Profiling of immune dysfunction in COVID-19 patients allows early prediction of disease progression.

TitleProfiling of immune dysfunction in COVID-19 patients allows early prediction of disease progression.
Publication TypeJournal Article
Year of Publication2021
AuthorsRendeiro AF, Casano J, Vorkas CKyriakos, Singh H, Morales A, DeSimone RA, Ellsworth GB, Soave R, Kapadia SN, Saito K, Brown CD, Hsu JM, Kyriakides C, Chiu S, Cappelli LVincenzo, Cacciapuoti MTeresa, Tam W, Galluzzi L, Simonson PD, Elemento O, Salvatore M, Inghirami G
JournalLife Sci Alliance
Date Published2021 02
KeywordsAdaptive Immunity, Adult, Aged, Aged, 80 and over, CD4-Positive T-Lymphocytes, CD8-Positive T-Lymphocytes, COVID-19, Disease Progression, Epidemics, Female, Humans, Immune System Diseases, Immunity, Innate, Lymphocyte Subsets, Male, Middle Aged, SARS-CoV-2, Severity of Illness Index

With a rising incidence of COVID-19-associated morbidity and mortality worldwide, it is critical to elucidate the innate and adaptive immune responses that drive disease severity. We performed longitudinal immune profiling of peripheral blood mononuclear cells from 45 patients and healthy donors. We observed a dynamic immune landscape of innate and adaptive immune cells in disease progression and absolute changes of lymphocyte and myeloid cells in severe versus mild cases or healthy controls. Intubation and death were coupled with selected natural killer cell KIR receptor usage and IgM+ B cells and associated with profound CD4 and CD8 T-cell exhaustion. Pseudo-temporal reconstruction of the hierarchy of disease progression revealed dynamic time changes in the global population recapitulating individual patients and the development of an eight-marker classifier of disease severity. Estimating the effect of clinical progression on the immune response and early assessment of disease progression risks may allow implementation of tailored therapies.

Alternate JournalLife Sci Alliance
PubMed ID33361110
PubMed Central IDPMC7768198
Grant ListT32 AI07613-19 / AI / NIAID NIH HHS / United States
T32 CA203702 / CA / NCI NIH HHS / United States
T32 AI007613 / AI / NIAID NIH HHS / United States
K08 AI132739 / AI / NIAID NIH HHS / United States
UL1 TR002384 / TR / NCATS NIH HHS / United States
K08 AI139360 / AI / NIAID NIH HHS / United States
KL2 TR002385 / TR / NCATS NIH HHS / United States
Related Faculty: 
Giorgio Inghirami, M.D. Paul Simonson, M.D., Ph.D. Robert DeSimone, M.D. Wayne Tam, M.D., Ph.D.


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