Virtual genetic diagnosis for familial hypercholesterolemia powered by machine learning.

Journal: European journal of preventive cardiology
PMID: 32019371

Abstract

AIMS: Familial hypercholesterolemia (FH) is the most common genetic disorder of lipid metabolism. The gold standard for FH diagnosis is genetic testing, available, however, only in selected university hospitals. Clinical scores - for example, the Dutch Lipid Score - are often employed as alternative, more accessible, albeit less accurate FH diagnostic tools. The aim of this study is to obtain a more reliable approach to FH diagnosis by a "virtual" genetic test using machine-learning approaches.

Authors

  • Ana Pina
    CEDOC - Centro de Estudos de Doenças Crónicas, NOVA Medical School/Faculdade de Ciências Médicas, Universidade Nova de Lisboa, Portugal.
  • Saga Helgadottir
    Department of Physics, University of Gothenburg, Sweden.
  • Rosellina Margherita Mancina
    Department of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, Wallenberg Laboratory, University of Gothenburg, Sweden.
  • Chiara Pavanello
    Centro E. Grossi Paoletti, Dipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Italy.
  • Carlo Pirazzi
    Department of Cardiology, Sahlgrenska University Hospital, Sweden.
  • Tiziana Montalcini
    Clinical Nutrition Unit, Department of Medical and Surgical Sciences, University Magna Graecia, Italy.
  • Roberto Henriques
    NOVA Information Management School, Campus de Campolide, Portugal.
  • Laura Calabresi
    Centro E. Grossi Paoletti, Dipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Italy.
  • Olov Wiklund
    Department of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, Wallenberg Laboratory, University of Gothenburg, Sweden.
  • M Paula Macedo
    CEDOC - Centro de Estudos de Doenças Crónicas, NOVA Medical School/Faculdade de Ciências Médicas, Universidade Nova de Lisboa, Portugal.
  • Luca Valenti
    Translational Medicine, Department of Transfusion Medicine and Hematology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico and Department of Pathophysiology and Transplantation, Università degli Studi di Milano, Italy.
  • Giovanni Volpe
    Department of Physics, University of Gothenburg, Sweden.
  • Stefano Romeo
    Department of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, Wallenberg Laboratory, University of Gothenburg, Sweden.

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