Identification of Small Airway Epithelium-Related Hub Genes in Chronic Obstructive Pulmonary Disease

Lin, Li; Lin, Guang-Tan; Chen, Xiaohui; Lin, Hai; Lin, Qinhui; Zeng, Yiming; Xu, Yuan

doi:10.2147/copd.s377026

Cited by 2 publications

(1 citation statement)

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“…We additionally corrected for potential batch effects using the ComBat algorithm in the sva package [ 24 ]. Moreover, scRNA-seq data related to COPD were obtained from the GSE173896 dataset [ 25 ], and epithelial cell data were extracted for subsequent analysis.…”

Section: Methodsmentioning

confidence: 99%

Deciphering the molecular regulatory of RAB32/GPRC5A axis in chronic obstructive pulmonary disease

Wu,

He,

Hua

et al. 2024

Respir Res

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Background Chronic obstructive pulmonary disease (COPD) is a significant public health problem characterized by persistent airflow limitation. Despite previous research into the pathogenesis of COPD, a comprehensive understanding of the cell-type-specific mechanisms in COPD remains lacking. Recent studies have implicated Rab GTPases in regulating chronic immune response and inflammation via multiple pathways. In this study, the molecular regulating mechanism of RAB32 in COPD was investigated by multiple bioinformatics mining and experimental verification. Methods We collected lung tissue surgical specimens from Zhongshan Hospital, Fudan University, and RT-qPCR and western blotting were used to detect the expression of Rabs in COPD lung tissues. Four COPD microarray datasets from the Gene Expression Omnibus (GEO) were analyzed. COPD-related epithelial cell scRNA-seq data was obtained from the GSE173896 dataset. Weighted gene co-expression network analysis (WGCNA), mfuzz cluster, and Spearman correlation analysis were combined to obtain the regulatory network of RAB32 in COPD. The slingshot algorithm was used to identify the regulatory molecule, and the co-localization of RAB32 and GPRC5A was observed with immunofluorescence. Results WGCNA identified 771 key module genes significantly associated with the occurrence of COPD, including five Rab genes. RAB32 was up-regulated in lung tissues from subjects with COPD as contrast to those without COPD on both mRNA and protein levels. Integrating the results of WGCNA, Mfuzz clusters, and Spearman analysis, nine potential interacting genes with RAB32 were identified. Among these genes, GPRC5A exhibited a similar molecular expression pattern to RAB32. Co-expression density analysis at the cell level demonstrated that the co-expression density of RAB32 and GPRC5A was higher in type I alveolar epithelial cells (AT1s) than in type II alveolar epithelial cells (AT2s). The immunofluorescence also confirmed the co-localization of RAB32 and GPRC5A, and the Pearson correlation analysis found the relationship between RAB32 and GPRC5A was significantly stronger in the COPD lungs (r = 0.65) compared to the non-COPD lungs (r = 0.33). Conclusions Our study marked endeavor to delineate the molecular regulatory axis of RAB32 in COPD by employing diverse methods and identifying GPRC5A as a potential interacting molecule with RAB32. These findings offered novel perspectives on the mechanism of COPD.

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Section: Methodsmentioning

confidence: 99%