Human Monocytes - CD14, CD16 - Ziegler-Heitbrock


Immune Response in Severe and Non-Severe Coronavirus Disease 2019 (COVID-19) Infection: A Mechanistic Landscape.


The mechanisms underlying the immune remodeling and severity response in coronavirus disease 2019 (COVID-19) are yet to be fully elucidated. Our comprehensive integrative analyses of single-cell RNA sequencing (scRNAseq) data from four published studies, in patients with mild/moderate and severe infections, indicate a robust expansion and mobilization of the innate immune response and highlight mechanisms by which low-density neutrophils and megakaryocytes play a crucial role in the cross talk between lymphoid and myeloid lineages. We also document a marked reduction of several lymphoid cell types, particularly natural killer cells, mucosal-associated invariant T (MAIT) cells, and gamma-delta T (gammadeltaT) cells, and a robust expansion and extensive heterogeneity within plasmablasts, especially in severe COVID-19 patients. We confirm the changes in cellular abundances for certain immune cell types within a new patient cohort. While the cellular heterogeneity in COVID-19 extends across cells in both lineages, we consistently observe certain subsets respond more potently to interferon type I (IFN-I) and display increased cellular abundances across the spectrum of severity, as compared with healthy subjects. However, we identify these expanded subsets to have a more muted response to IFN-I within severe disease compared to non-severe disease. Our analyses further highlight an increased aggregation potential of the myeloid subsets, particularly monocytes, in COVID-19. Finally, we provide detailed mechanistic insights into the interaction between lymphoid and myeloid lineages, which contributes to the multisystemic phenotype of COVID-19, distinguishing severe from non-severe responses.

Authors: Mukund K, Nayak P, Ashokkumar C, Rao S, Almeda J, Betancourt-Garcia MM, Sindhi R, Subramaniam S,
Journal: Front Immunol;2021; 12 738073. doi:10.3389/fimmu.2021.738073
Year: 2021
PubMed: PMID: 34721400 (Go to PubMed)