Comparative RNA-Seq Transcriptome Analysis on Pulmonary Inflammation in a Mouse Model of Asthma-COPD Overlap Syndrome

Abstract

Asthma-chronic obstructive pulmonary disease (COPD) overlap (ACO) is a severe clinical syndrome characterized to describe patients with both asthma and COPD clinical characteristics, which has posed a serious threat to patients' quality of life and life safety. However, there are many difficulties and uncertainties in its diagnosis and treatment in clinic; especially, its animal model has not been fully and thoroughly established, and the evaluation of therapeutic drugs is still in its infancy. Here, we used ovalbumin (OVA), lipopolysaccharide (LPS), and smoke costimulation to establish an ACO mouse model and then used RNA-seq technology to detect gene expression in mouse lung tissue. The results showed that ACO mice showed an overlap syndrome of asthma and COPD in lung histological changes and the levels of inflammatory cytokines in bronchoalveolar lavage fluid. The RNA-seq analysis results showed that 6,324 differentially expressed genes (DEGs) were screened between the ACO group and the control group, of which 2,717 (42.7%) were downregulated, and 3,607 (57.3%) were upregulated. Metascape analysis results showed that in the ACO model we established, due to the damage of the respiratory system, the accumulated diseased tissue involves lung, spleen, blood, bone marrow, thymus, etc. It has certain characteristics of pneumonia, pulmonary fibrosis, and chronic obstructive airway disease, lung tumors, rheumatoid arthritis. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis showed that DEGs were enriched in inflammation, immune system activation and imbalance, cell proliferation, and adhesion migration, and the upstream signaling pathways of inflammation were mainly affected by HLA-DRA, SYK, CTLA4, VAV1, NRAS, and JAK3. In short, our research established a mouse model that can better simulate the clinicopathological characteristics of ACO and suggested the foundations in elucidating the molecular mechanisms for pulmonary inflammation and fibrosis in ACO. This work may help further research and contribute substantially to prevention and clinical treatment of ACO in the future.

Keywords: ACO; RNA-seq transcriptome analysis; molecular mechanisms; mouse model; pulmonary inflammation.