Single-cell transcriptomics highlights immunological dysregulations of monocytes in the pathobiology of COPD

Abstract

Background Chronic obstructive pulmonary disease (COPD) is a common respiratory disease, whose pathogenetic complexity was strongly associated with aging/smoking and poorly understood. Methods Here we performed single-cell RNA sequencing (scRNA-seq) analysis of 66,610 cells from COPD and age-stratified control lung tissues of donors with different smoking histories to prioritize cell types most perturbed in COPD lungs in aging/smoking dependent or independent manner. By performing an array of advanced bioinformatic analyses, such as gene set enrichment analysis, trajectory analysis, cell–cell interactions analysis, regulatory potential analysis, weighted correlation network analysis, functional interaction analysis, and gene set variation analysis, we integrated cell-type-level alterations into a system-level malfunction and provided a more clarified COPD pathological model containing specific mechanisms by which aging and smoking facilitate COPD development. Finally, we integrated the publicly available scRNA-seq data of 9 individuals, resulting in a total of 110,931 cells, and replicated the analyses to enhance the credibility of our findings. Results Our study pointed to enrichment of COPD molecular alteration in monocytes, which further induced a previously unrecognized pro-inflammatory effect on alveolar epithelial cells. In addition, aged monocytes and club cells facilitated COPD development via maintaining an autoimmune airway niche. Unexpectedly, macrophages, whose defect to resolve inflammation was long-recognized in COPD pathogenesis, primarily induced an imbalance of sphingolipids rheostat in a smoking-dependent way. These findings were validated in a meta-analysis including other public single-cell transcriptomic data. Conclusions In sum, our study provided a clarified view of COPD pathogenesis and demonstrated the potential of targeting monocytes in COPD diagnosis and treatment.

Global Trends in Research Regarding Macrophages Associated with Chronic Obstructive Pulmonary Disease: A Bibliometric Analysis from 2011 to 2022

“…Furthermore, the application of new technologies that investigate the functional role of macrophages and, in particular, the combination of cell types as well as single-cell transcriptomics and proteomic approaches, are creating new opportunities to understand and clarify the pathophysiology and the clinical heterogeneity of COPD. [40][41][42][43][44] The results for the top 10 countries/regions with the most extensive literature regarding macrophages associated with COPD showed global distribution. The United States holds a leading position in the field of macrophage-associated COPD with the highest Np, Nc, and H-index, as well as the most international cooperation, compared to other countries/ regions, and also carried out research in this field earlier.…”

“…Furthermore, the application of new technologies that investigate the functional role of macrophages and, in particular, the combination of cell types as well as single-cell transcriptomics and proteomic approaches, are creating new opportunities to understand and clarify the pathophysiology and the clinical heterogeneity of COPD. 40–44 …”

Computational Deconvolution of Cell Type-Specific Gene Expression in COPD and IPF Lungs Reveals Disease Severity Associations

“…However, due to the practicality of needing fresh samples and the experimental cost, tissue and immune profiling studies have been limited in terms of sample sizes (typically <100 subjects) and the small number of molecular targets. Recently, scRNA-seq studies with more molecular targets have been conducted and highlighted immunological dysregulation of monocytes and macrophages in COPD [9,10,31,32]. However, the number of COPD donors was small in these studies, and there was limited information on the disease phenotypes, which limited the ability to test for associations with disease severity, clinical outcomes, and pathological changes.…”

Joint Clinical and Molecular Subtyping of Copd With Variational Autoencoders

“…This dual nature hinders the interpretability of gene expression results. Leveraging single cell RNA-seq data offers a way forward [72, 73]. By providing a higher resolution view of individual cell populations and their associated gene expression patterns, it becomes possible to discern between disease-associated shifts in cell populations and gene expression changes within specific cell types.…”