Genetic variants regulating the immune response improve the prediction of COVID-19 severity provided by clinical variables

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.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2024-09-05
DOI
https://doi.org/10.1038/s41598-024-71476-2
Citations
11
Primary Topic
COVID-19 Clinical Research Studies
Type
article
Field-Weighted Citation Impact
4.28

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Genetic variants regulating the immune response improve the prediction of COVID-19 severity provided by clinical variables

Gonzalo Villapalos‐García, Francisco Abad‐Santos, Isidoro González‐Álvaro, Diego Rodríguez et al.
11 citations
Scientific Reports
COVID-19 Clinical Research Studies
4.28
article

Genetic variants regulating the immune response improve the prediction of COVID-19 severity provided by clinical variables

Gonzalo Villapalos‐García, Francisco Abad‐Santos, Isidoro González‐Álvaro, Diego Rodríguez, Sara Fernández de Córdoba‐Oñate, Pablo Zubiaur, Elena Fernández‐Ruiz, Amalia Lamana, Ana Marcos‐Jiménez, Rosa P. Gomariz, Estíbaliz Alegría‐Carrasco, Cecilia Muñoz‐Calleja, Emilia Roy‐Vallejo, Núria Montés, Pablo Delgado‐Wicke, José María Galván‐Román, Rosario García‐Vicuña, Paula Díaz-Fernández, Rosa Carracedo-Rodríguez, Ana Nicolao-Gómez, Almudena Villa-Martí, Laura Rabes-Rodríguez, Marta Sanz-Alba, Carlos Rodríguez-Franco, Jesús Álvarez-Rodríguez, Ignacio De Los Santos
article en
11 citations

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.

Scientific ReportsVol. 14(1)
Universidad San Pablo CEU (ES), Universidad Complutense de Madrid (ES), Instituto de Salud Carlos III (ES), Hospital General Universitario Gregorio Marañón (ES), Centro de Investigación Biomédica en Red (ES), Hospital Universitario de La Princesa (ES), Universidad Autónoma de Madrid (ES)
Banco Santander, Comunidad de Madrid, European Commission, Universidad Autónoma de Madrid, Ministerio de Ciencia e Innovación, Instituto de Salud Carlos III, European Regional Development Fund
Zero hunger
Openalex Percentile: Top 5%
COVID-19 Clinical Research Studies
4.28
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.