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pmid:38873611

Identification of novel biomarkers related to neutrophilic inflammation in COPD.

Yuchen Huang · Yang Niu · Xuezhao Wang · Xiaochen Li · Yuanzhou He · Xiansheng Liu

Frontiers in immunology · 2024 doi:10.3389/fimmu.2024.1410158

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:38873611
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science-record
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2026-11-01T20:28:56Z
updated_at
2026-11-01T22:12:02Z
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paper object · 10 fields
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title
Identification of novel biomarkers related to neutrophilic inflammation in COPD.
doi
10.3389/fimmu.2024.1410158
pmid
38873611
authors array · 6 items
[0]
Yuchen Huang
[1]
Yang Niu
[2]
Xuezhao Wang
[3]
Xiaochen Li
[4]
Yuanzhou He
[5]
Xiansheng Liu
journal
Frontiers in immunology
year
2024
abstract
Background: Chronic obstructive pulmonary disease (COPD) is one of the most prevalent chronic respiratory diseases and the fourth cause of mortality globally. Neutrophilic inflammation has a vital role in the occurrence and progression of COPD. This study aimed to identify the novel hub genes involved in neutrophilic inflammation in COPD through bioinformatic prediction and experimental validation. Methods: Both the single-cell RNA sequencing (scRNA-seq) dataset (GSE173896) and the RNA sequencing (RNA-seq) dataset (GSE57148) were downloaded from the Gene Expression Omnibus (GEO) database. The Seurat package was used for quality control, dimensions reduction, and cell identification of scRNA-seq. The irGSEA package was used for scoring individual cells. The Monocle2 package was used for the trajectory analysis of neutrophils. The CIBERSORT algorithm was used for analysis of immune cell infiltration in the lungs of COPD patients and controls in RNA-seq dataset, and weighted gene co-expression network analysis (WGCNA) correlated gene modules with neutrophil infiltration. The Mendelian randomization (MR) analysis explored the causal relationship between feature DEGs and COPD. The protein-protein interaction (PPI) network of novel hub genes was constructed, and real-time quantitative polymerase chain reaction (qRT-PCR) was used to validate novel hub genes in clinical specimens. Results: In scRNA-seq, the gene sets upregulated in COPD samples were related to the neutrophilic inflammatory response and TNF-α activation of the NF-κB signaling pathway. In RNA-seq, immune infiltration analysis showed neutrophils were upregulated in COPD lung tissue. We combined data from differential and modular genes and identified 51 differential genes associated with neutrophilic inflammation. Using MR analysis, 6 genes were explored to be causally associated with COPD. Meanwhile, 11 hub genes were identified by PPI network analysis, and all of them were upregulated. qRT-PCR experiments validated 9 out of 11 genes in peripheral blood leukocytes of COPD patients. Furthermore, 5 genes negatively correlated with lung function in COPD patients. Finally, a network of transcription factors for NAMPT and PTGS2 was constructed. Conclusion: This study identified nine novel hub genes related to the neutrophilic inflammation in COPD, and two genes were risk factors of COPD, which may serve as potential biomarkers for the clinical severity of COPD.
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In this study, we further illustrated the causal role of hub genes in the risk of developing COPD by a two-sample MR approach.
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The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding author/s.
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This study identified nine novel hub genes related to the neutrophilic inflammation in COPD, and two genes were risk factors of COPD, which may serve as potential biomarkers for the clinical severity of COPD.
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This study identified nine novel hub genes related to the neutrophilic inflammation in COPD, and two genes were risk factors of COPD, which may serve as potential biomarkers for the clinical severity of COPD.
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This study identified nine novel hub genes related to the neutrophilic inflammation in COPD, and two genes were risk factors of COPD, which may serve as potential biomarkers for the clinical severity of COPD.
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Single-cell Transcriptome Analysis Reveals an Anomalous Epithelial Variation and Ectopic Inflammatory Response in Chronic Obstructive Pulmonary Disease
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d experimental validation. Methods: Both the single-cell RNA sequencing (scRNA-seq) dataset (GSE173896) and the RNA
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ethods: Both the single-cell RNA sequencing (scRNA-seq) dataset (GSE173896) and the RNA sequencing
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nsions reduction, and cell identification of scRNA-seq. The irGSEA package was used for scoring ind
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hub genes in clinical specimens. Results: In scRNA-seq, the gene sets upregulated in COPD samples w
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evidence array · 4 items
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dataset (GSE173896) and the RNA sequencing (RNA-seq) dataset (GSE57148) were downloaded from the
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cing (scRNA-seq) dataset (GSE173896) and the RNA sequencing (RNA-seq) dataset (GSE57148) were downloaded
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n the lungs of COPD patients and controls in RNA-seq dataset, and weighted gene co-expression net
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In this study, we further illustrated the causal role of hub genes in the risk of developing COPD by a two-sample MR approach.
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Complete file
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This study aimed to identify the novel hub genes involved in neutrophilic inflammation in COPD through bioinformatic prediction and experimental validation.\nMethods: Both the single-cell RNA sequencing (scRNA-seq) dataset (GSE173896) and the RNA sequencing (RNA-seq) dataset (GSE57148) were downloaded from the Gene Expression Omnibus (GEO) database. The Seurat package was used for quality control, dimensions reduction, and cell identification of scRNA-seq. The irGSEA package was used for scoring individual cells. The Monocle2 package was used for the trajectory analysis of neutrophils. The CIBERSORT algorithm was used for analysis of immune cell infiltration in the lungs of COPD patients and controls in RNA-seq dataset, and weighted gene co-expression network analysis (WGCNA) correlated gene modules with neutrophil infiltration. The Mendelian randomization (MR) analysis explored the causal relationship between feature DEGs and COPD. The protein-protein interaction (PPI) network of novel hub genes was constructed, and real-time quantitative polymerase chain reaction (qRT-PCR) was used to validate novel hub genes in clinical specimens.\nResults: In scRNA-seq, the gene sets upregulated in COPD samples were related to the neutrophilic inflammatory response and TNF-α activation of the NF-κB signaling pathway. In RNA-seq, immune infiltration analysis showed neutrophils were upregulated in COPD lung tissue. We combined data from differential and modular genes and identified 51 differential genes associated with neutrophilic inflammation. Using MR analysis, 6 genes were explored to be causally associated with COPD. Meanwhile, 11 hub genes were identified by PPI network analysis, and all of them were upregulated. qRT-PCR experiments validated 9 out of 11 genes in peripheral blood leukocytes of COPD patients. Furthermore, 5 genes negatively correlated with lung function in COPD patients. Finally, a network of transcription factors for NAMPT and PTGS2 was constructed.\nConclusion: This study identified nine novel hub genes related to the neutrophilic inflammation in COPD, and two genes were risk factors of COPD, which may serve as potential biomarkers for the clinical severity of COPD.", "claims": [{"id": "claim-method", "statement": "In this study, we further illustrated the causal role of hub genes in the risk of developing COPD by a two-sample MR approach.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38873611", "locator": "sections[1] \"Introduction\" paragraph 5", "quote": "In this study, we further illustrated the causal role of hub genes in the risk of developing COPD by a two-sample MR approach."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/ Supplementary Material . 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