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Machine Learning Based Prediction of COVID-19 Mortality Suggests Repositioning of Anticancer Drug for Treating Severe Cases.
Linden, Thomas; Hanses, Frank; Domingo-Fernández, Daniel; DeLong, Lauren Nicole; Kodamullil, Alpha Tom; Schneider, Jochen; Vehreschild, Maria J G T; Lanznaster, Julia; Ruethrich, Maria Madeleine; Borgmann, Stefan; Hower, Martin; Wille, Kai; Feldt, Torsten; Rieg, Siegbert; Hertenstein, Bernd; Wyen, Christoph; Roemmele, Christoph; Vehreschild, Jörg Janne; Jakob, Carolin E M; Stecher, Melanie; Kuzikov, Maria; Zaliani, Andrea; Fröhlich, Holger.
  • Linden T; Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Schloss Birlinghoven, 53757 Sankt Augustin, Germany.
  • Hanses F; University of Bonn, Bonn-Aachen International Center for IT, Friedrich Hirzebruch-Allee 6, 53115 Bonn, Germany.
  • Domingo-Fernández D; Emergency Department, University Hospital Regensburg, 93053 Regensburg, Germany.
  • DeLong LN; Department for Infectious Diseases and Infection Control, University Hospital Regensburg, Germany.
  • Kodamullil AT; Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Schloss Birlinghoven, 53757 Sankt Augustin, Germany.
  • Schneider J; Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Schloss Birlinghoven, 53757 Sankt Augustin, Germany.
  • Vehreschild MJGT; University of Bonn, Bonn-Aachen International Center for IT, Friedrich Hirzebruch-Allee 6, 53115 Bonn, Germany.
  • Lanznaster J; Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Schloss Birlinghoven, 53757 Sankt Augustin, Germany.
  • Ruethrich MM; Technical University of Munich, School of Medicine, University Hospital rechts der Isar, Department of Internal Medicine II, 81675 Munich, Germany.
  • Borgmann S; Department II of Internal Medicine, Infectious Diseases, University Hospital Frankfurt, Goethe University, 60590 Frankfurt, Germany.
  • Hower M; Department of Internal Medicine II, Hospital Passau, Innstraße 76, 94032 Passau, Germany.
  • Wille K; Institute for Infection Medicine and Hospital Hygiene, University Hospital Jena, 07743 Jena, Germany.
  • Feldt T; Department of Infectious Diseases and Infection Control, Hospital Ingolstadt, 85049 Ingolstadt, Germany.
  • Rieg S; Department of Pneumology, Infectious Diseases and Intensive Care, Klinikum Dortmund gGmbH, Hospital of University Witten / Herdecke, 44137 Dortmund, Germany.
  • Hertenstein B; University Clinic for Haematology, Oncology, Haemostaseology and Palliative Care, Johannes Wesling Medical Centre Minden, 32429 Minden, Germany.
  • Wyen C; Department of Gastroenterology, Hepatology and Infectious Diseases, University Hospital Düsseldorf, Medical Faculty of Heinrich Heine University Düsseldorf, Moorenstrasse 5, 40225 Düsseldorf, Germany.
  • Roemmele C; Department of Medicine II, University Hospital Freiburg, 79110 Freiburg, Germany.
  • Vehreschild JJ; Department of Medicine II, University Hospital Freiburg, 79110 Freiburg, Germany.
  • Jakob CEM; Christoph Wyen, Praxis am Ebertplatz Cologne, 50668 Cologne, Germany.
  • Stecher M; Internal Medicine III - Gastroenterology and Infectious Diseases, University Hospital Augsburg, 86156 Augsburg, Germany.
  • Kuzikov M; Department II of Internal Medicine, Infectious Diseases, University Hospital Frankfurt, Goethe University, 60590 Frankfurt, Germany.
  • Zaliani A; Department I for Internal Medicine, University Hospital of Cologne, University of Cologne, 50931 Cologne, Germany.
  • Fröhlich H; Fraunhofer Institute for Translational Medicine and Pharmacologie (ITMP), VolksparkLabs, Schnackenburgallee 114, 22535 Hamburg, Germany.
Artif Intell Life Sci ; 1: 100020, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1588542
Preprint
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ABSTRACT
Despite available vaccinations COVID-19 case numbers around the world are still growing, and effective medications against severe cases are lacking. In this work, we developed a machine learning model which predicts mortality for COVID-19 patients using data from the multi-center 'Lean European Open Survey on SARS-CoV-2-infected patients' (LEOSS) observational study (>100 active sites in Europe, primarily in Germany), resulting into an AUC of almost 80%. We showed that molecular mechanisms related to dementia, one of the relevant predictors in our model, intersect with those associated to COVID-19. Most notably, among these molecules was tyrosine kinase 2 (TYK2), a protein that has been patented as drug target in Alzheimer's Disease but also genetically associated with severe COVID-19 outcomes. We experimentally verified that anti-cancer drugs Sorafenib and Regorafenib showed a clear anti-cytopathic effect in Caco2 and VERO-E6 cells and can thus be regarded as potential treatments against COVID-19. Altogether, our work demonstrates that interpretation of machine learning based risk models can point towards drug targets and new treatment options, which are strongly needed for COVID-19.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study / Prognostic study Topics: Vaccines Language: English Journal: Artif Intell Life Sci Year: 2021 Document Type: Article Affiliation country: J.ailsci.2021.100020

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study / Prognostic study Topics: Vaccines Language: English Journal: Artif Intell Life Sci Year: 2021 Document Type: Article Affiliation country: J.ailsci.2021.100020