An Update on Animal Models of Alcohol-Associated Liver Disease.

IF 4.7 2区 医学 Q1 PATHOLOGY American Journal of Pathology Pub Date : 2025-01-28 DOI:10.1016/j.ajpath.2024.11.011
Peng Cao, Xiaojuan Chao, Hong-Min Ni, Wen-Xing Ding
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Abstract

Alcohol-associated liver disease (ALD) is a significant global health concern and a leading cause of liver disease-related deaths. However, the treatment options are limited due to the lack of animal models that accurately replicate ALD pathogenesis. An ideal ALD animal model should have pathological characteristics similar to those of human ALD, with a clear pathological process and ease of drug intervention. Over the years, researchers have focused on developing ideal ALD preclinical animal models by testing various methods, such as ad libitum drinking water with ethanol, acute, single large doses of ethanol gavage, multiple alcohol gavages in a short period, the Lieber-DeCarli liquid diet feeding model, the intragastric infusion model, and the Gao-binge model. With the increasing occurrence of obesity and metabolic dysfunction-associated steatotic liver disease, a new category of metabolic and alcohol-associated liver disease (MetALD) is also emerging. Studies have investigated the combined effects of a high-fat diet combined with binge alcohol or drinking water containing ethanol to mimic MetALD. In addition to mice, other species such as rats, guinea pigs, zebrafish, and non-human primates have also been tested to establish ALD preclinical models. This review aims to summarize current animal ALD models, particularly the emerging MetALD models, with the hope of providing a valuable reference for establishing more effective animal models in ALD studies in the future.

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来源期刊
CiteScore
11.40
自引率
0.00%
发文量
178
审稿时长
30 days
期刊介绍: The American Journal of Pathology, official journal of the American Society for Investigative Pathology, published by Elsevier, Inc., seeks high-quality original research reports, reviews, and commentaries related to the molecular and cellular basis of disease. The editors will consider basic, translational, and clinical investigations that directly address mechanisms of pathogenesis or provide a foundation for future mechanistic inquiries. Examples of such foundational investigations include data mining, identification of biomarkers, molecular pathology, and discovery research. Foundational studies that incorporate deep learning and artificial intelligence are also welcome. High priority is given to studies of human disease and relevant experimental models using molecular, cellular, and organismal approaches.
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