Version 1
: Received: 20 November 2023 / Approved: 21 November 2023 / Online: 21 November 2023 (09:36:57 CET)
How to cite:
Günter, M.; Müller, K.A.L.; Salazar, M.J.; Gekeler, S.; Prang, C.; Harm, T.; Gawaz, M.P.; Autenrieth, A.S.E. Immune Signature of Patients With Cardiovascular Disease Predicts Increased Risk for a Severe Course of COVID-19. Preprints2023, 2023111289. https://doi.org/10.20944/preprints202311.1289.v1
Günter, M.; Müller, K.A.L.; Salazar, M.J.; Gekeler, S.; Prang, C.; Harm, T.; Gawaz, M.P.; Autenrieth, A.S.E. Immune Signature of Patients With Cardiovascular Disease Predicts Increased Risk for a Severe Course of COVID-19. Preprints 2023, 2023111289. https://doi.org/10.20944/preprints202311.1289.v1
Günter, M.; Müller, K.A.L.; Salazar, M.J.; Gekeler, S.; Prang, C.; Harm, T.; Gawaz, M.P.; Autenrieth, A.S.E. Immune Signature of Patients With Cardiovascular Disease Predicts Increased Risk for a Severe Course of COVID-19. Preprints2023, 2023111289. https://doi.org/10.20944/preprints202311.1289.v1
APA Style
Günter, M., Müller, K.A.L., Salazar, M.J., Gekeler, S., Prang, C., Harm, T., Gawaz, M.P., & Autenrieth, A.S.E. (2023). Immune Signature of Patients With Cardiovascular Disease Predicts Increased Risk for a Severe Course of COVID-19. Preprints. https://doi.org/10.20944/preprints202311.1289.v1
Chicago/Turabian Style
Günter, M., Meinrad P. Gawaz and And Stella E. Autenrieth. 2023 "Immune Signature of Patients With Cardiovascular Disease Predicts Increased Risk for a Severe Course of COVID-19" Preprints. https://doi.org/10.20944/preprints202311.1289.v1
Abstract
SARS-CoV-2 infection can lead to life-threatening clinical manifestations. Patients with cardiovascular disease (CVD) are at higher risk for severe courses of COVID-19. However, strategies to predict the course of SARS-CoV-2 infection in CVD patients at the time of hospital admission are still missing. Here, we investigated whether this prediction is achievable by prospectively analysing the blood immunophenotype of 94 participants, including 20 uninfected and 37 acutely SARS-CoV-2-infected CVD patients and 37 healthy donors, using a 36-colour spectral flow cytometry panel. Unsupervised data analysis revealed little differences between healthy donors and CVD patients, whereas the distribution of the cell populations changed dramatically in SARS-CoV-2-infected CVD patients. The latter had more mature NK cells, activated monocyte subsets, central memory CD4+ T cells, and plasmablasts but fewer dendritic cells, CD16+ monocytes, innate lymphoid cells, and CD8+ T cell subsets. Moreover, we identified an immune signature characterised by mucosal-associated invariant T (MAIT) cells, intermediate effector CD8+ T cells, and natural killer T (NKT) cells that is predictive for CVD patients with a severe course of COVID-19. Thus, intensified immunophenotype analyses can help identify patients at risk of severe COVID-19 at hospital admission, improving clinical outcomes through specific treatment.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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