Age-Dependent Pharmacogenomics of Asthma Treatment (ADAPT)

 描述（由申请人提供）： 哮喘是最常见的慢性儿科疾病，影响着700多万美国儿童。尽管有有效的治疗选择，但哮喘急性发作造成了大量可预防的发病率，美国每年的医疗保健费用总计超过500亿美元。尽管药物基因组学在改善哮喘护理方面显示出巨大的潜力，但人类基因组计划产生的遗传知识还不能用于哮喘。我们的初步研究表明，关注年龄依赖性因素可能会产生适用于儿童的哮喘药物反应的重要指标。我们 认为，调节吸入性类固醇和β2受体激动剂反应的特定遗传机制在儿童和成人之间存在差异，关注这些差异将产生新的生物学发现，这将使反应可预测并有助于儿科临床护理。 使用ae依赖的生物标志物来预测哮喘药物反应，通过允许临床医生根据个人需要定制哮喘管理，可以显著改善哮喘管理。这将减少哮喘患者的痛苦和巨大的成本节约，因为哮喘加重的数量将减少。 本研究将阐明对两种最常用的哮喘药物（吸入性类固醇和β2受体激动剂）的反应。这项研究利用了来自临床试验和现实生活人群的现有遗传学、基因组学和代谢组学数据。将遗传变异与治疗反应以及其他信息联系起来 从基因组学和代谢组学将提供深入了解可能被激活的生物途径。通过整合和解释遗传学、基因组学和代谢组学之间的相互作用，我们将开发一个综合的特征，预测对吸入性类固醇和β2受体激动剂的反应。 在这项研究的结论，我们希望已经确定了遗传，基因组学和代谢组学指标的儿童反应吸入类固醇和β2-受体激动剂。拟议研究的结果将提供一个重要的机会，使预测哮喘药物反应在临床实践中成为现实，从而使国内和全球大量患者，医疗保健行业和整个社会受益。从这项研究中获得的知识将推动儿童哮喘个性化医学领域的发展。

 DESCRIPTION (provided by applicant): Asthma, the most common chronic pediatric disease, affects over 7 million U.S. children. Despite effective treatment options, exacerbations from asthma account for substantial preventable morbidity and annual U.S. healthcare costs totaling more than $50 billion. Applications of the genetic knowledge resulting from the Human Genome Project are not yet available for asthma despite the immense potential that pharmacogenomics demonstrates for improving asthma care. Our preliminary studies suggest that focusing on age-dependent factors is likely to yield important indicators of asthma drug response that are applicable to children. We believe that specific genetic mechanisms regulating response to inhaled steroids and β2-agonists differ between children and adults, and focusing on these differences will yield novel biologic findings that will allow response predictability and aid pediatric clinical care. Using ae-dependent biomarkers to predict asthma drug response carries tremendous promise to significantly improve asthma management by allowing clinicians to tailor asthma management to individual needs. This will result in less asthma suffering and huge cost-savings as the number of exacerbations from asthma will decrease. This study will elucidate response to the two most commonly used medications for asthma, inhaled steroids and β2-agonists. This research employs existing genetic, genomic, and metabolomics data from clinical trial and real-life populations. Linking genetic variants to the therapeutic responses with additional information from genomics and metabolomics will provide insight into the biologic pathways that may be activated. By integrating and accounting for the interplay between genetics, genomics, and metabolomics, we will develop a comprehensive signature that predicts response to inhaled steroids and β2-agonists. At the conclusion of this research, we expect to have identified genetic, genomic, and metabolomic indicators of child response to inhaled steroids and β2-agonists. The results from the proposed study would provide an important opportunity to make prediction of asthma drug response a reality in clinical practice, and thus benefit very large numbers of patients, the healthcare industry, and society at large both domestically and globally. Knowledge gained from this research will advance the field of personalized medicine for pediatric asthma.