ABSTRACT
Post-acute lung sequelae of COVID-19 are challenging many survivors across the world, yet the mechanisms behind are poorly understood. Our results delineate an inflammatory cascade of events occurring along disease progression within fibrovascular niches. It is initiated by endothelial dysfunction, followed by heme scavenging of CD163+ macrophages and production of CCL18. This chemokine synergizes with local CCL21 upregulation to influence the stromal composition favoring endothelial to mesenchymal transition. The local immune response is further modulated via recruitment of CCR7+ T cells into the expanding fibrovascular niche and imprinting an exhausted, T follicular helper-like phenotype in these cells. Eventually, this culminates in the formation of tertiary lymphoid structures, further perpetuating chronic inflammation. Thus, our work presents misdirected immune-stromal interaction mechanisms promoting a self-sustained and non-resolving local immune response that extends beyond active viral infection and leads to profound tissue repurposing and chronic inflammation.
ABSTRACT
BackgroundAcute kidney injury (AKI) occurs frequently in critically ill patients and is associated with adverse outcomes. Cellular mechanisms underlying AKI and kidney cell responses to injury remain incompletely understood. MethodsWe performed single-nuclei transcriptomics, bulk transcriptomics, molecular imaging studies, and conventional histology on kidney tissues from 8 individuals with severe AKI (stage 2 or 3 according to Kidney Disease: Improving Global Outcomes (KDIGO) criteria). Specimens were obtained within 1-2 hours after individuals had succumbed to critical illness associated with respiratory infections, with 4 of 8 individuals diagnosed with COVID-19. Control kidney tissues were obtained post-mortem or after nephrectomy from individuals without AKI. ResultsHigh-depth single cell-resolved gene expression data of human kidneys affected by AKI revealed enrichment of novel injury-associated cell states within the major cell types of the tubular epithelium, in particular in proximal tubules, thick ascending limbs and distal convoluted tubules. Four distinct, hierarchically interconnected injured cell states were distinguishable and characterized by transcriptome patterns associated with oxidative stress, hypoxia, interferon response, and epithelial-to-mesenchymal transition, respectively. Transcriptome differences between individuals with AKI were driven primarily by the cell type-specific abundance of these four injury subtypes rather than by private molecular responses. AKI-associated changes in gene expression between individuals with and without COVID-19 were similar. ConclusionThe study provides an extensive resource of the cell type-specific transcriptomic responses associated with critical illness-associated AKI in humans, highlighting recurrent disease-associated signatures and inter-individual heterogeneity. Personalized molecular disease assessment in human AKI may foster the development of tailored therapies.
ABSTRACT
The commensal microflora is a source for multiple antigens that may induce cross-reactive antibodies against host proteins and pathogens. However, whether commensal bacteria can induce cross-reactive antibodies against SARS-CoV-2 remains unknown. Here we report that several commensal bacteria contribute to the generation of cross-reactive IgA antibodies against the receptor-binding domain (RBD) of the SARS-CoV-2 Spike protein. We identified SARS-CoV-2 unexposed individuals with RBD-binding IgA antibodies at their mucosal surfaces. Conversely, neutralising monoclonal anti-RBD antibodies recognised distinct commensal bacterial species. Some of these bacteria, such as Streptococcus salivarius, induced a cross-reactive anti-RBD antibodies upon supplementation in mice. Conversely, severely ill COVID-19 patients showed reduction of Streptococcus and Veillonella in their oropharynx and feces and a reduction of anti-RBD IgA at mucosal surfaces. Altogether, distinct microbial species of the human microbiota can induce secretory IgA antibodies cross-reactive for the RBD of SARS-CoV-2.
ABSTRACT
Global healthcare systems are challenged by the COVID-19 pandemic. There is a need to optimize allocation of treatment and resources in intensive care, as clinically established risk assessments such as SOFA and APACHE II scores show only limited performance for predicting the survival of severely ill COVID-19 patients. Comprehensively capturing the host physiology, we speculated that proteomics in combination with new data-driven analysis strategies could produce a new generation of prognostic discriminators. We studied two independent cohorts of patients with severe COVID-19 who required intensive care and invasive mechanical ventilation. SOFA score, Charlson comorbidity index and APACHE II score were poor predictors of survival. Plasma proteomics instead identified 14 proteins that showed concentration trajectories different between survivors and non-survivors. A proteomic predictor trained on single samples obtained at the first time point at maximum treatment level (i.e. WHO grade 7) and weeks before the outcome, achieved accurate classification of survivors in an exploratory (AUROC 0.81) as well as in the independent validation cohort (AUROC of 1.0). The majority of proteins with high relevance in the prediction model belong to the coagulation system and complement cascade. Our study demonstrates that predictors derived from plasma protein levels have the potential to substantially outperform current prognostic markers in intensive care. Trial registrationGerman Clinical Trials Register DRKS00021688
ABSTRACT
COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. There is an urgent need for predictive markers that can guide clinical decision-making, inform about the effect of experimental therapies, and point to novel therapeutic targets. Here, we characterize the time-dependent progression of COVID-19 through different stages of the disease, by measuring 86 accredited diagnostic parameters and plasma proteomes at 687 sampling points, in a cohort of 139 patients during hospitalization. We report that the time-resolved patient molecular phenotypes reflect an initial spike in the systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution and immunomodulation. Further, we show that the early host response is predictive for the disease trajectory and gives rise to proteomic and diagnostic marker signatures that classify the need for supplemental oxygen therapy and mechanical ventilation, and that predict the time to recovery of mildly ill patients. In severely ill patients, the molecular phenotype of the early host response predicts survival, in two independent cohorts and weeks before outcome. We also identify age-specific molecular response to COVID-19, which involves increased inflammation and lipoprotein dysregulation in older patients. Our study provides a deep and time resolved molecular characterization of COVID-19 disease progression, and reports biomarkers for risk-adapted treatment strategies and molecular disease monitoring. Our study demonstrates accurate prognosis of COVID-19 outcome from proteomic signatures recorded weeks earlier.
