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Using symptom-based case predictions to identify host genetic factors that contribute to COVID-19 susceptibility
Irene V van Blokland; Pauline Lanting; Anil PS Ori; Judith M Vonk; Robert CA Warmerdam; Johanna C Herkert; Floranne Boulogne; Annique Claringbould; Esteban A Lopera-Maya; Meike Bartels; Jouke-Jan Hottenga; Andrea Ganna; Juha Karjalainen; - Lifelines COVID-19 cohort study; - The COVID-19 Host Genetics Initiative; Caroline Hayward; Chloe Fawns-Ritchie; Archie Campbell; David Porteous; Elizabeth T Cirulli; Kelly M Schiabor Barrett; Stephen Riffle; Alexandre Bolze; Simon White; Francisco Tanudjaja; Xueqing Wang; Jimmy M Ramirez III; Yan Wei Lim; James T Lu; Nicole L Washington; Eco JC de Geus; Patrick Deelen; H Marike Boezen; Lude H Franke.
Afiliación
  • Irene V van Blokland; University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, The Netherlands and University of Groningen, University Medica
  • Pauline Lanting; University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, The Netherlands
  • Anil PS Ori; University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, The Netherlands and University of Groningen, University Medica
  • Judith M Vonk; University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, The Netherlands
  • Robert CA Warmerdam; University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, The Netherlands
  • Johanna C Herkert; University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, The Netherlands
  • Floranne Boulogne; University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, The Netherlands
  • Annique Claringbould; University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, The Netherlands and Structural Computational Biology unit, EMB
  • Esteban A Lopera-Maya; University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, The Netherlands
  • Meike Bartels; Department of Biological Psychology, FGB, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands and Amsterdam Public Health research institute, Amsterdam UMC
  • Jouke-Jan Hottenga; Department of Biological Psychology, FGB, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
  • Andrea Ganna; Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
  • Juha Karjalainen; Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland; Broad Institute of MIT and Harvard, Cambridge, MA, USA and Analytic and Tra
  • - Lifelines COVID-19 cohort study;
  • - The COVID-19 Host Genetics Initiative;
  • Caroline Hayward; MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
  • Chloe Fawns-Ritchie; Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ
  • Archie Campbell; Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
  • David Porteous; Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
  • Elizabeth T Cirulli; Helix, 101 S Ellsworth Ave Suite 350, San Mateo, California 94401, USA
  • Kelly M Schiabor Barrett; Helix, 101 S Ellsworth Ave Suite 350, San Mateo, California 94401, USA
  • Stephen Riffle; Helix, 101 S Ellsworth Ave Suite 350, San Mateo, California 94401, USA
  • Alexandre Bolze; Helix, 101 S Ellsworth Ave Suite 350, San Mateo, California 94401, USA
  • Simon White; Helix, 101 S Ellsworth Ave Suite 350, San Mateo, California 94401, USA
  • Francisco Tanudjaja; Helix, 101 S Ellsworth Ave Suite 350, San Mateo, California 94401, USA
  • Xueqing Wang; Helix, 101 S Ellsworth Ave Suite 350, San Mateo, California 94401, USA
  • Jimmy M Ramirez III; Helix, 101 S Ellsworth Ave Suite 350, San Mateo, California 94401, USA
  • Yan Wei Lim; Helix, 101 S Ellsworth Ave Suite 350, San Mateo, California 94401, USA
  • James T Lu; Helix, 101 S Ellsworth Ave Suite 350, San Mateo, California 94401, USA
  • Nicole L Washington; Helix, 101 S Ellsworth Ave Suite 350, San Mateo, California 94401, USA
  • Eco JC de Geus; Department of Biological Psychology, FGB, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands and Amsterdam Public Health research institute, Amsterdam UMC
  • Patrick Deelen; University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, The Netherlands and Department of Genetics, University Medical
  • H Marike Boezen; University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, The Netherlands
  • Lude H Franke; University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, The Netherlands
Preprint en En | PREPRINT-MEDRXIV | ID: ppmedrxiv-20177246
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ABSTRACT
Epidemiological and genetic studies on COVID-19 are currently hindered by inconsistent and limited testing policies to confirm SARS-CoV-2 infection. Recently, it was shown that it is possible to predict potential COVID-19 cases using cross-sectional self-reported disease-related symptoms. Using a previously reported COVID-19 prediction model, we show that it is possible to conduct a GWAS on predicted COVID-19, and this GWAS benefits from the larger sample size to provide new insights into the genetic susceptibility of the disease. Furthermore, we find suggestive evidence that genetic variants for other viral infectious diseases do not overlap with COVID-19 susceptibility and that severity of COVID-19 may have a different genetic architecture compared to COVID-19 susceptibility. Our findings demonstrate the added value of using self-reported symptom assessments to quickly monitor novel endemic viral outbreaks in a scenario of limited testing. Should there be another outbreak of a novel infectious disease, we recommend repeatedly collecting data of disease-related symptoms.
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Texto completo: 1 Colección: 09-preprints Base de datos: PREPRINT-MEDRXIV Tipo de estudio: Observational_studies / Prognostic_studies / Rct Idioma: En Año: 2020 Tipo del documento: Preprint
Texto completo
Añadir a Mi BVS
Imprimir
XML
Buscar en Google
Texto completo: 1 Colección: 09-preprints Base de datos: PREPRINT-MEDRXIV Tipo de estudio: Observational_studies / Prognostic_studies / Rct Idioma: En Año: 2020 Tipo del documento: Preprint