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Authors: Vanderbeke L. et al 

Journal/ Pre-Print:SSRN 

Tags: Bioinformatics, Clinical, Immunology/Immunity, Inflammation, Modelling 

Research Highlights 

  1. COVID19 is characterized by myeloid driven cytokine storm different from one in macrophage activation syndrome (MAS).  

  1. Classical monocytes-identified as major cytokine and chemokine source, and neutrophils-undergoing NETosis systemically- dominate COVID19 immunopathology 

  1. Depressed antigen presentation and low CD8+ T cell numbers feature strongly in severe COVID19  

Summary 

Cytokine storm in COVID19 differs from the prototypical observed in MAS, with markedly lower IFNy and higher CXCL8 levels in COVID19. scRNA seq of PBMCs pointed classical monocytes as the main cytokine source-especially IL1b and CXCL8. CyTOF immunophenotyping of COVID19 blood showed overall decrease of immune populations, except for increased neutrophils and plasmablastsLymphocytopoenia affected CD8+ T cells more-identified as the major source of IFNy by the scRNAseq. Antigen presentation was also depressed as HLA-DR was reduced in CD14hi monocytes and DCs, especially in critical COVID19. COVID19 plasma showed evidence of systemic NETosis, confirmed by scRNAseq of bronchoalveolar lavage fluid that captured neutrophils, which were enriched in COVID19 compared to non-COVID pneumonia. Together, monocyte driven neutrophil recruitment and hyper-activation, alongside depressed adaptive immunity, underlies COVID19 pathology. 

Impact for SARS-CoV2/COVID19 research efforts

Understand the immune response to  SARS-CoV2/COVID19  

Clinical symptoms and pathogenesis of SARS-Cov2/COVID19 

In brief: COVID19 determinants are already described lymphocytopoenia, thrombocytosis and a strong hyper-activated myeloid compartment mainly responsible for cytokine storm with plenty of neutrophil attractants and less IFNy compared to classical cytokine storm. Neutrophils underlie systemic and local pathologies by upregulating deleterious functions-mainly NETosis and chemokine production. 

Study Type 

  • In silico study / bioinformatics study 

  • Patient Case study 

Strengths and limitations of the paper 

Novelty: The first study to directly compare COVID19 and MAS; the first study to use computational modelling to correlate cytokines with each other (co-expression), source cells and link gene ontology with respective cytokines in mild-moderate and critical COVID19 from published human immune cell-type expression profiles, CYTOF and serological data.  

Likewise, the first study to my knowledge that employs computational network biology assessments to correlate different cell clusters in mild-moderate and critical COVID19 with the aim of defining regulatory patterns. 

Also, the first study that compares BALF scRNA seq of COVID with non-COVID pneumonia emphasizing neutrophil deleterious signature.

Standing in the field:Largely corroborates current knowledge- confirms cytokine storm in part (defined better in this study), confirms lymphocytopoenia, thrombocytosis, neutrophil expansion and expansive NETosis, hyper-activity of classical monocytes as well as reduced antigen presentation capacities across immune cells.

Appropriate statistics: Yes 

Viral model used:NA 

Translatability:supports the use of anti-IL-1 and anti-IL-6, or broad-activity immunomodulatory drugs (e.g. azithromycin, colchicine). Researchers suggest neutrophil targeting- e.g. NET release by DNase, potentially locally in the lung. 

Main limitations: No difference in IFNy levels in mild-moderate and critical COVID19 yet researchers propose reduced IFNy signalling as the mechanism behind depressed adaptive immune response, specifically, reduced antigen presentation and T cell effector function. Researchers haven't shown any GO enrichment analysis of PBMC scRNAseq data on lymphocyte populations that would indicate specific alterations in effector functions. Alsoit would be great to functionally assess antigen presentation capacity of DCs from COVID patients alongside T cell proliferation.