The Transcriptome Characteristics of Severe Asthma From the Prospect of Co-Expressed Gene Modules.

Rationale: Severe asthma is a heterogeneous disease with multiple molecular mechanisms. Gene expression studies of asthmatic bronchial epithelial cells have provided biological insights and underscored possible pathological mechanisms, however, the molecular basis in severe asthma is still poorly understood. Objective: The objective of this study was to identify the features of asthma and uncover the molecular basis of severe asthma in distinct molecular phenotype. Methods: The k-means clustering and differentially expressed genes (DEGs) were performed in 129 asthma individuals in the Severe Asthma Research Program. The DEGs profiles were analyzed by weighted gene co-expression network analysis (WGCNA) and the expression value of each gene module in each individual was annotated by gene-set variation analysis (GSVA). Result: Expression analysis defined five stable asthma subtypes(AS): (1):Phagocytosis-Th2; (2):Normal-like; (3):Neutrophils; (4):Mucin-Th2; (5):Interferon-Th1 and 15 co-expressed gene modules. “Phagocytosis-Th2” enriched for receptor-mediated endocytosis, up-regulation of Toll-like receptor signal and myeloid leukocyte activation. “Normal-like” is most similar to normal samples. “Mucin-Th2” preferentially expressed genes involved in O-Glycan biosynthesis and unfolded protein response. “Interferon-Th1” displayed upregulation of genes that regulate networks involved in cell cycle, IFN gamma response and CD8 TCR. The dys-regulation of neural signal, REDOX, apoptosis and o-glycan process were related to the severity of asthma. In non-TH2 subtypes (Neutrophils and Interferon-Th1) with severe asthma individuals, the neural signals and IL26-related co-expression module were dys-regulated more significantly compared to that in non-severe asthma. These data infer differences in the molecular evolution of asthma subtypes and identify opportunities for therapeutic development. Conclusions: Asthma is a heterogeneous disease. The co-expression analysis provides new insights into the biological mechanisms related to its phenotypes and the severity.