Airway Microbial Community Structure and Function in Chronic Asthma

描述（由申请人提供）：这是一份K23指导患者导向研究职业发展奖的申请，申请对象是加州大学旧金山分校肺/重症医学医师Yvonne Huang博士。黄博士正在建立自己作为气道微生物定植（气道微生物群）在哮喘中的作用的临床研究者。本次K23奖将为黄博士实现以下职业发展目标提供必要的支持：(1)获得领导哮喘临床-转化研究的培训和实践经验；(2)学习并应用先进的统计方法，结合微阵列和下一代测序方法产生的气道微生物组数据，分析临床数据；(3)进一步积累研究气道环境中全局功能基因表达方法的知识和经验。为了实现这些目标，黄博士组建了一个多学科的指导团队，在这三个领域都有互补的专业知识。该团队由主要导师Homer Boushey博士（UCSF肺医学教授，国际公认的哮喘临床研究者）和两位共同导师Mark Segal博士（UCSF生物统计学教授，生物信息学和分子生物统计学中心主任，复杂分子和基因组数据分析的高级统计技术专家）组成；Susan Lynch博士，UCSF医学助理教授，一位微生物学家专家，指导UCSF医学院消化病学部门的微生物组研究核心。哮喘是一种常见的气道疾病，病因不明，社会经济负担沉重。哮喘的临床异质性现已得到充分认识，这使得研究人员认为可能存在不同的发病机制。一个越来越受关注的领域是气道细菌定植在哮喘发病机制或特定哮喘表型中的潜在作用。黄博士的研究将检查哮喘患者呼吸道标本中发现的细菌微生物群的组成是否受到吸入皮质类固醇或大环内酯类抗生素（两种用于哮喘治疗的药物）的影响（目的1和2）。此外，她将研究哮喘气道微生物组的整体功能基因表达谱，以研究它们如何与疾病的临床特征相关（目的3）。黄博士将利用UCSF气道临床研究中心的基础设施，招募哮喘患者和健康志愿者进行一项前瞻性试点研究，研究哮喘患者和健康个体之间气道微生物组的差异，以及常用处方疗法对微生物组的影响。她还将应用创新的、高通量的方法对哮喘患者的气道微生物组进行系统发育和功能分析。本研究将为未来更大规模哮喘患者或特定哮喘表型的气道微生物组研究奠定重要基础。

DESCRIPTION (provided by applicant): This is an application for a K23 mentored patient-oriented research career development award for Dr. Yvonne Huang, M.D., a pulmonary/critical care medicine physician at the University of California, San Francisco. Dr. Huang is establishing herself as a clinical investigator of the role of airway microbial colonization (airway microbiota) in asthma. This K23 award will provide Dr. Huang with the support necessary to accomplish the following career development goals: (1) to obtain training and practical experience in leading clinical- translational research studies of asthma; (2) to learn and apply advanced statistical methods to analyze clinical data in conjunction with airway microbiome data generated from microarray and next-generation sequencing approaches; and (3) to acquire further knowledge and experience on methods for studying global functional gene expression in the airway environment. To achieve these goals, Dr. Huang has assembled a multidisciplinary mentoring team with complementary expertise in each of these three areas. This team is comprised of a primary mentor, Dr. Homer Boushey, Professor of Pulmonary Medicine at UCSF and an internationally recognized clinical investigator of asthma, and two co-mentors: Dr. Mark Segal, Professor of Biostatistics at UCSF and Director of the Center for Bioinformatics and Molecular Biostatistics, an expert in advanced statistical techniques for the analysis of complex molecular and genomic data; and Dr. Susan Lynch, Assistant Professor of Medicine at UCSF, an expert microbiologist who directs the microbiome research core in the Division of Gastroenterology, Department of Medicine at UCSF. Asthma is a common airway disease of still unknown etiology that bears significant socioeconomic burden. Clinical heterogeneity in asthma is now well-recognized, leading researchers to consider that different pathogenetic mechanisms may exist. One area of increasing interest is the potential role of airway bacterial colonization in the pathogenesis of asthma or of specific asthma phenotypes. Dr. Huang's research will examine if the composition of bacterial microbiota found in respiratory specimens from asthma patients are influenced by the use of inhaled corticosteroids or macrolide antibiotics, two medications used in the management of asthma (Aims 1 and 2). She additionally will study global functional gene expression profiles in the asthma airway microbiome to examine how they may relate to clinical features of disease (Aim 3). Dr. Huang will use the infrastructure of the UCSF Airway Clinical Research Center to enroll asthmatic and healthy volunteers for a prospective pilot study of differences in the airway microbiome between asthmatic and healthy individuals, and the impact of commonly prescribed therapies on the microbiome. She also will apply innovative, high-throughput approaches to perform phylogenetic and functional profiling of the airway microbiome in asthmatic patients. This research will lay important groundwork for future studies of the airway microbiome in larger populations of asthma patients or of specific asthma phenotypes.