RESUMO
Since the outset of the COVID-19 pandemic, increasing evidence suggests that the innate immune responses play an important role in the disease development. A dysregulated inflammatory state has been proposed as key driver of clinical complications in COVID-19, with a potential detrimental role of granulocytes. However, a comprehensive phenotypic description of circulating granulocytes in SARS-CoV-2-infected patients is lacking. In this study, we used high-dimensional flow cytometry for granulocyte immunophenotyping in peripheral blood collected from COVID-19 patients during acute and convalescent phases. Severe COVID-19 was associated with increased levels of both mature and immature neutrophils, and decreased counts of eosinophils and basophils. Distinct immunotypes were evident in COVID-19 patients, with altered expression of several receptors involved in activation, adhesion and migration of granulocytes (e.g. CD62L, CD11a/b, CD69, CD63, CXCR4). Paired sampling revealed recovery and phenotypic restoration of the granulocytic signature in the convalescent phase. The identified granulocyte immunotypes correlated with distinct sets of soluble inflammatory markers supporting pathophysiologic relevance. Furthermore, clinical features, including multi-organ dysfunction and respiratory function, could be predicted using combined laboratory measurements and immunophenotyping. This study provides a comprehensive granulocyte characterization in COVID-19 and reveals specific immunotypes with potential predictive value for key clinical features associated with COVID-19. SignificanceAccumulating evidence shows that granulocytes are key modulators of the immune response to SARS-CoV-2 infection and their dysregulation could significantly impact COVID-19 severity and patient recovery after virus clearance. In the present study, we identify selected immune traits in neutrophil, eosinophil and basophil subsets associated to severity of COVID-19 and to peripheral protein profiles. Moreover, computational modeling indicates that the combined use of phenotypic data and laboratory measurements can effectively predict key clinical outcomes in COVID-19 patients. Finally, patient-matched longitudinal analysis shows phenotypic normalization of granulocyte subsets 4 months after hospitalization. Overall, in this work we extend the current understanding of the distinct contribution of granulocyte subsets to COVID-19 pathogenesis.
RESUMO
Understanding innate immune responses in COVID-19 is important for deciphering mechanisms of host responses and interpreting disease pathogenesis. Natural killer (NK) cells are innate effector lymphocytes that respond to acute viral infections, but might also contribute to immune pathology. Here, using 28-color flow cytometry, we describe a state of strong NK cell activation across distinct subsets in peripheral blood of COVID-19 patients, a pattern mirrored in scRNA-seq signatures of lung NK cells. Unsupervised high-dimensional analysis identified distinct immunophenotypes that were linked to disease severity. Hallmarks of these immunophenotypes were high expression of perforin, NKG2C, and Ksp37, reflecting a high presence of adaptive NK cell expansions in circulation of patients with severe disease. Finally, arming of CD56bright NK cells was observed in course of COVID-19 disease states, driven by a defined protein-protein interaction network of inflammatory soluble factors. This provides a detailed map of the NK cell activation-landscape in COVID-19 disease.
