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Employing a Systematic Approach to Biobanking and Analyzing Genetic and Clinical Data for Advancing COVID-19 Research (preprint)
medrxiv; 2020.
Preprint
in English
| medRxiv | ID: ppzbmed-10.1101.2020.07.24.20161307
ABSTRACT
Within the GEN-COVID Multicenter Study, biospecimens from more than 1,000 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 i) severe multisystemic failure with either thromboembolic or pancreatic variant; ii) cytokine storm type, either severe with liver involvement or moderate; iii) moderate heart type, either with or without liver damage; iv) moderate multisystemic involvement, either with or without liver damage; v) mild, either with or without hyposmia. GCB and GCPR are further linked to the GEN-COVID Genetic Data Repository (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.
Full text:
Available
Collection:
Preprints
Database:
medRxiv
Main subject:
COVID-19
Language:
English
Year:
2020
Document Type:
Preprint
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