ABSTRACT
Resting memory B-cells can be divided into classical and non-classical groups based on differential expression of markers such as CD27 and CD11c, while activated memory B-cells express a combination of markers, making their ontogeny hard to determine. Here by longitudinal analysis of COVID-19, bacterial sepsis, and BNT162b2 mRNA vaccine recipients by mass cytometry and CITE-seq we describe a three-branch structure of resting B-cell memory consisting of “classical” CD45RB+ memory and two branches of CD45RBlo memory further defined by expression of CD23 and CD11c respectively. Stable differences in CD45RB upon activation allowed tracking of activated B-cells and plasmablasts derived from CD45RB+ classical and CD45RBlo non-classical memory B-cells. In both COVID-19 patients and mRNA vaccination, CD45RBlo B-cells formed the majority of SARS-CoV2 specific memory B-cells and correlated with serum antibodies while CD45RB+ memory was most strongly activated by bacterial Sepsis. These results suggest that diverse non-classical CD45RBlo memory B-cells consisting of branches of CD11c+Tbet+ and CD23+ fractions form a critical part of responses to viral infection and vaccination.
Subject(s)
Sepsis , Virus Diseases , COVID-19ABSTRACT
Background: Although the development of vaccines has considerably reduced the severity of COVID-19, its incidence is still high. Hence, a targeted approach based on RNA endotypes of a population should be developed to help design biomarker-based therapies for COVID-19. Objectives: We evaluated the major RNAs transcribed in blood cells during COVID-19 using PCR to further elucidate its pathogenesis and determine predictive phenotypes in COVID-19 patients. Study design: In a discovery cohort of 40 patients with COVID-19, 26,354 RNAs were measured on day 1 and day 7. Five RNAs associated with disease severity and prognosis were derived. In a validation cohort of 153 patients with COVID-19 treated in the intensive care unit, we focused on prolactin (PRL), and toll-like receptor 3 (TLR3) among RNAs, which have a strong association with prognosis, and evaluated the accuracy for predicting survival of PRL-to-TL3 ratios (PRL/TLR3) with the areas under the ROC curves (AUC). The validation cohort was divided into two groups based on the cut-off value in the ROC curve with the maximum AUC. The two groups were defined by high PRL/TLR3 (n=47) and low PRL/TLR3 groups (n=106) and the clinical outcomes were compared. Results: In the validation cohort, the AUC for PRL/TLR3 was 0.79, showing superior prognostic ability compared to severity scores such as APACHE II and SOFA. The high PRL/TLR3 group had a significantly higher 28-day mortality than the low PRL/TLR3 group (17.0% vs 0.9%, P<0.01). Conclusions: A new RNA endotype classified using high PRL/TLR3 was associated with mortality in COVID-19 patients.
Subject(s)
COVID-19ABSTRACT
A cytokine storm induces acute respiratory distress syndrome, the main cause of death in coronavirus disease 2019 (COVID-19) patients. However, the detailed mechanisms of cytokine induction due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remain unclear. To examine the cytokine production in COVID-19, we mimicked the disease in SARS-CoV-2-infected alveoli by adding the lysate of SARS-CoV-2-infected cells to cultured macrophages or induced pluripotent stem cell-derived myeloid cells. The cells secreted interleukin (IL)-6 after the addition of SARS-CoV-2-infected cell lysate. Screening of 25 SARS-CoV-2 protein-expressing plasmids revealed that the N protein-coding plasmid alone induced IL-6 production. The addition of anti-N antibody further enhanced IL-6 production, but the F(ab’)2 fragment did not. Sera from COVID-19 patients also enhanced IL-6 production, and sera from patients with severer disease induced higher levels of IL-6. These results suggest that anti-N antibody promotes IL-6 production in SARS-CoV-2-infected alveoli, leading to the cytokine storm of COVID-19. (150 words)
Subject(s)
COVID-19ABSTRACT
Background: Resistin increases in septic subjects and is associated with severity and prognosis. Its role in Coronavirus disease 2019 (COVID-19) is unknown. We investigated relationships between resistin and the severity, prognosis and time to wean off mechanical ventilation (MV) in two cohorts. Methods: : Plasma resistin was available for 306 mild-to-critical COVID-19 patients on days 1, 4 and 8 from the Massachusetts General Hospital Emergency Department COVID-19 (MGH) cohort public proteomics data. The relationship between resistin and severity (World Health Organization COVID-19 outcomes) and the prognosis were evaluated. A cohort of 62 critical COVID-19 patients (Osaka cohort) was used to evaluate the relationship between resistin on days 1 (day of ICU admission), 2–3, 6–8 and 11–15 and the prognosis and time to wean off MV. Correlations among resistin, inflammatory cytokines and endothelial damage markers were evaluated. Results: : In the MGH cohort, day 1 resistin was associated with severity and predicted the prognosis in an ROC analysis (AUC, 0.739; 95% CI, 0.659–0.819). Twenty-eight-day non-survivors showed significantly greater resistin levels than 28-day survivors on days 1, 4 and 8. In the Osaka cohort, a Cox proportional hazards model (time dependent) showed a significant relationship between resistin and time to wean off MV (crude hazard ratio, 0.702 [95% CI, 0.508–0.969]). Resistin formed a network with inflammatory cytokines and endothelial damage markers. Conclusions: : Resistin was associated with severity, prognosis and time to wean off MV in COVID-19 patients. Resistin formed a network with inflammatory cytokines and endothelial damage markers, suggesting its contribution to the pathogenesis of COVID-19.