Jiale Zhao,1,2,* Xiahui Ge,3,* Hailong Li,4,* Genfei Jing,5,* Weirong Ma,2 Yuchun Fan,2 Juan Chen,2,6 Zhijun Zhao,7,8 Jia Hou2,6 

1School of Clinical Medicine, Ningxia Medical University, Yinchuan, Ningxia, People’s Republic of China; 2Department of Pulmonary and Critical Care Medicine, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, People’s Republic of China; 3Department of Respiratory and Critical Care Medicine, Shanghai Ninth People’s Hospital, Shanghai, People’s Republic of China; 4Department of Respiratory Medicine, Ningxia Hospital of Integrated Traditional Chinese and Western Medicine, Yinchuan, Ningxia, People’s Republic of China; 5Department of Respiratory and Critical Care Medicine, Yongning County People’s Hospital, Yinchuan, Ningxia, People’s Republic of China; 6Department of Key Laboratory of Ningxia Stem Cell and Regenerative Medicine, Institute of Medical Sciences, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, People’s Republic of China; 7Clinical Laboratory Center, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, People’s Republic of China; 8Ningxia Key Laboratory of Clinical and Pathogenic Microbiology, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, People’s Republic of China

*These authors contributed equally to this work

Correspondence: Jia Hou, Email houj@live.com Zhijun Zhao, Email z15815z@163.com

Background: Chronic Obstructive Pulmonary Disease (COPD), a complex respiratory disorder, results from genetic and environmental factors. Uncovering its genetic basis is vital for diagnostics and treatment. Robust genetic analysis is essential to establish a causal link.
Methods: Genome-wide DNA methylation analysis was performed using the Illumina Infinium HumanMethylation850 BeadChip in peripheral blood from 8 COPD patients and 8 healthy smoking controls. Differentially methylated genes (DMGs) were cross-analyzed with differentially expressed genes (DEGs) identified from the Gene Expression Omnibus (GEO) dataset GSE38974 (23 COPD, 9 controls). Weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) networks were utilized to identify COPD-associated hub genes. Mendelian randomization (MR) analysis examined the causal relationship between hub genes and COPD. The expression of selected hub genes was validated through RT-qPCR (80 COPD, 62 controls), immunohistochemistry, and Western blot analyses (10 COPD and 10 controls).
Results: We found 10,593 DMGs and 646 DEGs associated with COPD. These genes were compared with WGCNA module genes, and the Protein-Protein Interaction (PPI) network interaction diagram was drawn, thereby identifying five Hub genes: PPIB, HSPA2, PRPF19, FKBP10 and DOHH. The expression levels of DOHH, FKBP10, PPIB and PRPF19 are higher in COPD, while the expression level of HSPA2 is lower. MR results indicate a potential causal relationship between PRPF19, PPIB and COPD. RT-qPCR, immunohistochemistry and Western blot experiments verified that the expression of PRPF-19 and PPIB was up-regulated in peripheral blood and lung tissue, which was consistent with the results of bioinformatics analysis.
Conclusion: Our findings suggest that PRPF19 and PPIB may serve as promising diagnostic biomarkers in COPD. Further studies are required to fully elucidate their roles in COPD pathogenesis.

Keywords: chronic obstructive pulmonary disease, epigenetic susceptibility, hub genes, protein-protein interaction, Mendelian randomization