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Non‑alcoholic fatty liver disease (NAFLD) is a common chronic liver disease. Advanced glycation end products (AGEs) negatively affect the liver and accelerate NAFLD progression; however, the underlying mechanisms remain unclear. The present study aimed to examine the effect and mechanism of dietary AGEs on the mouse liver using bioinformatics and in vivo experimental approaches. Gene expression datasets associated with NAFLD were obtained from the Gene Expression Omnibus and differentially expressed genes (DEGs) were identified using GEO2R. Functional enrichment analyses were performed using the Database for Annotation, Visualization and Integrated Discovery and a protein‑protein interaction network for the DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes database. MCODE, a Cytoscape plugin, was subsequently used to identify the most significant module. The key genes involved were verified in a dietary AGE‑induced non‑alcoholic steatohepatitis (NASH) mouse model using reverse transcription‑quantitative PCR (RT‑qPCR). The 462 DEGs associated with NAFLD in the two datasets, of which 34 overlapping genes were found in two microarray datasets. Functional analysis demonstrated that the 34 DEGs were enriched in the 'PPAR signaling pathway', 'central carbon metabolism in cancer', and 'cell adhesion molecules (CAMs)'. Moreover, four hub genes (cell death‑inducing DFFA‑like effector a, cell death‑inducing DFFA‑like effector c, fatty acid‑binding protein 4 and perilipin 4) were identified from a protein‑protein interaction network and were verified using RT‑qPCR in a mouse model of NASH. The results suggested that AGEs and their receptor axis may be involved in NAFLD onset and/or progression. This integrative analysis identified candidate genes and pathways in NAFLD, as well as DEGs and hub genes related to NAFLD progression in silico and in vivo.

molecular medicine reports

Identification of hub genes and key pathways of dietary advanced glycation end products‑induced non‑alcoholic fatty liver disease by bioinformatics analysis and animal experiments