Using signatures of T-helper cell inflammation to phenotype human asthma

利用 T 辅助细胞炎症特征对人类哮喘进行表型分析

• 批准号: 8202823
• 负责人: Nirav Rati Bhakta
• 金额: $ 5.81万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-01-01 至 2012-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8202823
• 关键词: Accounting; Adrenal Cortex Hormones; Adult; Adverse effects; Affect; Algorithms; Allergens; Americas; Asthma; Biological Assay; Biological Markers; Biopsy Specimen; Blood; Blood specimen; Breathing; CD4 Positive T Lymphocytes; Caring; Cell Line; Characteristics; Clinical; Clinical Research; Clinical Trials; Data; Development; Diagnosis; Diagnostic; Diagnostic tests; Disease; Epithelial; Epithelial Cells; Exhalation; Funding; Gene Expression; Gene Expression Profile; Genes; Genome; Genomics; Goals; Gold; Grant; Helper-Inducer T-Lymphocyte; Heterogeneity; Human; IgE; In Vitro; Individual; Inflammation; Inflammatory; Interleukin-13; Lung diseases; Machine Learning; Medicine; Microarray Analysis; Molecular; Molecular Profiling; Mus; Nitric Oxide; Outcome; Pathway interactions; Patients; Pattern; Pharmaceutical Preparations; Phenotype; Publishing; Pulmonary Tuberculosis; RNA; Research; Sampling; Sarcoidosis; Serum; Severities; Techniques; Testing; Tissue Sample; Treatment Cost; Whole Blood; Work; airway hyperresponsiveness; airway inflammation; airway obstruction; airway remodeling; atopy; base; clinically relevant; cytokine; exposed human population; human subject; human tissue; molecular phenotype; peripheral blood; research study; response; therapy development; tool

DESCRIPTION (provided by applicant): Asthma is a common disease characterized by airway inflammation, reversible airway obstruction, and airway hyperresponsiveness. There is growing recognition of phenotypic heterogeneity in asthma, including in severity and response to medication. It is likely that these differences are driven by distinct underlying molecular phenotypes, the discovery of which would inform the development of targeted therapies. In prior studies using well-characterized patients with asthma, differences in gene expression from human airway epithelial cells identified two major groups of patients, one in which gene expression is strongly driven by the inflammatory the T-helper cell (Th2) cytokine interleukin-13 (IL-13), which has been called Th2 "high" asthma, and another in which IL-13 driven genes are not significantly expressed above that level found in healthy controls, or "Th2 low" asthma. This work demonstrated that compared to Th2-low asthmatics, Th2-high subjects a better response to inhaled corticosteroids. Based on published data and our own preliminary data, we hypothesize that Th1 and Th17 pathways of inflammation define additional molecular phenotypes of human asthma. Our aims are to test this hypothesis, associate phenotypes to clinical characteristics including response to corticosteroids, and develop diagnostic tools for molecular phenotyping of human subjects based on Th1, Th2 and Th17 signatures. Th1, Th2, and Th17 signatures will be developed from microarray- based whole genome expression-profiling of cytokine-stimulated epithelial cell lines. These signatures will be used to cluster research asthma subjects into T helper subset phenotypes based on the gene expression profiles of their own airway epithelial cells obtained. The most informative epithelial cell genes will be used to develop a PCR-based test. A non-invasive test for these molecular phenotypes will be developed through the use of machine learning algorithms to find patterns in the whole genome expression profiles of subjects' peripheral blood samples. The identification of molecular phenotypes, and the availability of reliable tests to assign Th2, Th1, or Th17 phenotypes non-invasively would provide the potential to predict which medication will work best for an individual while avoiding unnecessary side effects form ineffective therapies, and to inform the development of therapies targeted to specific phenotypes by providing biomarkers during clinical trials. PUBLIC HEALTH RELEVANCE: Asthma is a very common lung disease affecting 7% of adults in America, and despite high treatment costs, up to 30% of patients do not respond to medications. Asthma has many forms with varying triggers, long-term outcomes and responses to medications. The goals of this work are to 1) apply technological advances in human genomics to discover distinct classes of asthma, and 2) develop tests based on these classes to predict which individuals will respond to a specific therapy, leading to more efficient care and less side effects from ineffective medicines.

描述（由申请人提供）：哮喘是一种常见疾病，其特征是气道炎症，可逆气道阻塞和气道高反应性。哮喘中表型异质性的认识日益认识，包括严重性和对药物的反应。这些差异很可能是由不同的基本分子表型驱动的，这些分子表型的发现将导致靶向疗法的发展。在先前使用哮喘患者特征良好的患者的研究中，人类气道上皮细胞的基因表达差异鉴定出了两组主要的患者，其中一组由炎症性T助血器细胞（TH2）细胞因子介体Interleukin-13（IL-13）强烈驱动，这已经被称为TH2“高于“ Atthma”，并且在IL-1上不显着，并在IL-1上均未引起IL-13的级别。控制，或“ Th2低”哮喘。这项工作表明，与Th2-low哮喘患者相比，Th2高的受试者对吸入的皮质类固醇的反应更好。根据已发布的数据和我们自己的初步数据，我们假设炎症的TH1和TH17途径定义了人类哮喘的其他分子表型。我们的目的是检验该假设，将表型与临床特征相关联，包括对皮质类固醇的反应，并开发基于TH1，TH2和TH17特征的人类受试者分子表型的诊断工具。 TH1，TH2和TH17特征将是由基于微阵列的整个基因组表达的促进细胞因子刺激的上皮细胞系的。这些特征将根据其自身气道上皮细胞的基因表达谱图将哮喘受试者聚集到T辅助子集表型中。最有用的上皮细胞基因将用于开发基于PCR的测试。这些分子表型的非侵入性测试将通过使用机器学习算法来在受试者外周血样品的整个基因组表达谱中找到模式开发。分子表型的鉴定以及可靠的测试可用于分配TH2，TH1或TH17表型非侵入性的表型将提供潜力，可以预测哪种药物对个人最有效，同时避免不必要的副作用形式的疗效疗法，并通过为特定的临床生物标志性提供针对特定现象的治疗疗法，并告知针对特定现象的疗法的开发。 公共卫生相关性：哮喘是一种非常常见的肺部疾病，影响美国7％的成年人，尽管治疗费用很高，但多达30％的患者对药物没有反应。哮喘具有多种形式，具有不同的触发因素，长期结局和对药物的反应。这项工作的目标是1）在人类基因组学中应用技术进步来发现不同的哮喘类别，2）基于这些类别的测试，以预测哪些人将对特定的疗法做出反应，从而导致更有效的护理，而对无效药物的副作用更少。