Key genes and co‐expression network analysis in the livers of type 2 diabetes patients

Abstract Aims/Introduction The incidence of type 2 diabetes is increasing worldwide. Hepatic insulin resistance and liver lipid accumulation contributes to type 2 diabetes development. The aim of the present study was to investigate the key gene pathways and co‐expression networks in the livers of t...

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Bibliographic Details
Main Authors: Lu Li, Zongfu Pan, Xi Yang
Format: Article
Language:English
Published: Wiley 2019-07-01
Series:Journal of Diabetes Investigation
Subjects:
Online Access:https://doi.org/10.1111/jdi.12998
Description
Summary:Abstract Aims/Introduction The incidence of type 2 diabetes is increasing worldwide. Hepatic insulin resistance and liver lipid accumulation contributes to type 2 diabetes development. The aim of the present study was to investigate the key gene pathways and co‐expression networks in the livers of type 2 diabetes patients. Materials and Methods Dataset GSE15653 containing nine healthy individuals and nine type 2 diabetes patients was downloaded from the National Center for Biotechnology Information Gene Expression Omnibus database. Differentially expressed genes were obtained from the livers of type 2 diabetes patients, annotated pathway enrichment and protein–protein interaction network analysis. Next, functional modules and transcription factor networks were constructed. Gene co‐expression networks were analyzed by weighted correlation network analysis to identify key modules related to clinical traits, and the candidate key genes were validated in hepatic insulin resistance models in vitro. Results A total of 778 differentially expressed genes were filtered in the livers of type 2 diabetes patients, pathway enrichment analysis identified ke y pathways, such as the mitogen‐activated protein kinase signaling pathway, Hippo signaling pathway and hypoxia‐inducible factor‐1 signaling pathway, that were associated with type 2 diabetes. Several transcription factors of three functional modules identified from protein–protein interaction networks are likely to be implicated in type 2 diabetes. Furthermore, weighted correlation network analysis identified five modules that were shown to be highly correlated with type 2 diabetes and other clinical traits. Functional annotation showed that these modules were mainly enriched in pathways such as metabolic pathways, phosphoinositide 3‐kinase‐protein kinase B signaling pathway and natural killer cell‐mediated cytotoxicity. UBE2M and GPER were upregulated in L02 and HepG2 models, whereas P2RY11 only upregulated in L02 model, and UBE2N only downregulated in HepG2 model at a significant level. Conclusions These results would offer new insights into hepatic insulin resistance, type 2 diabetes pathogenesis, development and drug discovery.
ISSN:2040-1116
2040-1124