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pmid:36550577

Identification of candidate aberrant differentially methylated/expressed genes in asthma.

Zongling Wang · Lizhi Wang · Lina Dai · Yanan Wang · Erhong Li · Shuyuan An · Fengliang Wang · Dan Liu · Wen Pan

Allergy, asthma, and clinical immunology : official journal of the Canadian Society of Allergy and Clinical Immunology · 2022 doi:10.1186/s13223-022-00744-5

Paper

complete

Experiment

partial

Data

partial

Analysis

partial

Execution

absent

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title
Identification of candidate aberrant differentially methylated/expressed genes in asthma.
doi
10.1186/s13223-022-00744-5
pmid
36550577
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[0]
Zongling Wang
[1]
Lizhi Wang
[2]
Lina Dai
[3]
Yanan Wang
[4]
Erhong Li
[5]
Shuyuan An
[6]
Fengliang Wang
[7]
Dan Liu
[8]
Wen Pan
journal
Allergy, asthma, and clinical immunology : official journal of the Canadian Society of Allergy and Clinical Immunology
year
2022
abstract
BACKGROUND: Asthma is an important non-communicable disease worldwide. DNA methylation is associated with the occurrence and development of asthma. We are aimed at assuring differential expressed genes (DEGs) modified by aberrantly methylated genes (DMGs) and pathways related to asthma by integrating bioinformatics analysis. METHODS: One mRNA dataset (GSE64913) and one gene methylation dataset (GSE137716) were selected from the Gene Expression Omnibus (GEO) database. Functional enrichment analysis was performed using GeneCodies 4.0 database. All gene expression matrices were analyzed by Gene set enrichment analysis (GSEA) software. STRING was applied to construct a protein-protein interaction (PPI) network to find the hub genes. Then, electronic validation was performed to verify the hub genes, followed by the evaluation of diagnostic value. Eventually, quantitative real-time polymerase chain reaction (qRT-PCR) was utilized to detect the expression of hub genes. RESULTS: In total, 14 hypomethylated/high-expression genes and 10 hypermethylated/low-expression genes were obtained in asthma. Among them, 10 hub genes were identified in the PPI network. Functional analysis demonstrated that the differentially methylated/expressed genes were primarily associated with the lung development, cytosol and protein binding. Notably, HLA-DOA was enriched in asthma. FKBP5, WNT5A, TM4SF1, PDK4, EPAS1 and GMPR had potential diagnostic value for asthma. CONCLUSION: The project explored the pathogenesis of asthma, which may provide a research basis for the prediction and the drug development of asthma.
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The AUC value of FKBP5 (AUC = 0.832), WNT5A (AUC = 0.813), TM4SF1 (AUC = 0.769), PDK4 (AUC = 0.753), EPAS1 (AUC = 0.748) and GMPR (AUC = 0.705) was more than 0.7, which suggesting higher diagnostic value for asthma.
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DNA methylation is associated with the occurrence and development of asthma. We are aimed at assuring differential expressed genes (DEGs) modified by aberrantly methylated genes (DMGs) and pathways related to asthma by integrating bioinformatics analysis.\nMETHODS: One mRNA dataset (GSE64913) and one gene methylation dataset (GSE137716) were selected from the Gene Expression Omnibus (GEO) database. Functional enrichment analysis was performed using GeneCodies 4.0 database. All gene expression matrices were analyzed by Gene set enrichment analysis (GSEA) software. STRING was applied to construct a protein-protein interaction (PPI) network to find the hub genes. Then, electronic validation was performed to verify the hub genes, followed by the evaluation of diagnostic value. 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