Metabolic Divergence Between MASLD and Metabolic Syndrome: Distinct Clinical Phenotypes and Risk Stratification Implications

Background and Aims Metabolic dysfunction‐associated steatotic liver disease (MASLD) has become the leading cause of chronic liver disease worldwide. Metabolic syndrome (MetS) has traditionally been used as an indicator to define metabolic dysfunction, but it may not fully reflect the risk spectrum of MASLD, underscoring the need to better understand its clinical heterogeneity. The aim of this study was to explore phenotypic heterogeneity within MASLD, in particular its overlap and divergence from MetS to improve clinical stratification. Methods We applied an unsupervised clustering approach in a discovery cohort of 600 adults recruited through a local health screening programme, using standardised clinical and metabolic variables to identify distinct phenotypes. Associations between clustering, MASLD and MetS were assessed. External validation was performed on an independent cohort of 407 individuals using cluster centroids derived from the discovery cohort. Results In the two‐cluster model, we identified a low‐risk group with favourable profiles and a high‐risk group enriched for MASLD and MetS. The three‐cluster model further refined these patterns, revealing an intermediate group characterised by MASLD without MetS, with heterogeneous yet clinically relevant metabolic features. Cluster structures were preserved in the validation cohort. Cluster membership was significantly associated with steatosis and liver fibrosis parameters. Conclusions Our findings underscore the phenotypic heterogeneity of MASLD and its partial divergence from MetS. As MetS may not fully capture the spectrum of metabolic dysfunction in MASLD, phenotype‐based approaches grounded in clinical and metabolic data may enhance risk stratification and support more individualised management strategies.