Clinical and non-invasive assessment of metabolic dysfunction-associated steatotic liver disease and glycogenic hepatopathy in individuals with type 1 diabetes

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ID: 332019
2026
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Abstract
Abstract Objective To deepen understanding of metabolic dysfunction-associated steatotic liver disease (MASLD) and presumptive glycogenic hepatopathy (GH) in adults with type 1 diabetes (T1D), and to evaluate non-invasive indices and novel biomarkers for their differentiation. Methods We conducted a cross-sectional study including 202 adults with T1D. Hepatic steatosis was assessed using a stepwise imaging approach: all participants underwent ultrasound (US); liver magnetic resonance imaging-proton density fat fraction (MRI-PDFF) was performed when US was abnormal. Based on imaging, participants were categorized into three hepatic phenotypes: normal liver (NL), MASLD (steatosis on both US and MRI), and presumptive GH (hyperechogenicity on US but <5% fat on MRI). MRI-derived fat correlations and the performance of non-invasive indices and biomarkers were assessed. Results Hepatic steatosis was identified by US in 39 participants, yielding a MASLD prevalence of 19.3%. Among the 32 participants with abnormal US who underwent MRI-PDFF, only 50% had liver fat ≥5%, indicating limited specificity of US and enabling identification of a presumptive GH phenotype (8.2%). MASLD was associated with a worse metabolic profile than presumptive GH or NL. The Fatty Liver Index (FLI) correlated strongly with MRI liver fat (ρ = 0.726, p < 0.0001) and showed promising exploratory performance (AUC = 0.842, 95% CI 0.687–0.998). Conclusions US may overestimate hepatic steatosis in adults with T1D, partly due to presumptive GH. Among participants undergoing MRI-PDFF, FLI showed promising exploratory performance for identifying steatosis, but requires further validation in cohorts undergoing systematic MRI-PDFF assessment.
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openalex_W7221364446 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors
Journal the journal of clinical endocrinology & metabolism
Year 2026
DOI
10.1210/clinem/dgag422
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Keywords Keywords not found

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