Identifying correlates of risk for future tuberculosis disease progression in children (INTREPID)

确定儿童未来结核病进展风险的相关性 (INTREPID)

基本信息

批准号：
10637036
负责人：
James Alexander Seddon
金额：
$ 84.09万
依托单位：
STELLENBOSCH UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-05-05 至 2028-04-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10637036
关键词：
5 year old Adult Affect Age Antibodies Antitubercular Agents Bacille Calmette-Guerin vaccination Bacillus Bacteria Bioinformatics Biological Biological Markers Biology Cessation of life Child Childhood Classification Clinical Clinical Research Collection Cross-Sectional Studies Cytomegalovirus Data Data Collection Development Diagnostic Disease Disease Progression Drug resistance in tuberculosis Epidemiology Exposure to Family Future Goals HIV HIV/TB Health Services Household Immunologic Sensitization Immunologics Immunology Immunology procedure Individual Infection Longitudinal cohort Mass Spectrum Analysis Meningeal Tuberculosis Metabolic Methods Morbidity - disease rate Mycobacterium tuberculosis Nested Case-Control Study Nutritional status Organism Pathway Analysis Pediatrics Performance Population Positioning Attribute Prevention Preventive therapy Proteomics Recommendation Research Risk Sampling Scientist Serology South Africa Subgroup System Testing Therapy trial Time Toxic effect Training Tuberculosis Viral Virus Virus Diseases biomarker identification biomarker signature biosignature clinical epidemiology clinical translation clinically relevant co-infection cohort cost design disease classification epidemiologic data high risk insight metabolomics mortality novel marker overtreatment pathogen pathogenic virus predictive marker predictive signature prevent progression risk prospective recruit repository response transcriptomics treatment response tuberculosis treatment

项目摘要

PROJECT SUMMARY Background: Seventy million children globally are estimated to be infected with Mycobacterium tuberculosis (Mtb), the bacteria which causes tuberculosis (TB). Of these, 1 million develop TB disease each year with a quarter of them dying. Young children and those living with HIV are at high risk of progressing from Mtb infection to TB disease and of developing severe forms of TB. They therefore represent a key population to target with TB preventive therapy (TPT). Providing TPT to all children exposed to TB, especially in settings with high TB burden, results in substantial overtreatment, with associated costs and toxicity. Yet the current tests of Mtb infection are inadequate to predict future progression to disease in children. Developing new tests that accurately predict which TB-exposed children will progress to TB, is a critical priority and will allow for more targeted approaches to TB prevention. The identification of Mtb biomarkers in children should also consider relevant other factors, including age, and exposure to other common pathogens. Several common viruses have been shown to influence the risk of developing TB and are likely to affect biomarker signatures, yet few studies have evaluated the influence of viruses on childhood TB biomarkers. Finally, current tests of Mtb infection indicate immunological sensitization to Mtb rather than viable bacilli. If it were possible to identify a biosignature associated with Mtb death, this could provide an additional strategy for targeted TPT approaches in young children. Our group has an extensive track record of translational clinical research into pediatric TB. Our team consists of world leaders in the fields of clinical pediatrics, epidemiology, immunology, proteomics, transcriptomics, and bioinformatics. Methods: We will use samples from our three rigorously conducted studies in children <5 years, a drug-resistant TB preventive therapy trial, an observational household contact study, and a prospective diagnostic study, all conducted in a setting with high burden of TB and HIV. We will carry out a cross-sectional analysis to explore differences in biosignatures along the TB disease spectrum, nested case-control studies in longitudinal cohorts to evaluate risks of progression to Mtb infection and TB disease, and studies to evaluate changes in signatures on treatment for Mtb infection and early disease. We will use proteomic (SomaScan), transcriptomic (RNA-seq), metabolomic (mass spectrometry) and antibody (Systems Serology) approaches, and use a training/test design, to identify biomarker signatures. We will examine biosignatures in the context of clinical co-variates and viral exposure (PepSeq and RNA-seq). Finally, we will integrate the different approaches to generate the most robust biomarker combinations and provide the most granular insight into the biology of TB disease progression. Impact: Identifying novel biomarkers of TB disease progression in young children, including those living with HIV, would transform the global response to pediatric TB. For the first time, it would be possible to prevent TB by identifying and effectively treating children at the highest risk of future disease. This would have a substantial impact on overall morbidity and mortality.

项目概要背景：全球估计有 7000 万儿童感染结核分枝杆菌 (Mtb)，引起结核病 (TB) 的细菌。其中，每年有 100 万人患上结核病其中四分之一正在死亡。幼儿和艾滋病毒感染者感染结核杆菌的风险很高结核病和发展为严重形式的结核病。因此，他们是重点目标人群结核病预防治疗（TPT）。向所有接触结核病的儿童提供 TPT，特别是在结核病高发地区负担，导致严重的过度治疗，以及相关的费用和毒性。然而目前 Mtb 的测试感染不足以预测儿童未来疾病的进展。开发准确的新测试预测哪些接触结核病的儿童将发展为结核病，是一个至关重要的优先事项，并且可以更有针对性结核病预防方法。儿童 Mtb 生物标志物的鉴定还应考虑其他相关因素因素，包括年龄和接触其他常见病原体。已显示几种常见病毒影响患结核病的风险，并可能影响生物标志物特征，但很少有研究评估病毒对儿童结核病生物标志物的影响。最后，目前的结核分枝杆菌感染测试表明免疫学对 Mtb 而非活杆菌敏感。如果有可能识别与 Mtb 相关的生物特征死亡，这可以为幼儿的有针对性的 TPT 方法提供额外的策略。我们组有儿科结核病转化临床研究的广泛记录。我们的团队由世界领导人组成在临床儿科、流行病学、免疫学、蛋白质组学、转录组学和生物信息学领域。方法：我们将使用三项针对 5 岁以下儿童（一种耐药性儿童）进行严格研究的样本。结核病预防治疗试验、观察性家庭接触研究和前瞻性诊断研究，全部在结核病和艾滋病毒高负担的环境中进行。我们将进行横断面分析来探索结核病谱中生物特征的差异，纵向队列中的巢式病例对照研究评估进展为结核分枝杆菌感染和结核病的风险，以及评估特征变化的研究关于 Mtb 感染和早期疾病的治疗。我们将使用蛋白质组学 (SomaScan)、转录组学 (RNA-seq)、代谢组学（质谱法）和抗体（系统血清学）方法，并使用训练/测试设计，识别生物标志物签名。我们将在临床协变量和病毒的背景下检查生物特征暴露（PepSeq 和 RNA-seq）。最后，我们将整合不同的方法来生成最稳健的生物标志物组合，并提供对结核病进展生物学的最细致的了解。影响：识别幼儿（包括患有结核病的儿童）结核病进展的新生物标志物艾滋病毒将改变全球对儿童结核病的应对措施。第一次有可能预防结核病通过识别和有效治疗未来疾病风险最高的儿童。这将产生实质性的对总体发病率和死亡率的影响。