Human in vivo neuroimaging to detect reprogramming of the cerebral immune response following repeated systemic inflammation

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Monocytic HLA-DR expression kinetics in septic shock patients with different pathogens, sites of infection and adverse outcomes

Abstract Background Decreased monocytic (m)HLA-DR expression is the most studied biomarker of sepsis-induced immunosuppression. To date, little is known about the relationship between sepsis characteristics, such as the site of infection, causative pathogen, or severity of disease, and mHLA-DR expression kinetics. Methods We evaluated mHLA-DR expression kinetics in 241 septic shock patients with different primary sites of infection and pathogens. Furthermore, we used unsupervised clustering analysis to identify mHLA-DR trajectories and evaluated their association with outcome parameters. Results No differences in mHLA-DR expression kinetics were found between groups of patients with different sites of infection (abdominal vs. respiratory, p = 0.13; abdominal vs. urinary tract, p = 0.53) and between pathogen categories (Gram-positive vs. Gram-negative, p = 0.54; Gram-positive vs. negative cultures, p = 0.84). The mHLA-DR expression kinetics differed between survivors and non-survivors ( p < 0.001), with an increase over time in survivors only. Furthermore, we identified three mHLA-DR trajectories (‘early improvers’, ‘delayed or non-improvers’ and ‘decliners’). The probability for adverse outcome (secondary infection or death) was higher in the delayed or non-improvers and decliners vs. the early improvers (delayed or non-improvers log-rank p = 0.03, adjusted hazard ratio 2.0 [95% CI 1.0–4.0], p = 0.057 and decliners log-rank p = 0.01, adjusted hazard ratio 2.8 [95% CI 1.1–7.1], p = 0.03). Conclusion Sites of primary infection or causative pathogens are not associated with mHLA-DR expression kinetics in septic shock patients. However, patients showing delayed or no improvement in or a declining mHLA-DR expression have a higher risk for adverse outcome compared with patients exhibiting a swift increase in mHLA-DR expression. Our study signifies that changes in mHLA-DR expression over time, and not absolute values or static measurements, are of clinical importance in septic shock patients

Longitudinal Multi-omics Analyses Identify Responses of Megakaryocytes, Erythroid Cells, and Plasmablasts as Hallmarks of Severe COVID-19.

Temporal resolution of cellular features associated with a severe COVID-19 disease trajectory is needed for understanding skewed immune responses and defining predictors of outcome. Here, we performed a longitudinal multi-omics study using a two-center cohort of 14 patients. We analyzed the bulk transcriptome, bulk DNA methylome, and single-cell transcriptome (>358,000 cells, including BCR profiles) of peripheral blood samples harvested from up to 5 time points. Validation was performed in two independent cohorts of COVID-19 patients. Severe COVID-19 was characterized by an increase of proliferating, metabolically hyperactive plasmablasts. Coinciding with critical illness, we also identified an expansion of interferon-activated circulating megakaryocytes and increased erythropoiesis with features of hypoxic signaling. Megakaryocyte- and erythroid-cell-derived co-expression modules were predictive of fatal disease outcome. The study demonstrates broad cellular effects of SARS-CoV-2 infection beyond adaptive immune cells and provides an entry point toward developing biomarkers and targeted treatments of patients with COVID-19

Disease severity-specific neutrophil signatures in blood transcriptomes stratify COVID-19 patients

Background!#!The SARS-CoV-2 pandemic is currently leading to increasing numbers of COVID-19 patients all over the world. Clinical presentations range from asymptomatic, mild respiratory tract infection, to severe cases with acute respiratory distress syndrome, respiratory failure, and death. Reports on a dysregulated immune system in the severe cases call for a better characterization and understanding of the changes in the immune system.!##!Methods!#!In order to dissect COVID-19-driven immune host responses, we performed RNA-seq of whole blood cell transcriptomes and granulocyte preparations from mild and severe COVID-19 patients and analyzed the data using a combination of conventional and data-driven co-expression analysis. Additionally, publicly available data was used to show the distinction from COVID-19 to other diseases. Reverse drug target prediction was used to identify known or novel drug candidates based on finding from data-driven findings.!##!Results!#!Here, we profiled whole blood transcriptomes of 39 COVID-19 patients and 10 control donors enabling a data-driven stratification based on molecular phenotype. Neutrophil activation-associated signatures were prominently enriched in severe patient groups, which was corroborated in whole blood transcriptomes from an independent second cohort of 30 as well as in granulocyte samples from a third cohort of 16 COVID-19 patients (44 samples). Comparison of COVID-19 blood transcriptomes with those of a collection of over 3100 samples derived from 12 different viral infections, inflammatory diseases, and independent control samples revealed highly specific transcriptome signatures for COVID-19. Further, stratified transcriptomes predicted patient subgroup-specific drug candidates targeting the dysregulated systemic immune response of the host.!##!Conclusions!#!Our study provides novel insights in the distinct molecular subgroups or phenotypes that are not simply explained by clinical parameters. We show that whole blood transcriptomes are extremely informative for COVID-19 since they capture granulocytes which are major drivers of disease severity