@article {{\v S}elb00216-2022, author = {Julij {\v S}elb and Barbara Bite{\v z}nik and Ur{\v s}ka Bidovec Stojkovi{\'c} and Bo{\v s}tjan Rituper and Katarina Osolnik and Peter Kopa{\v c} and Petra Svetina and Kristina Cerk Porenta and Franc {\v S}ifrer and Petra Lorber and Darinka Trinkaus Leiler and Toma{\v z} Hafner and Tina Jeri{\v c} and Robert Mar{\v c}un and Nika Lalek and Nina Frelih and Mojca Bizjak and Rok Lombar and Vesna Nikoli{\'c} and Katja Adami{\v c} and Katja Mohor{\v c}i{\v c} and Sanja Grm Zupan and Irena {\v S}arc and Jerneja Debeljak and Ana Koren and Dem{\v s}ar Luzar MSc Ajda and Matija Rijavec and Izidor Kern and Matja{\v z} Fle{\v z}ar and Ale{\v s} Rozman and Peter Koro{\v s}ec}, title = {Immunophenotypes of anti-SARS-CoV-2 responses associated with fatal COVID-19}, elocation-id = {00216-2022}, year = {2022}, doi = {10.1183/23120541.00216-2022}, publisher = {European Respiratory Society}, abstract = {Background The relationship between anti-SARS-CoV-2 humoral immune response, pathogenic inflammation, lymphocytes and fatal COVID-19 is poorly understood.Methods Longitudinal prospective cohort of hospitalized patients with COVID-19 (N=254) was followed up to 35 d after admission (median, 8 d). We measured early anti-SARS-CoV-2 S1 antibody IgG levels and dynamic (698 samples) of quantitative circulating T, B, NK lymphocyte subsets and serum interleukin-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 hospitalization. We identified six clusters representing discrete anti-SARS-CoV-2 immunophenotypes. Clusters differed considerably in COVID-19 survival. Two clusters, the anti-S1-IgGlowestTlowestBlowestNKmodIL-6mod, and the anti-S1-IgGhighTlowBmodNKmodIL-6highest had a high risk of fatal COVID-19 (HR, 3.36{\textendash}21.69; 95\% CI, 1.51{\textendash}163.61 and HR, 8.39{\textendash}10.79; 95\% CI, 1.20{\textendash}82.67; P<=0.03, respectively). The anti-S1-IgGhighestTlowestBmodNKmodIL-6mod and anti-S1-IgGlowThighestBhighestNKhighestIL-6low cluster were associated with moderate risk of mortality. In contrast, two clusters the anti-S1- anti-S1-IgGhighThighBmodNKmodIL-6low and anti-S1-IgGhighestThighestBhighNKhighIL-6lowest clusters were characterized 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.FootnotesThis manuscript has recently been accepted for publication in the ERJ Open Research. It is published here in its accepted form prior to copyediting and typesetting by our production team. After these production processes are complete and the authors have approved the resulting proofs, the article will move to the latest issue of the ERJOR online. Please open or download the PDF to view this article.Conflict of interest: The authors have nothing to disclose.}, URL = {https://openres.ersjournals.com/content/early/2022/09/16/23120541.00216-2022}, eprint = {https://openres.ersjournals.com/content/early/2022/09/16/23120541.00216-2022.full.pdf}, journal = {ERJ Open Research} }