Lu-Lu He1, Feng Xu1, Xue-Qin Zhan2, Zhi-Hua Chen1, Hua-Hao Shen3. 1. Key Laboratory of Respiratory Disease of Zhejiang Province, Department of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Zhejiang University, School of Medicine, Hangzhou, China. 2. Department of Pulmonology, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, China. 3. Key Laboratory of Respiratory Disease of Zhejiang Province, Department of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Zhejiang University, School of Medicine, Hangzhou, China; State Key Lab of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou, China. Electronic address: huahaoshen@zju.edu.cn.
Abstract
INTRODUCTION: Asthma is a worldwide problem that is caused by complex underlying immune dysregulation. The identification of potential prognostic markers of asthma may provide information for treatment. The purpose of this study was to explore the key mechanisms involved in the development of asthma on the basis of microarray analysis. METHODS: The expression profile data of GSE43696, which contains 20 endobronchial epithelial brushing samples from healthy patients and 88 from asthma patients, were obtained from Gene Expression Omnibus. For the present study, we built co-expression modules by weighted gene co-expression network analysis (WGCNA). This new analysis strategy was applied to the data set to investigate the relationships underlying the modules and the pathogenesis of asthma. Functional enrichment analysis was performed on these co-expression genes from the modules, and a gene network was then constructed. In addition, mouse models of HDM-induced and OVA-induced asthma were established, and the expression of hub genes was measured. RESULTS: First, using WGCNA, 20 co-expression modules were constructed with 19,596 genes obtained from 108 human endobronchial epithelial brushing samples. The number of genes within the modules ranged from 41 to 845. According to the colours assigned by the system, the module positively correlated with asthma status was named 'red module', and the module positively correlated with asthma severity was named 'purple module'. The results of a functional enrichment analysis showed that the red module was mainly enriched in intracellular calcium-activated chloride channel activity, intracellular chloride channel activity and endopeptidase inhibitor activity. The purple module was mainly enriched in microtubule motor activity and microtubule-binding and motor activity. Moreover, the mRNA expression levels of the 15 hub genes were confirmed to be significantly upregulated in the HDM mouse model, and 12 hub genes were upregulated in the OVA model. CONCLUSIONS: The hub genes ANO7, PYCR1 and UBE2C might play potential roles in the pathogenesis of asthma. Our findings provided a framework of co-expression gene modules of asthma and led to the identification of some new markers that might be potential targets for the development of new drugs and diagnostic markers.
INTRODUCTION:Asthma is a worldwide problem that is caused by complex underlying immune dysregulation. The identification of potential prognostic markers of asthma may provide information for treatment. The purpose of this study was to explore the key mechanisms involved in the development of asthma on the basis of microarray analysis. METHODS: The expression profile data of GSE43696, which contains 20 endobronchial epithelial brushing samples from healthy patients and 88 from asthmapatients, were obtained from Gene Expression Omnibus. For the present study, we built co-expression modules by weighted gene co-expression network analysis (WGCNA). This new analysis strategy was applied to the data set to investigate the relationships underlying the modules and the pathogenesis of asthma. Functional enrichment analysis was performed on these co-expression genes from the modules, and a gene network was then constructed. In addition, mouse models of HDM-induced and OVA-induced asthma were established, and the expression of hub genes was measured. RESULTS: First, using WGCNA, 20 co-expression modules were constructed with 19,596 genes obtained from 108 human endobronchial epithelial brushing samples. The number of genes within the modules ranged from 41 to 845. According to the colours assigned by the system, the module positively correlated with asthma status was named 'red module', and the module positively correlated with asthma severity was named 'purple module'. The results of a functional enrichment analysis showed that the red module was mainly enriched in intracellular calcium-activated chloride channel activity, intracellular chloride channel activity and endopeptidase inhibitor activity. The purple module was mainly enriched in microtubule motor activity and microtubule-binding and motor activity. Moreover, the mRNA expression levels of the 15 hub genes were confirmed to be significantly upregulated in the HDM mouse model, and 12 hub genes were upregulated in the OVA model. CONCLUSIONS: The hub genes ANO7, PYCR1 and UBE2C might play potential roles in the pathogenesis of asthma. Our findings provided a framework of co-expression gene modules of asthma and led to the identification of some new markers that might be potential targets for the development of new drugs and diagnostic markers.