Department of Hematology, Oncology, Clinical Immunology and Rheumatology, University Hospital Tuebingen, Eberhard Karls University Tuebingen, Tuebingen, Germany.
German Cancer Research Centre, Research Group Dendritic Cells in Infection and Cancer, Heidelberg, Germany.
Eur J Immunol. 2024 Nov;54(11):e2451145. doi: 10.1002/eji.202451145. Epub 2024 Aug 2.
Severe acute respiratory syndrome coronavirus type 2 (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. So far, however, there are hardly any strategies for predicting the course of SARS-CoV-2 infection in CVD patients at hospital admission. Thus, we investigated whether this prediction is achievable by prospectively analysing the blood immunophenotype of 94 nonvaccinated participants, including uninfected and acutely SARS-CoV-2-infected CVD patients and 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 CD161 T 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.
严重急性呼吸综合征冠状病毒 2 型(SARS-CoV-2)感染可导致危及生命的临床表现。患有心血管疾病(CVD)的患者患 COVID-19 重症的风险更高。然而,迄今为止,几乎没有任何策略可以预测住院时 CVD 患者 SARS-CoV-2 感染的病程。因此,我们通过使用 36 色光谱流式细胞术面板对 94 名未接种疫苗的参与者(包括未感染和急性 SARS-CoV-2 感染的 CVD 患者和健康供体)的血液免疫表型进行前瞻性分析,来研究是否可以实现这种预测。非监督数据分析显示,健康供体与 CVD 患者之间几乎没有差异,而 SARS-CoV-2 感染的 CVD 患者中细胞群的分布则发生了巨大变化。后者具有更多成熟的 NK 细胞、活化的单核细胞亚群、中央记忆 CD4 T 细胞和浆母细胞,但树突状细胞、CD16 单核细胞、固有淋巴细胞和 CD8 T 细胞亚群较少。此外,我们确定了一个免疫特征,其特征是 CD161 T 细胞、中间效应 CD8 T 细胞和自然杀伤 T(NKT)细胞,可预测 COVID-19 重症的 CVD 患者。因此,强化免疫表型分析可以帮助识别住院时 COVID-19 重症风险较高的患者,通过特定治疗改善临床结局。