Changes in hepatic bile acid profile in a mouse model of metabolic-associated steatohepatitis induced by a high-fat, high-sugar, and high-cholesterol diet combined with carbon tetrachloride
Journal Title: Journal of Clinical Hepatology - Year 2025, Vol 41, Issue 4
Abstract
[Objective] To compare the hepatic bile acid profile between a mouse model of metabolic-associated steatohepatitis (MASH) induced by a high-fat, high-sugar, and high-cholesterol diet combined with intraperitoneal injection of 10% carbon tetrachloride (CCl4) and MASH cases in clinical practice, and to investigate the feasibility of this model in studying drug interventions on bile acid profile in MASH. [Methods] A total of 30 male C57BL/6J mice were randomly divided into control group and model group, with 15 mice in each group. The mice in the control group were given normal diet and drinking water and weekly injections of olive oil, and those in the model group were given a high-fat, high-sugar, and high-cholesterol diet, high-sugar drinking water, and weekly injections of CCl4+olive oil. At the end of weeks 8, 12, and 16, 5 mice were selected from each group to collect samples. Behavioral assessments were performed, and body weight and liver wet weight were measured; liver pathology and lipid deposition were evaluated by HE staining, SAF scoring, oil Red O staining, the semi-quantitative analysis of stained area, the serum levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST), and liver triglyceride (TG) content; Sirius Red staining was performed for liver tissue to assess liver fibrosis; ultra-performance liquid chromatography-tandem mass spectrometry and targeted metabolomics were used to measure the hepatic bile acid profile, including cholic acid (CA), glycocholic acid (GCA), chenodeoxycholic acid (CDCA), glycochenodeoxycholic acid (GCDCA), ursodeoxycholic acid (UDCA), tauroursodeoxycholic acid (TUDCA), hyodeoxycholic acid (HDCA), and glycodeoxycholic acid (GDCA). The independent-samples t test was used for comparison of normally distributed continuous data between two groups, and the Wilcoxon rank-sum test was used for comparison of non-normally distributed continuous data between two groups. [Results] Compared with the control group at the same time point, the model group had disheveled and dull fur, reduced activity, and relatively slow reactions at weeks 8, 12, and 16, as well as significant increases in liver wet weight (P<0.05), the serum level of ALT (P<0.05), the content of TG in the liver (P<0.05), and SAF score (P<0.05). As for the differentially expressed bile acids in liver tissue, compared with the control group at week 8, the model group had significantly higher levels of CA and CDCA and significantly lower levels of UDCA, TUDCA, HDCA, and GDCA (all P<0.05); compared with the control group at week 12, the model group had significantly higher levels of CA, GCA, CDCA, and GCDCA and significantly lower levels of UDCA and HDCA (all P<0.05); compared with the control group at week 16, the model group had significantly higher levels of CA, GCA, CDCA, GCDCA, and TUDCA and significantly lower levels of UDCA, HDCA, and GDCA (all P<0.05). As for the differentially expressed bile acids in the bile acid pool of liver tissue, compared with the control group at week 8, the model group had significantly higher levels of CA and CDCA and significantly lower levels of UDCA, TUDCA, GDCA, and HDCA (all P<0.05); compared with the control group at weeks 12 and 16, the model group had significantly higher levels of GCA and GCDCA and significantly lower levels of UDCA, GDCA, and HDCA (all P<0.05). [Conclusion] There are significant changes in the hepatic bile acid profile in a mouse model of MASH induced by a high-fat, high-sugar, and high-cholesterol diet combined with CCl4, which are similar to the changes in bile acids in MASH cases in clinical practice, suggesting that this model can be used to explore the interventional effect of drugs on the bile acid profile in MASH.
Authors and Affiliations
Jingjing WANG, Jinghua PENG, Yu LIU, Feipeng XU, Wei LIU, Hailin YANG, Ping LIU
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