ArticleHepatology communications2024
Validation of a screening panel for pediatric metabolic dysfunction-associated steatotic liver disease using metabolomics.
Article in Hepatology communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 9 citations in OpenAlex.
- Integrated serum metabolomics and MRI biomarkers for MASLD: a practical framework for noninvasive staging and monitoring.Abdominal radiology (New York) · 2026Review
- Amino Acids-Potential Biomarkers of Histological Features for MASLD in Pediatric Obesity.International journal of molecular sciences · 2026Review
- The application of artificial intelligence in the intersection of metabolic dysfunction-associated steatotic liver disease and cardiovascular diseases.Frontiers in immunology · 2026Review
- Evaluation for Fatty Liver Infiltration Should Become Standard in Pediatric Cholecystectomy Patients.Cureus · 2025Article
- The Use of Non-i nvasive Biomarkers to Screen for Advanced Fibrosis Associated with Metabolic Dysfunction-associated Steatotic Liver Disease in People with Type 2 Diabetes: A Narrative Review.TouchREVIEWS in endocrinology · 2025Review
- Clinical Features and Plasma Metabolites Analysis in Obese Chinese Children With Nonalcoholic Fatty Liver Disease.Journal of the Endocrine Society · 2025Article
- From traditional metabolic markers to ensemble learning: comparative application of machine learning models for predicting NAFLD risk in adolescents.Frontiers in endocrinology · 2025Article
- Cardiovascular-kidney-metabolic progression associated with major adverse liver outcomes: mediating roles of plasma metabolites.Frontiers in nutrition · 2025Article
- Metabolomic Hallmarks of Obesity and Metabolic Dysfunction-Associated Steatotic Liver Disease.International journal of molecular sciences · 2024Review
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundMetabolic dysfunction-associated steatotic liver disease (MASLD), formerly known as NAFLD, is the most common liver disease in children. Liver biopsy remains the gold standard for diagnosis, although more efficient screening methods are needed. We previously developed a novel NAFLD screening panel in youth using machine learning applied to high-resolution metabolomics and clinical phenotype data. Our objective was to validate this panel in a separate cohort, which consisted of a combined cross-sectional sample of 161 children with stored frozen samples (75% male, 12.8±2.6 years of age, body mass index 31.0±7.0 kg/m2, 81% with MASLD, 58% Hispanic race/ethnicity).
methodsClinical data were collected from all children, and high-resolution metabolomics was performed using their fasting serum samples. MASLD was assessed by MRI-proton density fat fraction or liver biopsy and cardiometabolic factors. Our previously developed panel included waist circumference, triglycerides, whole-body insulin sensitivity index, 3 amino acids, 2 phospholipids, dihydrothymine, and 2 unknowns. To improve feasibility, a simplified version without the unknowns was utilized in the present study. Since the panel was modified, the data were split into training (67%) and test (33%) sets to assess the validity of the panel.
resultsOur present highest-performing modified model, with 4 clinical variables and 8 metabolomics features, achieved an AUROC of 0.92, 95% sensitivity, and 80% specificity for detecting MASLD in the test set.
conclusionsTherefore, this panel has promising potential for use as a screening tool for MASLD in youth.
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