Immunophenotypes of anti-SARS-CoV-2 responses associated with fatal COVID-19. Issue 4 (5th December 2022)

• Record Type: Journal Article
• Authors: 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;
• Is Part Of: ERJ open research. Volume 8:Issue 4(2022)
• Publication Date: 2022-12-05
• Subjects: Respiratory organs -- Diseases -- Periodicals; Respiration -- Periodicals; Respiration; Respiratory organs -- Diseases; Respiratory organs -- Diseases -- Treatment; Respiratory Tract Diseases; Electronic journals; Fulltext; Internet Resources; Periodicals; Periodical; 616.2005
• DOI: 10.1183/23120541.00216-2022
• Languages: English
• ISSNs: 2312-0541

Abstract

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. By employing unsupervised machine learning, this study identified multiple anti-SARS-CoV-2 immune response profiles and observed major differences in #COVID19 mortality between these profiles https://bit.ly/3SgMh6n