Back

Interplay of Monocytes and T Lymphocytes in COVID-19 Severity

Padgett, L. E.; Dinh, H. Q.; Chee, S. J.; Olingy, C. E.; Wu, R.; Araujo, D. J.; Vijayanand, P.; Ottensmeier, C. H.; Hedrick, C. C.

2020-07-18 immunology
10.1101/2020.07.17.209304 bioRxiv
Show abstract

The COVID-19 pandemic represents an ongoing global crisis that has already impacted over 13 million people. The responses of specific immune cell populations to the disease remain poorly defined, which hinders improvements in treatment and care management. Here, we utilized mass cytometry (CyTOF) to thoroughly phenotype peripheral myeloid cells and T lymphocytes from 30 convalescent patients with mild, moderate, and severe cases of COVID-19. We identified 10 clusters of monocytes and dendritic cells and 17 clusters of T cells. Examination of these clusters revealed that both CD14+CD16+ intermediate and CD14dimCD16+ nonclassical monocytes, as well as CD4+ stem cell memory T (TSCM) cells, correlated with COVID-19 severity, coagulation factor levels, and/or inflammatory indicators. We also identified two nonclassical monocyte subsets distinguished by expression of the sugar residue 6-Sulfo LacNac (Slan). One of these subsets (Slanlo, nMo1) was depleted in moderately and severely ill patients, while the other (Slanhi, nMo2) increased with disease severity and was linked to CD4+ T effector memory (TEM) cell frequencies, coagulation factors, and inflammatory indicators. Intermediate monocytes tightly correlated with loss of naive T cells as well as an increased abundance of effector memory T cells expressing the exhaustion marker PD-1. Our data suggest that both intermediate and non-classical monocyte subsets shape the adaptive immune response to SARS-CoV-2. In summary, our study provides both broad and in-depth characterization of immune cell phenotypes in response to COVID-19 and suggests functional interactions between distinct cell types during the disease. One Sentence SummaryUse of mass cytometry on peripheral blood mononuclear cells from convalescent COVID-19 patients allows correlation of distinct monocyte and T lymphocyte subsets with clinical factors.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.