Dataset Information

Diagnostic Value of CK-18, FGF-21, and Related Biomarker Panel in Nonalcoholic Fatty Liver Disease: A Systematic Review and Meta-Analysis.

ABSTRACT: Liver biopsy still remains the gold standard for diagnosing nonalcoholic steatohepatitis (NASH), but with limitations. There is an urgent need to develop noninvasive tests that accurately distinguish NASH from simple steatosis. The purpose of this meta-analysis was to evaluate the diagnostic value of serum biomarkers including cytokeratin 18 (CK-18), fibroblast growth factor 21 (FGF-21), and combined biomarker panel (CBP) in the diagnosis of NAFLD, especially NASH. A total of 25 studies met the inclusion criteria. Pooled sensitivity and specificity values for chosen serum markers for diagnosing NASH are as follows: CK-18 (M30), 0.75 and 0.77; CK-18 (M65), 0.71 and 0.77; FGF-21, 0.62 and 0.78; and CBP, 0.92 and 0.85. CBP demonstrated better accuracy with higher sensitivity and specificity than those tested individually. Furthermore, the AUROC of CBP was 0.94 (95% CI, 0.92-0.96), compared to CK-18 or FGF-21 assay, which showed the most significant ability to distinguish NASH from simple steatosis. The results suggest that increased circulating CK-18 and FGF-21 are associated with NASH and may be used for initial assessment, but not enough. Importantly, CBP is potentially used as accurate diagnostic tools for NASH. Further prospective designed studies are warranted to confirm our findings.

SUBMITTER: He L

PROVIDER: S-EPMC5343245 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Diagnostic Value of CK-18, FGF-21, and Related Biomarker Panel in Nonalcoholic Fatty Liver Disease: A Systematic Review and Meta-Analysis.

He Lei L Deng Linfeng L Zhang Quan Q Guo Jianli J Zhou Jinan J Song Wenjian W Yuan Fahu F

BioMed research international 20170223

Liver biopsy still remains the gold standard for diagnosing nonalcoholic steatohepatitis (NASH), but with limitations. There is an urgent need to develop noninvasive tests that accurately distinguish NASH from simple steatosis. The purpose of this meta-analysis was to evaluate the diagnostic value of serum biomarkers including cytokeratin 18 (CK-18), fibroblast growth factor 21 (FGF-21), and combined biomarker panel (CBP) in the diagnosis of NAFLD, especially NASH. A total of 25 studies met the ...[more]

PMID: 28326329

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Project description:BackgroundMuscle biopsy is the gold standard for diagnosis of mitochondrial disorders because of the lack of sensitive biomarkers in serum. Fibroblast growth factor 21 (FGF-21) is a growth factor with regulatory roles in lipid metabolism and the starvation response, and concentrations are raised in skeletal muscle and serum in mice with mitochondrial respiratory chain deficiencies. We investigated in a retrospective diagnostic study whether FGF-21 could be a biomarker for human mitochondrial disorders.MethodsWe assessed samples from adults and children with mitochondrial disorders or non-mitochondrial neurological disorders (disease controls) from seven study centres in Europe and the USA, and recruited healthy volunteers (healthy controls), matched for age where possible, from the same centres. We used ELISA to measure FGF-21 concentrations in serum or plasma samples (abnormal values were defined as >200 pg/mL). We compared these concentrations with values for lactate, pyruvate, lactate-to-pyruvate ratio, and creatine kinase in serum or plasma and calculated sensitivity, specificity, and positive and negative predictive values for all biomarkers.FindingsWe analysed serum or plasma from 67 patients (41 adults and 26 children) with mitochondrial disorders, 34 disease controls (22 adults and 12 children), and 74 healthy controls. Mean FGF-21 concentrations in serum were 820 (SD 1151) pg/mL in adult and 1983 (1550) pg/mL in child patients with respiratory chain deficiencies and 76 (58) pg/mL in healthy controls. FGF-21 concentrations were high in patients with mitochondrial disorders affecting skeletal muscle but not in disease controls, including those with dystrophies. In patients with abnormal FGF-21 concentrations in serum, the odds ratio of having a muscle-manifesting mitochondrial disease was 132·0 (95% CI 38·7-450·3). For the identification of muscle-manifesting mitochondrial disease, the sensitivity was 92·3% (95% CI 81·5-97·9%) and specificity was 91·7% (84·8-96·1%). The positive and negative predictive values for FGF-21 were 84·2% (95% CI 72·1-92·5%) and 96·1 (90·4-98·9%). The accuracy of FGF-21 to correctly identify muscle-manifesting respiratory chain disorders was better than that for all conventional biomarkers. The area under the receiver-operating-characteristic curve for FGF-21 was 0·95; by comparison, the values for other biomarkers were 0·83 lactate (p=0·037, 0·83 for pyruvate (p=0·015), 0·72 for the lactate-to-pyruvate ratio (p=0·0002), and 0·77 for creatine kinase (p=0·013).InterpretationMeasurement of FGF-21 concentrations in serum identified primary muscle-manifesting respiratory chain deficiencies in adults and children and might be feasible as a first-line diagnostic test for these disorders to reduce the need for muscle biopsy.FundingSigrid Jusélius Foundation, Jane and Aatos Erkko Foundation, Molecular Medicine Institute of Finland, University of Helsinki, Helsinki University Central Hospital, Academy of Finland, Novo Nordisk, Arvo and Lea Ylppö Foundation.

Project description: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.

Dataset Information

Diagnostic Value of CK-18, FGF-21, and Related Biomarker Panel in Nonalcoholic Fatty Liver Disease: A Systematic Review and Meta-Analysis.

Publications

Diagnostic Value of CK-18, FGF-21, and Related Biomarker Panel in Nonalcoholic Fatty Liver Disease: A Systematic Review and Meta-Analysis.

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