Integrative Single-Cell and Bulk RNA Sequencing Analysis Identifies Ion Channel-Related Biomarkers in Chronic Obstructive Pulmonary Disease
- 1Department of Respiratory and Critical Care Medicine, The Second Affiliated Hospital, Anhui Medical University, Hefei, Anhui, 230601, People’s Republic of China
- 2Department of Respiratory and Critical Care Medicine, Anhui Provincial Chest Hospital, Hefei, Anhui, 230022, People’s Republic of China
Abstract
Background: Human ion channel genes (HICGs), as core effectors of transmembrane signal transduction, play a critical role in the initiation and progression of chronic obstructive pulmonary disease (COPD); however, the underlying mechanisms remain largely unclear. This study aimed to investigate the potential value of ion channel genes in COPD.
Methods: Differential expression analysis was performed to screen HICGs in COPD datasets. A total of 107 machine learning models were employed to identify hub HICGs and evaluate their diagnostic performance, and SHAP analysis was used to assess feature contributions. GSEA, immune cell infiltration, and inflammatory cytokine correlation analyses were conducted on the hub HICGs. Consensus clustering and WGCNA were used to define two disease subtypes and key modules. Single-cell RNA-seq data were used to examine the expression patterns of the hub HICGs. Subsequently, virtual knockout, virtual drug screening, and molecular docking were performed.
Results: The nine hub HICGs showed high diagnostic performance in cross-dataset validation, with LRRC8D ranking first in the SHAP analysis. These HICGs were significantly correlated with immune cells and inflammatory cytokines. Consensus clustering revealed significant gender differences between the two subtypes (BH-adjusted P = 0.01), and the two subtypes were enriched in phagocytosis and MAPK signaling pathways, respectively. Single-cell RNA-seq analysis using the Ro/e index suggested enrichment of macrophages and a reduction in smooth muscle cells in the disease group. Virtual knockout of LRRC8D was predicted to preferentially affect CD68 and the affected genes were enriched in human cytomegalovirus infection. Virtual screening prioritized Tezacaftor as a potential therapeutic agent, and molecular docking predicted that Tezacaftor may exhibit high binding affinity for the hub HICGs.
Conclusion: We identified potential HICGs in COPD and suggested a potential role for LRRC8D, as well as the potential utility of hub HICGs in disease subtyping, particularly with respect to gender, and Tezacaftor may serve as a candidate therapeutic agent.
Related
- Identification of candidate selenium-associated transcriptomic biomarkers in chronic obstructive pulmonary disease: an integrated bioinformatics and expression validation study
- Integrative bulk and single-cell transcriptomics identifies a HERC5-linked immune-attenuated risk program for pulmonary metastasis/relapse in osteosarcoma.
- Integrative Multi-omics and machine learning analysis of sphingolipid-associated molecular stratification identifies diagnostic and prognostic signatures in idiopathic pulmonary fibrosis
- Integrative analysis reveals shared biomarkers and pathways in osteoporosis and rheumatoid arthritis using machine learning and single-cell sequencing
- Non-Coding RNA Regulates Pyroptosis in Chronic Obstructive Pulmonary Disease
BibTeX
@article{xue2026integrative,
title = {{Integrative Single-Cell and Bulk RNA Sequencing Analysis Identifies Ion Channel-Related Biomarkers in Chronic Obstructive Pulmonary Disease}},
author = {Cheng Xue and Lei Huang and Heng Mei and Yingchun Gao and Pengcheng Liu and Jing Ye and Changxiu Ma and Dahai Zhao},
journal = {International Journal of Chronic Obstructive Pulmonary Disease},
year = {2026},
month = oct,
doi = {10.2147/copd.s638940},
url = {https://doi.org/10.2147/copd.s638940},
note = {CC BY-NC 4.0},
}
RIS
TY - JOUR
TI - Integrative Single-Cell and Bulk RNA Sequencing Analysis Identifies Ion Channel-Related Biomarkers in Chronic Obstructive Pulmonary Disease
AU - Cheng Xue
AU - Lei Huang
AU - Heng Mei
AU - Yingchun Gao
AU - Pengcheng Liu
AU - Jing Ye
AU - Changxiu Ma
AU - Dahai Zhao
PY - 2026
DA - 2026/10/30
JO - International Journal of Chronic Obstructive Pulmonary Disease
DO - 10.2147/copd.s638940
UR - https://doi.org/10.2147/copd.s638940
AB - Background: Human ion channel genes (HICGs), as core effectors of transmembrane signal transduction, play a critical role in the initiation and progression of chronic obstructive pulmonary disease (COPD); however, the underlying mechanisms remain largely unclear. This study aimed to investigate the potential value of ion channel genes in COPD. Methods: Differential expression analysis was performed to screen HICGs in COPD datasets. A total of 107 machine learning models were employed to identify hub HICGs and evaluate their diagnostic performance, and SHAP analysis was used to assess feature contributions. GSEA, immune cell infiltration, and inflammatory cytokine correlation analyses were conducted on the hub HICGs. Consensus clustering and WGCNA were used to define two disease subtypes and key modules. Single-cell RNA-seq data were used to examine the expression patterns of the hub HICGs. Subsequently, virtual knockout, virtual drug screening, and molecular docking were performed. Results: The nine hub HICGs showed high diagnostic performance in cross-dataset validation, with LRRC8D ranking first in the SHAP analysis. These HICGs were significantly correlated with immune cells and inflammatory cytokines. Consensus clustering revealed significant gender differences between the two subtypes (BH-adjusted P = 0.01), and the two subtypes were enriched in phagocytosis and MAPK signaling pathways, respectively. Single-cell RNA-seq analysis using the Ro/e index suggested enrichment of macrophages and a reduction in smooth muscle cells in the disease group. Virtual knockout of LRRC8D was predicted to preferentially affect CD68 and the affected genes were enriched in human cytomegalovirus infection. Virtual screening prioritized Tezacaftor as a potential therapeutic agent, and molecular docking predicted that Tezacaftor may exhibit high binding affinity for the hub HICGs. Conclusion: We identified potential HICGs in COPD and suggested a potential role for LRRC8D, as well as the potential utility of hub HICGs in disease subtyping, particularly with respect to gender, and Tezacaftor may serve as a candidate therapeutic agent.
SN - 1176-9106
SN - 1178-2005
ER -