Profiling the Lung Transcriptome for Precision Diagnosis of Respiratory Infections using Host/Pathogen Metagenomic Sequencing

项目摘要/摘要 作为一名年轻的临床医生兼研究员，我专注于并致力于通过 面向患者的呼吸道感染研究、应用基因组学和临床医学。这款K23将提供 为建立一个成功的研究生涯所需的支持和培训，重点是改善诊断和 利用先进的基因组技术治疗呼吸系统疾病。 与我的导师和共同导师一起，我组建了一个杰出的K23研究委员会 以及专注于基因组学、肺部和重症监护医学、传染病、 免疫学和生物信息学。他们帮助我制定了一项强有力的培训计划，以便在三年内获得专业知识 主要领域：1)临床研究设计和分析，2)生物统计学和流行病学，3)生物信息学。这 计划包括课程作业、直接指导、实践经验和每周手稿同行评审 课程，通过加州大学旧金山分校的K学者计划，资助写作研讨会和职业建议。 我的提议的目标是受到我照顾过的许多危重病人的启发，这些病人都是急性 呼吸系统疾病，接受经验性治疗，有时无效，在许多情况下长期治疗 急性呼吸道疾病，因为现有的诊断方法无法提供信息的微生物学 诊断。这些经历让我意识到对更好的检测方法的迫切需要，这种检测方法可以提供 数据驱动--而不是经验--治疗严重下呼吸道感染(LRTI)的方法。我的K23 建议通过使用元基因组下一代测序(MNGS)来分析直接满足这一需求 危重病人呼吸道的宿主转录组和微生物病原体。 一个积极招募的、预期的成人急性呼吸衰竭需要机械治疗的队列 通风将通过三个具体目标进行研究。AIM 1将开发一种宿主基因表达分类器 将LRTI与非传染性急性呼吸道疾病区分开来。目标2将评估以下各项的性能 MNGS用于临床判定的下呼吸道感染患者的病原体检测。目标3将决定表现 基于mNGS基因组的耐药细菌LRTI患者耐药性预测。 这一建议结合了元基因组学和生物信息学，重点放在以患者为中心的肺病 感染研究。这项工作所产生的结果将为后续的展望提供基础 评估mNGS诊断对患者预后的影响的临床试验。这项建议直接与 我的职业目标是成为一名独立的内科医生-科学家，致力于推动肺病领域的发展 通过开发新的工具来加强临床诊断和提供精确的治疗策略。 通过以患者为中心的分子医学研究，受到独特和具有挑战性的案例的启发，我的目标是减少 呼吸道感染的负担。

PROJECT SUMMARY/ABSTRACT As a young clinician-investigator, I am focused and committed to improving human wellbeing through patient-oriented respiratory infection research, applied genomics and clinical medicine. This K23 will provide the support and training needed to build a successful research career focused on improving the diagnosis and treatment of respiratory diseases using advanced genomic technologies. Working with my mentor and co-mentors, I have assembled a K23 Research Committee of outstanding and dedicated faculty who are leaders in genomics, pulmonary and critical care medicine, infectious diseases, immunology and bioinformatics. They have helped me devise a robust training plan to acquire expertise in three key areas: 1) clinical research design and analysis, 2) biostatistics and epidemiology and 3) bioinformatics. This plan includes coursework, direct mentoring, hands-on experiences, and weekly manuscript peer review sessions, grant writing seminars and career advisement via the UCSF K Scholars program. The goals of my proposal are inspired by the many critically ill patients that I have cared for with acute respiratory illnesses who receive empiric, sometimes ineffective, and in many cases protracted treatments for acute respiratory illnesses because available diagnostics are unable to provide an informative microbiologic diagnosis. These experiences have made me realize the outstanding need for better assays that can provide a data driven – and not empiric – approach to treating severe lower respiratory tract infections (LRTIs). My K23 proposal directly addresses this need by engaging metagenomic next generation sequencing (mNGS) to assay both the host transcriptome and microbial pathogens from the airways of critically ill patients. An actively enrolling, prospective cohort of adults with acute respiratory failure requiring mechanical ventilation will be studied via three specific aims. Aim 1 will develop a host gene expression classifier that distinguishes LRTI from non-infectious acute respiratory conditions. Aim 2 will evaluate the performance of mNGS for pathogen detection in patients with clinically adjudicated LRTI. Aim 3 will determine the performance of mNGS genome-based antimicrobial resistance prediction in patients with drug-resistant bacterial LRTI. This proposal incorporates metagenomics and bioinformatics with a focus on patient-centered pulmonary infection research. The results generated from this work will provide the foundation for a subsequent prospective clinical trial evaluating the impact of mNGS diagnostics on patient outcomes. This proposal directly aligns with my career goals of becoming an independent physician-scientist working to advance the field of pulmonary medicine by developing new tools that enhance clinical diagnosis and inform precision treatment strategies. Through patient-focused molecular medicine research inspired by unique and challenging cases, I aim to reduce the burden of respiratory infections.