Abstract
SARS-CoV-2 utilizes the angiotensin-converting enzyme 2 (ACE2) receptor and transmembrane serine protease (TMPRSS2) to infect human lung cells. Previous studies have suggested that different host ACE2 and TMPRSS2 genetic backgrounds might contribute to differences in the rate of SARS-CoV-2 infection or COVID-19 severity. Recent studies have also shown that variants in 15 genes related to type I interferon immunity to influenza virus might predispose patients toward life-threatening COVID-19 pneumonia. Other genes (SLC6A20, LZTFL1, CCR9, FYCO1, CXCR6, XCR1, IL6, CTSL, ABO, and FURIN) and HLA alleles have also been implicated in the response to infection with SARS-CoV-2. Currently, Brazil has recorded the third-highest number of COVID-19 cases worldwide. We aimed to investigate the genetic variation present in COVID-19-related genes in the Brazilian population. We analyzed 27 candidate genes and HLA alleles in 954 admixed Brazilian exomes. We used the information available in two public databases (http://www.bipmed.org and http://abraom.ib.usp.br/) and additional exomes from individuals born in southeast Brazil, the region of the country with the highest number of COVID-19 patients. Variant allele frequencies were compared with the 1000 Genomes Project phase 3 (1KGP) and gnomAD databases. We detected 395 nonsynonymous variants; of these, 325 were also found in the 1KGP and/or gnomAD. Six of these variants were previously reported to influence the rate of infection or clinical prognosis of COVID-19. The remaining 70 variants were identified exclusively in the Brazilian sample, with a mean allele frequency of 0.0025. In silico analysis revealed that seven of these variants are predicted to affect protein function. Furthermore, we identified HLA alleles previously associated with the COVID-19 response at loci DQB1 and DRB1. Our results showed genetic variability common to other populations and rare and ultrarare variants exclusively found in the Brazilian population. These findings might lead to differences in the rate of infection or response to infection by SARS-CoV-2 and should be further investigated in patients with this disease.
Highlights
Introduction COVID19 disease, caused by the coronavirus SARS-CoV-2, is currently a worldwide pandemic
The alternative allele frequency (AAF) of the admixed Brazilian sample follows the distribution of nonFinish Europeans (NFE)/Europeans (EUR), sub-Saharan Africans (AFR), and admixed Americans (AMR) in the gnomAD and 1KGP databases (Supplementary Table 2), we observed differences in the AAF of these common and rare variants in the admixed Brazilian sample compared to the gnomAD21 and/or 1KGP22 databases (Supplementary Table 2 and Supplementary Data 1)
70 variants are exclusive to the Brazilian sample, including 11 variants in genes related to type I interferon (INF) immunity to influenza virus[9], six in candidate genes for COVID-19 response identified by GWAS11, and five related to SARS-CoV-2 entry into lung cells and virus replication[2,10]
Summary
Introduction COVID19 disease, caused by the coronavirus SARS-CoV-2, is currently a worldwide pandemic. SARS-CoV-2 used its spike protein to enter human lung cells, a process primed by the host serine protease TMPRSS2, followed by Official journal of the Japan Society of Human Genetics. Specific variants in the genes ACE2 and TMPRSS2 have been reported among diverse populations worldwide, suggesting that different host genetic backgrounds might contribute to differences in COVID-19 infection and severity[2,10]. Ellinghaus et al.[11] performed a genome-wide association study (GWAS) including Italian and Spanish patients with confirmed COVID-19 and controls and identified six candidate genes associated with the COVID-19 response on chromosome (chr) 3p21.31 (SLC6A20, LZTFL1, FYCO1, CXCR6, XCR1, CCR9) and one on chr 9q34.2, the locus harboring genes encoding ABO blood group antigens. No evidence of association was found for the previously identified candidate genes potentially involved in the response to infection by SARSCoV-2, namely, ACE2, TMPRSS2, FURIN, and IL6
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