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Updated: Apr 13, 2026

Mouse Model of Metabolic Dysfunction-Associated Steatotic Liver Disease with Fibrosis
Published on: July 18, 2025
Dysregulation of the Gut-Adipose Tissue-Liver Axis: a Possible Mechanism Behind the Relationship Between Metabolic
Susanna Longo1,2, Tommaso Giovanni Rinaldi1, Jose Manuel Fernández-Real2,3,4,5,6
1Department of Systems Medicine and Center for Atherosclerosis, University of Rome Tor Vergata, Via Montpellier 1, 00133, Rome, Italy.
Purpose Of Review:
Metabolic dysfunction-associated steatotic liver disease (MASLD) is a hepatic manifestation of metabolic syndrome, frequently occurring alongside type 2 diabetes (T2D), and it can present in varied phenotypes. This review provides a critical analysis of gut-adipose tissue-liver axis (GALA) dysregulation in MASLD pathogenesis, contextualizing the discussion within both established and emerging paradigms. The review elucidates how GALA dysregulation shapes the interplay between MASLD and T2D, emphasizing inter-organ crosstalk among the gut, liver, and adipose tissue, and highlighting the role of microbial metabolites, notably bile acids. The review further summarizes recent advances in stratifying MASLD into distinct clusters, examining intricate associations with cardiometabolic comorbidities, and critically evaluates novel therapeutic approaches targeting GALA modulation.
Recent Findings:
MASLD can show heterogeneous phenotypes. It significantly increases the risk of developing new-onset T2D, and both conditions often coexist due to their shared pathophysiological basis in insulin resistance. The gut microbiota influences immune function and modulates host metabolism by regulating glucose tolerance and insulin sensitivity through a specific crosstalk between the gut, liver, and adipose tissue. The dysregulation of the GALA may be a mechanism underlying the interplay between MASLD and T2D, influencing IR and metabolic syndrome. A thorough investigation of GALA's role in the physiopathogenesis of MASLD and T2D highlights its potential to distinguish specific MASLD clusters and to identify personalized therapeutic strategies.
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