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 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: (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.
Employing a systematic approach to biobanking and analyzing clinical and genetic data for advancing COVID-19 research / Daga, S.; Fallerini, C.; Baldassarri, M.; Fava, F.; Valentino, F.; Doddato, G.; Benetti, E.; Furini, S.; Giliberti, A.; Tita, R.; Amitrano, S.; Bruttini, M.; Meloni, I.; Pinto, A. M.; Raimondi, F.; Stella, A.; Biscarini, F.; Picchiotti, N.; Gori, M.; Pinoli, P.; Ceri, S.; Sanarico, M.; Crawley, F. P.; Birolo, G.; Montagnani, F.; Di Sarno, L.; Tommasi, A.; Palmieri, M.; Croci, S.; Emiliozzi, A.; Fabbiani, M.; Rossetti, B.; Zanelli, G.; Bergantini, L.; D'Alessandro, M.; Cameli, P.; Bennet, D.; Anedda, F.; Marcantonio, S.; Scolletta, S.; Franchi, F.; Mazzei, M. A.; Guerrini, S.; Conticini, E.; Cantarini, L.; Frediani, B.; Tacconi, D.; Spertilli, C.; Feri, M.; Donati, A.; Scala, R.; Guidelli, L.; Spargi, G.; Corridi, M.; Nencioni, C.; Croci, L.; Caldarelli, G. P.; Spagnesi, M.; Piacentini, P.; Bandini, M.; Desanctis, E.; Cappelli, S.; Canaccini, A.; Verzuri, A.; Anemoli, V.; Ognibene, A.; Vaghi, M.; D'Arminio Monforte, A.; Merlini, E.; Mondelli, M. U.; Mantovani, S.; Ludovisi, S.; Girardis, M.; Venturelli, S.; Sita, M.; Cossarizza, A.; Antinori, A.; Vergori, A.; Rusconi, S.; Siano, M.; Gabrieli, A.; Riva, A.; Francisci, D.; Schiaroli, E.; Scotton, P. G.; Andretta, F.; Panese, S.; Scaggiante, R.; Gatti, F.; Parisi, S. G.; Castelli, F.; Quiros-Roldan, M. E.; Magro, P.; Zanella, I.; Della Monica, M.; Piscopo, C.; Capasso, M.; Russo, R.; Andolfo, I.; Iolascon, A.; Fiorentino, G.; Carella, M.; Castori, M.; Merla, G.; Aucella, F.; Raggi, P.; Marciano, C.; Perna, R.; Bassetti, M.; Di Biagio, A.; Sanguinetti, M.; Masucci, L.; Gabbi, C.; Valente, S.; Meloni, I.; Mencarelli, M. A.; Rizzo, C. L.; Bargagli, E.; Mandala, M.; Giorli, A.; Salerni, L.; Zucchi, P.; Parravicini, P.; Menatti, E.; Baratti, S.; Trotta, T.; Giannattasio, F.; Coiro, G.; Lena, F.; Coviello, D. A.; Mussini, C.; Bosio, G.; Mancarella, S.; Tavecchia, L.; Renieri, A.; Mari, F.; Frullanti, E.. - In: EUROPEAN JOURNAL OF HUMAN GENETICS. - ISSN 1018-4813. - 29:5(2021), pp. 745-759. [10.1038/s41431-020-00793-7]
Employing a systematic approach to biobanking and analyzing clinical and genetic data for advancing COVID-19 research
Fava F.;Amitrano S.;Stella A.;Gori M.;Zanelli G.;Girardis M.;Venturelli S.;Sita M.;Cossarizza A.;Riva A.;Andretta F.;Gatti F.;Carella M.;Mussini C.;
2021
Abstract
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 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: (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.
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