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Updated: Jun 27, 2025

Author Spotlight: Establishing MASLD Cell Models for Investigating Disease Mechanisms and the Lipid-Lowering Effects of Koumiss
Published on: July 19, 2024
Prevalence and predictive features of metabolic dysfunction-associated steatotic liver disease in type 1 diabetes
Coco M Fuhri Snethlage1, Abraham S Meijnikman1, Anne Linde Mak1
1Department of Vascular Medicine, Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam UMC, University of Amsterdam, Amsterdam, AZ 1105, The Netherlands.
Aims/Hypothesis:
The prevalence and severity of metabolic dysfunction-associated steatotic liver disease (MASLD) in type 1 diabetes remain unclear. Therefore, we investigated the prevalence and severity of MASLD in type 1 diabetes and assessed which clinical features are most important in predicting MASLD severity.
Methods:
A total of 453 individuals with type 1 diabetes (41.6 ± 15.0 years, 64% female, body mass index [BMI] 25.4 ± 4.2 kg/m2, and HbA1c 55.6 ± 12 mmol/mol) underwent vibration-controlled transient elastography (VCTE), with a controlled attenuation parameter (CAP) score for steatosis (≥280.0 dB/m) and a liver stiffness measurement (LMS) for fibrosis (≥8.0 kPa). A machine learning Extra-Trees classification model was performed to assess the predictive power of the clinical features associated with type 1 diabetes with respect to steatosis and fibrosis.
Results:
The prevalence of hepatic steatosis and fibrosis was 9.5% (95% CI, 6.8-12.2) and 3.5% (95% CI, 1.8-5.2). Higher LMS was associated with a longer duration of type 1 diabetes (median 30.5 [IQR 18.0-39.3] years vs 15.0 [IQR 6.0-27.0] years), and individuals were older, had a higher BMI (mean 27.8 ± 5.2 vs 25.3 ± 4.1 kg/m2), and a higher CAP score (mean 211.4 ± 51.7 dB/m vs 241.4 ± 75.6 dB/m). The most important predictive features of fibrosis were duration of type 1 diabetes, age, and systolic blood pressure, with a mean ± SD area under the curve of 0.73 ± 0.03.
Conclusion:
Individuals with type 1 diabetes and high blood pressure, older age, higher BMI, and longer duration of disease could be considered at high-risk for developing MASLD.
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