Bioinformatics Analysis of Next Generation Sequencing Data Identifies Molecular Biomarkers Associated With Type 2 Diabetes Mellitus.
Type 2 diabetes mellitus
bioinformatics analysis
differentially expressed genes
hub genes
pathway enrichment analysis
Journal
Clinical medicine insights. Endocrinology and diabetes
ISSN: 1179-5514
Titre abrégé: Clin Med Insights Endocrinol Diabetes
Pays: United States
ID NLM: 101578235
Informations de publication
Date de publication:
2023
2023
Historique:
received:
22
06
2022
accepted:
19
01
2023
entrez:
27
2
2023
pubmed:
28
2
2023
medline:
28
2
2023
Statut:
epublish
Résumé
Type 2 diabetes mellitus (T2DM) is the most common metabolic disorder. The aim of the present investigation was to identify gene signature specific to T2DM. The next generation sequencing (NGS) dataset GSE81608 was retrieved from the gene expression omnibus (GEO) database and analyzed to identify the differentially expressed genes (DEGs) between T2DM and normal controls. Then, Gene Ontology (GO) and pathway enrichment analysis, protein-protein interaction (PPI) network, modules, miRNA (micro RNA)-hub gene regulatory network construction and TF (transcription factor)-hub gene regulatory network construction, and topological analysis were performed. Receiver operating characteristic curve (ROC) analysis was also performed to verify the prognostic value of hub genes. A total of 927 DEGs (461 were up regulated and 466 down regulated genes) were identified in T2DM. GO and REACTOME results showed that DEGs mainly enriched in protein metabolic process, establishment of localization, metabolism of proteins, and metabolism. The top centrality hub genes The potential crucial genes, especially
Sections du résumé
Background
UNASSIGNED
Type 2 diabetes mellitus (T2DM) is the most common metabolic disorder. The aim of the present investigation was to identify gene signature specific to T2DM.
Methods
UNASSIGNED
The next generation sequencing (NGS) dataset GSE81608 was retrieved from the gene expression omnibus (GEO) database and analyzed to identify the differentially expressed genes (DEGs) between T2DM and normal controls. Then, Gene Ontology (GO) and pathway enrichment analysis, protein-protein interaction (PPI) network, modules, miRNA (micro RNA)-hub gene regulatory network construction and TF (transcription factor)-hub gene regulatory network construction, and topological analysis were performed. Receiver operating characteristic curve (ROC) analysis was also performed to verify the prognostic value of hub genes.
Results
UNASSIGNED
A total of 927 DEGs (461 were up regulated and 466 down regulated genes) were identified in T2DM. GO and REACTOME results showed that DEGs mainly enriched in protein metabolic process, establishment of localization, metabolism of proteins, and metabolism. The top centrality hub genes
Conclusion
UNASSIGNED
The potential crucial genes, especially
Identifiants
pubmed: 36844983
doi: 10.1177/11795514231155635
pii: 10.1177_11795514231155635
pmc: PMC9944228
doi:
Types de publication
Journal Article
Langues
eng
Pagination
11795514231155635Informations de copyright
© The Author(s) 2023.
Déclaration de conflit d'intérêts
The author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
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