{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T02:46:03Z","timestamp":1791945963525,"version":"4.3.4"},"reference-count":47,"publisher":"Wiley","issue":"11","license":[{"start":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T00:00:00Z","timestamp":1763683200000},"content-version":"vor","delay-in-days":20,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T00:00:00Z","timestamp":1761955200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Journal of Medical Virology"],"published-print":{"date-parts":[[2025,11]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>\n                    Genome\u2010wide association studies (GWAS) have identified numerous genetic loci associated with COVID\u201019 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\u2010differentiating SNPs (sdSNPs) by directly comparing GWAS summary statistics between critical and hospitalized COVID\u201019 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\n                    <jats:italic>FUT2<\/jats:italic>\n                    ,\n                    <jats:italic>ICAM5<\/jats:italic>\n                    ,\n                    <jats:italic>IFNA10<\/jats:italic>\n                    ,\n                    <jats:italic>PLSCR1<\/jats:italic>\n                    ,\n                    <jats:italic>IZUMO1<\/jats:italic>\n                    ,\n                    <jats:italic>ICAM1<\/jats:italic>\n                    ,\n                    <jats:italic>RASIP1<\/jats:italic>\n                    , and\n                    <jats:italic>MICB<\/jats:italic>\n                    , 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\u201019 (\n                    <jats:italic>\u03b2<\/jats:italic>\n                    \u2009=\u20090.227,\n                    <jats:italic>p<\/jats:italic>\n                    \u2009=\u20092.69\u2009\u00d7\u200910\n                    <jats:sup>\u22123<\/jats:sup>\n                    ), compared to a weaker effect in hospitalized COVID\u201019 (\n                    <jats:italic>\u03b2<\/jats:italic>\n                    \u2009=\u20090.096,\n                    <jats:italic>p<\/jats:italic>\n                    \u2009=\u20093.97\u2009\u00d7\u200910\n                    <jats:sup>\u22122<\/jats:sup>\n                    ). In contrast, MR analysis using cis\u2010pQTLs revealed that higher plasma levels of soluble\n                    <jats:italic>ICAM5<\/jats:italic>\n                    (sICAM5) exerted protective effects, with stronger estimates in critical COVID\u201019 (\n                    <jats:italic>\u03b2<\/jats:italic>\n                    \u2009=\u2009\u22120.186,\n                    <jats:italic>p<\/jats:italic>\n                    \u2009=\u20095.54\u2009\u00d7\u200910\n                    <jats:sup>\u22127<\/jats:sup>\n                    ) than in hospitalized COVID\u201019 (\n                    <jats:italic>\u03b2<\/jats:italic>\n                    \u2009=\u2009\u22120.095,\n                    <jats:italic>p<\/jats:italic>\n                    \u2009=\u20091.69\u2009\u00d7\u200910\n                    <jats:sup>\u22124<\/jats:sup>\n                    ). These findings identify a distinct set of severity\u2010specific genetic variants and offer mechanistic insights into how missense mutations may influence disease progression through structural and regulatory pathways.\n                  <\/jats:p>","DOI":"10.1002\/jmv.70719","type":"journal-article","created":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T10:35:46Z","timestamp":1763721346000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Genetic Variants Specific to Critical COVID\u201019: Insights From Genome\u2010Wide Association Studies and Structural Analysis"],"prefix":"10.1002","volume":"97","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9010-9728","authenticated-orcid":false,"given":"Hongwei","family":"Chen","sequence":"first","affiliation":[{"name":"Shenzhen Key Laboratory of Pathogenic Microbes and Biosafety, School of Public Health (Shenzhen) Shenzhen Campus of Sun Yat\u2010sen University Shenzhen P. 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