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.; Renieri A.; Mari F.; Frullanti E.; GEN-COVID Multicenter Study; 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.; Mandalà 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.

doi:10.1038/s41431-020-00793-7

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., et al. (2021). Employing a systematic approach to biobanking and analyzing clinical and genetic data for advancing COVID-19 research. EUROPEAN JOURNAL OF HUMAN GENETICS, 29(5), 745-759 [10.1038/s41431-020-00793-7].