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.

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., Employing a systematic approach to biobanking and analyzing clinical and genetic data for advancing COVID-19 research, <<EUROPEAN JOURNAL OF HUMAN GENETICS>>, 2021; 29 (5): 745-759. [doi:10.1038/s41431-020-00793-7] [https://hdl.handle.net/10807/294296]

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

Sanguinetti, Maurizio;Masucci, Luca;
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.
2021
Inglese
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., Employing a systematic approach to biobanking and analyzing clinical and genetic data for advancing COVID-19 research, <<EUROPEAN JOURNAL OF HUMAN GENETICS>>, 2021; 29 (5): 745-759. [doi:10.1038/s41431-020-00793-7] [https://hdl.handle.net/10807/294296]
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