Abstract
Background Obstructive sleep apnea syndrome (OSAS) is the most common type of sleep apnea disorder. The disease seriously affects the patient's respiratory system. At present, the prognosis of the disease is poor and there is a lack of effective treatments. Therefore, it is urgent to explore its pathogenesis and treatment methods. Method We downloaded a set of expression profile data from GSE75097 related to OSAS based on the Gene Expression Omnibus (GEO) database and selected the representative differentially expressed genes (DEGs) from the sample of the GSE75097 dataset. WGCNA was used to find genes related to OSAS and obtain coexpression modules. The Gene Ontology (GO) function and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were used to analyze genes from key modules. Finally, Cytoscape software was used to construct a protein-protein interaction (PPI) network and analyze the hub genes. Result We obtained a total of 7565 DEGs. Through WGCNA, we got four coexpression modules and the modules most related to OSAS were green-yellow, magenta, purple, and turquoise, and we screened out eight hub genes (DDX46, RNF115, COPA, FBXO4, PA2G4, NHP2L1, CDC20, and PCNA). GO and KEGG analyses indicated that the key modules were mainly enriched in tRNA modification, nucleobase metabolic process, DNA ligation, regulation of cellular component movement, basal transcription factors, Huntington disease, and vitamin digestion and absorption. Conclusion These pathways and hub genes can facilitate understanding the molecular mechanism of OSAS and provide a meaningful reference for finding biological targets of OSAS treatment.
Highlights
Obstructive sleep apnea syndrome (OSAS) is the most common type of sleep apnea disorder
We conduct a series of bioinformatics analyses on 48 samples in the GSE75097 dataset based on weighted gene coexpression network analysis (WGCNA)
In the functional enrichment analysis of Gene Ontology (GO), the genes of these modules are mainly enriched in biological processes related to epigenetics, including RNA modification, DNA binding and tRNA, nucleobase metabolic process, pyrimidine nucleobase metabolic process, negative regulation of JNK
Summary
Obstructive sleep apnea syndrome (OSAS) is the most common type of sleep apnea disorder. The disease seriously affects the patient’s respiratory system. WGCNA was used to find genes related to OSAS and obtain coexpression modules. We obtained a total of 7565 DEGs. Through WGCNA, we got four coexpression modules and the modules most related to OSAS were green-yellow, magenta, purple, and turquoise, and we screened out eight hub genes (DDX46, RNF115, COPA, FBXO4, PA2G4, NHP2L1, CDC20, and PCNA). These pathways and hub genes can facilitate understanding the molecular mechanism of OSAS and provide a meaningful reference for finding biological targets of OSAS treatment. Goldfield et al believe that genomic technology can help to better understand disease subtypes and characteristics at the human level and provide individual-level diagnosis and personalized treatment [9]. Gui et al identified the candidate markers related to the pathology of Alzheimer’s disease (AD) and provided comprehensive
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