Your browser doesn't support javascript.
loading
Employing a Systematic Approach to Biobanking and Analyzing Genetic and Clinical Data for Advancing COVID-19 Research
Sergio Daga; Chiara Fallerini; Margherita Baldassarri; Francesca Fava; Floriana Valentino; Gabriella Doddato; Elisa Benetti; Simone Furini; Annarita Giliberti; Rossella Tita; Sara Amitrano; Mirella Bruttini; Ilaria Meloni; Anna Maria Pinto; Francesco Raimondi; Alessandra Stella; Filippo Biscarini; Nicola Picchiotti; Marco Gori; Pietro Pinoli; Stefano Ceri; Maurizio Sanarico; Francis P. Crawley; - GEN-COVID Multicenter Study; Alessandra Renieri; Francesca Mari; Elisa Frullanti.
Afiliación
  • Sergio Daga; Medical Genetics, University of Siena, Italy
  • Chiara Fallerini; Medical Genetics, University of Siena, Italy
  • Margherita Baldassarri; Medical Genetics, University of Siena, Italy
  • Francesca Fava; Medical Genetics, University of Siena, Italy; Genetica Medica, Azienda Ospedaliero-Universitaria Senese, Italy
  • Floriana Valentino; Medical Genetics, University of Siena, Italy
  • Gabriella Doddato; Medical Genetics, University of Siena, Italy
  • Elisa Benetti; Department of Medical Biotechnologies, University of Siena, Italy
  • Simone Furini; Department of Medical Biotechnologies, University of Siena, Italy
  • Annarita Giliberti; Medical Genetics, University of Siena, Italy
  • Rossella Tita; Genetica Medica, Azienda Ospedaliero-Universitaria Senese, Italy
  • Sara Amitrano; Genetica Medica, Azienda Ospedaliero-Universitaria Senese, Italy
  • Mirella Bruttini; Medical Genetics, University of Siena, Italy; Genetica Medica, Azienda Ospedaliero-Universitaria Senese, Italy
  • Ilaria Meloni; Medical Genetics, University of Siena, Italy
  • Anna Maria Pinto; Genetica Medica, Azienda Ospedaliero-Universitaria Senese, Italy
  • Francesco Raimondi; Scuola Normale Superiore, Pisa, Italy
  • Alessandra Stella; CNR-Consiglio Nazionale delle Ricerche, Istituto di Biologia e Biotecnologia Agraria (IBBA), Milano, Italy
  • Filippo Biscarini; CNR-Consiglio Nazionale delle Ricerche, Istituto di Biologia e Biotecnologia Agraria (IBBA), Milano, Italy
  • Nicola Picchiotti; University of Siena, DIISM- SAILAB, Siena, Italy; Department of Mathematics, University of Pavia, Pavia, Italy
  • Marco Gori; University of Siena, DIISM - SAILAB, Siena, Italy; Universite Cote d Azur, Inria, CNRS, I3S, Maasai
  • Pietro Pinoli; Department of Electronics, Information and Bioengineering (DEIB), Politecnico di Milano, Milano, Italy
  • Stefano Ceri; Department of Electronics, Information and Bioengineering (DEIB), Politecnico di Milano, Milano, Italy
  • Maurizio Sanarico; Independent Data Scientist, Milan, Italy
  • Francis P. Crawley; Good Clinical Practice Alliance-Europe (GCPA) and Strategic Initiative for Developing Capacity in Ethical Review-Europe (SIDCER), Brussels, Belgium.
  • - GEN-COVID Multicenter Study;
  • Alessandra Renieri; Medical Genetics, University of Siena, Italy; Genetica Medica, Azienda Ospedaliero-Universitaria Senese, Italy
  • Francesca Mari; Medical Genetics, University of Siena, Italy; Genetica Medica, Azienda Ospedaliero-Universitaria Senese, Italy
  • Elisa Frullanti; Medical Genetics, University of Siena, Italy
Preprint en En | PREPRINT-MEDRXIV | ID: ppmedrxiv-20161307
ABSTRACT
Within the GEN-COVID Multicenter Study, biospecimens from more than 1,000 SARS-CoV-2-positive individuals have thus far been collected in the GEN-COVID Biobank (GCB). Sample types include whole blood, plasma, serum, leukocytes, and DNA. The GCB links samples to detailed clinical data available in the GEN-COVID Patient Registry (GCPR). It includes hospitalized patients (74.25%), broken down into intubated, treated by CPAP-biPAP, treated with O2 supplementation, and without respiratory support (9.5%, 18.4%, 31.55% and 14.8, respectively); and non-hospitalized subjects (25.75%), either pauci- or asymptomatic. More than 150 clinical patient-level data fields have been collected and binarized for further statistics according to the organs/systems primarily affected by COVID-19 heart, liver, pancreas, kidney, chemosensors, innate or adaptive immunity, and clotting system. Hierarchical Clustering analysis identified five main clinical categories i) severe multisystemic failure with either thromboembolic or pancreatic variant; ii) cytokine storm type, either severe with liver involvement or moderate; iii) moderate heart type, either with or without liver damage; iv) moderate multisystemic involvement, either with or without liver damage; v) mild, either with or without hyposmia. GCB and GCPR are further linked to the GEN-COVID Genetic Data Repository (GCGDR), which includes data from Whole Exome Sequencing and high-density SNP genotyping. The data are available for sharing through the Network for Italian Genomes, found within the COVID-19 dedicated section. The study objective is to systematize this comprehensive data collection and begin identifying multi-organ involvement in COVID-19, defining genetic parameters for infection susceptibility within the population and mapping genetically COVID-19 severity and clinical complexity among patients.
Licencia
cc_by_nc_nd
Texto completo: 1 Colección: 09-preprints Base de datos: PREPRINT-MEDRXIV Tipo de estudio: Experimental_studies / Prognostic_studies / Systematic_reviews Idioma: En Año: 2020 Tipo del documento: Preprint
Texto completo: 1 Colección: 09-preprints Base de datos: PREPRINT-MEDRXIV Tipo de estudio: Experimental_studies / Prognostic_studies / Systematic_reviews Idioma: En Año: 2020 Tipo del documento: Preprint