Genetic variants are identified to increase risk of COVID-19 related mortality from UK Biobank data

Abstract

Background: The severity of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is highly heterogenous. Studies have reported that males and some ethnic groups are at increased risk of death from COVID-19, which implies that individual risk of death might be influenced by host genetic factors.

Methods: In this project, we consider the mortality as the trait of interest and perform a genome-wide association study (GWAS) of data for 1,778 infected cases (445 deaths, 25.03%) distributed by the UK Biobank. Traditional GWAS failed to identify any genome-wide significant genetic variants from this dataset. To enhance the power of GWAS and account for possible multi-loci interactions, we adopt the concept of super-variant for the detection of genetic factors. A discovery-validation procedure is used for verifying the potential associations.

Results: We find 8 super-variants that are consistently identified across multiple replications as susceptibility loci for COVID-19 mortality. The identified risk factors on Chromosomes 2, 6, 7, 8, 10, 16, and 17 contain genetic variants and genes related to cilia dysfunctions (DNAH7 and CLUAP1), cardiovascular diseases (DES and SPEG), thromboembolic disease (STXBP5), mitochondrial dysfunctions (TOMM7), and innate immune system (WSB1). It is noteworthy that DNAH7 has been reported recently as the most downregulated gene after infecting human bronchial epithelial cells with SARS-CoV2.

Conclusions: Eight genetic variants are identified to significantly increase risk of COVID-19 mortality among the patients with white British ancestry. These findings may provide timely evidence and clues for better understanding the molecular pathogenesis of COVID-19 and genetic basis of heterogeneous susceptibility, with potential impact on new therapeutic options.

Keywords: COVID-19; GWAS; Host genetic factors; Mortality; SARS-CoV2; UK Biobank.

Figure 1:

Survival curves of 8 identified super-variants in the complete dataset. The x-axis represents days since testing, and the y-axis represents the survival probability.

Figure 2:

Survival curves stratified by the number of super-variants in the complete dataset. The x-axis represents days since testing, and the y-axis represents the survival probability.

Figure 3:

Manhattan plot of traditional single SNP association analysis based on samples with white British ancestry only and controlled for gender and age. The red horizontal line corresponds to the commonly adopted genome-wide significant level at 5×10⁻⁸, and the blue horizontal line gives to the suggestive significant level at 1×10⁻⁵. Top SNPs above the suggestive line in each chromosome are annotated.