Combined analysis of bulk RNA and single-cell RNA sequencing to identify pyroptosis-related markers and the role of dendritic cells in chronic obstructive pulmonary disease

Abstract

Chronic obstructive pulmonary disease (COPD) is characterized by dyspnea caused by airflow limitation. Further development may lead to decreased lung function and other lung diseases. Pyroptosis is a type of programmed cell death that involves multiple pathways. For example, the pathway induced by the NLR family pyrin domain containing 3 (NLRP3) inflammasome is closely associated with COPD exacerbation. Therefore, in this study, various machine learning algorithms were applied to screen for diagnostically relevant pyroptosis-related genes from the GEO dataset, and the results were verified using external datasets. The results showed that deep neural networks and logistic regression algorithms had the highest AUC of 0.91 and 0.74 in the internal and external test sets, respectively. Here, we explored the immune landscape of COPD using diagnosis-related genes. We found that the infiltrating abundance of dendritic cells significantly differed between the COPD and control groups. Finally, the communication patterns of each cell type were explored based on scRNA-seq data. The critical role of significant pathways involved in communication between DCS and other cell populations in the occurrence and progression of COPD was identified.