, and analyze both host and pathogen genomic data individually and in combination. In these aims we will investigate host and pathogen gene variants associated with TB disease and clinical endpoints, as well as with “intermediate phenotypes” such as host control of bacterial replication, bacterial survival in the host, and bacterial clearance. In aim 3 we will use bacterial genome sequence to identify Mtb gene variants contributing to disease transmissibility by 1/ interrogating genomic signals of evolution and 2/ by utilizing epidemiological data of households with low and high TB transmission. The aims of core A Genetics will deliver gene discoveries to the 3 projects for functional analysis, while functional candidates identified in the 3 projects using in vitro and in vivo models will be assessed within our clinical cohorts to bridge the “investigative” gap between TB disease models and human TB disease. Through human and bacterial genomics, the outcome of core A will be the identification of key mechanisms in the response to Mtb infection, Mtb transmissibility, TB susceptibility and disease outcome. This research will have impact by advancing our fundamental understanding of TB which is essential to drive innovation for the future control of the TB epidemic.