ENOrphanet Journal of Rare Diseases | Predicting Hepatic Adenoma Risk in Glycogen Storage Disease Patients Using Biomarkers and Imaging Parameters
Date: March 12, 2026
Classification: Frontiers
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This study integrates routine biochemical markers with elastography techniques to develop a highly discriminative model for predicting hepatic adenoma risk, proposing clinically actionable thresholds that can help optimize monitoring strategies for patients with glycogen storage disease.
Literature Overview
The article titled 'Correlation of biochemical and imaging markers with hepatic adenoma in patients with glycogen storage disease: a retrospective single-center study,' published in the Orphanet Journal of Rare Diseases, retrospectively reviewed clinical data from 93 genetically confirmed glycogen storage disease (GSD) patients. The study systematically analyzed factors associated with hepatic adenoma development. By comparing ultrasound, FibroScan, shear-wave elastography (SWE), and biochemical markers between patients with and without adenomas, the study identified significantly different variables and constructed a logistic regression model to evaluate predictive performance. Additionally, it examined the relationship between dynamic changes in adenoma size and clinical parameters, further revealing potential biomarkers for disease progression. This work provides a practical tool for non-invasive screening and risk stratification of hepatic adenomas in GSD patients, demonstrating clear clinical translational value.Background Knowledge
Glycogen storage diseases are a group of rare inherited metabolic disorders caused by defects in enzymes involved in glycogen metabolism, leading to abnormal glycogen accumulation in tissues such as the liver. Patients with type I and III GSD face a long-term risk of developing hepatic adenomas, which may progress to hemorrhage or hepatocellular carcinoma, significantly affecting prognosis. Current guidelines recommend regular imaging surveillance, but effective non-invasive predictive tools are lacking. Although prior studies suggest metabolic disturbances like hyperlipidemia are associated with adenomas, research integrating routine biochemical tests with liver elastography parameters for risk prediction remains limited. FibroScan and SWE, non-invasive tools for assessing liver fibrosis and steatosis, are widely used in chronic liver diseases, but their role in predicting tumor risk in GSD has not been clearly established. This study fills that gap by exploring quantifiable and easily accessible clinical indicators using real-world data, aiming to improve early identification of high-risk individuals and optimize follow-up strategies and patient management.
Methods and Experiments
This single-center retrospective observational study included 93 genetically confirmed GSD patients who underwent liver ultrasound, FibroScan, shear-wave elastography (SWE), and routine biochemical testing at Gangwon Provincial Hospital, Yonsei University College of Medicine, between December 2020 and March 2025. Data collected included age, sex, GSD subtype, liver stiffness (LS) and controlled attenuation parameter (CAP) measured by FibroScan, LS measured by SWE, and biochemical markers including ALT, AST, GGT, total cholesterol, triglycerides, uric acid, and M2BPGi. Hepatic adenoma diagnosis was based on ultrasound findings. Mann-Whitney U tests were used to compare differences between adenoma and non-adenoma groups. A logistic regression model was built to predict adenoma risk, with performance evaluated using ROC curves. Longitudinal analysis was performed in patients with serial imaging data to assess the relationship between changes in adenoma size and parameter dynamics.Key Findings and Insights
Implications and Future Directions
This study is the first to systematically evaluate the value of combining routine biochemical markers with elastography for predicting hepatic adenomas in GSD. The developed model shows high predictive accuracy, and the parameters used are readily available in clinical practice, ensuring good generalizability. The proposed simplified thresholds offer clinicians an intuitive tool for risk assessment, aiding in the identification of high-risk patients and timely scheduling of imaging follow-ups for early intervention.
The results highlight the sensitivity of GGT and CAP in monitoring adenoma progression, outperforming structural stiffness measures, suggesting that inflammation and steatosis may play earlier roles in dynamic adenoma changes. Future multicenter prospective studies are needed to validate the model's robustness and explore the role of these biomarkers in guiding personalized treatment decisions. Furthermore, combining metabolic markers with radiomics or liquid biopsy may further enhance predictive performance.
Conclusion
This study systematically analyzed predictive factors for hepatic adenomas in glycogen storage disease patients, finding that age, GGT, triglycerides, total cholesterol, and FibroScan-measured liver stiffness were significantly elevated in patients with adenomas. By integrating multiple routine clinical parameters, the logistic regression model demonstrated excellent discriminative ability (AUC = 0.87), providing an effective tool for non-invasive screening. Importantly, changes in GGT and FibroScan CAP were shown to be closely associated with dynamic changes in adenoma size, indicating their superior sensitivity over liver stiffness measures in monitoring disease progression. The proposed simplified clinical thresholds (e.g., GGT > 60 IU/L, CAP > 280 dB/m) have practical value and can support clinical decision-making, optimizing monitoring strategies for high-risk patients. Although limited by the single-center retrospective design and sample size, this work provides important evidence for the personalized management of glycogen storage disease, and external validation is needed to facilitate clinical translation.
