Multi-omics regulatory networks reveal the key driver genes in the development of type 2 diabetes

Abstract

BackgroundType 2 diabetes (T2D) onset is a complex, organized biological process with multilevel regulation, and its physiopathological mechanisms are yet to be elucidated. This study aims to find out the hub genes and pathways involved in the pathogenesis of T2D through multi-omics analysis.MethodsThe datasets used in the experiments com-prise three groups: (1) genomic (2) transcriptomic, and (3) epigenomic categories. Then, a series of bioinformatics technologies including Marker set enrichment analysis (MSEA), weighted key driver analysis (wKDA), and protein-protein interaction (PPI) network analysis was performed to identify hub genes. The hub genes were further verified by the Receiver Operator Characteristic (ROC) Curve analysis and Real-time quantitative polymerase chain reaction (RT-qPCR). The multi-omics network was applied to four databases (the Pharmomics pipeline in Mergeomics, Connectivity Map, the Drug Gene Interaction Database, and the L1000 Fireworks Display) to identify drug candidates for T2D treatment. Then, we used the drug-gene interaction network STITCH to conduct network pharmacological analysis.Results MSEA revealed a significant enrichment of immune-related activities and glucose metabolism. Ten hub genes ( PSMB9, COL1A1, COL4A1, HLA-DQB1, COL3A1, IRF7, COL5A1, CD74, HLA-DQA1, and HLA-DRB1 ) were selected by Cytoscape. Among these, COL5A1, IRF7, CD74 , and HLA-DRB1 were verified to have the capability to diagnose T2D, and expression levels of PSMB9 and CD74 had significantly higher in T2D patients. We further predict the transcription factor (TF) binding specificity of hub gene. Besides, based on multi-omics networks, 19 compounds are considered to possess T2D-control potential, such as VX-702. The results of network pharmacological analysis show that VX-702 may affect the IL-17 and TNF signaling pathways, thereby influencing the development of T2D. Conclusions We identified PSMB9 and CD74 as hub genes of T2D based on MSEA, wKDA, and PPI network analysis, which have provided insights into the pathophysiological mechanisms and promising therapeutic perspective of T2D.

Deciphering FFAR4 Mediated Functional Pathways and Potential Drug Targets in Diabetes Mellitus: An Integrated Protein Interaction Network Analysis and Kinetic Simulation

“…Various diseases, including cancers, focus on driver mechanisms such as epigenetic regulators, mutations, transcription factors and gene regulation for generating therapy and personalized treatment opportunities. [5,6] Our findings reveal the crucial links between disease progression and novel drivers. Furthermore, we have extensively studied the role of FFAR4 in diabetes and diabetes-linked disorders, which not only validates the potential of FFAR4 to be used as a therapeutic target for T2DM.…”