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Immunophenotypes of anti-SARS-CoV-2 responses associated with fatal COVID-19

BACKGROUND: The relationship between anti-SARS-CoV-2 humoral immune response, pathogenic inflammation, lymphocytes and fatal COVID-19 is poorly understood. METHODS: A longitudinal prospective cohort of hospitalised patients with COVID-19 (n=254) was followed up to 35 days after admission (median, 8...

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Detalles Bibliográficos
Autores principales: Šelb, Julij, Bitežnik, Barbara, Bidovec Stojković, Urška, Rituper, Boštjan, Osolnik, Katarina, Kopač, Peter, Svetina, Petra, Cerk Porenta, Kristina, Šifrer, Franc, Lorber, Petra, Trinkaus Leiler, Darinka, Hafner, Tomaž, Jerič, Tina, Marčun, Robert, Lalek, Nika, Frelih, Nina, Bizjak, Mojca, Lombar, Rok, Nikolić, Vesna, Adamič, Katja, Mohorčič, Katja, Grm Zupan, Sanja, Šarc, Irena, Debeljak, Jerneja, Koren, Ana, Luzar, Ajda Demšar, Rijavec, Matija, Kern, Izidor, Fležar, Matjaž, Rozman, Aleš, Korošec, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: European Respiratory Society 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9510901/
https://www.ncbi.nlm.nih.gov/pubmed/36474964
http://dx.doi.org/10.1183/23120541.00216-2022
Descripción
Sumario:BACKGROUND: The relationship between anti-SARS-CoV-2 humoral immune response, pathogenic inflammation, lymphocytes and fatal COVID-19 is poorly understood. METHODS: A longitudinal prospective cohort of hospitalised patients with COVID-19 (n=254) was followed up to 35 days after admission (median, 8 days). We measured early anti-SARS-CoV-2 S1 antibody IgG levels and dynamic (698 samples) of quantitative circulating T-, B- and natural killer lymphocyte subsets and serum interleukin-6 (IL-6) response. We used machine learning to identify patterns of the immune response and related these patterns to the primary outcome of 28-day mortality in analyses adjusted for clinical severity factors. RESULTS: Overall, 45 (18%) patients died within 28 days after hospitalisation. We identified six clusters representing discrete anti-SARS-CoV-2 immunophenotypes. Clusters differed considerably in COVID-19 survival. Two clusters, the anti-S1-IgG(lowest)T(lowest)B(lowest)NK(mod)IL-6(mod,) and the anti-S1-IgG(high)T(low)B(mod)NK(mod)IL-6(highest) had a high risk of fatal COVID-19 (HR 3.36–21.69; 95% CI 1.51–163.61 and HR 8.39–10.79; 95% CI 1.20–82.67; p≤0.03, respectively). The anti-S1-IgG(highest)T(lowest)B(mod)NK(mod)IL-6(mod) and anti-S1-IgG(low)T(highest)B(highest)NK(highest)IL-6(low) cluster were associated with moderate risk of mortality. In contrast, two clusters the anti-S1-IgG(high)T(high)B(mod)NK(mod)IL-6(low) and anti-S1-IgG(highest)T(highest)B(high)NK(high)IL-6(lowest) clusters were characterised by a very low risk of mortality. CONCLUSIONS: By employing unsupervised machine learning we identified multiple anti-SARS-CoV-2 immune response clusters and observed major differences in COVID-19 mortality between these clusters. Two discrete immune pathways may lead to fatal COVID-19. One is driven by impaired or delayed antiviral humoral immunity, independently of hyper-inflammation, and the other may arise through excessive IL-6-mediated host inflammation response, independently of the protective humoral response. Those observations could be explored further for application in clinical practice.