4.8 Article

Epigenetic immune monitoring for COVID-19 disease course prognosis

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FRONTIERS IN IMMUNOLOGY
卷 14, 期 -, 页码 -

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FRONTIERS MEDIA SA
DOI: 10.3389/fimmu.2023.1107900

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COVID-19; SARS-CoV-2; epigenetic qPCR; immune monitoring; lymphopenia; disease prognosis

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The course of COVID-19 is associated with dysbalance of the immune system, and immune cell monitoring can provide valuable prognostic information. This study used epigenetic immune cell counting to monitor immune status in blood, dried blood spots, and nasopharyngeal swabs, and found that COVID-19 patients had decreased lymphocytes and increased neutrophils compared to healthy individuals. Male patients also showed significantly lower levels of regulatory T cells. The results suggest that immune cell counts can be used as a predictor of disease progression.
Background: The course of COVID-19 is associated with severe dysbalance of the immune system, causing both leukocytosis and lymphopenia. Immune cell monitoring may be a powerful tool to prognosticate disease outcome. However, SARS-CoV-2 positive subjects are isolated upon initial diagnosis, thus barring standard immune monitoring using fresh blood. This dilemma may be solved by epigenetic immune cell counting. Methods: In this study, we used epigenetic immune cell counting by qPCR as an alternative way of quantitative immune monitoring for venous blood, capillary blood dried on filter paper (dried blood spots, DBS) and nasopharyngeal swabs, potentially allowing a home-based monitoring approach. Results: Epigenetic immune cell counting in venous blood showed equivalence with dried blood spots and with flow cytometrically determined cell counts of venous blood in healthy subjects. In venous blood, we detected relative lymphopenia, neutrophilia, and a decreased lymphocyte-to-neutrophil ratio for COVID-19 patients (n =103) when compared with healthy donors (n = 113). Along with reported sex-related differences in survival we observed dramatically lower regulatory T cell counts in male patients. In nasopharyngeal swabs, T and B cell counts were significantly lower in patients compared to healthy subjects, mirroring the lymphopenia in blood. Naive B cell frequency was lower in severely ill patients than in patients with milder stages. Conclusions: Overall, the analysis of immune cell counts is a strong predictor of clinical disease course and the use of epigenetic immune cell counting by qPCR may provide a tool that can be used even for home-isolated patients.

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