Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease in children, but diagnosis is challenging due to limited availability of noninvasive biomarkers. Machine learning applied to high-resolution metabolomics and clinical phenotype data offers a novel framework for developing a NAFLD screening panel in youth. Here, untargeted metabolomics by liquid chromatography-mass spectrometry was performed on plasma samples from a combined cross-sectional sample of children and adolescents ages 2-25 years old with NAFLD (n = 222) and without NAFLD (n = 337), confirmed by liver biopsy or magnetic resonance imaging. Anthropometrics, blood lipids, liver enzymes, and glucose and insulin metabolism were also assessed. A machine learning approach was applied to the metabolomics and clinical phenotype data sets, which were split into training and test sets, and included dimension reduction, feature selection, and classification model development. The selected metabolite features were the amino acids serine, leucine/isoleucine, and tryptophan; three putatively annotated compounds (dihydrothymine and two phospholipids); and two unknowns. The selected clinical phenotype variables were waist circumference, whole-body insulin sensitivity index (WBISI) based on the oral glucose tolerance test, and blood triglycerides. The highest performing classification model was random forest, which had an area under the receiver operating characteristic curve (AUROC) of 0.94, sensitivity of 73%, and specificity of 97% for detecting NAFLD cases. A second classification model was developed using the homeostasis model assessment of insulin resistance substituted for the WBISI. Similarly, the highest performing classification model was random forest, which had an AUROC of 0.92, sensitivity of 73%, and specificity of 94%. Conclusion: The identified screening panel consisting of both metabolomics and clinical features has promising potential for screening for NAFLD in youth. Further development of this panel and independent validation testing in other cohorts are warranted.

We assessed the performance of magnetic resonance imaging (MRI) proton density fat fraction (PDFF) in children to stratify hepatic steatosis grade before and after treatment in the Cysteamine Bitartrate Delayed-Release for the Treatment of Nonalcoholic Fatty Liver Disease in Children (CyNCh) trial, using centrally scored histology as reference. Participants had multiecho 1.5 Tesla (T) or 3T MRI on scanners from three manufacturers. Of 169 enrolled children, 110 (65%) and 83 (49%) had MRI and liver biopsy at baseline and at end of treatment (EOT; 52 weeks), respectively. At baseline, 17% (19 of 110), 28% (31 of 110), and 55% (60 of 110) of liver biopsies showed grades 1, 2, and 3 histological steatosis; corresponding PDFF (mean ± SD) values were 10.9 ± 4.1%, 18.4 ± 6.2%, and 25.7 ± 9.7%, respectively. PDFF classified grade 1 versus 2-3 and 1-2 versus 3 steatosis with areas under receiving operator characteristic curves (AUROCs) of 0.87 (95% confidence interval [CI], 0.80, 0.94) and 0.79 (0.70, 0.87), respectively. PDFF cutoffs at 90% specificity were 17.5% for grades 2-3 steatosis and 23.3% for grade 3 steatosis. At EOT, 47% (39 of 83), 41% (34 of 83), and 12% (10 of 83) of biopsies showed improved, unchanged, and worsened steatosis grade, respectively, with corresponding PDFF (mean ± SD) changes of –7.8 ± 6.3%, –1.2 ± 7.8%, and 4.9 ± 5.0%, respectively. PDFF change classified steatosis grade improvement and worsening with AUROCs (95% CIs) of 0.76 (0.66, 0.87) and 0.83 (0.73, 0.92), respectively. PDFF change cut-off values at 90% specificity were –11.0% and +5.5% for improvement and worsening. Conclusion: MRI-estimated PDFF has high diagnostic accuracy to both classify and predict histological steatosis grade and change in histological steatosis grade in children with NAFLD. (Hepatology 2018;67:858–872).

Hereditary hemorrhagic telangiectasia (HHT) is an underreported autosomal dominant vascular dysplasia. Neonatal presentations of HHT are rare, as this disorder typically presents in adolescence or beyond with epistaxis. We report a female neonate with hematochezia on the 1st day of life secondary to multiple gastrointestinal arteriovenous malformations (AVMs) along with intracranial hemorrhage. We describe her clinical course and management, as well as her novel family mutation in ENG. This is the first reported HHT case with significant gastrointestinal bleeding in the newborn. We review neonatal HHT and raise the consideration for more directed prenatal imaging and delivery options for fetuses at high risk of HHT.