Genetic association at the genomic level (genomewide association study - GWAS), requencing by NGS (whole exome sequencing) and gene expression studies to identify the main ones hereditary genetic determinants of predisposition to the development of SARS (symptomatic pathology associated with development of insufficiency respiratory disease of any degree) in Italian subjects affected by SARSCoV-2.

Lombardy region in Northern Italy is now in the midst of an outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 (COVID-19) . The COVID-19 epidemic situation needs little introduction and represent a global world-wide emergency with mortality rates rapidly increasing in Europe and the US. Evidence is accumulating that the majority of individuals infected by SARS-CoV-2 are asymptomatic and the major source of viral spread 3, and that a considerable fraction of these has active viral replication 4,5. Furthermore, disease behavior is variable, with the majority of patients experiencing only mild symptoms or no symptoms at all. Some patients develop severe pulmonary affection, with aggressive and extensive inflammatory destruction of lung parenchyma and associated inflammatory responses and superinfections, driving large fractions of the COVID-19 related mortality. What exactly drives this development of severe lung disease remains unknown, but old age, obesity, diabetes and other co-morbidities increase the risk, while the role played by specific medications is still uncertain. Variation in virus genetics and patient immunology are also likely involved. As to the latter point, the investigators hypothesize that host genetics may play a role in determining development of severe lung disease in SARS-CoV-2 infection. Genome-wide association studies (GWAS) have been applied to decipher the genetic predisposition in thousands of disease traits since the study design was invented in 2005. The genetic signals detected vary from very strong effects that can be detected in a few hundred individuals, to very weak effects requiring cohorts of tens of thousands for detection. By 2020, the study design is now a robust, off-the-shelf, easyto-perform industry-standard screening tool for genetic predisposition, even available through "consumer genetics" online-based companies. The study design is simple: testing for genetic variants throughout the genome (single nucleotide polymorphisms, SNPs) using SNP microarrays, comparing their frequencies in patients versus controls (or across other variables). For inflammatory phenotypes in particular, GWAS has proven an efficient tool, delineating hundreds of susceptibility loci in many conditions, some of which has provided novel and surprising disease insights. GWAS serve two purposes. Most importantly they allow to determine biological factors involved in disease development, thus potentially guiding drug development and therapy. This would be particularly relevant during the current COVID-19 emergency, when hundreds of trials have begun and there is an urgent need to prioritize well-conducted collaborative studies based on robust pathophysiological data. Secondly, and increasingly popular, they allow for the calculation of a "polygenic risk score" to predict disease development. Both aspects appear crucial to clarify for COVID-19 lung disease: (a) are there genetic signatures suggesting which biological mechanisms are involved that may suggest relevant therapeutic approaches, and (b) can we predict those at risk (or those with very low risk)?

Inclusion Criteria:

Cohort 1 inclusion criteria:

• SARS-CoV-2 positive patients (no age limit) with severe pulmonary compromise, hospitalized with failure respiratory that requires support of any kind
• Signature of informed consent

Cohort 2 inclusion criteria:

• Blood donors (18-70 years old) who donated between 24/02/2020 and 31/12/2021
• exposure to the SARS-CoV-2 virus confirmed by viremia positive and presence of IgG/IgM
• Signature of informed consent

Cohort 3 inclusion criteria:

Healthy controls available from previous studies (n=5,000, ages 14-80 years), whose data are already available for genetic association analyses within the Kiel University database.