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Accuracy of metabolomics profiles to non-invasively diagnose NAFLD stages and evolution by mean of machine-learning automated algorithms

  • M. Masarone
    Affiliations
    Department of Medicine, Surgery and Dentistry, “Scuola Medica Salernitana”, University of Salerno, Via Salvador Allende -84081 - Baronissi (SA). Italy
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  • J. Troisi
    Affiliations
    Department of Medicine, Surgery and Dentistry, “Scuola Medica Salernitana”, University of Salerno, Via Salvador Allende -84081 - Baronissi (SA). Italy

    Theoreo srl, Via degli Ulivi 3, 84090 Montecorvino Pugliano (SA), Italy

    European Biomedical Research Institute of Salerno (EBRIS), Via S. de Renzi, 3, 84125 Salerno (SA), Italy

    Hosmotic srl, Via R. Bosco 178, 80069, Vico Equense (NA), Italy
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  • A. Aglitti
    Affiliations
    Department of Medicine, Surgery and Dentistry, “Scuola Medica Salernitana”, University of Salerno, Via Salvador Allende -84081 - Baronissi (SA). Italy
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  • G. Calvanese
    Affiliations
    Department of Medicine, Surgery and Dentistry, “Scuola Medica Salernitana”, University of Salerno, Via Salvador Allende -84081 - Baronissi (SA). Italy
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  • P. Torre
    Affiliations
    Department of Medicine, Surgery and Dentistry, “Scuola Medica Salernitana”, University of Salerno, Via Salvador Allende -84081 - Baronissi (SA). Italy
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  • R. Caruso
    Affiliations
    Department of Medicine, Surgery and Dentistry, “Scuola Medica Salernitana”, University of Salerno, Via Salvador Allende -84081 - Baronissi (SA). Italy
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  • A. Colucci
    Affiliations
    Theoreo srl, Via degli Ulivi 3, 84090 Montecorvino Pugliano (SA), Italy
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  • M. Dallio
    Affiliations
    Hepatogastroenterology Division, University of Campania “Luigi Vanvitelli”; Via S Pansini 5, 80131 Naples, Italy
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  • A. Federico
    Affiliations
    Hepatogastroenterology Division, University of Campania “Luigi Vanvitelli”; Via S Pansini 5, 80131 Naples, Italy
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  • C. Balsano
    Affiliations
    MESVA Department, University of L’Aquila, Piazza S. Salvatore Tommasi 1, 67100, Coppito, L’Aquila, Italy

    F. Balsano Foundation, Via Giovanni Battista Martini 6, 00198, Rome, Italy
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  • M. Persico
    Affiliations
    Department of Medicine, Surgery and Dentistry, “Scuola Medica Salernitana”, University of Salerno, Via Salvador Allende -84081 - Baronissi (SA). Italy
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      Background and Aims: Non-Alcoholic Fatty Liver Disease encompasses a spectrum of diseases ranging from simple steatosis to NASH and cirrhosis/HCC. The challenge in this field is to recognize the more severe and/or progressive pathology. A reliable non-invasive method based on biomarkers does not exist at the moment. Metabolomics technique has a great potential for this task, because it can non-invasively perform a complete “metabolic fingerprint” of a disease and, in turn, potentially detect all its evolution steps. With this aim, we performed a serum metabolomics characterization of several NAFLD forms and then tested its accuracy confronting it with an independent cohort by mean of machine-learning models’ approach. Moreover, we performed a time-series analysis to verify if there were metabolomic profiles that change during the evolutionary steps of NAFLD.
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