Liraglutide alters hepatic metabolism in high-fat fed obese mice: A bioinformatic prediction and functional analysis

Abstract

Liraglutide, an important pharmacological agent used to improve glycemic status and weight control, has emerged as a therapeutic strategy for hepatic steatosis treatment. ObjectiveThe aim of the present study was to analyze the influence of liraglutide in hepatic steatosis and evaluate the potential target genes involved in the liraglutide action in the hepatic steatosis through a bioinformatics study. Methods & proceduresWe performed an animal study with male mice divided into three groups: standard, high-fat diet and the third group were fed a high-fat diet and treated with liraglutide at a dose of 0.6 mg/kg body weight. Blood parameters (glucose tolerance and insulin sensitivity tests, total cholesterol, high-density lipoprotein-C, triglycerides and glucose levels) were evaluated. mRNA analysis for ACC and FAS were performed. Gene databases, and bioinformatics algorithms were used to generate molecular targets for liraglutide and hepatic steatosis based on in silico investigation. Interactions networks between protein coding were accessed. ResultsThe present study showed that liraglutide decreased glucose levels, total cholesterol and triglycerides in obese animals as compared to the high-fat-fed obese mice. AKT and RPS6KB1 genes presented higher disease-related connectivity. Interaction Network exhibited a power law behavior in correlation: 0.896; R2: 0.796. Ontological analysis demonstrated different mechanisms associated such as regulation of signaling process. ConclusionThe present study reveals relevant information regarding the liraglutide effects in hepatic steatosis. The liraglutide improved hyperglycemia and attenuated hepatic steatosis in mice fed a high-fat diet.