ArticleDiabetes care2026
Longitudinal Analysis of Liver Chemistry Trajectories and Risk of Type 2 Diabetes in Children With Metabolic Dysfunction-Associated Steatotic Liver Disease: A Multicenter Cohort Study.
Article in Diabetes care, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Editorial: Natural products: a microecological perspective for treating diabetes and its complications.Frontiers in nutrition · 2026Article
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11 authors.
Funding
Abstract
objectiveMetabolic dysfunction-associated steatotic liver disease (MASLD) is the most common chronic liver disease in children and is linked to type 2 diabetes. This study evaluates whether longitudinal changes in liver chemistries-γ-glutamyl transferase (GGT), aspartate aminotransferase (AST), and alanine aminotransferase (ALT)-can serve as biomarkers of increased type 2 diabetes risk in children with MASLD. RESEARCH DESIGN AND
methodsThis multicenter longitudinal cohort study followed 1,035 children with biopsy-confirmed MASLD, without type 2 diabetes at baseline, for a mean of 3.9 years. Liver chemistries were measured annually, and type 2 diabetes was diagnosed based on fasting glucose, HbA1c, and clinical diagnosis. Extended Cox models with inverse probability weighting were used to evaluate associations between liver enzyme trajectories and type 2 diabetes risk.
resultsThe cumulative incidence of type 2 diabetes was 12.3%. Increases in GGT (hazard ratio [HR] 1.55; 95% CI 1.34-1.80), AST (HR 1.31; 95% CI 1.20-1.43), and ALT (HR 1.13; 95% CI 1.07-1.20) were associated with a higher risk of developing type 2 diabetes in the independent models. In the mutual model with all three liver chemistries, only GGT and AST remained significant.
conclusionsA 30-unit increase in GGT over time was associated with a substantially higher risk of developing type 2 diabetes in children with MASLD. Together with AST, GGT may provide clinicians with concrete, routinely available parameters to monitor for early risk stratification. Further validation in independent cohorts is needed to confirm these findings and inform clinical application.
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