Observational studyCellular and molecular life sciences : CMLS2021
High dimensional profiling identifies specific immune types along the recovery trajectories of critically ill COVID19 patients.
Observational study in Cellular and molecular life sciences : CMLS, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
12 citing papers in PubMed.
- Early Cytokine Profiles in Critically Ill Patients with COVID-19 and Their Association with Mortality.Metabolites · 2026Article
- Mass Cytometry Analysis of High-Dimensional Single-Cell Immune Profiles in ZF2001-Vaccinated Patients Infected with SARS-CoV-2.Infection and drug resistance · 2025Article
- Immunomics in one health: understanding the human, animal, and environmental aspects of COVID-19.Frontiers in immunology · 2024Review
- Immunomodulatory approaches in managing lung inflammation in COVID-19: A double-edge sword.Immunity, inflammation and disease · 2023Review
- Single-cell molecular profiling using ex vivo functional readouts fuels precision oncology in glioblastoma.Cellular and molecular life sciences : CMLS · 2023Article
- Monocytic HLA-DR Expression in Immune Responses of Acute Pancreatitis and COVID-19.International journal of molecular sciences · 2023Review
- A cross entropy test allows quantitative statistical comparison of t-SNE and UMAP representations.Cell reports methods · 2023Article
- Machine learning of flow cytometry data reveals the delayed innate immune responses correlate with the severity of COVID-19.Frontiers in immunology · 2023Article
- Alterations of blood monocyte subset distribution and surface phenotype are linked to infection severity in COVID-19 inpatients.European journal of immunology · 2022Article
- Immunomodulatory therapy for the management of critically ill patients with COVID-19: A narrative review.World journal of critical care medicine · 2022Article
- Severe COVID-19 patients display hyper-activated NK cells and NK cell-platelet aggregates.Frontiers in immunology · 2022Article
- Human immune diversity: from evolution to modernity.Nature immunology · 2021Review
Corrections and comments
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Authors and funding
22 authors.
Funding
Abstract
The COVID-19 pandemic poses a major burden on healthcare and economic systems across the globe. Even though a majority of the population develops only minor symptoms upon SARS-CoV-2 infection, a significant number are hospitalized at intensive care units (ICU) requiring critical care. While insights into the early stages of the disease are rapidly expanding, the dynamic immunological processes occurring in critically ill patients throughout their recovery at ICU are far less understood. Here, we have analysed whole blood samples serially collected from 40 surviving COVID-19 patients throughout their recovery in ICU using high-dimensional cytometry by time-of-flight (CyTOF) and cytokine multiplexing. Based on the neutrophil-to-lymphocyte ratio (NLR), we defined four sequential immunotypes during recovery that correlated to various clinical parameters, including the level of respiratory support at concomitant sampling times. We identified classical monocytes as the first immune cell type to recover by restoration of HLA-DR-positivity and the reduction of immunosuppressive CD163 + monocytes, followed by the recovery of CD8 + and CD4 + T cell and non-classical monocyte populations. The identified immunotypes also correlated to aberrant cytokine and acute-phase reactant levels. Finally, integrative analysis of cytokines and immune cell profiles showed a shift from an initially dysregulated immune response to a more coordinated immunogenic interplay, highlighting the importance of longitudinal sampling to understand the pathophysiology underlying recovery from severe COVID-19.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.