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

Julij Šelb; Barbara Bitežnik; Urška Bidovec Stojković; Boštjan Rituper; Katarina Osolnik; Peter Kopač; Petra Svetina; Kristina Cerk Porenta; Franc Šifrer; Petra Lorber; Darinka Trinkaus Leiler; Tomaž Hafner; Tina Jerič; Robert Marčun; Nika Lalek; Nina Frelih; Mojca Bizjak; Rok Lombar; Vesna Nikolić; Katja Adamič; Katja Mohorčič; Sanja Grm Zupan; Irena Šarc; Jerneja Debeljak; Ana Koren; Ajda Demšar Luzar; Matija Rijavec; Izidor Kern; Matjaž Fležar; Aleš Rozman; Peter Korošec

doi:10.1183/23120541.00216-2022

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

ERJ Open Res. 2022 Dec 5;8(4):00216-2022. doi: 10.1183/23120541.00216-2022. eCollection 2022 Oct.

Authors

Julij Šelb^{1

2

3}, Barbara Bitežnik^{1

2

3}, Urška Bidovec Stojković¹, Boštjan Rituper^{1

2}, Katarina Osolnik¹, Peter Kopač^{1

2}, Petra Svetina¹, Kristina Cerk Porenta¹, Franc Šifrer¹, Petra Lorber^{1

2}, Darinka Trinkaus Leiler¹, Tomaž Hafner^{1

2}, Tina Jerič¹, Robert Marčun^{1

2}, Nika Lalek^{1

2}, Nina Frelih¹, Mojca Bizjak¹, Rok Lombar¹, Vesna Nikolić^{1

2}, Katja Adamič¹, Katja Mohorčič¹, Sanja Grm Zupan¹, Irena Šarc^{1

2}, Jerneja Debeljak¹, Ana Koren¹, Ajda Demšar Luzar¹, Matija Rijavec^{1

4}, Izidor Kern¹, Matjaž Fležar^{1

2}, Aleš Rozman^{1

2}, Peter Korošec^{1

5}

Affiliations

¹ University Clinic of Respiratory and Allergic Diseases, Golnik, Slovenia.
² Medical Faculty, University of Ljubljana, Ljubljana, Slovenia.
³ These authors contributed equally.
⁴ Biotechnical Faculty, University of Ljubljana, Ljubljana, Slovenia.
⁵ Faculty of Pharmacy, University of Ljubljana, Ljubljana, Slovenia.

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^lowestT^lowestB^lowestNK^modIL-6^mod, and the anti-S1-IgG^highT^lowB^modNK^modIL-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^highestT^lowestB^modNK^modIL-6^mod and anti-S1-IgG^lowT^highestB^highestNK^highestIL-6^low cluster were associated with moderate risk of mortality. In contrast, two clusters the anti-S1-IgG^highT^highB^modNK^modIL-6^low and anti-S1-IgG^highestT^highestB^highNK^highIL-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.