Cargando…

Identification of Hub Genes in Patients with Alzheimer Disease and Obstructive Sleep Apnea Syndrome Using Integrated Bioinformatics Analysis

BACKGROUND: Obstructive sleep apnea syndrome (OSA) is associated with an increased risk of Alzheimer’s disease (AD). This study aimed to identify the key common genes in AD and OSA and explore molecular mechanism value in AD. METHODS: Expression profiles GSE5281 and GSE135917 were acquired from Gene...

Descripción completa

Detalles Bibliográficos
Autores principales: Wu, Lanxiang, Wang, Wenjun, Tian, Sheng, Zheng, Heqing, Liu, Pan, Wu, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8668230/
https://www.ncbi.nlm.nih.gov/pubmed/34916831
http://dx.doi.org/10.2147/IJGM.S341078
_version_ 1784614525735010304
author Wu, Lanxiang
Wang, Wenjun
Tian, Sheng
Zheng, Heqing
Liu, Pan
Wu, Wei
author_facet Wu, Lanxiang
Wang, Wenjun
Tian, Sheng
Zheng, Heqing
Liu, Pan
Wu, Wei
author_sort Wu, Lanxiang
collection PubMed
description BACKGROUND: Obstructive sleep apnea syndrome (OSA) is associated with an increased risk of Alzheimer’s disease (AD). This study aimed to identify the key common genes in AD and OSA and explore molecular mechanism value in AD. METHODS: Expression profiles GSE5281 and GSE135917 were acquired from Gene Expression Omnibus (GEO) database, respectively. Weighted gene co-expression network analysis (WGCNA) and R 4.0.2 software were used for identifying differentially expressed genes (DEGs) related to AD and OSA. Function enrichment analyses using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and the protein–protein interaction network (PPI) using the STRING database were subsequently performed on the shared DEGs. Finally, the hub genes were screened from the PPI network using the MCC algorithm of CytoHubba plugin. RESULTS: Seven modules and four modules were the most significant with AD and OSA by WGCNA, respectively. A total of 33 common genes were screened in AD and OSA by VENN. Functional enrichment analysis indicated that DEGs were mainly involved in cellular response to oxidative stress, neuroinflammation. Among these DEGs, the top 10 hub genes (high scores in cytoHubba) were selected in the PPI network, including AREG, SPP1, CXCL2, ITGAX, DUSP1, COL1A1, SCD, ACTA2, CCND2, ATF3. CONCLUSION: This study presented ten target genes on the basis of common genes to AD and OSA. These candidate genes may provide a novel perspective to explore the underlying mechanism that OSA leads to an increased risk of AD at the transcriptome level.
format Online
Article
Text
id pubmed-8668230
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Dove
record_format MEDLINE/PubMed
spelling pubmed-86682302021-12-15 Identification of Hub Genes in Patients with Alzheimer Disease and Obstructive Sleep Apnea Syndrome Using Integrated Bioinformatics Analysis Wu, Lanxiang Wang, Wenjun Tian, Sheng Zheng, Heqing Liu, Pan Wu, Wei Int J Gen Med Original Research BACKGROUND: Obstructive sleep apnea syndrome (OSA) is associated with an increased risk of Alzheimer’s disease (AD). This study aimed to identify the key common genes in AD and OSA and explore molecular mechanism value in AD. METHODS: Expression profiles GSE5281 and GSE135917 were acquired from Gene Expression Omnibus (GEO) database, respectively. Weighted gene co-expression network analysis (WGCNA) and R 4.0.2 software were used for identifying differentially expressed genes (DEGs) related to AD and OSA. Function enrichment analyses using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and the protein–protein interaction network (PPI) using the STRING database were subsequently performed on the shared DEGs. Finally, the hub genes were screened from the PPI network using the MCC algorithm of CytoHubba plugin. RESULTS: Seven modules and four modules were the most significant with AD and OSA by WGCNA, respectively. A total of 33 common genes were screened in AD and OSA by VENN. Functional enrichment analysis indicated that DEGs were mainly involved in cellular response to oxidative stress, neuroinflammation. Among these DEGs, the top 10 hub genes (high scores in cytoHubba) were selected in the PPI network, including AREG, SPP1, CXCL2, ITGAX, DUSP1, COL1A1, SCD, ACTA2, CCND2, ATF3. CONCLUSION: This study presented ten target genes on the basis of common genes to AD and OSA. These candidate genes may provide a novel perspective to explore the underlying mechanism that OSA leads to an increased risk of AD at the transcriptome level. Dove 2021-12-09 /pmc/articles/PMC8668230/ /pubmed/34916831 http://dx.doi.org/10.2147/IJGM.S341078 Text en © 2021 Wu et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Wu, Lanxiang
Wang, Wenjun
Tian, Sheng
Zheng, Heqing
Liu, Pan
Wu, Wei
Identification of Hub Genes in Patients with Alzheimer Disease and Obstructive Sleep Apnea Syndrome Using Integrated Bioinformatics Analysis
title Identification of Hub Genes in Patients with Alzheimer Disease and Obstructive Sleep Apnea Syndrome Using Integrated Bioinformatics Analysis
title_full Identification of Hub Genes in Patients with Alzheimer Disease and Obstructive Sleep Apnea Syndrome Using Integrated Bioinformatics Analysis
title_fullStr Identification of Hub Genes in Patients with Alzheimer Disease and Obstructive Sleep Apnea Syndrome Using Integrated Bioinformatics Analysis
title_full_unstemmed Identification of Hub Genes in Patients with Alzheimer Disease and Obstructive Sleep Apnea Syndrome Using Integrated Bioinformatics Analysis
title_short Identification of Hub Genes in Patients with Alzheimer Disease and Obstructive Sleep Apnea Syndrome Using Integrated Bioinformatics Analysis
title_sort identification of hub genes in patients with alzheimer disease and obstructive sleep apnea syndrome using integrated bioinformatics analysis
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8668230/
https://www.ncbi.nlm.nih.gov/pubmed/34916831
http://dx.doi.org/10.2147/IJGM.S341078
work_keys_str_mv AT wulanxiang identificationofhubgenesinpatientswithalzheimerdiseaseandobstructivesleepapneasyndromeusingintegratedbioinformaticsanalysis
AT wangwenjun identificationofhubgenesinpatientswithalzheimerdiseaseandobstructivesleepapneasyndromeusingintegratedbioinformaticsanalysis
AT tiansheng identificationofhubgenesinpatientswithalzheimerdiseaseandobstructivesleepapneasyndromeusingintegratedbioinformaticsanalysis
AT zhengheqing identificationofhubgenesinpatientswithalzheimerdiseaseandobstructivesleepapneasyndromeusingintegratedbioinformaticsanalysis
AT liupan identificationofhubgenesinpatientswithalzheimerdiseaseandobstructivesleepapneasyndromeusingintegratedbioinformaticsanalysis
AT wuwei identificationofhubgenesinpatientswithalzheimerdiseaseandobstructivesleepapneasyndromeusingintegratedbioinformaticsanalysis