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A Panel of Protein Kinase Chemosensors Distinguishes Different Types of Fatty Liver Disease.

ABSTRACT: The worldwide incidence of fatty liver disease continues to rise, which may account for concurrent increases in the frequencies of more aggressive liver ailments. Given the existence of histologically identical fatty liver disease subtypes, there is a critical need for the identification of methods that can classify disease and potentially predict progression. Herein, we show that a panel of protein kinase chemosensors can distinguish fatty liver disease subtypes. These direct activity measurements highlight distinct differences between histologically identical fatty liver diseases arising from diets rich in fat versus alcohol and identify a previously unreported decrease in p38? activity associated with a high-fat diet. In addition, we have profiled kinase activities in both benign (diet-induced) and progressive (STAM) disease models. These experiments provide temporal insights into kinase activity during disease development and progression. Altogether, this work provides the basis for the future development of clinical diagnostics and potential treatment strategies.

SUBMITTER: Beck JR

PROVIDER: S-EPMC6820001 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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A Panel of Protein Kinase Chemosensors Distinguishes Different Types of Fatty Liver Disease.

Beck Jon R JR Cabral Fatima F Rasineni Karuna K Casey Carol A CA Harris Edward N EN Stains Cliff I CI

Biochemistry 20190829 37

The worldwide incidence of fatty liver disease continues to rise, which may account for concurrent increases in the frequencies of more aggressive liver ailments. Given the existence of histologically identical fatty liver disease subtypes, there is a critical need for the identification of methods that can classify disease and potentially predict progression. Herein, we show that a panel of protein kinase chemosensors can distinguish fatty liver disease subtypes. These direct activity measureme ...[more]

PMID: 31433166

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Project description:Background and aimsNeutrophil infiltration is a hallmark of nonalcoholic steatohepatitis (NASH), but how this occurs during the progression from steatosis to NASH remains obscure. Human NASH features hepatic neutrophil infiltration and up-regulation of major neutrophil-recruiting chemokines (e.g., chemokine [C-X-C motif] ligand 1 [CXCL1] and interleukin [IL]-8). However, mice fed a high-fat diet (HFD) only develop fatty liver without significant neutrophil infiltration or elevation of chemokines. The aim of this study was to determine why mice are resistant to NASH development and the involvement of p38 mitogen-activated protein kinase (p38) activated by neutrophil-derived oxidative stress in the pathogenesis of NASH.Approach and resultsInflamed human hepatocytes attracted neutrophils more effectively than inflamed mouse hepatocytes because of the greater induction of CXCL1 and IL-8 in human hepatocytes. Hepatic overexpression of Cxcl1 and/or IL-8 promoted steatosis-to-NASH progression in HFD-fed mice by inducing liver inflammation, injury, and p38 activation. Pharmacological inhibition of p38α/β or hepatocyte-specific deletion of p38a (a predominant form in the liver) attenuated liver injury and fibrosis in the HFD+Cxcl1 -induced NASH model that is associated with strong hepatic p38α activation. In contrast, hepatocyte-specific deletion of p38a in HFD-induced fatty liver where p38α activation is relatively weak exacerbated steatosis and liver injury. Mechanistically, weak p38α activation in fatty liver up-regulated the genes involved in fatty acid β-oxidation through peroxisome proliferator-activated receptor alpha phosphorylation, thereby reducing steatosis. Conversely, strong p38α activation in NASH promoted caspase-3 cleavage, CCAAT-enhancer-binding proteins homologous protein expression, and B cell lymphoma 2 phosphorylation, thereby exacerbating hepatocyte death.ConclusionsGenetic ablation of hepatic p38a increases simple steatosis but ameliorates oxidative stress-driven NASH, indicating that p38α plays distinct roles depending on the disease stages, which may set the stage for investigating p38α as a therapeutic target for the treatment of NASH.

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

A Panel of Protein Kinase Chemosensors Distinguishes Different Types of Fatty Liver Disease.

Publications

A Panel of Protein Kinase Chemosensors Distinguishes Different Types of Fatty Liver Disease.

Similar Datasets

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