Improved Prediction of Response to Asthma Medication Using Small Molecules

描述(由申请人提供)：巴德临床试验旨在为对低剂量吸入皮质类固醇(ICS)无反应的黑人个体确定最合适的附加疗法。这一独特的队列提供了4种治疗方案的重复采样，并提供了比较儿童和成人反应的机会。使用基线和以下4种治疗方案获得的样本，这项辅助研究建议通过量化Th2、炎症和分解标记物以及通过使用互补代谢组学技术，显著增加来自BARD的临床和遗传数据。我们假设ICS反应性个体将具有Th2高表型，反映在IL4、IL13、IL5、IgE和Periostin的升高上。我们先前已经发现尿白三烯E4(ULTE4)与哮喘以及鞘磷脂与COPD之间的关系。因此，我们将检验LTE4和其他促炎分子在ICS反应性个体中增加的假设。由于哮喘是一种异质性疾病，需要了解多个分子的动力学才能全面了解发病机制，我们将利用无偏见的代谢组学方法来发现新的标志物。我们预计，根据Th2、炎症和其他与疾病相关的分子的相对丰富程度，可以预测对药物的反应，药物反应的水平将恢复到正常水平。最后，我们预计，个体群体将基于机械性差异进行集群。因此，在特定目标1(SA1)中，我们将对Th2、炎症和分解标志物进行量化，并将对基线血浆、痰(仅限成人)和尿样进行代谢组学研究。在SA2中，我们将开发预测模型，执行聚类分析，并将痰、血浆和尿液的结果关联起来。在SA3中，我们将使用纵向收集的尿样来确定增加ICS治疗对特定分子的影响。这项高影响力的临床研究将提供一个前所未有的机会来确定血浆标志物是否可以用来预测治疗反应，从而回答临床医学中的紧迫问题。

DESCRIPTION (provided by applicant): The BARD clinical trial aims to determine the most appropriate add-on therapy for Black individuals who are not responding to low dose inhaled corticosteroids (ICS). This unique cohort offers repeated sampling across 4 treatment regimens and provides an opportunity to compare response in children and adults. Using samples obtained at baseline and following 4 treatment regimens, this ancillary study proposes to significantly augment clinical and genetic data from BARD with mechanistic information through quantitation of Th2, inflammatory, and resolving markers and through the use of complementary metabolomics techniques. We hypothesize that ICS-responsive individuals will have a Th2-high phenotype, reflected in increased IL4, IL13, IL5, IgE, and periostin. We have previously found a relationship between urinary leukotriene E4 (uLTE4) and asthma, and between sphingolipids and COPD. Therefore we will test the hypothesis that LTE4 and other pro-inflammatory molecules are increased in ICS- responsive individuals. Because asthma is a heterogeneous condition, knowing the dynamics of multiple molecules will be required in order to fully understand mechanism, and we will utilize an unbiased metabolomics approach to discover new markers. We expect that response to medication can be predicted based on the relative abundance of Th2, inflammatory, and other disease-related molecules and that levels will revert to normal levels in response to medication. Finally, we expect that groups of individuals will cluster based on mechanistic differences. Therefore, in specific aim 1 (SA1), we will quantitate Th2, inflammatory, and resolving markers and will perform metabolomics on baseline plasma, sputum (adults only), and urine samples. In SA2 we will develop prediction models, perform cluster analysis, and correlate results from sputum, plasma, and urine. In SA3 we will use longitudinally collected urine samples to determine the effect of increased ICS therapy on specific molecules. This high impact clinical study will provide an unprecedented opportunity to determine if plasma markers can be used to predict response to therapy, thereby answering urgent questions in clinical medicine.