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. 2024 Dec 23;20(12):e1012786.
doi: 10.1371/journal.ppat.1012786. eCollection 2024 Dec.

Systematic assessment of COVID-19 host genetics using whole genome sequencing data

Axel Schmidt  1   2 Nicolas Casadei  3   4 Fabian Brand  5 German Demidov  4   6 Elaheh Vojgani  7 Ayda Abolhassani  8 Rana Aldisi  5 Guillaume Butler-Laporte  9   10 DeCOI host genetics groupT Madhusankha Alawathurage  1 Max Augustin  11   12   13 Robert Bals  14   15 Carla Bellinghausen  16 Marc Moritz Berger  17 Michael Bitzer  18   19 Christian Bode  20 Jannik Boos  1 Thorsten Brenner  17 Oliver A Cornely  11   12   13   21   22 Thomas Eggermann  23 Johanna Erber  24 Torsten Feldt  25 Christian Fuchsberger  26 Julien Gagneur  27   28   29 Siri Göpel  19   30 Tobias Haack  4 Helene Häberle  31 Frank Hanses  32   33 Julia Heggemann  1 Ute Hehr  34 Johannes C Hellmuth  35   36 Christian Herr  14 Anke Hinney  37 Per Hoffmann  1 Thomas Illig  38 Björn-Erik Ole Jensen  25 Verena Keitel  25 Sarah Kim-Hellmuth  39   40 Philipp Koehler  11   12   22 Ingo Kurth  23 Anna-Lisa Lanz  39 Eicke Latz  41 Clara Lehmann  11   12   13 Tom Luedde  25 Carlo Maj  42 Michael Mian  43 Abigail Miller  1 Maximilian Muenchhoff  35   44 Isabell Pink  45 Ulrike Protzer  46   47 Hana Rohn  48 Jan Rybniker  11   12   13 Federica Scaggiante  49 Anna Schaffeldt  23 Clemens Scherer  35   50 Maximilian Schieck  38 Susanne V Schmidt  41 Philipp Schommers  11   12   13 Christoph D Spinner  24   46 Maria J G T Vehreschild  51 Thirumalaisamy P Velavan  52   53 Sonja Volland  38 Sibylle Wilfling  34   54 Christof Winter  55   56   57   58 J Brent Richards  9   59   60   61   62   63 DeCOIAndré Heimbach  1   64 Kerstin Becker  7   65 Stephan Ossowski  4   6 Joachim L Schultze  66   67   68 Peter Nürnberg  7 Markus M Nöthen  1 Susanne Motameny  7   65 Michael Nothnagel  7 Olaf Riess  3   4 Eva C Schulte  1   8   47   69   70 Kerstin U Ludwig  1
Affiliations

Systematic assessment of COVID-19 host genetics using whole genome sequencing data

Axel Schmidt et al. PLoS Pathog. .

Abstract

Courses of SARS-CoV-2 infections are highly variable, ranging from asymptomatic to lethal COVID-19. Though research has shown that host genetic factors contribute to this variability, cohort-based joint analyses of variants from the entire allelic spectrum in individuals with confirmed SARS-CoV-2 infections are still lacking. Here, we present the results of whole genome sequencing in 1,220 mainly vaccine-naïve individuals with confirmed SARS-CoV-2 infection, including 827 hospitalized COVID-19 cases. We observed the presence of autosomal-recessive or likely compound heterozygous monogenic disorders in six individuals, all of which were hospitalized and significantly younger than the rest of the cohort. We did not observe any suggestive causal variants in or around the established risk gene TLR7. Burden testing in the largest population subgroup (i.e., Europeans) suggested nominal enrichments of rare variants in coding and non-coding regions of interferon immune response genes in the overall analysis and male subgroup. Case-control analyses of more common variants confirmed associations with previously reported risk loci, with the key locus at 3p21 reaching genome-wide significance. Polygenic scores accurately captured risk in an age-dependent manner. By enabling joint analyses of different types of variation across the entire frequency spectrum, this data will continue to contribute to the elucidation of COVID-19 etiology.

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Conflict of interest statement

JBR is CEO and founder of the company 5 Prime Sciences Inc, which offers analyses of human genetic data for the selection of drug targets. PK received grants or personal fees from Ambu GmbH, Gilead Sciences, Mundipharma Resarch Limited, Noxxon N.V. and Pfizer Pharma; he received honoraria for lectures from Akademie für Infektionsmedizin e.V., Ambu GmbH, Astellas Pharma, BioRad Laboratories Inc., Datamed GmbH, European Confederation of Medical Mycology, Gilead Sciences, GPR Academy Ruesselsheim, HELIOS Kliniken GmbH, Lahn-Dill-Kliniken GmbH, medupdate GmbH, MedMedia GmbH, MSD Sharp & Dohme GmbH, Pfizer Pharma GmbH, Scilink Comunicación Científica SC, streamedup! GmbH and University Hospital and LMU Munich and he participates in an Advisory Board from Ambu GmbH, Gilead Sciences, Mundipharma Resarch Limited and Pfizer Pharma. CDS received grants or personal fees from AstraZeneca, BBraun Melsungen, BioNtech, Gilead Sciences, Janssen-Cilag, Eli Lilly, Formycon, Pfizer, Roche, Apeiron, MSD, Cepheid, GSK, Molecular partners, SOBI, AbbVie, Synairgen, Shionogi and ViiV Healthcare. None of the funders did have any influence on study design or execution.

Figures

Fig 1
Fig 1. The DeCOI and the DeCOIEUR cohort.
(A) Individuals in the DeCOI cohort are classified into three phenotypes based on WHO definition. In addition, the cohort was subsetted to an unrelated cohort of the European population (DeCOIEUR) for association analyses. Based on the phenotypes, case-control definitions were established within DeCOIEUR. (B) Composition of the DeCOI cohort according to sex (inner circle), phenotype (color coded, middle circle), and population (outer circle). Shaded intervals in the outer circle represent non-European individuals. (C) Age distribution of individuals from the DeCOI cohort (n = 1,220) and the European subcohort (DeCOIEUR; n = 1,017), as stratified according to severity (color coded). In both subcohorts, the average age increases with disease course severity. Numbers indicate individuals in the respective group. (D) Phenotype distribution of individuals harboring ClinVar-annotated variants, as grouped according to disorder class. Autosomal recessive patterns of inheritance (AR/likely compound-heterozygous (CH), n = 6 diseases in six individuals) are displayed in the upper panel, and autosomal dominant inheritance patterns (AD, n = 79 diseases in 77 individuals) are displayed in the lower panel.
Fig 2
Fig 2. Effect sizes of nominally significant gene-set based tests in the DeCOIEUR cohort.
Gene-sets and the corresponding functional masks (S4 Table) that were tested are given on the y-axis. On the x-axis, effect size estimates (betas) are shown as markers with error bars indicating the standard errors of betas. Note that phenotypes are color-coded, and the markers outlined in black indicate analyses that only included males. Nominally significant findings were only obtained in the overall analyses and male sub-stratification. None was observed in female-only or age-stratified analyses. A list of genes that were included in each gene-set can be found in S3 Table.
Fig 3
Fig 3. Analysis of common variants within the DeCOIEUR cohort.
(A) and (B): Manhattan plots of association analyses of single variants (MAF>0.5%) in DeCOIEUR (n = 1,017 individuals), for phenotype Ex (272 severely affected individuals vs. 362 mild controls) and B1 (655 hospitalized individuals vs. 362 non-hospitalized controls), respectively. Genomic inflation factors were 1.04 (Ex) and 1.00 (B1). Among the strongest associations is the well-established risk locus at 3p21.31. Panels (C) and (D) show the distribution of individual polygenic risk scores (PRS) among cases (orange or yellow) and controls (gray) of Ex (C) or B1 (D) overall (density plots in the left parts) or when stratified according to age below or above 60 years (box plots in the right parts). The elements of the box plots correspond to the following values: thick line: median, box: 25th and 75th percentile, whiskers: largest / smallest value not further away from the box than 1.5 times the interquartile range, points: values outside of the range of the whiskers. *: p<0.05, ***: p<0.001; Wald test followed by Bonferroni correction. MAF: Minor Allele Frequency.

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