Autophagy-Related Genes Are Involved in the Progression and Prognosis of Asthma and Regulate the Immune Microenvironment - Yang, Fan; Kong, Jingwei; Zong, Yuhan; Li, Zhuqing; Lyu, Mingsheng; Li, Wanyang; Li, Wenle; Zhu, Haoyue; Chen, Shunqi; Zhao, Xiaoshan; Wang, Ji (Frontiers in Immunology, 2022)
Background: Autophagy has been proven to play an important role in the pathogenesis of asthma and the regulation of the airway epithelial immune microenvironment. However, a systematic analysis of the clinical importance of autophagy-related genes (ARGs) regulating the immune microenvironment in patients with asthma remains lacking. Methods: Clustering based on the k-means unsupervised clustering method was performed to identify autophagy-related subtypes in asthma. ARG-related diagnostic markers in low-autophagy subtypes were screened, the infiltration of immune cells in the airway epithelium was evaluated by the CIBERSORT, and the correlation between diagnostic markers and infiltrating immune cells was analyzed. Finally, on the basis of the expression of ARGs and combined with asthma control, a risk prediction model was established and verified by experiments, and the ssGSEA method was used to analyze the differences in immune cells and immune responses between high- and low-risk groups. The cMAP database and molecular docking were used to predict potential therapeutic agents and establish the ceRNA network of risk prediction models associated with ARGs. Results: A total of 66 differentially expressed ARGs and 2 subtypes were identified between mild to moderate and severe asthma. Significant differences were observed in asthma control and FEV1 reversibility between the two subtypes, and the low-autophagy subtype was closely associated with severe asthma, energy metabolism, and hormone metabolism. The autophagy gene SERPINB10 was identified as a diagnostic marker and was related to the infiltration of immune cells, such as activated mast cells and neutrophils. Combined with asthma control, a risk prediction model was constructed, the expression of five risk genes was supported by animal experiments, and the ceRNA network, including 20 lncRNAs and 28 miRNAs, was established for ARGs related to the prediction model. The model could effectively distinguish between high- and low-risk groups, and significant differences in immune cells and immune responses were observed between high- and low-risk groups. Eight small molecules, which might have therapeutic effect on asthma, were obtained from the cMAP database. Conclusion: Autophagy plays a crucial role in the diversity and complexity of the asthma immune microenvironment and has clinical value in treatment response and prognosis.