Qin Shen,1,2,* Jin-Bo Huang,1,* Mi Zhu,3,* Dao-Jun Ji,2 Si-Jia Huang,2 Jun Li1 

1Department of Respiratory and Critical Care Medicine, Affiliated Hospital of Nantong University, Nantong Key Laboratory of Respiratory Medicine, Nantong, Jiangsu, 226001, People’s Republic of China; 2Medical School of Nantong University, Nantong, Jiangsu, 226001, People’s Republic of China; 3Department of Pulmonary and Critical Care Medicine, Changshu No.1 People’s Hospital, Jiangsu, People’s Republic of China

*These authors contributed equally to this work

Correspondence: Jun Li, Department of Respiratory and Critical Care Medicine, Affiliated Hospital of Nantong University, Nantong Key Laboratory of Respiratory Medicine, Nantong, Jiangsu, 226001, People’s Republic of China, Email junli11231@163.com

Background: Chronic obstructive pulmonary disease (COPD) is a leading cause of death worldwide, and its pathogenesis and potentially relevant biomarkers require further study. Imbalance in copper (Cu2+) metabolism is related to a series of diseases, but its role in COPD has not been specified.
Methods: A dataset relevant to COPD was downloaded from Gene Expression Omnibus database, among which a total of 18 cuproptosis-related genes (CRGs) were screened. The SimDesign package was used to perform single-factor Rogers regression to screen genes associated with disease phenotypes, risk score prediction models were constructed, and Receiver Operating Characteristic (ROC) curves were used to evaluate the efficacy of the prediction models. In addition, we verified the expression of CRGs in subtypes and the correlation between subtypes and clinical characteristics using a database. Finally, immune correlation analysis was used to explore immune cell infiltration.
Results: Five biomarkers (DLST, GLS, LIPT1, MTF1, and PDHB) were identified. ROC analysis illustrated that these five biomarkers performed well (area under the curve (AUCs)> 0.7), and the enrichment scores of diagnostic CRGs were significantly different among subtypes, among which the chi-square test P-values of the age groups were significantly different. The immune infiltration evaluation of cuproptosis subtypes revealed that the correlation analysis results of 22 types of immune cells showed a significant correlation between these cells, and the five CRGs were significantly correlated with the content of most immune cells in the 22 types of immune cells. The four pathways with the most significant differences in GSEA among subtypes were Oxidative Phosphorylation, Parkinson’s Disease, Purine Metabolism, and Drug Metabolism Cytochrome P450.
Conclusion: This study identified five candidate genes for further investigation (DLST, GLS, LIPT1, MTF1, and PDHB) and constructed disease prediction models and pathogenesis pathways. This study can provide a basis for further research on the role of cuproptosis in COPD.

Keywords: chronic obstructive pulmonary disease, cuproptosis, gene expression