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      Role of Matrix Gla Protein in Transforming Growth Factor-β Signaling and Nonalcoholic Steatohepatitis in Mice

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          Abstract

          Background & Aims

          Nonalcoholic steatohepatitis (NASH) is a complex disease involving both genetic and environmental factors in its onset and progression. We analyzed NASH phenotypes in a genetically diverse cohort of mice, the Hybrid Mouse Diversity Panel, to identify genes contributing to disease susceptibility.

          Methods

          A “systems genetics” approach, involving integration of genetic, transcriptomic, and phenotypic data, was used to identify candidate genes and pathways in a mouse model of NASH. The causal role of Matrix Gla Protein (MGP) was validated using heterozygous MGP knockout ( Mgp +/-) mice. The mechanistic role of MGP in transforming growth factor-beta (TGF-β) signaling was examined in the LX-2 stellate cell line by using a loss of function approach.

          Results

          Local cis-acting regulation of MGP was correlated with fibrosis, suggesting a causal role in NASH, and this was validated using loss of function experiments in 2 models of diet-induced NASH. Using single-cell RNA sequencing, Mgp was found to be primarily expressed in hepatic stellate cells and dendritic cells in mice. Knockdown of MGP expression in stellate LX-2 cells led to a blunted response to TGF-β stimulation. This was associated with reduced regulatory SMAD phosphorylation and TGF-β receptor ALK1 expression as well as increased expression of inhibitory SMAD6. Hepatic MGP expression was found to be significantly correlated with the severity of fibrosis in livers of patients with NASH, suggesting relevance to human disease.

          Conclusions

          MGP regulates liver fibrosis and TGF-β signaling in hepatic stellate cells and contributes to NASH pathogenesis.

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          Most cited references53

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          WGCNA: an R package for weighted correlation network analysis

          Background Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial. Results The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings. Conclusion The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data. The R package along with its source code and additional material are freely available at .
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            Design and validation of a histological scoring system for nonalcoholic fatty liver disease.

            Nonalcoholic fatty liver disease (NAFLD) is characterized by hepatic steatosis in the absence of a history of significant alcohol use or other known liver disease. Nonalcoholic steatohepatitis (NASH) is the progressive form of NAFLD. The Pathology Committee of the NASH Clinical Research Network designed and validated a histological feature scoring system that addresses the full spectrum of lesions of NAFLD and proposed a NAFLD activity score (NAS) for use in clinical trials. The scoring system comprised 14 histological features, 4 of which were evaluated semi-quantitatively: steatosis (0-3), lobular inflammation (0-2), hepatocellular ballooning (0-2), and fibrosis (0-4). Another nine features were recorded as present or absent. An anonymized study set of 50 cases (32 from adult hepatology services, 18 from pediatric hepatology services) was assembled, coded, and circulated. For the validation study, agreement on scoring and a diagnostic categorization ("NASH," "borderline," or "not NASH") were evaluated by using weighted kappa statistics. Inter-rater agreement on adult cases was: 0.84 for fibrosis, 0.79 for steatosis, 0.56 for injury, and 0.45 for lobular inflammation. Agreement on diagnostic category was 0.61. Using multiple logistic regression, five features were independently associated with the diagnosis of NASH in adult biopsies: steatosis (P = .009), hepatocellular ballooning (P = .0001), lobular inflammation (P = .0001), fibrosis (P = .0001), and the absence of lipogranulomas (P = .001). The proposed NAS is the unweighted sum of steatosis, lobular inflammation, and hepatocellular ballooning scores. In conclusion, we present a strong scoring system and NAS for NAFLD and NASH with reasonable inter-rater reproducibility that should be useful for studies of both adults and children with any degree of NAFLD. NAS of > or =5 correlated with a diagnosis of NASH, and biopsies with scores of less than 3 were diagnosed as "not NASH."
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              Global burden of NAFLD and NASH: trends, predictions, risk factors and prevention

              NAFLD is one of the most important causes of liver disease worldwide and will probably emerge as the leading cause of end-stage liver disease in the coming decades, with the disease affecting both adults and children. The epidemiology and demographic characteristics of NAFLD vary worldwide, usually parallel to the prevalence of obesity, but a substantial proportion of patients are lean. The large number of patients with NAFLD with potential for progressive liver disease creates challenges for screening, as the diagnosis of NASH necessitates invasive liver biopsy. Furthermore, individuals with NAFLD have a high frequency of metabolic comorbidities and could place a growing strain on health-care systems from their need for management. While awaiting the development effective therapies, this disease warrants the attention of primary care physicians, specialists and health policy makers.
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                Author and article information

                Contributors
                Journal
                Cell Mol Gastroenterol Hepatol
                Cell Mol Gastroenterol Hepatol
                Cellular and Molecular Gastroenterology and Hepatology
                Elsevier
                2352-345X
                21 August 2023
                2023
                21 August 2023
                : 16
                : 6
                : 943-960
                Affiliations
                [1 ]Department of Medicine, Division of Cardiology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
                [2 ]Institute of Clinical Medical Sciences, China-Japan Friendship Hospital, Beijing, China
                [3 ]Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, California
                [4 ]Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
                [5 ]Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
                [6 ]Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
                [7 ]Department of Medicine, Endocrinology, and Clinical Nutrition, Kuopio University Hospital, Kuopio, Finland
                Author notes
                [] Correspondence Address correspondence to: Aldons J. Lusis, PhD, 675 Charles E. Young Dr S, Department of Medicine/Division of Cardiology, University of California, Los Angeles, Los Angeles, California 90095. jlusis@ 123456mednet.ucla.edu
                []Simon T. Hui, 675 Charles E. Young Dr S, Department of Medicine/Division of Cardiology, University of California, Los Angeles, Los Angeles, California 90095. sthui@ 123456mednet.ucla.edu
                [∗]

                Authors share co-first authorship.

                Article
                S2352-345X(23)00152-2
                10.1016/j.jcmgh.2023.08.007
                10632746
                37611662
                85049d23-ef38-43c0-b48d-76008cb99fbb
                © 2023 The Authors

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 20 August 2022
                : 16 August 2023
                Categories
                Original Research

                gene network analysis,liver fibrosis,nonalcoholic steatohepatitis,systems genetics

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