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February 27, 2026Shengming kexue0 citationsOpen Access

Research progress on animal models of metabolic dysfunction-associated fatty liver disease

LZLin-Yun ZHAOXZXin ZhangZXZi-Meng XI

Key Points

  • To systematically summarize and compare available animal models of metabolic dysfunction-associated fatty liver disease (MAFLD).
  • Categorized MAFLD animal models into diet-induced, drug/chemical-induced, genetically engineered, and non-human primate models.
  • Discussed each model type focusing on specifics like formulation, induction timelines, and metabolic features.
  • Provided guidance on model selection based on research objectives and cost-effectiveness.
  • Highlighted diet-induced models, particularly high-fat diets, as close mimics of human MAFLD pathology.
  • Noted that drug/chemical-induced models lack metabolic features but induce rapid hepatic inflammation.
  • Emphasized the translational potential of non-human primate models despite ethical and cost limitations.

Abstract

Metabolic dysfunction-associated fatty liver disease (MAFLD) represents a global health challenge with a complex and incompletely understood pathogenesis. Animal models serve as indispensable tools for elucidating the mechanisms underlying MAFLD development, evaluating potential therapeutic interventions, and facilitating drug translation. This review aims to systematically summarize and compare the currently available animal models of MAFLD, providing practical guidance for selecting appropriate models in basic and translational research. We categorize MAFLD animal models into four main types: diet-induced models, drug/chemical-induced models, genetically engineered models, and non-human primate (NHP) models. Each model type is discussed in detail, focusing on formulation specifics, induction timelines, reproducible human pathological and metabolic features, and inherent limitations. Diet-induced models, particularly high-fat diets (HFD), are highlighted for their ability to closely mimic human MAFLD pathology, including obesity, insulin resistance, and hepatic steatosis. Drug/chemical-induced models, such as the methionine-choline deficient (MCD) diet and carbon tetrachloride (CCl4) treatment, offer rapid induction of hepatic inflammation and fibrosis but often lack metabolic features observed in human MAFLD. Genetically engineered models provide insights into specific gene functions and pathways but may not fully recapitulate the polygenic and environmental interactions characteristic of human MAFLD. NHP models, due to their close physiological and metabolic resemblance to humans, offer unparalleled translational potential but are limited by high costs and ethical considerations. The selection of an appropriate MAFLD animal model should be guided by the specific research objectives, taking into account factors such as the desired disease stage (e.g., simple steatosis vs. fibrosis), metabolic features, induction timeline, and cost-effectiveness. For mechanistic studies focusing on metabolic pathways, HFD models or genetically engineered models may be preferred. For drug efficacy screening, models that rapidly induce hepatic inflammation and fibrosis, such as MCD combined with CCl4, may be more suitable. NHP models should be reserved for high-value translational studies where close physiological resemblance to humans is critical. Standardization of reporting practices, including detailed descriptions of animal strains, diets, induction protocols, and outcome measures, is essential to enhance the reproducibility and comparability of research findings. Additionally, the use of multiple complementary models is encouraged to capture the heterogeneous nature of MAFLD and strengthen the validity of research conclusions. In conclusion, this review provides a comprehensive overview of the current landscape of MAFLD animal models, highlighting their strengths, limitations, and optimal applications. By adhering to the proposed recommendations, researchers can enhance the rigor, reproducibility, and translational value of their MAFLD studies, ultimately accelerating the development of effective therapeutic strategies for this global health burden.

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Cite This Study

ZHAO et al. (2026) studied this question.

synapsesocial.com/papers/69a134fbed1d949a99abe6c3https://doi.org/10.3724/cbls.2026017
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