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Multicenter Study
. 2024 Feb 6;14(1):3000.
doi: 10.1038/s41598-024-53310-x.

A genome-wide association study for survival from a multi-centre European study identified variants associated with COVID-19 risk of death

Collaborators, Affiliations
Multicenter Study

A genome-wide association study for survival from a multi-centre European study identified variants associated with COVID-19 risk of death

Francesca Minnai et al. Sci Rep. .

Abstract

The clinical manifestations of SARS-CoV-2 infection vary widely among patients, from asymptomatic to life-threatening. Host genetics is one of the factors that contributes to this variability as previously reported by the COVID-19 Host Genetics Initiative (HGI), which identified sixteen loci associated with COVID-19 severity. Herein, we investigated the genetic determinants of COVID-19 mortality, by performing a case-only genome-wide survival analysis, 60 days after infection, of 3904 COVID-19 patients from the GEN-COVID and other European series (EGAS00001005304 study of the COVID-19 HGI). Using imputed genotype data, we carried out a survival analysis using the Cox model adjusted for age, age2, sex, series, time of infection, and the first ten principal components. We observed a genome-wide significant (P-value < 5.0 × 10-8) association of the rs117011822 variant, on chromosome 11, of rs7208524 on chromosome 17, approaching the genome-wide threshold (P-value = 5.19 × 10-8). A total of 113 variants were associated with survival at P-value < 1.0 × 10-5 and most of them regulated the expression of genes involved in immune response (e.g., CD300 and KLR genes), or in lung repair and function (e.g., FGF19 and CDH13). Overall, our results suggest that germline variants may modulate COVID-19 risk of death, possibly through the regulation of gene expression in immune response and lung function pathways.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Manhattan plot of the results of the GWAS for survival of COVID-19 patients. SNPs are plotted on the x-axis according to their genomic position (GChr 38, hg38 release), and P-values (− log10(P)) for their association with survival probability are plotted on the y-axis. The horizontal solid line represents the threshold of significance (P-value < 5.0 × 10−8), whereas the dashed one represents a suggestive threshold (P-value < 1.0 × 105). Names, hazard ratios and P-values of the two most significant SNPs are shown on top.
Figure 2
Figure 2
Zoomed plots of six loci associated with patient survival. SNPs are plotted on the x-axis according to their chromosome position (GChr 38, hg38 release), and P-values (− log10(P)) for their association with survival probability are plotted on the y-axis. The horizontal line represents the threshold of significance (P-value < 5.0 × 10−8). Below the x axis, the mapped genes are plotted (according to University of California Santa Cruz Genome Browser notation).
Figure 3
Figure 3
Kaplan–Meier survival curves for COVID-19 patients according to the genotype of the top significant variants (A) rs117011822 and (B) rs7208524. Black line represents patients homozygous for the major allele and grey line represents patients with at least one copy of the minor allele (according to the dominant model, patients with heterozygous genotype and homozygous for the minor allele were grouped together). Crosses denote censored samples. Numbers of patients at risk are shown below the plot. Log–rank test P‐value is shown.

References

    1. Long QX, Tang XJ, Shi QL, et al. Clinical and immunological assessment of asymptomatic SARS-CoV-2 infections. Nat. Med. 2020;26:1200–1204. doi: 10.1038/s41591-020-0965-6. - DOI - PubMed
    1. Guan W, Ni Z, Hu Y, et al. Clinical Characteristics of Coronavirus Disease 2019 in China. N. Engl. J. Med. 2020;382:1708–1720. doi: 10.1056/NEJMoa2002032. - DOI - PMC - PubMed
    1. White-Dzuro G, Gibson LE, Zazzeron L, et al. Multisystem effects of COVID-19: A concise review for practitioners. Postgrad. Med. 2020;133:1. - PMC - PubMed
    1. Michelozzi P, De’Donato F, Scortichini M, et al. Temporal dynamics in total excess mortality and COVID-19 deaths in Italian cities. BMC Public Health. 2020;20:1–8. doi: 10.1186/S12889-020-09335-8. - DOI - PMC - PubMed
    1. Rostami A, Sepidarkish M, Leeflang MMG, et al. SARS-CoV-2 seroprevalence worldwide: A systematic review and meta-analysis. Clin. Microbiol. Infect. 2021;27:331. doi: 10.1016/j.cmi.2020.10.020. - DOI - PMC - PubMed

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