Host Proteomic Biosignatures for a Urine-based Diagnosis of Pulmonary Tuberculosis in Children

用于基于尿液诊断儿童肺结核的宿主蛋白质组生物特征

• 批准号: 10248492
• 负责人: Devan Jaganath
• 金额: $ 21.06万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10248492
• 关键词: Address; Adult; Age; Bioinformatics; Biological Assay; Biological Markers; Blood; California; Cessation of life; Child; Child Care; Childhood; Clinical; Consensus; Coupling; Data; Development; Diagnosis; Diagnostic; Diagnostic Sensitivity; Diagnostic tests; Disease; Enrollment; Environment; Evaluation; Funding; Gene Expression; Gene Expression Profile; Goals; Health system; Hospital Referrals; Human; Immune response; Immunoassay; Infection; Infrastructure; International; Lead; Machine Learning; Mass Spectrum Analysis; Measures; Mentored Patient-Oriented Research Career Development Award; Mentors; Mentorship; Mycobacterium tuberculosis; Nested Case-Control Study; Pathogenesis; Pathway Analysis; Pathway interactions; Performance; Physicians; Post-Translational Protein Processing; Prospective cohort; Proteins; Proteome; Proteomics; Public Health; Pulmonary Tuberculosis; Reporting; Research; Research Personnel; Resources; Role; Sampling; San Francisco; Scientist; Shotguns; Site; Specificity; Sputum; Testing; Training; Translating; Triage; Tuberculosis; Uganda; United States National Institutes of Health; Universities; Urine; Work; accurate diagnosis; base; biomarker discovery; biomarker panel; biosignature; candidate marker; career; career development; cohort; disease phenotype; experience; improved; mortality; multidisciplinary; novel; novel marker; point of care; point of care testing; pre-clinical; prospective; protein biomarkers; research and development; sample collection; tool; Address; Adult; Age; Bioinformatics; Biological Assay; Biological Markers; Blood; California; Cessation of life; Child; Child Care; Childhood; Clinical; Consensus; Coupling; Data; Development; Diagnosis; Diagnostic; Diagnostic Sensitivity; Diagnostic tests; Disease; Enrollment; Environment; Evaluation; Funding; Gene Expression; Gene Expression Profile; Goals; Health system; Hospital Referrals; Human; Immune response; Immunoassay; Infection; Infrastructure; International; Lead; Machine Learning; Mass Spectrum Analysis; Measures; Mentored Patient-Oriented Research Career Development Award; Mentors; Mentorship; Mycobacterium tuberculosis; Nested Case-Control Study; Pathogenesis; Pathway Analysis; Pathway interactions; Performance; Physicians; Post-Translational Protein Processing; Prospective cohort; Proteins; Proteome; Proteomics; Public Health; Pulmonary Tuberculosis; Reporting; Research; Research Personnel; Resources; Role; Sampling; San Francisco; Scientist; Shotguns; Site; Specificity; Sputum; Testing; Training; Translating; Triage; Tuberculosis; Uganda; United States National Institutes of Health; Universities; Urine; Work; accurate diagnosis; base; biomarker discovery; biomarker panel; biosignature; candidate marker; career; career development; cohort; disease phenotype; experience; improved; mortality; multidisciplinary; novel; novel marker; point of care; point of care testing; pre-clinical; prospective; protein biomarkers; research and development; sample collection; tool

PROJECT ABSTRACT Tuberculosis (TB) is a leading cause of mortality in children worldwide. Difficulty in obtaining sputum and a low sputum bacillary load are major barriers to diagnosis, and necessitate the development of a non-sputum, biomarker-based assay for childhood intrathoracic TB disease. Host biomarker discovery for childhood TB requires a greater focus on downstream proteins and their post-translational modifications (PTMs) that are more likely to be specific to a disease phenotype and can be more easily translated into a point-of-care test. With the support of this K23 award, Dr. Devan Jaganath will identify a host proteomic biosignature in urine that can achieve the goal accuracy for a triage and/or diagnostic test for pulmonary TB in children. To complete this objective, he will leverage an ongoing prospective cohort of symptomatic children being evaluated for intrathoracic TB in Kampala, Uganda, with the extensive proteomic facilities available at the University of California, San Francisco (UCSF). In Aim 1, he will perform targeted mass spectrometry on urine samples from children with confirmed vs. unlikely TB, and examine the abundance and ubiquitylation of 10 host proteins that have prior evidence of specific interactions with M. tuberculosis (Mtb) proteins as candidate biomarkers. In Aim 2, he will use shotgun mass spectrometry on the urine samples to identify all host proteins and their PTMs that can differentiate TB status as novel biomarkers, and perform pathway analysis to determine the subset with functional relevance to Mtb pathogenesis. In Aim 3, he will apply machine learning analyses to identify the smallest combination of biomarkers that can achieve the target accuracy thresholds for a triage and/or diagnostic test for intrathoracic TB disease. He will then evaluate the performance of promising biosignatures in an independent, prospectively enrolled test set. Through this approach, Dr. Jaganath seeks to optimize biomarker discovery for childhood TB diagnosis by coupling prospective clinical cohorts with a targeted and untargeted high-throughput approach to comprehensively examine non-sputum samples for host biomarkers for children. Dr. Jaganath's career goal is to be a physician scientist who translates non-sputum biomarkers into clinical tools that can improve the care of children with TB. To support his path to independence, the proposed work will be paired with a dedicated, multidisciplinary mentorship team and training in international pediatric TB biomarker studies, bioinformatics for proteomic analysis, and machine learning. UCSF is an outstanding environment that is committed to junior investigators with extensive resources for research and career development, and Mulago National Referral Hospital in Uganda is a leader in pediatric TB research, and has the established infrastructure for ongoing enrollment and sample collection. The findings will support an NIH R01 application to validate the biomarkers and biosignatures in large, diverse cohorts in comparison to existing non-sputum diagnostics. Thus, the K23 award will provide Dr. Jaganath with the critical mentorship, training, resources and experience to become an independent investigator who can make important contributions to the field of childhood TB.

项目摘要 结核病（TB）是全球儿童死亡率的主要原因。难以获得痰液和低 痰细菌负荷是诊断的主要障碍，需要开发非量表 基于生物标志物的儿童期胸前结核病测定法。宿主生物标志物发现儿童结核病 需要更加专注于下游蛋白及其翻译后修饰（PTMS） 可能是特定于疾病表型的，并且可以更容易地转化为护即点测试。与 Devan Jaganath博士对这一K23奖的支持将确定尿液中的宿主蛋白质组学生物签名 实现儿童肺结核分类和/或诊断测试的目标准确性。要完成 目的，他将利用正在评估有症状儿童的前瞻性队列 乌干达坎帕拉的胸前结核病，拥有广泛的蛋白质组学设施。 加利福尼亚，旧金山（UCSF）。在AIM 1中，他将对来自 患有确认与不太可能结核的儿童，并检查10种宿主蛋白​​的丰度和泛素化。 先前有与结核分枝杆菌（MTB）蛋白作为候选生物标志物的特定相互作用的证据。目标 2，他将在尿液样品上使用shot弹枪质谱法来识别所有宿主蛋白及其PTMS 可以将结核病状态作为新型生物标志物区分开，并执行途径分析以确定子集 与MTB发病机理的功能相关。在AIM 3中，他将应用机器学习分析以确定 生物标志物的最小组合可以实现分类和/或诊断的目标精度阈值 测试胸前TB疾病。然后，他将评估一个有希望的生物签名的表现 独立的，前瞻性的测试集。通过这种方法，Jaganath博士试图优化生物标志物 通过将前瞻性临床队列与有针对性和无目标的前瞻性临床队列耦合，发现儿童结核病诊断 高通量方法可以全面检查儿童宿主生物标志物的非投散样品。 Jaganath博士的职业目标是成为一名医师科学家 这可以改善结核病儿童的护理。为了支持他的独立之路，拟议的工作将是 与专门的，多学科的指导团队和国际小儿结核病生物标志物培训 研究，用于蛋白质组学分析的生物信息学和机器学习。 UCSF是一个杰出的环境 致力于为研究和职业发展提供广泛资源的初级调查员，以及mulago 乌干达的国家推荐医院是小儿结核病研究的领导者，并拥有建立的基础设施 进行持续的注册和样本收集。这些发现将支持NIH R01申请，以验证 与现有的非投散诊断相比，大型，多样的同类群体中的生物标志物和生物签名。因此， K23奖将为Jaganath博士提供关键的指导，培训，资源和经验 成为一个独立的研究者，可以为儿童结核病领域做出重要贡献。