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Updated: Jun 14, 2025

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
Published on: January 16, 2019
Genetic variants regulating the immune response improve the prediction of COVID-19 severity provided by clinical
Pablo Delgado-Wicke1, Sara Fernández de Córdoba-Oñate2,3,4, Emilia Roy-Vallejo5
1Molecular Biology Unit, Hospital Universitario La Princesa and Health Research Institute (IIS-Princesa), Madrid, Spain.
Abstract:
The characteristics of the host are crucial in the final outcome of COVID-19. Herein, the influence of genetic and clinical variants in COVID-19 severity was investigated in a total of 1350 patients. Twenty-one single nucleotide polymorphisms of genes involved in SARS-CoV-2 sensing as Toll-like-Receptor 7, antiviral immunity as the type I interferon signalling pathway (TYK2, STAT1, STAT4, OAS1, SOCS) and the vasoactive intestinal peptide and its receptors (VIP/VIPR1,2) were studied. To analyse the association between polymorphisms and severity, a model adjusted by age, sex and different comorbidities was generated by ordinal logistic regression. The genotypes rs8108236-AA (OR 0.12 [95% CI 0.02-0.53]; p = 0.007) and rs280519-AG (OR 0.74 [95% CI 0.56-0.99]; p = 0.03) in TYK2, and rs688136-CC (OR 0.7 [95% CI 0.5-0.99]; p = 0.046) in VIP, were associated with lower severity; in contrast, rs3853839-GG in TLR7 (OR 1.44 [95% CI 1.07-1.94]; p = 0.016), rs280500-AG (OR 1.33 [95% CI 0.97-1.82]; p = 0.078) in TYK2 and rs1131454-AA in OAS1 (OR 1.29 [95% CI 0.95-1.75]; p = 0.110) were associated with higher severity. Therefore, these variants could influence the risk of severe COVID-19.
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