文章基本信息

标题：Multi-dimensional and longitudinal systems profiling reveals predictive pattern of severe COVID-19
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作者：Marcel S. Woo ; Friedrich Haag ; Axel Nierhaus 等
期刊名称：iScience
印刷版ISSN：2589-0042
出版年度：2021
卷号：24
期号：7
页码：1-23
DOI：10.1016/j.isci.2021.102752
语种：English
出版社：Elsevier
摘要：SummaryCOVID-19 is a respiratory tract infection that can affect multiple organ systems. Predicting the severity and clinical outcome of individual patients is a major unmet clinical need that remains challenging due to intra- and inter-patient variability. Here, we longitudinally profiled and integrated more than 150 clinical, laboratory, and immunological parameters of 173 patients with mild to fatal COVID-19. Using systems biology, we detected progressive dysregulation of multiple parameters indicative of organ damage that correlated with disease severity, particularly affecting kidneys, hepatobiliary system, and immune landscape. By performing unsupervised clustering and trajectory analysis, we identified T and B cell depletion as early indicators of a complicated disease course. In addition, markers of hepatobiliary damage emerged as robust predictor of lethal outcome in critically ill patients. This allowed us to propose a novel clinicalCOVID-19SeveriTy (COST) score that distinguishes complicated disease trajectories and predicts lethal outcome in critically ill patients.Graphical abstractDisplay OmittedHighlights•Unsupervised integration of clinical, laboratory, and immunological data of COVID-19•Multi-organ dysfunctions are detectable across all disease severities•Liver damage is an early marker of complicated disease trajectories•Novel COST score predicts fatal outcome in complicated COVID-19Immunology; Virology; Systems biology