Identification of key genes in non‑alcoholic fatty liver disease progression based on bioinformatics analysis

Mol Med Rep. 2018 Jun;17(6):7708-7720. doi: 10.3892/mmr.2018.8852. Epub 2018 Apr 5.

Abstract

Due to economic development and lifestyle changes, the incidence of non‑alcoholic fatty liver disease (NAFLD) has gradually increased in recent years. However, the pathogenesis of NAFLD is not yet fully understood. To identify candidate genes that contribute to the development and progression of NAFLD, two microarray datasets were downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) were identified and functional enrichment analyses were performed. A protein‑protein interaction network was constructed and modules were extracted using the Search Tool for the Retrieval of Interacting Genes and Cytoscape. The enriched functions and pathways of the DEGs included 'cellular macromolecule biosynthetic process', 'cellular response to chemical stimulus', 'extracellular matrix organization', 'metabolic pathways', 'insulin resistance' and 'forkhead box protein O1 signaling pathway'. The DEGs, including type‑1 angiotensin II receptor, formin‑binding protein 1‑like, RNA‑binding protein with serine‑rich domain 1, Ras‑related C3 botulinum toxin substrate 1 and polyubiquitin‑C, were identified using multiple bioinformatics methods and validated in vitro with reverse transcription‑quantitative polymerase chain reaction analysis. In conclusion, five hub genes were identified in the present study, and they may aid in understanding of the molecular mechanisms underlying the development and progression of NAFLD.

MeSH terms

  • Computational Biology* / methods
  • Disease Progression
  • Gene Expression Profiling / methods
  • Gene Expression Regulation
  • Gene Ontology
  • Gene Regulatory Networks
  • Genetic Predisposition to Disease*
  • Humans
  • Insulin Resistance
  • Non-alcoholic Fatty Liver Disease / genetics*
  • Non-alcoholic Fatty Liver Disease / pathology*
  • Protein Interaction Mapping / methods
  • Protein Interaction Maps
  • Reproducibility of Results