Background

Variations in drug response between individuals have prevented us from achieving high drug efficacy in treating many complex diseases, including asthma. Genetics plays an important role in accounting for such interindividual variations in drug response. However, systematic approaches for addressing how genetic factors and their regulators determine variations in drug response in asthma treatment are lacking.

Objective

We sought to identify key transcriptional regulators of corticosteroid response in asthma using a novel systems biology approach.

Methods

We used Passing Attributes between Networks for Data Assimilations (PANDA) to construct the gene regulatory networks associated with good responders and poor responders to inhaled corticosteroids based on a subset of 145 white children with asthma who participated in the Childhood Asthma Management Cohort. PANDA uses gene expression profiles and published relationships among genes, transcription factors (TFs), and proteins to construct the directed networks of TFs and genes. We assessed the differential connectivity between the gene regulatory network of good responders versus that of poor responders.

Results

When compared with poor responders, the network of good responders has differential connectivity and distinct ontologies (eg, proapoptosis enriched in network of good responders and antiapoptosis enriched in network of poor responders). Many of the key hubs identified in conjunction with clinical response are also cellular response hubs. Functional validation demonstrated abrogation of differences in corticosteroid-treated cell viability following siRNA knockdown of 2 TFs and differential downstream expression between good responders and poor responders.

Conclusions

We have identified and validated multiple TFs influencing asthma treatment response. Our results show that differential connectivity analysis can provide new insights into the heterogeneity of drug treatment effects.

中文翻译：

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基因调控网络的差异连通性可区分哮喘中的皮质类固醇激素反应

背景

个体之间药物反应的差异使我们无法在治疗包括哮喘在内的许多复杂疾病中获得较高的药物疗效。遗传学在解释此类个体间药物反应变异中起着重要作用。然而，缺乏用于解决遗传因素及其调节物如何确定哮喘治疗中药物反应差异的系统方法。

客观的

我们试图使用一种新型的系统生物学方法来鉴定哮喘中皮质类固醇反应的关键转录调节因子。

方法

我们根据参加儿童哮喘管理队列的145名白人哮喘儿童的子集，使用了数据同化网络之间的传递属性（PANDA）来构建与吸入皮质类固醇的良好应答者和不良应答者相关的基因调控网络。PANDA使用基因表达谱和基因，转录因子（TF）和蛋白质之间的公开关系来构建TF和基因的定向网络。我们评估了良好反应者与较差反应者的基因调控网络之间的差异连通性。

结果

与反应较差的人相比，反应良好的人的网络具有不同的连通性和不同的本体论（例如，凋亡丰富于反应良好的人的网络而抗凋亡则丰富于反应较差的人的网络）。结合临床反应确定的许多关键枢纽也是细胞应答枢纽。功能验证表明，siRNA敲低2个TF后，皮质类固醇激素处理的细胞生存能力的差异被消除，并且良好反应者和较差反应者之间下游表达差异。

结论

我们已经确定并验证了影响哮喘治疗反应的多种TF。我们的结果表明，差异连通性分析可以为药物治疗效果的异质性提供新的见解。