Hidden in the Fat: Unpacking the Metabolic Tango Between Metabolic Dysfunction-Associated Steatotic Liver Disease and Metabolic Syndrome

Metabolic syndrome (MetS) and metabolic dysfunction-associated steatotic liver disease (MASLD) are closely related, with rapidly increasing prevalence globally, driving significant public health concerns. Both conditions share common pathophysiological mechanisms such as insulin resistance (IR), adipose tissue dysfunction, oxidative stress, and gut microbiota dysbiosis, which contribute to their co-occurrence and progression. While the clinical implications of this overlap, including increased cardiovascular, renal, and hepatic risk, are well recognized, current diagnostic and therapeutic approaches remain insufficient due to the clinical and individuals’ heterogeneity and complexity of these diseases. This review aims to provide an in-depth exploration of the molecular mechanisms linking MetS and MASLD, identify critical gaps in our understanding, and highlight existing challenges in early detection and treatment. Despite advancements in biomarkers and therapeutic interventions, the need for a comprehensive, integrated approach remains. The review also discusses emerging therapies targeting specific pathways, the potential of precision medicine, and the growing role of artificial intelligence in enhancing research and clinical management. Future research is urgently needed to combine multi-omics data, precision medicine, and novel biomarkers to better understand the complex interactions between MetS and MASLD. Collaborative, multidisciplinary efforts are essential to develop more effective diagnostic tools and therapies to address these diseases on a global scale.

• Publication year

  2025

• Venue

  International Journal of Molecular Sciences

• Publication date

  2025-04-01

• Fields of study

  Biology, Medicine, Environmental Science

• Identifiers
  DOI 10.3390/ijms26073448PMID 40244398PMCID 11989262
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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