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An Update in Epigenetics in Metabolic-Associated Fatty Liver Disease.

ABSTRACT: Metabolic-associated fatty liver disease (MAFLD) is characterized by hepatic steatosis accompanied by one of three features: overweight or obesity, T2DM, or lean or normal weight with evidence of metabolic dysregulation. It is distinguished by excessive fat accumulation in hepatocytes, and a decrease in the liver's ability to oxidize fats, the accumulation of ectopic fat, and the activation of proinflammatory pathways. Chronic damage will keep this pathophysiologic cycle active causing progression from hepatic steatosis to cirrhosis and eventually, hepatocarcinoma. Epigenetics affecting gene expression without altering DNA sequence allows us to study MAFLD pathophysiology from a different perspective, in which DNA methylation processes, histone modifications, and miRNAs expression have been closely associated with MAFLD progression. However, these considerations also faced us with the circumstance that modifying those epigenetics patterns might lead to MAFLD regression. Currently, epigenetics is an area of great interest because it could provide new insights in therapeutic targets and non-invasive biomarkers. This review comprises an update on the role of epigenetic patterns, as well as innovative therapeutic targets and biomarkers in MAFLD.

SUBMITTER: Rodriguez-Sanabria JS

PROVIDER: S-EPMC8787199 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundNonalcoholic fatty liver disease (NAFLD) is the most common liver disease. Metabolism-related genes significantly influence the onset and progression of the disease. Hence, it is necessary to screen metabolism-related biomarkers for the diagnosis and treatment of NAFLD patients.MethodsGSE48452, GSE63067, and GSE89632 datasets including nonalcoholic steatohepatitis (NASH) and healthy controls (HC) analyzed in this study were retrieved from the Gene Expression Omnibus (GEO) database. First, differentially expressed genes (DEGs) between NASH and HC samples were obtained. Next, metabolism-related DEGs (MR-DEGs) were identified by overlapping DEGs and metabolism-related genes (MRG). Further, a protein-protein interaction (PPI) network was developed to show the interaction among MR-DEGs. Subsequently, the "Least absolute shrinkage and selection operator regression" and "Random Forest" algorithms were used to screen metabolism-related genes (MRGs) in patients with NAFLD. Next, immune cell infiltration and gene set enrichment analyses (GSEA) were performed on these metabolism-related genes. Finally, the expression of metabolism-related gene was determined at the transcription level.ResultsFirst, 129 DEGs related to NAFLD development were identified among patients with nonalcoholic steatohepatitis (NASH) and healthy control. Next, 18 MR-DEGs were identified using the Venn diagram. Subsequently, four genes, including AMDHD1, FMO1, LPL, and P4HA1, were identified using machine learning algorithms. Moreover, a regulatory network consisting of four genes, 25 microRNAs (miRNAs), and 41 transcription factors (TFs) was constructed. Finally, a significant increase in FMO1 and LPL expression levels and a decrease in AMDHD1 and P4HA1 expression levels were observed in patients in the NASH group compared to the HC group.ConclusionMetabolism-related genes associated with NAFLD were identified, containing AMDHD1, FMO1, LPL, and P4HA1, which provide insights into diagnosing and treating patients with NAFLD.

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An Update in Epigenetics in Metabolic-Associated Fatty Liver Disease.

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