To study the tissue-infiltrating immune cells of the emphysema phenotype of chronic obstructive pulmonary disease (COPD) and find the molecular mechanism related to the development of emphysema to offer potential targets for more precise treatment of patients with COPD.
Combined analyses of COPD emphysema phenotype lung tissue-related datasets, GSE47460 and GSE1122, were performed. CIBERSORT was used to assess the distribution of tissue-infiltrating immune cells. Weighted gene co-expression network analysis (WGCNA) was used to select immune key genes closely related to clinical features. Rt-qPCR experiments were used for the validation of key genes. Emphysema risk prediction models were constructed by logistic regression analysis and a nomogram was developed.
In this study, three immune cells significantly associated with clinical features of emphysema (FEV1 post-bronchodilator % predicted, GOLD Stage, and DLCO) were found. The proportion of neutrophils (p=0.025) infiltrating in the emphysema phenotype was significantly increased compared with the non-emphysema phenotype, while the proportions of M2 macrophages (p=0.004) and resting mast cells (p=0.01) were significantly decreased. Five immune-related differentially expressed genes (DEGs) were found. WGCNA and clinical lung tissue validation of patients with emphysema phenotype were performed to further screen immune-related genes closely related to clinical features. A key gene (SERPINA3) was selected and included in the emphysema risk prediction model. Compared with the traditional clinical prediction model (AUC=0.923), the combined prediction model, including SERPINA3 and resting mast cells (AUC=0.941), had better discrimination power and higher net benefit.
This study comprehensively analyzed the tissue-infiltrating immune cells significantly associated with emphysema phenotype, including M2 macrophages, neutrophils, and resting mast cells, and identified SERPINA3 as a key immune-related gene.