Host Genetic Variants Potentially Associated With SARS-CoV-2: A Multi-Population Analysis - Smatti, Maria K.; Al-Sarraj, Yasser A.; Albagha, Omar; Yassine, Hadi M. (Frontiers in Genetics, 2020)
Background: Clinical outcomes of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 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. Given the similarity between SARS-CoV-1 and SARS-CoV-2, we aimed at exploring the frequency of SARS-CoV-1 associated SNPs in different populations. Methods: We extracted SARS-CoV-1 associated SNPs from previous genome wide association studies (GWAS) and expression quantitative trait loci (eQTLs) databases. Sequences from Qatar Genome Programme (QGP, n=6054) 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 6-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 9-fold decrease compared to other populations. Conclusion: 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.