Early stimulated immune responses predict clinical disease severity in hospitalized COVID-19 patients

Abstract

Background The immune pathogenesis underlying the diverse clinical course of COVID-19 is poorly understood. Currently, there is an unmet need in daily clinical practice for early biomarkers and improved risk stratification tools to help identify and monitor COVID-19 patients at risk of severe disease. Methods We performed longitudinal assessment of stimulated immune responses in 30 patients hospitalized with COVID-19. We used the TruCulture whole-blood ligand-stimulation assay applying standardized stimuli to activate distinct immune pathways, allowing quantification of cytokine responses. We further characterized immune cell subsets by flow cytometry and used this deep immunophenotyping data to map the course of clinical disease within and between patients. Results Here we demonstrate impairments in innate immune response pathways at time of COVID-19 hospitalization that are associated with the development of severe disease. We show that these impairments are transient in those discharged from hospital, as illustrated by functional and cellular immune reconstitution. Specifically, we identify lower levels of LPS-stimulated IL-1β, and R848-stimulated IL-12 and IL-17A, at hospital admission to be significantly associated with increasing COVID-19 disease severity during hospitalization. Furthermore, we propose a stimulated immune response signature for predicting risk of developing severe or critical COVID-19 disease at time of hospitalization, to validate in larger cohorts. Conclusions We identify early impairments in innate immune responses that are associated with subsequent COVID-19 disease severity. Our findings provide basis for early identification of patients at risk of severe disease which may have significant implications for the early management of patients hospitalized with COVID-19.

Measuring health care continuum with multifaceted indicators for people who use drugs in Vietnam

“…The analytical framework used in this study can be readily applied to investigate populations or subgroups of interest, e.g., patients with certain health-related conditions. The use of heatmap, in particular, provides a powerful tool for visual display of high dimensional data and has been heavily used in the various research fields, e.g., visualizing high-throughput gene expression data in the fields of bioinformatics and patterns of fatty infiltration score in the imaging studies ( Gómez-Andrés et al, 2019 ; Gruber et al, 2022 ; Svanberg et al, 2022 ). As demonstrated in this study, this tool can be customized and exploited to measure care continuum at different stages in a few different aspects: (1) visualizing the high-dimensional data without losing information, (2) understanding patterns of multifaceted outcomes in relation with the overall fulfillment score, and (3) differentiating patterns of high-dimensional data across subgroup of interest (e.g., STTR individual components for short- vs. long-term use) or different sources of data (e.g., electronic health records and survey assessments).…”

SARS‐CoV‐2 variants of concern elicit divergent early immune responses in hACE2 transgenic mice

“…These findings may contribute toward a more comprehensive understanding of prophylactic vaccine efficacy. Furthermore, our data contribute to the basic understanding of early postexposure immune responses to SARS‐CoV‐2 infection, which is critical to improve our knowledge about early predictors of disease severity and the prevention of hospitalization of patients [79].…”

Immune cell populations and induced immune responses at admission in patients hospitalized with vaccine breakthrough SARS-CoV-2 infections

“…In addition, we retrospectively assessed clinical outcomes for the whole hospitalization period and evaluated mortality 90 days after admission. The characteristics of the complete COVIMUN cohort have been described elsewhere ( 15 ).…”

“…We investigated nine different cytokines in each supernatant using a Luminex 200 instrument (LX200, R&D Systems, BIO-Techne LTD, Abingdon, UK): interleukin (IL) -1β, IL-6, IL-8, IL-10, IL-12, IL-17A, interferon (IFN)-α, IFN-γ and tumor necrosis factor (TNF)-α. The selection of cytokine panel has been described in our previously published paper ( 15 ). Reference values for cytokine release from healthy individuals were available for comparison.…”