Longitudinal Analysis of Transcriptomic Endophenotypes in Asthma

描述(由申请人提供)： 项目摘要尽管哮喘的基本致病机制不同，但驱动肺部生物学的基本过程存在于大多数(如果不是全部)损伤和修复反应中。然而，一个主要的挑战是确定这些情况下存在的共同模式。目前，哮喘表型的定义是有限的和不精确的临床范例，依赖于过敏史、发病年龄、肺功能和“严重”症状等特征。这些研究，包括重症哮喘研究计划(SARP)对哮喘集群的描述，是有用的，但受到人口统计和生理变量差异的推动，这些指标远离疾病的许多生物学方面。4与这些方法相比，综合功能基因组学有可能在反映对哮喘发病机制具有重要机械意义的真实内表型的水平上定义哮喘内表型。为此，我们的多学科研究团队开发了一种分子表型分析方法，利用在哮喘患者的痰和循环中测量的全基因组基因表达来评估转录型哮喘的内表型，并确定了3种哮喘的转录内表型(痰茶簇)。TEA组1的呼吸道炎症水平较低，且最可逆的气道阻塞；TEA组2的呼吸道炎症程度中等，可逆性气流阻塞，痰IL-13水平较高(Th2组)；而TEA组3的气道炎症水平最高，最不可逆的气道阻塞(重塑的组)，以及高水平的痰YKL-40(我们已证明与重塑和严重哮喘有关的几丁质酶样蛋白)。此外，使用来自该队列的匹配的血液基因表达数据，我们开发了一个包含69个基因的预测模型，该模型可以以85%的准确率确定个人的痰茶分类。综上所述，这些数据表明转录衍生的哮喘内表型与呼吸道炎症、生理重塑和免疫表型相关的细胞因子相关。在这一应用中，将使用整合功能基因组学来评估茶叶集群模型的稳定性。将对哮喘患者的第二个独立队列进行纵向研究，并确定与茶群相关的先天和获得性免疫系统反应。将评估茶簇对其他肺部疾病的概括性，以确定与茶簇相关的基本表达网络。最终，这些研究将提高我们在疾病部位分子水平上对哮喘异质性的理解，并识别具有相似基因网络调制的患者。这些结果将产生新的哮喘内表型分子诊断，可用于利用血液和痰基因表达对患者进行病理和治疗研究的细分，并为候选基因研究确定新的靶点。

DESCRIPTION (provided by applicant): PROJECT SUMMARY Despite differences in the underlying pathogenic mechanisms of asthma, the fundamental processes that drive lung biology are present across most, if not all, injury and repair responses. However, a major challenge is the identification of common patterns present in these conditions. Currently, asthma phenotypes have been defined in limited terms and imprecise clinical paradigms that rely on features such as allergic history, age of onset, lung function, and symptoms of "severity." These studies, including the Severe Asthma Research Program (SARP) characterization of asthma clusters, have been useful, but are driven by differences in demographic and physiologic variables, measures that are distal to many biologic aspects of the disease.4 In contrast to these approaches, integrative functional genomics has the potential to define asthma endophenotypes at a level reflective of true endophenotypes that are mechanistically important to the pathogenesis of asthma. To this end, our multidisciplinary research team has developed a molecular phenotyping protocol to evaluate transcriptomic asthma endophenotypes using genome-wide gene expression measured in the sputum and circulation of asthmatics and has identified 3 transcriptional endophenotypes of asthma (sputum TEA clusters). TEA cluster 1 has a low level of airway inflammation and the most reversible airway obstruction; TEA cluster 2 has a moderate amount of airway inflammation, reversible airflow obstruction, and high sputum IL-13 levels (Th2 cluster); and TEA cluster 3 has the highest level of airway inflammation, the least reversible airway obstruction (remodeled cluster), and high levels of sputum YKL-40 (a chitinase-like-protein we have shown to be associated with remodeling and severe asthma). In addition, using matched blood gene expression data from this cohort, we developed a predictive model using 69 genes that can determine an individual's sputum TEA cluster assignment with 85% accuracy. Taken together, these data demonstrate that transcriptomically-derived asthma endophenotypes are associated with airway inflammation, physiologic remodeling, and immunophenotype-associated cytokines. In this application, integrative functional genomics will be used to evaluate the stability of the TEA cluster model. A second independent cohort of asthma subjects will be studied longitudinally, and the innate and adaptive immune system responses associated with the TEA clusters will be determined. The generalizability of TEA clusters to other lung diseases will be evaluated to identify the fundamental expression networks associated with the TEA clusters. Ultimately, these studies will improve our understanding of asthma heterogeneity at the molecular level at the site of disease, and identify patients with similar modulation of gene networks. The results will generate new molecular diagnoses of asthma endophenotypes that can be used to sub-classify patients for pathogenetic and therapeutic studies using blood and sputum gene expression and identify novel targets for candidate gene studies.