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，但哮喘的恶化占了大量可预防的发病率，美国每年的医疗费用总计超过500亿美元。尽管药物基因组学在改善哮喘治疗方面显示出巨大的潜力，但人类基因组计划所产生的遗传知识在哮喘中的应用尚不可用。我们的初步研究表明，关注年龄相关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 我们相信，调节吸入类固醇和β-2激动剂反应的特定遗传机制在儿童和成人之间是不同的，关注这些差异将产生新的生物学发现，从而实现反应的可预测性，并有助于儿科临床护理。使用ae依赖的生物标记物预测哮喘药物反应，通过允许临床医生根据个人需求量身定做哮喘治疗，极有可能显著改善哮喘治疗。这将导致较少的哮喘痛苦和巨大的成本节省，因为哮喘加重的数量将减少。这项研究将阐明两种最常用的哮喘药物，吸入类固醇和β-2激动剂的反应。这项研究利用了现有的遗传、基因组和代谢组学数据，这些数据来自临床试验和真实人群。用更多信息将遗传变异与治疗反应联系起来 基因组学和新陈代谢组学将提供对可能被激活的生物途径的洞察。通过整合和考虑遗传学、基因组学和代谢组学之间的相互作用，我们将开发一个预测吸入类固醇和β-2激动剂反应的综合信号。在这项研究的结论中，我们希望确定儿童对吸入类固醇和β-2激动剂反应的遗传、基因组和代谢指标。拟议研究的结果将提供一个重要的机会，使哮喘药物反应的预测在临床实践中成为现实，从而使大量患者、医疗保健行业和整个社会受益于国内和全球。从这项研究中获得的知识将推动儿童哮喘个性化药物领域的发展。

 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.