Genetic Variants Specific to Critical COVID‐19: Insights From Genome‐Wide Association Studies and Structural Analysis

Genome-wide association studies (GWAS) have identified numerous genetic loci associated with COVID-19 susceptibility and severity. However, it remains unclear which variants specifically contribute to the progression from hospitalization to critical illness. To address this, we identified 394 symptom-differentiating SNPs (sdSNPs) by directly comparing GWAS summary statistics between critical and hospitalized COVID-19 cases. Among these, 13 were missense variants that may trigger phenotype conversion. To investigate their functional consequences, we performed structural modeling to evaluate the impact of these variants on protein stability. Eight proteins were predicted to be affected, including FUT2, ICAM5, IFNA10, PLSCR1, IZUMO1, ICAM1, RASIP1, and MICB, suggesting potential disruptions in immune signaling and host response pathways. Furthermore, Mendelian randomization analyses provided direct causal evidence: SMR analysis based on lung eQTL data demonstrated that higher FUT2 expression was significantly associated with increased risk of critical COVID-19 (β = 0.227, p = 2.69 × 10<sup>-3</sup>), compared to a weaker effect in hospitalized COVID-19 (β = 0.096, p = 3.97 × 10<sup>-2</sup>). In contrast, MR analysis using cis-pQTLs revealed that higher plasma levels of soluble ICAM5 (sICAM5) exerted protective effects, with stronger estimates in critical COVID-19 (β = -0.186, p = 5.54 × 10<sup>-7</sup>) than in hospitalized COVID-19 (β = -0.095, p = 1.69 × 10<sup>-4</sup>). These findings identify a distinct set of severity-specific genetic variants and offer mechanistic insights into how missense mutations may influence disease progression through structural and regulatory pathways.

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Journal
Journal of Medical Virology
Published
2025-11-01
DOI
https://doi.org/10.1002/jmv.70719
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
0.00

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article

Genetic Variants Specific to Critical COVID‐19: Insights From Genome‐Wide Association Studies and Structural Analysis

Shumiao Zhang, Hongwei Chen, Haoyang Zhang, Zan Li et al.
Journal of Medical Virology
Genetic Associations and Epidemiology
article

Genetic Variants Specific to Critical COVID‐19: Insights From Genome‐Wide Association Studies and Structural Analysis

Shumiao Zhang, Hongwei Chen, Haoyang Zhang, Zan Li, Yuelong Shu, Xue Han, Yongkun Chen
article en

Abstract

Genome-wide association studies (GWAS) have identified numerous genetic loci associated with COVID-19 susceptibility and severity. However, it remains unclear which variants specifically contribute to the progression from hospitalization to critical illness. To address this, we identified 394 symptom-differentiating SNPs (sdSNPs) by directly comparing GWAS summary statistics between critical and hospitalized COVID-19 cases. Among these, 13 were missense variants that may trigger phenotype conversion. To investigate their functional consequences, we performed structural modeling to evaluate the impact of these variants on protein stability. Eight proteins were predicted to be affected, including FUT2, ICAM5, IFNA10, PLSCR1, IZUMO1, ICAM1, RASIP1, and MICB, suggesting potential disruptions in immune signaling and host response pathways. Furthermore, Mendelian randomization analyses provided direct causal evidence: SMR analysis based on lung eQTL data demonstrated that higher FUT2 expression was significantly associated with increased risk of critical COVID-19 (β = 0.227, p = 2.69 × 10<sup>-3</sup>), compared to a weaker effect in hospitalized COVID-19 (β = 0.096, p = 3.97 × 10<sup>-2</sup>). In contrast, MR analysis using cis-pQTLs revealed that higher plasma levels of soluble ICAM5 (sICAM5) exerted protective effects, with stronger estimates in critical COVID-19 (β = -0.186, p = 5.54 × 10<sup>-7</sup>) than in hospitalized COVID-19 (β = -0.095, p = 1.69 × 10<sup>-4</sup>). These findings identify a distinct set of severity-specific genetic variants and offer mechanistic insights into how missense mutations may influence disease progression through structural and regulatory pathways.

Journal of Medical VirologyVol. 97(11)
Sun Yat-sen University (CN), Shenzhen University (CN), Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Shenzhen University Health Science Center (CN)
Shenzhen University, National Key Research and Development Program of China
Openalex Percentile: Top 62%
Genetic Associations and Epidemiology
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