Using the Mycobacterium tuberculosis Genome to Predict Tuberculosis Pathology, Drug Resistance Acquisition and Identify Community Transmission Sites

使用结核分枝杆菌基因组预测结核病病理、耐药性获得和识别社区传播位点

• 批准号: 10598532
• 负责人: ROBERT H GILMAN
• 金额: $ 65.2万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-04-15 至 2025-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10598532
• 关键词: Age; Americas; Bacteria; Bacterial Genes; Biological Assay; Biological Markers; Cessation of life; Chest; Clinical; Collection; Communicable Diseases; Communities; Confounding Factors (Epidemiology); Contact Tracing; Data; Data Set; Diagnosis; Disease; Disputes; Drug resistance; Drug resistance in tuberculosis; Ecology; Event; Genetic; Genetic Polymorphism; Genome; Genotype; Home; In Vitro; Incidence; Infectious Agent; Laboratories; Link; M. tuberculosis genome; Maps; Metadata; Monitor; Pathology; Patients; Peru; Pharmaceutical Preparations; Phylogenetic Analysis; Phylogeny; Population; Population Heterogeneity; Predisposition; Questionnaires; Radiology Specialty; Sampling; Site; Techniques; Thoracic Radiography; Time; Treatment Protocols; Tuberculosis; Variant; acquired drug resistance; bacterial genetics; community transmission; drug resistance development; genetic association; genome sequencing; genome wide association study; genomic biomarker; novel; pathogen genome; personalized medicine; prevent; sex; socioeconomics; suburb; transmission process; whole genome

PROJECT SUMMARY Peru has the second highest incidence of tuberculosis (TB) disease in the Americas [1]. Despite causing the largest number of deaths worldwide due to any single agent infectious disease, no study has yet examined the influence of the pathogen genome on TB pathology as defined by the extent of radiological involvement on the chest radiograph. Therefore, our first Aim is to combine population level genome sequencing data with radiological data and linked clinical and demographic metadata to determine using novel multivariate genome wide association (GWAS) techniques the bacterial genomic biomarkers of TB pathology More than 80% of TB disease arises following a transmission event that occurs outside the home [2]. Understanding where, when and how frequently transmission events occur in the community is therefore critical in order to intervene and prevent spread of the disease. Identifying transmission sites, intervening and thereby preventing transmission is critical to diminishing the spread of primary drug resistance [3]. Therefore, our second Aim is to use population level whole genome sequencing together with real time GPS monitoring and the latest in spatial ecology mapping analysis to uncover new sites of TB transmission relative to matched controls Acquired drug resistance also contributes significantly to the global burden of drug resistance [4]. How TB strain genotype influences the acquisition of drug resistance remains disputed and insufficiently understood [5–11]. Identifying which genetic background is most associated with the acquisition of drug resistance to specific drugs would enable patients with drug susceptible TB to receive a personalized treatment regimen that minimizes the development of drug resistance on that genetic background. Therefore, our third aim is to use a unique set of >9000 bacterial strains collected in Peru at the population level over 20 years to phylogenetically infer which genetic background is associated with drug resistance acquisition; then confirm these findings in the laboratory and on a similar Moldovan dataset collection of >3000 strains. Preliminary studies have identified a TB bacterial genetic background that is highly associated with drug resistance [12]. We have also identified new community sites where significant TB transmission occurs [13] as well as identifying putative bacterial genetic polymorphisms independently associated with pathology in drug resistant TB. Our proposed study could help to diminish TB transmission in the region, identify new biomarkers of pathology, uncover new sites of TB transmission, and identify the bacterial genetic associations with drug resistance acquisition.

项目概要 秘鲁的结核病发病率位居美洲第二[1]。 世界范围内因单一病原体感染而死亡的人数最多，但尚未有研究检验过 病原体基因组对结核病病理学的影响，定义为放射学参与程度 因此，我们的首要目标是将群体水平的基因组测序数据与 放射学数据以及关联的临床和人口统计元数据以确定使用新型多变量基因组 广泛关联（GWAS）技术结核病病理学细菌基因组生物标志物 超过 80% 的结核病是在家庭以外发生的传播事件后产生的 [2]。 因此，了解社区中传播事件发生的地点、时间和频率至关重要 以干预和防止疾病传播。 预防传播对于减少原发性耐药性的传播至关重要[3]。 目标是将群体水平的全基因组测序与实时 GPS 监测和最新的 进行空间生态图分析，以发现相对于匹配对照的结核病传播新位点 获得性耐药性也对全球耐药性负担造成重大影响[4]。 基因型对耐药性获得的影响仍然存在争议且尚未得到充分理解[5-11]。 确定哪种遗传背景与获得特定药物的耐药性最相关 将使药物敏感结核病患者能够接受个性化治疗方案，最大限度地减少 因此，我们的第三个目标是使用一套独特的方法。 超过 9000 种细菌菌株在秘鲁 20 年来在人群水平上收集，以从系统发育上推断出哪些菌株 遗传背景与耐药性获得相关；然后在实验室中确认这些发现 以及超过 3000 个菌株的类似摩尔多瓦数据集。 初步研究已确定结核菌遗传背景与药物高度相关 我们还确定了发生大量结核病传播的新社区地点 [13]。 以及鉴定与药物病理学独立相关的推定细菌遗传多态性 我们提出的研究可能有助于减少该地区的结核病传播，识别新的生物标志物。 病理学，发现结核病传播的新位点，并确定细菌遗传与药物的关联 电阻获取。