Employing a systematic approach to biobanking and analyzing clinical and genetic data for advancing COVID-19 research
Academic Article
Publication Date:
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 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.
Iris type:
01.01 Articolo in rivista
Keywords:
covid-19; genetics; biobanking; clinical data; exome; snp; genotyping
List of contributors:
Stella, Alessandra; Biscarini, Filippo
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