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    Relação entre gravidade da Covid-19 e perfil genético do SARS-CoV-2
    (Universidade Federal de São Paulo (UNIFESP), 2021) Silva, Luiz Claudio Santana Da [UNIFESP]; Diaz, Ricardo Sobhie [UNIFESP]; Universidade Federal de São Paulo
    In December 2019, SARS-CoV-2 was detected in Wuhan, China, and in March 2020, the World Health Organization (WHO) declared it a pandemic named COVID-19. The study of the molecular epidemiology of SARS-CoV-2 with the evaluation of the relationship of viral mutations and coinfections with infection severity can help elucidate the disease's pathophysiology. In this study, SARS-CoV-2 positive nasal swab samples collected in early 2020 were subjected to NGS RNA metagenomic methodology to characterize the complete SARS-CoV-2 genome and viral coinfections. Twenty-four samples collected in early 2020 were analyzed: i) Mild infection (n=8), ii) Moderate infection (n=9) and iii) Severe infection (n=7). Eleven patients (45.8%) are female, and 13 are male (54.2%) with a mean age of 54 years. Of the 24 samples analyzed, it was possible to classify the variants (Pangolin) of 22 samples, which belonged to the variants B.1.1.28 (68.18%), B.1.1.33 (27.27%), and B.1.1 (5.4%). Mutations in 52 genome positions were identified, with a prevalence of non-synonymous substitutions of 57.69% mainly detected in the ORF1a gene (55.17%), without association with the disease severity. There was no relationship in the selective regimes as inferred by the synonymous/ non-synonymous substitution and the severity of the disease. It was not possible to identify viral coinfections of clinical relevance and association between mutations and infection severity. It was possible to identify the D614G variant, characteristic of the B.1 strain, which became the globally dominant form in June 2020 due to its greater transmission capacity. There was a statistically significant difference between the mean age of the mild and severe groups, with older age relating to the severe form of the disease. Ongoing molecular characterization of viral and host genetic profiles can lead to a greater understanding of the factors influencing the severity of COVID-19.