Bile acids (BA) play a significant role in the pathophysiology of nonalcoholic steatohepatitis (NASH). The present study evaluates the modulation of bile acid metabolomics by atorvastatin, a cholesterol-lowering agent commonly used to treat cardiovascular complications accompanying NASH. NASH was induced in mice by 24 weeks of consuming a high–saturated fat, high-fructose, and high-cholesterol diet (F), with atorvastatin administered orally (20 mg/kg/day) during the last three weeks. Biochemical and histological analyses confirmed the effectiveness of the F diet in inducing NASH. Untreated NASH animals had significantly reduced biliary secretion of BA and increased fecal excretion of BA via decreased apical sodium-dependent bile salt transporter (Asbt)-mediated reabsorption. Atorvastatin decreased liver steatosis and inflammation in NASH animals consistently with a reduction in crucial lipogenic enzyme stearoyl–coenzyme A (CoA) desaturase-1 and nuclear factor kappa light chain enhancer of activated B-cell pro-inflammatory signaling, respectively. In this group, atorvastatin also uniformly enhanced plasma concentration, biliary secretion and fecal excretion of the secondary BA, deoxycholic acid (DCA). However, in the chow diet–fed animals, atorvastatin decreased plasma concentrations of BA, and reduced BA biliary secretions. These changes stemmed primarily from the increased fecal excretion of BA resulting from the reduced Asbt-mediated BA reabsorption in the ileum and suppression of synthesis in the liver. In conclusion, our results reveal that atorvastatin significantly modulates BA metabolomics by altering their intestinal processing and liver synthesis in control and NASH mice.

The search for non-invasive, fast, and low-cost diagnostic tools has gained significant traction among many researchers worldwide. Dielectric properties calculated from microwave signals offer unique insights into biological tissue. Material properties, such as relative permittivity (${\mathsf{\epsilon }}_{\mathrm{r}}$) and conductivity ($\mathsf{\sigma }$), can vary significantly between healthy and unhealthy tissue types at a given frequency. Understanding this difference in properties is key for identifying the disease state. The frequency-dependent nature of the dielectric measurements results in large datasets, which can be postprocessed using artificial intelligence (AI) methods. In this work, the dielectric properties of liver tissues in three mouse models of liver disease are characterized using dielectric spectroscopy. The measurements are grouped into four categories based on the diets or disease state of the mice, i.e., healthy mice, mice with non-alcoholic steatohepatitis (NASH) induced by choline-deficient high-fat diet, mice with NASH induced by western diet, and mice with liver fibrosis. Multi-class classification machine learning (ML) models are then explored to differentiate the liver tissue groups based on dielectric measurements. The results show that the support vector machine (SVM) model was able to differentiate the tissue groups with an accuracy up to 90%. This technology pipeline, thus, shows great potential for developing the next generation non-invasive diagnostic tools.

Nonalcoholic steatohepatitis (NASH) is characterized by hepatic steatosis with inflammation and fibrosis. Membrane endoglin (Eng) expression is shown to participate in fibrosis, and plasma concentrations of soluble endoglin (sEng) are increased in patients with hypercholesterolemia and type 2 diabetes mellitus. We hypothesize that NASH increases both hepatic Eng expression and sEng in blood and that high levels of sEng modulate cholesterol and bile acid (BA) metabolism and affect NASH progression. Three-month-old transgenic male mice overexpressing human sEng and their wild type littermates are fed for six months with either a high-saturated fat, high-fructose high-cholesterol (FFC) diet or a chow diet. Evaluation of NASH, Liquid chromatography–mass spectrometry (LC/MS) analysis of BA, hepatic expression of Eng, inflammation, fibrosis markers, enzymes and transporters involved in hepatic cholesterol and BA metabolism are assessed using Real-Time Quantitative Reverse Transcription Polymerase Chain reaction (qRT-PCR) and Western blot. The FFC diet significantly increases mouse sEng levels and increases hepatic expression of Eng. High levels of human sEng results in increased hepatic deposition of cholesterol due to reduced conversion into BA, as well as redirects the metabolism of triglycerides (TAG) to its accumulation in the liver, via reduced TAG elimination by β-oxidation combined with reduced hepatic efflux. We propose that sEng might be a biomarker of NASH development, and the presence of high levels of sEng might support NASH aggravation by impairing the essential defensive mechanism protecting NASH liver against excessive TAG and cholesterol accumulation, suggesting the importance of high sEng levels in patients prone to develop NASH.