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pmid:33469280

Identification and Validation of Autophagy-Related Genes in Chronic Obstructive Pulmonary Disease.

Shulei Sun · Yuehao Shen · Jie Wang · Jinna Li · Jie Cao · Jing Zhang

International journal of chronic obstructive pulmonary disease · 2021 doi:10.2147/COPD.S288428

Paper

complete

Experiment

partial

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:33469280
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science-record
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created_at
2026-11-01T15:41:23Z
updated_at
2026-11-01T22:46:00Z
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paper object · 10 fields
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title
Identification and Validation of Autophagy-Related Genes in Chronic Obstructive Pulmonary Disease.
doi
10.2147/COPD.S288428
pmid
33469280
authors array · 6 items
[0]
Shulei Sun
[1]
Yuehao Shen
[2]
Jie Wang
[3]
Jinna Li
[4]
Jie Cao
[5]
Jing Zhang
journal
International journal of chronic obstructive pulmonary disease
year
2021
abstract
PURPOSE: Autophagy plays essential roles in the development of COPD. We aim to identify and validate the potential autophagy-related genes of COPD through bioinformatics analysis and experiment validation. METHODS: The mRNA expression profile dataset GSE38974 was obtained from GEO database. The potential differentially expressed autophagy-related genes of COPD were screened by R software. Then, protein-protein interactions (PPI), correlation analysis, gene-ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were applied for the differentially expressed autophagy-related genes. Finally, RNA expression of top five differentially expressed autophagy-related genes was validated in blood samples from COPD patients and healthy controls by qRT-PCR. RESULTS: A total of 40 differentially expressed autophagy-related genes (14 up-regulated genes and 26 down-regulated genes) were identified between 23 COPD patients and 9 healthy controls. The PPI results demonstrated that these autophagy-related genes interacted with each other. The GO and KEGG enrichment analysis of differentially expressed autophagy-related genes indicated several enriched terms related to autophagy and mitophagy. The results of qRT-PCR showed that the expression levels of HIF1A, CDKN1A, BAG3, ERBB2 and ATG16L1 in COPD patients and healthy controls were consistent with the bioinformatics analysis results from mRNA microarray. CONCLUSION: We identified 40 potential autophagy-related genes of COPD through bioinformatics analysis. HIF1A, CDKN1A, BAG3, ERBB2 and ATG16L1 may affect the development of COPD by regulating autophagy. These results may expand our understanding of COPD and might be useful in the treatment of COPD.
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The “limma” package of R software was used to identify the differentially expressed autophagy-related genes.
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The 40 Differentially Expressed Autophagy-Related Genes in COPD Samples Compared to Healthy Samples
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Differentially Expressed Autophagy-Related Genes in COPD-Retrospective Analysis of Autophagy-Related Genes
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The 40 Differentially Expressed Autophagy-Related Genes in COPD Samples Compared to Healthy Samples
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Clinicopathological Variables of Cases and Controls in This Study
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Validation the Differentially Expressed Autophagy-Related Genes in COPD Patients – Prospective Analysis in New Population
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Clinicopathological Variables of Cases and Controls in This Study
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64.75 ± 5.33
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he bioinformatics analysis results from mRNA microarray. CONCLUSION: We identified 40 potential auto
[1]
ed Genes The normalized expression matrix of microarray data was downloaded from the GSE38974 datase
[2]
d in Table 2. Similar to the results of mRNA microarray in lung tissue samples, the expression level
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The “limma” package of R software was used to identify the differentially expressed autophagy-related genes.
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33469280", "kind": "science-record", "revision": 8, "content_hash": "sha256:5861312be8aeb055f91a003359e08dccdddb0c9356aa4c38dafa3e6f7a30a24a", "created_at": "2026-11-01T15:41:23Z", "updated_at": "2026-11-01T22:46:00Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification and Validation of Autophagy-Related Genes in Chronic Obstructive Pulmonary Disease.", "doi": "10.2147/COPD.S288428", "pmid": "33469280", "authors": ["Shulei Sun", "Yuehao Shen", "Jie Wang", "Jinna Li", "Jie Cao", "Jing Zhang"], "journal": "International journal of chronic obstructive pulmonary disease", "year": 2021, "abstract": "PURPOSE: Autophagy plays essential roles in the development of COPD. We aim to identify and validate the potential autophagy-related genes of COPD through bioinformatics analysis and experiment validation.\nMETHODS: The mRNA expression profile dataset GSE38974 was obtained from GEO database. The potential differentially expressed autophagy-related genes of COPD were screened by R software. Then, protein-protein interactions (PPI), correlation analysis, gene-ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were applied for the differentially expressed autophagy-related genes. Finally, RNA expression of top five differentially expressed autophagy-related genes was validated in blood samples from COPD patients and healthy controls by qRT-PCR.\nRESULTS: A total of 40 differentially expressed autophagy-related genes (14 up-regulated genes and 26 down-regulated genes) were identified between 23 COPD patients and 9 healthy controls. The PPI results demonstrated that these autophagy-related genes interacted with each other. The GO and KEGG enrichment analysis of differentially expressed autophagy-related genes indicated several enriched terms related to autophagy and mitophagy. The results of qRT-PCR showed that the expression levels of HIF1A, CDKN1A, BAG3, ERBB2 and ATG16L1 in COPD patients and healthy controls were consistent with the bioinformatics analysis results from mRNA microarray.\nCONCLUSION: We identified 40 potential autophagy-related genes of COPD through bioinformatics analysis. HIF1A, CDKN1A, BAG3, ERBB2 and ATG16L1 may affect the development of COPD by regulating autophagy. 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