Xu, Guangyu and Zhao, Yuehan and Bai, Yu and Lin, Yan (2024) Study of hub nodes of transcription factor-target gene regulatory network and immune mechanism for type 2 diabetes based on chip analysis of GEO database. Frontiers in Molecular Biosciences, 11. ISSN 2296-889X
fmolb-11-1410004.pdf - Published Version
Download (2MB)
Abstract
Identification of novel therapeutic targets for type 2 diabetes is a key area of contemporary research. In this study, we screened differentially expressed genes in type 2 diabetes through the GEO database and sought to identify the key virulence factors for type 2 diabetes through a transcription factor regulatory network. Our findings may help identify new therapeutic targets for type 2 diabetes. Data pertaining to the humoral (whole blood) gene expression profile of diabetic patients were obtained from the NCBI’s GEO Datasets database and gene sets with differential expression were identified. Subsequently, the TRED transcriptional regulatory element database was integrated to build a gene regulatory network for type 2 diabetes. Functional analysis (GO-Analysis) and Pathway-analysis of differentially expressed genes were performed using the DAVID database and the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Finally, gene-disease correlation analysis was performed using the DAVID online annotation tool. A total of 236 pathogenic genes, four transcription factors related to the pathogenic genes, and 261 corresponding target genes were identified. A transcription factor-target gene regulatory network for type 2 diabetes was constructed. Most of the key factors of the transcription factor-target gene regulatory network for type 2 diabetes were found closely related to the immune metabolic system and the functions of cell proliferation and transformation.
Item Type: | Article |
---|---|
Subjects: | Apsci Archives > Medical Science |
Depositing User: | Unnamed user with email support@apsciarchives.com |
Date Deposited: | 24 May 2024 12:54 |
Last Modified: | 24 May 2024 12:54 |
URI: | http://eprints.go2submission.com/id/eprint/2797 |