Differential connectivity of gene regulatory networks distinguishes corticosteroid response in asthma

被引:27
作者
Qiu, Weiliang [1 ,2 ]
Guo, Feng [1 ,2 ]
Glass, Kimberly [1 ,2 ]
Yuan, Guo Cheng [3 ,4 ]
Quackenbush, John [3 ,4 ]
Zhou, Xiaobo [1 ,2 ]
Tantisira, Kelan G. [1 ,2 ,5 ]
机构
[1] Brigham & Womens Hosp, Channing Div Network Med, 75 Francis St, Boston, MA 02115 USA
[2] Harvard Med Sch, Boston, MA USA
[3] Dana Farber Canc Inst, Dept Biostat & Computat Biol, Boston, MA 02115 USA
[4] Harvard TH Chan Sch Publ Hlth, Dept Biostat, Boston, MA USA
[5] Brigham & Womens Hosp, Div Pulm & Crit Care Med, 75 Francis St, Boston, MA 02115 USA
基金
美国国家卫生研究院;
关键词
Pharmacogenomics; gene expression; inhaled corticosteroids; apoptosis; system biology; STEROID-RESISTANT ASTHMA; GLUCOCORTICOID-RECEPTOR; MONONUCLEAR-CELLS; PHARMACOGENETICS; EXPRESSION; PROMOTER; THERAPY; ASSOCIATION; MECHANISMS; DIFFICULT;
D O I
10.1016/j.jaci.2017.05.052
中图分类号
R392 [医学免疫学];
学科分类号
100102 ;
摘要
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.
引用
收藏
页码:1250 / 1258
页数:9
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