Pharmacogenomics of Adrenal Suppression with Inhaled Corticosteroids (PhASIC)

吸入糖皮质激素抑制肾上腺的药物基因组学(阶段) Amber Dahlin博士MMSc，Jessica Lasky-Su ScD，Ann Wu MD mph，Kelan Tantisira MD mph，Scott Weiss 马里兰州英里每小时 项目说明 系统生物学的最新进展使识别治疗的分子预测因子成为可能。 对包括哮喘在内的复杂疾病的结果。哮喘是人类最常见的慢性病之一。 吸入性皮质类固醇是治疗症状的常规处方药。而当 通常耐受性良好，长期使用皮质类固醇会引起严重的副作用，包括肾上腺。 抑制，一个重要的不良事件，可能导致急性肾上腺危机，因为抑制 皮质醇。由于30%或更多的哮喘患者对类固醇的反应性较差，需要增加 在控制哮喘症状的剂量下，这些患者发生肾上腺抑制的风险增加。 皮质类固醇反应和肾上腺抑制均显示可重复的个体间差异。 这在一定程度上是由于遗传学；然而，基因和分子对类固醇反应和 对肾上腺的抑制还不是很清楚。 考虑到对皮质类固醇反应不良的潜在严重性，临床医生预测 哮喘患者可能会做出反应，这可能会减轻不必要的药物暴露，降低副作用的风险， 包括肾上腺抑制。这一创新最终可能允许临床医生量身定做治疗方案 更准确地说，是为了避免不良事件，从而解决未得到满足的临床需求。药物基因组学 承诺改善哮喘治疗，并专注于确定皮质类固醇的分子“驱动因素” 有效的治疗可以显著改善患者的治疗结果。 这项研究的目标是确定与类固醇反应有关的基因和代谢物。 哮喘。我们将使用一种创新的系统来阐明哮喘激素耐药的分子驱动因素。 基于生物学的方法，将大种群的基因组和代谢图谱与预测 计算机建模，使发现治疗反应的生物学意义变得更有可能，因为没有 单一的“组学”方法可能会导致可翻译的研究结果。这些分子预报器最终可能 包括未来的临床或诊断测试，以推进哮喘治疗的精准医学努力。在……里面 此外，通过这项研究工作，我们将增加对肾上腺等不良事件的理解 抑制与治疗结果有关。这项工作有望为驾驶提供新的信息 新的治疗模式，并最终改善哮喘患者的风险状况。

Pharmacogenomics of Adrenal Suppression with Inhaled Corticosteroids (PhASIC) Amber Dahlin PhD MMSc, Jessica Lasky-Su ScD, Ann Wu MD MPH, Kelan Tantisira MD MPH, Scott Weiss MD MPH Project Description Recent advances in systems biology have enabled the identification of molecular predictors of treatment outcomes for complex diseases, including asthma. Asthma is one of the most common chronic diseases in the world, and inhaled corticosteroids are routinely prescribed medications for management of symptoms. While generally well tolerated, the long-term use of corticosteroids can elicit serious side effects, including adrenal suppression, an important adverse event with the potential to lead to acute adrenal crisis due to suppression of cortisol. As 30% or more of asthma patients experience poor steroid responsiveness and require increased doses to control asthma symptoms, these patients are at increased risk of developing adrenal suppression. Both corticosteroid responsiveness and adrenal suppression demonstrate repeatable inter-individual variation that is partly due to genetics; however, the genetic and molecular contributions to both steroid response and adrenal suppression are not well understood. Given the potential severity of poor responsiveness to corticosteroids, the ability of clinicians to predict how asthma patients may respond could mitigate unnecessary drug exposure and reduce the risk of side effects, including adrenal suppression. This innovation could ultimately allow clinicians to tailor treatment regimens more precisely to avoid adverse events, thereby addressing an unmet clinical need. Pharmacogenomics bears the promise to improve asthma care, and focusing on identifying the molecular ‘drivers’ of corticosteroid response could significantly improve treatment outcomes for patients. The goal of this study is to identify the genes and metabolites that contribute to steroid responsiveness in asthma. We will clarify the molecular drivers of steroid resistance in asthma using an innovative, systems biology-based approach that integrates genomic and metabolomic profiling of large populations with predictive computational modeling, making the discovery of biologic implications of treatment response more likely, as no single ‘omics’ approach is likely to lead to translatable findings. These molecular predictors could ultimately comprise a future clinical or diagnostic test to advance precision medicine efforts for asthma treatment. In addition, through this research effort, we will increase understanding of how adverse events such as adrenal suppression are linked to treatment outcomes. This work is anticipated to provide novel information to drive new treatment paradigms and, ultimately, improve patient risk profiles for asthma.