In a recent “Ask the Author” session, Professor Stefano Romeo discussed his groundbreaking work on data-driven cluster analysis to identify distinct types of metabolic dysfunction associated with steatotic liver disease. The conversation highlighted a significant shift from “non-alcoholic” to “metabolic” in defining liver diseases, emphasizing a positive and more inclusive approach. This blog post delves into the key insights from the session, exploring the study’s design, findings, and implications for managing patients with Metabolic dysfunction-associated steatotic liver disease (MASLD).

Prof. Stefano Romeo answering to the questions of Prof. Jean-François Dufour.



Study Design and Methodology Professor Romeo’s study aimed to address the heterogeneity observed in Metabolic dysfunction-associated steatotic liver disease (MASLD). The research began with a simple clustering approach using six readily available clinical variables: HbA1c, triglycerides, LDL, age, BMI, and ALT . This unsupervised machine learning method identified three distinct clusters, two of which showed histological evidence of Metabolic dysfunction-associated steatotic liver disease (MASLD) .

Key Findings The study revealed significant differences between the identified clusters:

  • Cluster 1: Characterized by higher triglycerides and HbA1c levels, indicating more pronounced dyslipidemia and diabetes .
  • Cluster 2: Showed increased ALT levels, suggesting a more liver-specific disease .
  • UK Biobank Replication: The findings were replicated in the UK Biobank, confirming that the cluster with higher triglycerides and HbA1c was associated with more cardiovascular events, while the cluster with elevated ALT was primarily linked to liver-related events .

Causality between Liver Disease and Cardiovascular Events Further research explored the causal relationship between Metabolic dysfunction-associated steatotic liver disease (MASLD) and cardiovascular events using polygenic risk scores based on genes affecting fatty liver disease: TM6SF2 and PNPLA3 .

  • TM6SF2 and PNPLA3: Associated with lipoprotein retention, higher MASH and fibrosis, and lower cardiovascular disease risk .
  • Increased Lipogenesis: The group without lipoprotein retention showed an association with the entire spectrum of cardio-renal metabolic syndrome .

Two Distinct Phenotypes of MASLD The combined results from the cluster analysis and genetic studies suggest the existence of two distinct types of Metabolic dysfunction-associated steatotic liver disease (MASLD) :

  1. Liver-Specific MASLD: Primarily affects the liver due to liver-specific mechanisms .
  2. Systemic MASLD: Affects the entire body, with broader systemic implications .

Implications for Patient Management These findings have significant implications for how Metabolic dysfunction-associated steatotic liver disease (MASLD) patients are managed . Recognizing these distinct phenotypes allows for more targeted treatment strategies, addressing specific metabolic dysfunctions and reducing the risk of cardiovascular events in susceptible individuals .

Conclusion Professor Romeo’s work marks a significant advancement in understanding the complexities of Metabolic dysfunction-associated steatotic liver disease (MASLD). By identifying distinct metabolic subtypes and their associated risks, this research paves the way for more personalized and effective treatment approaches, ultimately improving patient outcomes .

Link to full article in Nature journal.