Objective: 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 hospital admission are still missing. Here, we investigated whether the severity of SARS-CoV-2 infection can be predicted by analyzing the immunophenotype in the blood of CVD patients. Approach and Results: We prospectively analyzed the peripheral blood of 94 participants, including CVD patients with acute SARS-CoV-2 infection, uninfected CVD patients, and healthy donors using a 36-color spectral flow cytometry panel. Clinical assessment included blood sampling, echocardiography, and electrocardiography. Patients were classified by their ISARIC WHO 4C-Mortality-Score on the day of admission into three subgroups of an expected mild, moderate, or severe course of COVID-19. Unsupervised data analysis revealed 40 clusters corresponding to major circulating immune cell populations. This 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 than uninfected CVD patients. In contrast, fewer dendritic cells, CD16+monocytes, innate lymphoid cells, and CD8+T cell subsets were detected in SARS-CoV-2-infected CVD patients. We identified an immune signature characterized by low frequencies of MAIT and intermediate effector CD8+T cells in combination with a high frequency of NKT cells that is predictive for CVD patients with a severe course of SARS-CoV-2 infection on hospital admission. Conclusion: Acute SARS-CoV-2 infected CVD patients revealed marked changes in abundance and phenotype of several immune cell populations associated with COVID-19 severity. Our data indicate that intensified immunophenotype analyses can help identify patients at risk of severe COVID-19 at hospital admission, improving clinical outcomes through specific treatment.
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