Issue 6, 2024

A CDAHFD-induced mouse model mimicking human NASH in the metabolism of hepatic phosphatidylcholines and acyl carnitines

Abstract

Non-alcoholic steatohepatitis (NASH) is the hepatic manifestation of a cluster of conditions associated with lipid metabolism disorders. Ideal animal models mimicking the human NASH need to be explored to better understand the pathogenesis. A choline-deficient, L-amino acid-defined, high-fat diet (CDAHFD) has recently been used to induce the NASH model, but the advantages are not established. NASH models were induced using the well-known traditional methionine- and choline-deficient (MCD) diet for 5 weeks and the recently used CDAHFD for 3 weeks. Liver phenotypes were analyzed to evaluate the differences in markers related to NASH. Lipidomics and metabolism analyses were used to investigate the effects of dietary regimens on the lipidome of the liver. The CDAHFD induced stronger NASH responses than the MCD, including lipid deposition, liver injury, inflammation, bile acid overload and hepatocyte proliferation. A significant difference in the hepatic lipidome was revealed between the CDAHFD and MCD-induced NASH models. In particular, the CDAHFD reduced the hepatic levels of phosphatidylcholines (PCs) and acylcarnitines (ACs), which was supported by the metabolism analysis and in line with the tendency of human NASH. Pathologically, the CDAHFD could effectively induce a more human-like NASH model over the traditional MCD. The hepatic PCs, ACs and their metabolism in CDAHFD-treated mice were down-regulated, similar to those in human NASH.

Graphical abstract: A CDAHFD-induced mouse model mimicking human NASH in the metabolism of hepatic phosphatidylcholines and acyl carnitines

Supplementary files

Article information

Article type
Paper
Submitted
27 Nov 2023
Accepted
12 Feb 2024
First published
27 Feb 2024

Food Funct., 2024,15, 2982-2995

A CDAHFD-induced mouse model mimicking human NASH in the metabolism of hepatic phosphatidylcholines and acyl carnitines

J. Yang, M. Dai, Y. Wang, Z. Yan, S. Mao, A. Liu and C. Lu, Food Funct., 2024, 15, 2982 DOI: 10.1039/D3FO05111K

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