Investigation of the pathogenesis of liver cirrhosis associated with type 2 diabetes mellitus via bioinformatic analysis

Abstract

Background The prevalence of type 2 diabetes mellitus (T2DM) with liver cirrhosis continues to increase globally. T2DM is identified as an independent risk factor for liver cirrhosis and an important prognostic factor for clinical outcomes in patients with liver cirrhosis. However, this co-occurring mechanism has not yet been elucidated. Therefore, this study aims to investigate the mechanisms underlying the co‐pathogenesis of liver cirrhosis and T2DM and to provide reference information for future diagnoses and treatment of patients with liver cirrhosis associated with T2DM. Methods RNA-seq profile of liver cirrhosis and T2DM was downloaded from Gene Expression Omnibus (GEO) database and analyzed. Differentially expressed genes (DEGs) associated with liver cirrhosis and T2DM were identified using GEO2R. Thereafter, the co‐differentially expressed genes (co‐DEGs) associated with liver cirrhosis and T2DM were obtained from the intersection of the datasets on the DEGs. Subsequently, 175 overlapping DEGs were identified and further analyzed using a bioinformatic approach, which included Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, protein–protein interaction (PPI) network analysis, transcription factors (TFs)–gene interaction network analysis, and drug candidate prediction analysis. Results The intersection of datasets on DEGs associated with liver cirrhosis and T2DM enabled the selection of 175 co-DEGs for subsequent analyses. Functional enrichment analyses showed that these co‐DEGs are associated with inflammatory cytokine responses and positive regulation of transforming growth factor‐β1 (TGF‐β1). The KEGG analysis showed that advanced glycation end products–receptor for advanced glycation end products signaling pathway was markedly involved in liver cirrhosis associated with T2DM. Thereafter, a total of eight hub genes: SPARC, COL4A2, THBS1, LUM, TIMP3, COL3A1, IGFBP7, and FSTL1, associated with the diseases were identified using five algorithms from Cytoscape app for network centrality analysis and CytoHubba (a plug‐in in the Cytoscape software). In total, 29 TFs of the hub genes were detected by NetworkAnalyst and Drug SIGnatures DataBase, which predicted that retinoic acid is one of the promising agents that may be used for the treatment of liver cirrhosis associated with T2DM. Conclusions This study elucidated the common pathogenesis of liver cirrhosis and T2DM and predicted a potential clinical therapeutic drug. Therefore, these novel findings may contribute to the literature on the pathogenesis of liver cirrhosis associated with T2DM.