Cargando…

Employing a systematic approach to biobanking and analyzing clinical and genetic data for advancing COVID-19 research

Within the GEN-COVID Multicenter Study, biospecimens from more than 1000 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...

Descripción completa

Detalles Bibliográficos
Autores principales: Daga, Sergio, Fallerini, Chiara, Baldassarri, Margherita, Fava, Francesca, Valentino, Floriana, Doddato, Gabriella, Benetti, Elisa, Furini, Simone, Giliberti, Annarita, Tita, Rossella, Amitrano, Sara, Bruttini, Mirella, Meloni, Ilaria, Pinto, Anna Maria, Raimondi, Francesco, Stella, Alessandra, Biscarini, Filippo, Picchiotti, Nicola, Gori, Marco, Pinoli, Pietro, Ceri, Stefano, Sanarico, Maurizio, Crawley, Francis P., Birolo, Giovanni, Renieri, Alessandra, Mari, Francesca, Frullanti, Elisa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7811682/
https://www.ncbi.nlm.nih.gov/pubmed/33456056
http://dx.doi.org/10.1038/s41431-020-00793-7
_version_ 1783637532312862720
author Daga, Sergio
Fallerini, Chiara
Baldassarri, Margherita
Fava, Francesca
Valentino, Floriana
Doddato, Gabriella
Benetti, Elisa
Furini, Simone
Giliberti, Annarita
Tita, Rossella
Amitrano, Sara
Bruttini, Mirella
Meloni, Ilaria
Pinto, Anna Maria
Raimondi, Francesco
Stella, Alessandra
Biscarini, Filippo
Picchiotti, Nicola
Gori, Marco
Pinoli, Pietro
Ceri, Stefano
Sanarico, Maurizio
Crawley, Francis P.
Birolo, Giovanni
Renieri, Alessandra
Mari, Francesca
Frullanti, Elisa
author_facet Daga, Sergio
Fallerini, Chiara
Baldassarri, Margherita
Fava, Francesca
Valentino, Floriana
Doddato, Gabriella
Benetti, Elisa
Furini, Simone
Giliberti, Annarita
Tita, Rossella
Amitrano, Sara
Bruttini, Mirella
Meloni, Ilaria
Pinto, Anna Maria
Raimondi, Francesco
Stella, Alessandra
Biscarini, Filippo
Picchiotti, Nicola
Gori, Marco
Pinoli, Pietro
Ceri, Stefano
Sanarico, Maurizio
Crawley, Francis P.
Birolo, Giovanni
Renieri, Alessandra
Mari, Francesca
Frullanti, Elisa
author_sort Daga, Sergio
collection PubMed
description Within the GEN-COVID Multicenter Study, biospecimens from more than 1000 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 O(2) 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: (1) severe multisystemic failure with either thromboembolic or pancreatic variant; (2) cytokine storm type, either severe with liver involvement or moderate; (3) moderate heart type, either with or without liver damage; (4) moderate multisystemic involvement, either with or without liver damage; (5) mild, either with or without hyposmia. GCB and GCPR are further linked to the 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.
format Online
Article
Text
id pubmed-7811682
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Springer International Publishing
record_format MEDLINE/PubMed
spelling pubmed-78116822021-01-18 Employing a systematic approach to biobanking and analyzing clinical and genetic data for advancing COVID-19 research Daga, Sergio Fallerini, Chiara Baldassarri, Margherita Fava, Francesca Valentino, Floriana Doddato, Gabriella Benetti, Elisa Furini, Simone Giliberti, Annarita Tita, Rossella Amitrano, Sara Bruttini, Mirella Meloni, Ilaria Pinto, Anna Maria Raimondi, Francesco Stella, Alessandra Biscarini, Filippo Picchiotti, Nicola Gori, Marco Pinoli, Pietro Ceri, Stefano Sanarico, Maurizio Crawley, Francis P. Birolo, Giovanni Renieri, Alessandra Mari, Francesca Frullanti, Elisa Eur J Hum Genet Article Within the GEN-COVID Multicenter Study, biospecimens from more than 1000 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 O(2) 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: (1) severe multisystemic failure with either thromboembolic or pancreatic variant; (2) cytokine storm type, either severe with liver involvement or moderate; (3) moderate heart type, either with or without liver damage; (4) moderate multisystemic involvement, either with or without liver damage; (5) mild, either with or without hyposmia. GCB and GCPR are further linked to the 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. Springer International Publishing 2021-01-17 2021-05 /pmc/articles/PMC7811682/ /pubmed/33456056 http://dx.doi.org/10.1038/s41431-020-00793-7 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Daga, Sergio
Fallerini, Chiara
Baldassarri, Margherita
Fava, Francesca
Valentino, Floriana
Doddato, Gabriella
Benetti, Elisa
Furini, Simone
Giliberti, Annarita
Tita, Rossella
Amitrano, Sara
Bruttini, Mirella
Meloni, Ilaria
Pinto, Anna Maria
Raimondi, Francesco
Stella, Alessandra
Biscarini, Filippo
Picchiotti, Nicola
Gori, Marco
Pinoli, Pietro
Ceri, Stefano
Sanarico, Maurizio
Crawley, Francis P.
Birolo, Giovanni
Renieri, Alessandra
Mari, Francesca
Frullanti, Elisa
Employing a systematic approach to biobanking and analyzing clinical and genetic data for advancing COVID-19 research
title Employing a systematic approach to biobanking and analyzing clinical and genetic data for advancing COVID-19 research
title_full Employing a systematic approach to biobanking and analyzing clinical and genetic data for advancing COVID-19 research
title_fullStr Employing a systematic approach to biobanking and analyzing clinical and genetic data for advancing COVID-19 research
title_full_unstemmed Employing a systematic approach to biobanking and analyzing clinical and genetic data for advancing COVID-19 research
title_short Employing a systematic approach to biobanking and analyzing clinical and genetic data for advancing COVID-19 research
title_sort employing a systematic approach to biobanking and analyzing clinical and genetic data for advancing covid-19 research
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7811682/
https://www.ncbi.nlm.nih.gov/pubmed/33456056
http://dx.doi.org/10.1038/s41431-020-00793-7
work_keys_str_mv AT dagasergio employingasystematicapproachtobiobankingandanalyzingclinicalandgeneticdataforadvancingcovid19research
AT fallerinichiara employingasystematicapproachtobiobankingandanalyzingclinicalandgeneticdataforadvancingcovid19research
AT baldassarrimargherita employingasystematicapproachtobiobankingandanalyzingclinicalandgeneticdataforadvancingcovid19research
AT favafrancesca employingasystematicapproachtobiobankingandanalyzingclinicalandgeneticdataforadvancingcovid19research
AT valentinofloriana employingasystematicapproachtobiobankingandanalyzingclinicalandgeneticdataforadvancingcovid19research
AT doddatogabriella employingasystematicapproachtobiobankingandanalyzingclinicalandgeneticdataforadvancingcovid19research
AT benettielisa employingasystematicapproachtobiobankingandanalyzingclinicalandgeneticdataforadvancingcovid19research
AT furinisimone employingasystematicapproachtobiobankingandanalyzingclinicalandgeneticdataforadvancingcovid19research
AT gilibertiannarita employingasystematicapproachtobiobankingandanalyzingclinicalandgeneticdataforadvancingcovid19research
AT titarossella employingasystematicapproachtobiobankingandanalyzingclinicalandgeneticdataforadvancingcovid19research
AT amitranosara employingasystematicapproachtobiobankingandanalyzingclinicalandgeneticdataforadvancingcovid19research
AT bruttinimirella employingasystematicapproachtobiobankingandanalyzingclinicalandgeneticdataforadvancingcovid19research
AT meloniilaria employingasystematicapproachtobiobankingandanalyzingclinicalandgeneticdataforadvancingcovid19research
AT pintoannamaria employingasystematicapproachtobiobankingandanalyzingclinicalandgeneticdataforadvancingcovid19research
AT raimondifrancesco employingasystematicapproachtobiobankingandanalyzingclinicalandgeneticdataforadvancingcovid19research
AT stellaalessandra employingasystematicapproachtobiobankingandanalyzingclinicalandgeneticdataforadvancingcovid19research
AT biscarinifilippo employingasystematicapproachtobiobankingandanalyzingclinicalandgeneticdataforadvancingcovid19research
AT picchiottinicola employingasystematicapproachtobiobankingandanalyzingclinicalandgeneticdataforadvancingcovid19research
AT gorimarco employingasystematicapproachtobiobankingandanalyzingclinicalandgeneticdataforadvancingcovid19research
AT pinolipietro employingasystematicapproachtobiobankingandanalyzingclinicalandgeneticdataforadvancingcovid19research
AT ceristefano employingasystematicapproachtobiobankingandanalyzingclinicalandgeneticdataforadvancingcovid19research
AT sanaricomaurizio employingasystematicapproachtobiobankingandanalyzingclinicalandgeneticdataforadvancingcovid19research
AT crawleyfrancisp employingasystematicapproachtobiobankingandanalyzingclinicalandgeneticdataforadvancingcovid19research
AT birologiovanni employingasystematicapproachtobiobankingandanalyzingclinicalandgeneticdataforadvancingcovid19research
AT employingasystematicapproachtobiobankingandanalyzingclinicalandgeneticdataforadvancingcovid19research
AT renierialessandra employingasystematicapproachtobiobankingandanalyzingclinicalandgeneticdataforadvancingcovid19research
AT marifrancesca employingasystematicapproachtobiobankingandanalyzingclinicalandgeneticdataforadvancingcovid19research
AT frullantielisa employingasystematicapproachtobiobankingandanalyzingclinicalandgeneticdataforadvancingcovid19research