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

描述（由申请人提供）：哮喘是一种常见疾病，其特征为气道炎症、可逆性气道阻塞和气道高反应性。越来越多的人认识到哮喘的表型异质性，包括严重程度和对药物的反应。这些差异很可能是由不同的潜在分子表型驱动的，其发现将为靶向治疗的开发提供信息。在先前使用特征良好的哮喘患者的研究中，来自人气道上皮细胞的基因表达的差异确定了两个主要的患者组，其中一个患者组的基因表达强烈受炎性T辅助细胞（Th 2）细胞因子白细胞介素-13（IL-13）驱动，这被称为Th 2“高”哮喘，另一种是IL-13驱动的基因的表达不显著高于健康对照或“Th 2低”哮喘中发现的水平。这项工作表明，与Th 2低哮喘患者相比，Th 2高受试者对吸入皮质类固醇的反应更好。基于已发表的数据和我们自己的初步数据，我们假设Th 1和Th 17炎症通路定义了人类哮喘的其他分子表型。我们的目的是测试这一假设，关联表型的临床特征，包括对皮质类固醇的反应，并开发基于Th 1，Th 2和Th 17签名的人类受试者的分子表型诊断工具。Th 1、Th 2和Th 17特征将从细胞因子刺激的上皮细胞系的基于微阵列的全基因组表达谱中开发出来。这些特征将用于根据获得的哮喘受试者自身气道上皮细胞的基因表达谱将其聚类为辅助性T细胞亚群表型。将使用信息量最大的上皮细胞基因开发基于PCR的检测。将通过使用机器学习算法来开发这些分子表型的非侵入性测试，以发现受试者外周血样本的全基因组表达谱中的模式。分子表型的鉴定，以及非侵入性地分配Th 2，Th 1或Th 17表型的可靠测试的可用性将提供预测哪种药物对个体最有效的潜力，同时避免无效疗法的不必要的副作用，并通过在临床试验期间提供生物标志物来告知针对特定表型的疗法的开发。 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，但高达30%的患者对药物没有反应。哮喘有多种形式，具有不同的触发因素，长期结果和对药物的反应。这项工作的目标是：1）应用人类基因组学的技术进步来发现不同类别的哮喘，2）根据这些类别开发测试，以预测哪些人会对特定疗法产生反应，从而提高护理效率，减少无效药物的副作用。

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.