A bioinformatics analysis to identify shared molecular pathways and hub genes between NAFLD and Gestational Diabetes Mellitus.

Aim: This research aimed to identify the possible links between Non-alcoholic fatty liver disease (NAFLD) and gestational diabetes mellitus (GDM) by examining shared genes and pathways through the use of bioinformatics tools. Background: NAFLD presents several potential risk factors for the onset of GDM. Methods: We downloaded relevant microarray datasets from the Gene Expression Omnibus (GEO) database for screening common differentially expressed genes (DEGs) between NAFLD and GDM by GEO2R. Then, we used gene ontology analysis to explore the biological processes and KEGG pathways of NAFLD and GDM occurrence. The hub genes of each disease were screened by analysis of the PPI network, and the common hub genes were identified. We designed a co-expression network and miRNA hub gene regulatory network for selected hub genes by using GeneMANIA and miRNet platforms, respectively. Results: We identified 521 and 185 DEGs for NAFLD and GDM, respectively. 10 shared genes (FOS, CD22, AMZ1, ANGPT2, ATP1B2, STAB2, EGR1, MMP9, CXCL9, and LCN2) were screened among DEGs of two diseases, with analysis revealing enrichment in pathways such as IL-7 and TNF signaling pathways. Then, common hub genes (FOS, MMP9, and CXCL9) were identified via PPI network analysis, which were strongly correlated with both diseases. In addition, has-mir-34a-5p and has-mir-335-5p were detected as shared miRs that target hubs. Conclusion: We found 3 shared hub genes involved in NAFLD and GDM. Our research established a connection between the two diseases and could aid in formulating possible intervention strategies aimed at addressing both disorders by utilizing these risk factors.