Improved Prediction of Response to Asthma Medication Using Small Molecules

描述（由申请人提供）：BARD临床试验旨在确定对低剂量吸入皮质类固醇（ICS）无反应的黑人患者最合适的附加治疗。这个独特的队列提供了4种治疗方案的重复抽样，并提供了比较儿童和成人反应的机会。使用基线和4种治疗方案后获得的样本，本辅助研究建议通过定量Th2、炎症和溶解标记物以及使用补充代谢组学技术，显著增加BARD的临床和遗传数据，并提供机制信息。我们假设ics应答个体将具有高th2表型，反映在IL4， IL13, IL5， IgE和periostin升高。我们之前已经发现尿白三烯E4 （uLTE4）与哮喘、鞘脂与COPD之间的关系。因此，我们将验证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，为了充分了解其机制，需要了解多分子的动力学，我们将利用无偏见的代谢组学方法来发现新的标记物。我们期望对药物的反应可以根据Th2、炎症和其他疾病相关分子的相对丰度来预测，并且这些分子的水平会在药物治疗后恢复到正常水平。最后，我们期望个体群体将基于机制差异聚类。因此，在特定目标1 （SA1）中，我们将量化Th2、炎症和溶解标志物，并对基线血浆、痰（仅限成人）和尿液样本进行代谢组学分析。在SA2中，我们将建立预测模型，进行聚类分析，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液样本来确定增加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于预测治疗反应，从而回答临床医学中的迫切问题。

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.