Asthma is a chronic inflammatory airway disease characterized by bronchial hyperresponsiveness and reversible airway obstruction. Corticosteroids are known to the most effective treatment for asthma. However, there is substantial variability in respon...
Asthma is a chronic inflammatory airway disease characterized by bronchial hyperresponsiveness and reversible airway obstruction. Corticosteroids are known to the most effective treatment for asthma. However, there is substantial variability in response to corticosteroids in asthma patients. Ineffective response to corticosteroids may result in exacerbation of asthma. Although many genetic studies have been conducted, the mechanisms of asthma pathogenesis and steroid insensitivity in asthma have not been fully elucidated. Gene expression profile represents the complete set of RNA transcripts that are produced by the genome under specific circumstances or in a specific cell. High-throughput methods such as microarray, and recent advances in biostatistics based on network-based approaches provide a quick and effective way of identifying novel genes and pathways related to asthma. This study aimed to understand the pathogenesis and steroid insensitivity in asthma using gene expression profiles of blood cells from asthma patients. To obtain a comprehensive picture of the gene expression in these cells, we used network-based approaches. The study was divided into two separate parts. In the first part of the study, important genetic signatures of acute exacerbation (AE) in asthma were identified using weighted gene co-expression network analysis (WGCNA) in peripheral blood mononuclear cells (PBMCs) from 29 adult asthma patients and lymphoblastoid cell lines (LCLs) from 107 childhood asthma patients. An AE-associated gene module composed of 77 genes was identified from childhood asthma patients and the conservation of this gene module structure was validated in adult asthma patients. The identified module was found to be conserved in terms of the gene expression profile and associated with AE in both childhood and adult asthma patients, and thus it was defined as an AE-associated common gene module. Changes in the expression of genes in the AE-associated common gene module following in vitro dexamethasone (Dex) treatment were examined, to better understand the mechanisms associated with steroid insensitivity. The differential gene expression profiles were classified into two classes according to Dex-induced changes in childhood asthma patients. Thirteen genes showed significant Dex-induced differential expression and were categorized as the A gene set. Sixty-four genes were not significantly altered by Dex were categorized as the B gene set. In the A gene set, the expression of eukaryotic translation initiation factor 2-alpha kinase 2 (EIF2AK2) showed significant Dex-induced differential expression in adult asthma patients as well. In addition, the basal expression of EIF2AK2 (pre-Dex) were significantly higher in asthma patients with AE compared to those without AE in both childhood and adult asthma. In the B gene set, based on a pathway-based approach, the protein repair pathway was found to be significantly enriched. Among the genes that belong to this pathway, the basal expression of methionine sulfoxide reductase A (MSRA) and methionine sulfoxide reductase B2 (MSRB2) were significantly lower in asthma patients with AE compared to those without AE in both childhood and adult asthma. These findings suggest that alternate treatment options, apart from corticosteroids, may be needed to prevent AE in asthma. Expression of EIF2AK2, MSRA, and MSRB2 in blood cells may help us to identify AE-susceptible asthma patients and adjust treatments to prevent AE events. In the second study, gene regulatory networks identified gene expression profiles of PBMCs from 23 adult asthma patients were assessed to elucidate the differences in responsiveness to inhaled corticosteroids (ICSs). Among these the top five (top-5) transcriptional factors (TFs; Top-5 TFs: GATA1, JUN, NFκB1, SPl1, and RELA) showing differential connections between good-responders (GRs) and poor-responders (PRs) were identified. Interestingly, GATA1 and JUN also showed differential connections in the gene regulatory networks identified gene expression profiles of LCLs from 107 childhood asthma patients in a previous study. The top-5 TFs and their connected genes were significantly enriched in distinct biological pathways associated with asthma. Among the genes connected to the top-5 TFs, the expression of TBX4, which is regulated by the TF, NFκB1, may be helpful in identifying GRs to ICS treatment. In conclusion, the novel genes and biological pathways identified in this study may deepen our understanding of asthma pathophysiology and steroid insensitivity in asthma.