Identification of Potential Key Genes in the Pathogenesis of Chronic Obstructive Pulmonary Disease Through Bioinformatics Analysis.

Qingzhou Guan,Peng Zhao,Jiansheng Li,Zhenzhen Zhang,Lanxi Zhang,Yange Tian

doi:10.3389/fgene.2021.754569

Qingzhou Guan, Peng Zhao + Show 4 more

Open Access

https://doi.org/10.3389/fgene.2021.754569

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Abstract

Chronic obstructive pulmonary disease (COPD) is a common respiratory disease with high morbidity and mortality. The etiology of COPD is complex, and the pathogenesis mechanisms remain unclear. In this study, we used rat and human COPD gene expression data from our laboratory and the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) between individuals with COPD and healthy individuals. Then, protein–protein interaction (PPI) networks were constructed, and hub genes were identified. Cytoscape was used to construct the co-expressed network and competitive endogenous RNA (ceRNA) networks. A total of 198 DEGs were identified, and a PPI network with 144 nodes and 355 edges was constructed. Twelve hub genes were identified by the cytoHubba plugin in Cytoscape. Of these genes, CCR3, CCL2, COL4A2, VWF, IL1RN, IL2RA, and CCL13 were related to inflammation or immunity, or tissue-specific expression in lung tissue, and their messenger RNA (mRNA) levels were validated by qRT-PCR. COL4A2, VWF, and IL1RN were further verified by the GEO dataset GSE76925, and the ceRNA network was constructed with Cytoscape. These three genes were consistent with COPD rat model data compared with control data, and their dysregulation direction was reversed when the COPD rat model was treated with effective-component compatibility of Bufei Yishen formula III. This bioinformatics analysis strategy may be useful for elucidating novel mechanisms underlying COPD. We pinpointed three key genes that may play a role in COPD pathogenesis and therapy, which deserved to be further studied.

Highlights

Chronic obstructive pulmonary disease (COPD) is a common chronic respiratory disease, characterized by airflow limitation that is not completely reversible
In 2011, Global Initiative for Chronic Obstructive Pulmonary Disease (GOLD) provided a multidimensional evaluation method that combined the FEV1 value with an individual’s previous exacerbations and symptoms history, including dyspnea based on the modified Medical Research Council scale and health status according to the Chronic obstructive pulmonary disease Assessment Test (CAT) (Bernabeu-Mora et al, 2020)
We obtained the differentially expressed genes (DEGs) in COPD compared with normal lung tissues using the multiple gene expression data from human and rat tissues

Summary

INTRODUCTION

Chronic obstructive pulmonary disease (COPD) is a common chronic respiratory disease, characterized by airflow limitation that is not completely reversible. Lung macrophages in COPD generate a proinflammatory scenario that may cause tissue damage, and defective immune surveillance and protective (phagocytic) functions that collectively contribute to the progression of COPD (Yamasaki and Eeden, 2018; Eapen et al, 2019) Other risk factors, such as age, sex, and socioeconomic status, are involved in COPD development (Gershon et al, 2011; Landis et al, 2014; Beran et al, 2015; Mercado et al, 2015). We further validated/optimized the identified genes using a GEO dataset and COPD rat data, and ceRNA networks were constructed based on the prediction results of long noncoding RNAs (lncRNAs) using starBase database. This work provides insight into the mechanisms of disease development in COPD at the transcriptome level, contributing potential guidance for COPD treatment

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ETHICS STATEMENT