Host Genetic Variants Potentially Associated With SARS-CoV-2: A Multi-Population Analysis

Abstract

Background Clinical outcomes of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) showed enormous inter-individual and inter-population differences, possibly due to host genetics differences. Earlier studies identified single nucleotide polymorphisms (SNPs) associated with SARS-CoV-1 in Eastern Asian (EAS) populations. In this report, we aimed at exploring the frequency of a set of genetic polymorphisms that could affect SARS-CoV-2 susceptibility or severity, including those that were previously associated with SARS-CoV-1. Methods We extracted the list of SNPs that could potentially modulate SARS-CoV-2 from the genome wide association studies (GWAS) on SARS-CoV-1 and other viruses. We also collected the expression data of these SNPs from the expression quantitative trait loci (eQTLs) databases. Sequences from Qatar Genome Programme (QGP, n = 6,054) and 1000Genome project were used to calculate and compare allelic frequencies (AF). Results A total of 74 SNPs, located in 10 genes: ICAM3 , IFN -γ, CCL2 , CCL5 , AHSG, MBL , Furin , TMPRSS2 , IL4 , and CD209 promoter, were identified. Analysis of Qatari genomes revealed significantly lower AF of risk variants linked to SARS-CoV-1 severity ( CCL2 , MBL , CCL5 , AHSG , and IL4 ) compared to that of 1000Genome and/or the EAS population (up to 25-fold change). Conversely, SNPs in TMPRSS2 , IFN -γ, ICAM3 , and Furin were more common among Qataris (average 2-fold change). Inter-population analysis showed that the distribution of risk alleles among Europeans differs substantially from Africans and EASs. Remarkably, Africans seem to carry extremely lower frequencies of SARS-CoV-1 susceptibility alleles, reaching to 32-fold decrease compared to other populations. Conclusion Multiple genetic variants, which could potentially modulate SARS-CoV-2 infection, are significantly variable between populations, with the lowest frequency observed among Africans. Our results highlight the importance of exploring population genetics to understand and predict COVID-19 outcomes. Indeed, further studies are needed to validate these findings as well as to identify new genetic determinants linked to SARS-CoV-2.

Dipeptidylpeptidase-4 levels and DPP4 gene polymorphisms in patients with COVID-19. Association with disease and with severity

“…It has been suggested that the variability in SARS-CoV-2 infection prevalence and COVID-19 mortality in different populations depend largely on individual variations in genes that encode proteins relevant in viral pathogenicity mechanisms. Bioinformatics, case-control and GWAS studies have shown polymorphisms located in several genes as possible susceptibility markers for COVID-19 infection and severity in several populations [ [47] , [48] , [49] , [50] , [51] ]. Located in the 2p24.3 region, the gene that encodes DPP4 is polymorphic and some of its SNPs have been associated not only with the risk of developing some diseases, such as myocardial infarction [ 18 ], rheumatoid arthritis [ 52 ], and T2DM [ 17 ], but also with variations in levels of DPP4 [ 17 ] and apolipoprotein B [ 53 ].…”

Factors for COVID-19 Infection that Govern the Severity of Illness

“…These events are absent in asymptomatic or patients with milder symptoms. Studies also state that certain immune responsive genes like AHSG, CCL5, CCL2, IL4 variants have a role in disease severity [143].…”

Transmembrane serine protease 2 Polymorphisms and Susceptibility to Severe Acute Respiratory Syndrome Coronavirus Type 2 Infection: A German Case-Control Study

“…Single nucleotide polymorphisms (SNPs) in the gene TMPRSS2 (chromosome 21q22.3, reverse strand) have been associated with susceptibility to and severity of H1N1 or H1N9 influenza A virus infections ( Cheng et al, 2015 ). Currently, SNPs altering gene expression or protein function are frequently discussed in the light of Coronavirus disease 2019 (COVID-19) in literature reviews and in in silico analyses utilizing genotyping data from existing databases ( Asselta et al, 2020 ; Barash et al, 2020 ; Fujikura and Uesaka, 2020 ; Ghafouri-Fard et al, 2020 ; Hou et al, 2020 ; Paniri et al, 2020 ; Russo et al, 2020 ; Senapati et al, 2020 ; Singh et al, 2020 ; Smatti et al, 2020 ; Vargas-Alarcón et al, 2020 ; Zarubin et al, 2020 ). Three variants, rs2070788, rs383510, and rs12329760, seem to be of particular interest based on preliminary work in the context of other virus infections.…”