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

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. 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, = 6,054) and 1000Genome project were used to calculate and compare allelic frequencies (AF). A total of 74 SNPs, located in 10 genes: , -γ, , , , , , , and promoter, were identified. Analysis of Qatari genomes revealed significantly lower AF of risk variants linked to SARS-CoV-1 severity (, , , , and ) compared to that of 1000Genome and/or the EAS population (up to 25-fold change). Conversely, SNPs in , -γ, , and 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. 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.This work was supported by the Qatar University High Impact Grant (Grant Number: QUHI-BRC-20_21-1). OA was supported by a startup grant from the College of Health and Life Sciences, Hamad Bin Khalifa University. This work makes use of data generated by the Qatar Genome Programme (QGP) and Qatar Biobank (QBB), which are funded by Qatar Foundation for Education, Science and Community