Early and rapid identification of COVID-19 patients with neutralizing type I-interferon auto-antibodies by an easily implementable algorithm

PurposeSix-19% of critically ill COVID-19 patients display circulating auto-antibodies against type I interferons (IFN-AABs). Here, we establish a clinically applicable strategy for early identification of IFN-AAB-positive patients for potential subsequent clinical interventions. MethodsWe analysed sera of 430 COVID-19 patients with severe and critical disease from four hospitals for presence of IFN-AABs by ELISA. Binding specificity and neutralizing activity were evaluated via competition assay and virus-infection-based neutralization assay. We defined clinical parameters associated with IFN-AAB positivity. In a subgroup of critically ill patients, we analyzed effects of therapeutic plasma exchange (TPE) on the levels of IFN-AABs, SARS-CoV-2 antibodies and clinical outcome. ResultsThe prevalence of neutralizing AABs to IFN- and IFN-{omega} in COVID-19 patients was 4.2% (18/430), while being undetectable in an uninfected control cohort. Neutralizing IFN-AABs were detectable exclusively in critically affected, predominantly male (83%) patients (7.6% IFN- and 4.6% IFN-{omega} in 207 patients with critical COVID-19). IFN-AABs were present early post-symptom onset and at the peak of disease. Fever and oxygen requirement at hospital admission co-presented with neutralizing IFN-AAB positivity. IFN-AABs were associated with higher mortality (92.3% versus 19.1 % in patients without IFN-AABs). TPE reduced levels of IFN-AABs in three of five patients and may increase survival of IFN-AAB-positive patients compared to those not undergoing TPE. ConclusionIFN-AABs may serve as early biomarker for development of severe COVID-19. We propose to implement routine screening of hospitalized COVID-19 patients according to our algorithm for rapid identification of patients with IFN-AABs who most likely benefit from specific therapies.

Severity of respiratory failure and computed chest tomography in acute COVID-19 correlates with pulmonary function and respiratory symptoms after infection with SARS-CoV-2: an observational longitudinal study over 12 months

BackgroundProspective and longitudinal data on pulmonary injury over one year after acute coronavirus disease 2019 (COVID-19) are sparse. Research questionWith this study, we aim to investigate pulmonary outcome following SARS-CoV-2 infection including pulmonary function, computed chest tomography, respiratory symptoms and quality of life over 12 months. Study design and Methods180 patients after acute COVID-19 were enrolled into a single-centre, prospective observational study and examined 6 weeks, 3, 6 and 12 months after onset of COVID-19 symptoms. Chest CT-scans, pulmonary function and symptoms assessed by St. Georges Respiratory Questionnaire were used to evaluate objective and subjective respiratory limitations. Patients were stratified according to acute COVID-19 disease severity. ResultsOf 180 patients enrolled, 42/180 were not hospitalized during acute SARS-CoV-2 infection, 29/180 were hospitalized without need for oxygen, 43/180 with need for low-flow and 24/180 with high-flow oxygen, 26/180 required invasive mechanical ventilation and 16/180 were treated with ECMO. After acute COVID-19, pulmonary restriction and reduced carbon monoxide diffusion capacity was associated with disease severity after the acute phase and improved over 12 months except for those requiring ECMO treatment. Patients with milder disease showed a predominant reduction of ventilated area instead of simple restriction. The CT score of lung involvement in the acute phase increased significantly with COVID-19 severity and was associated with restriction and reduction in diffusion capacity in follow-up. Respiratory symptoms improved for patients in higher severity groups during follow-up, but not for patients with mild initially disease. InterpretationSeverity of respiratory failure during COVID-19 correlates with the degree of pulmonary function impairment and respiratory quality of life in the year after acute infection. Patients with mild vs. severe disease show different patterns of lung involvement and symptom resolution. Clinical Trial RegistrationThe study is registered at the German registry for clinical studies (DRKS00021688)

New susceptibility loci for severe COVID-19 by detailed GWAS analysis in European populations

Given the highly variable clinical phenotype of Coronavirus disease 2019 (COVID-19), a deeper analysis of the host genetic contribution to severe COVID-19 is important to improve our understanding of underlying disease mechanisms. Here, we describe an extended GWAS meta-analysis of a well-characterized cohort of 3,260 COVID-19 patients with respiratory failure and 12,483 population controls from Italy, Spain, Norway and Germany/Austria, including stratified analyses based on age, sex and disease severity, as well as targeted analyses of chromosome Y haplotypes, the human leukocyte antigen (HLA) region and the SARS-CoV-2 peptidome. By inversion imputation, we traced a reported association at 17q21.31 to a highly pleiotropic [~]0.9-Mb inversion polymorphism and characterized the potential effects of the inversion in detail. Our data, together with the 5th release of summary statistics from the COVID-19 Host Genetics Initiative, also identified a new locus at 19q13.33, including NAPSA, a gene which is expressed primarily in alveolar cells responsible for gas exchange in the lung.

A proteomic survival predictor for COVID-19 patients in intensive care

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

Complement activation induces excessive T cell cytotoxicity in severe COVID-19

Severe COVID-19 is linked to both dysfunctional immune response and unrestrained immunopathogenesis, and it remains unclear if T cells also contribute to disease pathology. Here, we combined single-cell transcriptomics and proteomics with mechanistic studies to assess pathogenic T cell functions and inducing signals. We identified highly activated, CD16+ T cells with increased cytotoxic functions in severe COVID-19. CD16 expression enabled immune complex-mediated, T cell receptor-independent degranulation and cytotoxicity not found in other diseases. CD16+ T cells from COVID-19 patients promoted microvascular endothelial cell injury and release of neutrophil and monocyte chemoattractants. CD16+ T cell clones persisted beyond acute disease maintaining their cytotoxic phenotype. Age-dependent generation of C3a in severe COVID-19 induced activated CD16+ cytotoxic T cells. The proportion of activated CD16+ T cells and plasma levels of complement proteins upstream of C3a correlated with clinical outcome of COVID-19, supporting a pathological role of exacerbated cytotoxicity and complement activation in COVID-19.

Reactogenicity of homologous and heterologous prime-boost immunization with BNT162b2 and ChAdOx1-nCoV19: a prospective cohort study

Heterologous prime-boost vaccination is of increasing interest for COVID-19 vaccines. Evidence of rare thrombotic events associated with ChAdOx1-nCoV19 (Vaxzevria, ChAdOx) has lead several European countries to recommend a heterologous booster with mRNA vaccines for certain age groups (e.g. persons <60years in Germany), who have already received one dose of ChAdOx, although data on reactogenicity and safety of this vaccination regimen are still missing. Here we report reactogenicity data of homologous BNT162b2 (Comirnaty, BNT) or heterologous ChAdOx/BNT prime-boost immunisations in a prospective observational cohort study of 326 healthcare workers. Reactogenicity of heterologous ChAdOx/BNT booster vaccination was largely comparable to homologous BNT/BNT vaccination and overall well-tolerated. No major differences were observed in the frequency or severity of local reactions after either of the vaccinations. In contrast, notable differences between the regimens were observed for systemic reactions, which were most frequent after prime immunisation with ChAdOx (86%, 95CI: 79-91), and less frequent after homologous BNT/BNT (65%, 95CI: 56-72), or heterologous ChAdOx/BNT boosters (48%, 95CI: 36-59). This interim analysis supports the safety of currently recommended heterologous ChAdOx/BNT prime-boost immunisations with 12-week intervals.

HLA-C* 04:01 is a Genetic Risk Allele for Severe Course of COVID-19

BackgroundSince the beginning of the coronavirus disease 2019 (COVID-19) pandemic, there has been increasing demand to identify predictors of severe clinical course in patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Human leukocyte antigen alleles (HLA) have been suggested as potential genetic host factors. We sought to evaluate this hypothesis by conducting an international multicenter study using HLA sequencing with subsequent independent validation. MethodsWe analyzed a total of 332 samples. First, we enrolled 233 patients in Germany, Spain, and Switzerland for HLA and whole exome sequencing. Furthermore, we validated our results in a public data set (United States, n=99). Patients older than 18 years presenting with COVID-19 were included, representing the full spectrum of the disease. HLA candidate alleles were identified in the derivation cohort (n=92) and tested in two independent validation cohorts (n=240). ResultsWe identified HLA-C* 04:01 as a novel genetic predictor for severe clinical course in COVID-19. Carriers of HLA-C* 04:01 had twice the risk of intubation when infected with SARS-CoV-2 (hazard ratio 2.1, adjusted p-value=0.0036). Importantly, these findings were successfully replicated in an independent data set. Furthermore, our findings are biologically plausible, as HLA-C* 04:01 has fewer predicted bindings sites with relevant SARS-CoV-2 peptides as compared to other HLA alleles. Exome sequencing confirmed findings from HLA analysis. ConclusionsHLA-C* 04:01 carriage is associated with a twofold increased risk of intubation in patients infected with SARS-CoV-2. Testing for HLA-C* 04:01 could have clinical implications to identify high-risk patients and individualize management.

Clinical and Virological Characteristics of Hospitalized COVID-19 Patients in a German Tertiary Care Center during the First Wave of the SARS-CoV-2 Pandemic

BackgroundAdequate patient allocation is pivotal for optimal resource management in strained healthcare systems, and requires detailed knowledge of clinical and virological disease trajectories. MethodsA cohort of 168 hospitalized adult COVID-19 patients enrolled in a prospective observational study at a large European tertiary care center was analyzed. ResultsForty-four percent (71/161) of patients required invasive mechanical ventilation (IMV). Shorter duration of symptoms before admission (aOR 1.22 per day less, 95%CI 1.10-1.37, p<0.01), age 60-69 as compared to 18-59 years (aOR 4.33, 95%CI 1.07-20.10, p=0.04), and history of hypertension (aOR 5.55, 95%CI 2.00-16.82, p<0.01) were associated with need for IMV. Patients on IMV had higher maximal concentrations, slower decline rates, and longer shedding of SARS-CoV-2 than non-IMV patients (33 days, IQR 26-46.75, vs 18 days, IQR 16-46.75, respectively, p<0.01). Median duration of hospitalization was 9 days (IQR 6-15.5) for non-IMV and 49.5 days (IQR 36.8-82.5) for IMV-patients. ConclusionOur results indicate a short duration of symptoms before admission as a risk factor for severe disease and different viral load kinetics in severely affected patients.

A time-resolved proteomic and diagnostic map characterizes COVID-19 disease progression and predicts outcome

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.

Suppressive myeloid cells are a hallmark of severe COVID-19

Severe Acute Respiratory Syndrome - Coronavirus-2 (SARS-CoV-2) infection causes Coronavirus Disease 2019 (COVID-19), a mild to moderate respiratory tract infection in the majority of patients. A subset of patients, however, progresses to severe disease and respiratory failure with acute respiratory distress syndrome (ARDS). Severe COVID-19 has been associated with increased neutrophil counts and dysregulated immune responses. The mechanisms of protective immunity in mild forms and the pathogenesis of dysregulated inflammation in severe courses of COVID-19 remain largely unclear. Here, we combined two single-cell RNA-sequencing technologies and single-cell proteomics in whole blood and peripheral blood mononuclear cells (PBMC) to determine changes in immune cell composition and activation in two independent dual-center patient cohorts (n=46+n=54 COVID-19 samples), each with mild and severe cases of COVID-19. We observed a specific increase of HLA-DRhiCD11chi inflammatory monocytes that displayed a strong interferon (IFN)-stimulated gene signature in patients with mild COVID-19, which was absent in severe disease. Instead, we found evidence of emergency myelopoiesis, marked by the occurrence of immunosuppressive pre-neutrophils and immature neutrophils and populations of dysfunctional and suppressive mature neutrophils, as well as suppressive HLA-DRto monocytes in severe COVID-19. Our study provides detailed insights into systemic immune response to SARS-CoV-2 infection and it reveals profound alterations in the peripheral myeloid cell compartment associated with severe courses of COVID-19.

Studying the pathophysiology of coronavirus disease 2019 - a protocol for the Berlin prospective COVID-19 patient cohort (Pa- COVID-19)

PurposeSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread worldwide causing a global health emergency. Pa-COVID-19 aims to provide comprehensive data on clinical course, pathophysiology, immunology and outcome of COVID-19, in order to identify prognostic biomarkers, clinical scores, and therapeutic targets for improved clinical management and preventive interventions. MethodsPa-COVID-19 is a prospective observational cohort study of patients with confirmed SARS-CoV-2 infection treated at Charite - Universitatsmedizin Berlin. We collect data on epidemiology, demography, medical history, symptoms, clinical course, pathogen testing and treatment. Systematic, serial blood sampling will allow deep molecular and immunological phenotyping, transcriptomic profiling, and comprehensive biobanking. Longitudinal data and sample collection during hospitalization will be supplemented by long-term follow-up. ResultsOutcome measures include the WHO clinical ordinal scale on day 15 and clinical, functional and health-related quality of life assessments at discharge and during follow-up. We developed a scalable dataset to (i) suit national standards of care (ii) facilitate comprehensive data collection in medical care facilities with varying resources and (iii) allow for rapid implementation of interventional trials based on the standardized study design and data collection. We propose this scalable protocol as blueprint for harmonized data collection and deep phenotyping in COVID-19 in Germany. ConclusionWe established a basic platform for harmonized, scalable data collection, pathophysiological analysis, and deep phenotyping of COVID-19, which enables rapid generation of evidence for improved medical care and identification of candidate therapeutic and preventive strategies. The electronic database accredited for interventional trials allows fast trial implementation for candidate therapeutic agents.

Clinical classifiers of COVID-19 infection from novel ultra-high-throughput proteomics

The COVID-19 pandemic is an unprecedented global challenge. Highly variable in its presentation, spread and clinical outcome, novel point-of-care diagnostic classifiers are urgently required. Here, we describe a set of COVID-19 clinical classifiers discovered using a newly designed low-cost high-throughput mass spectrometry-based platform. Introducing a new sample preparation pipeline coupled with short-gradient high-flow liquid chromatography and mass spectrometry, our methodology facilitates clinical implementation and increases sample throughput and quantification precision. Providing a rapid assessment of serum or plasma samples at scale, we report 27 biomarkers that distinguish mild and severe forms of COVID-19, of which some may have potential as therapeutic targets. These proteins highlight the role of complement factors, the coagulation system, inflammation modulators as well as pro-inflammatory signalling upstream and downstream of Interleukin 6. Application of novel methodologies hence transforms proteomics from a research tool into a rapid-response, clinically actionable technology adaptable to infectious outbreaks. Highlights- A completely redesigned clinical proteomics platform increases throughput and precision while reducing costs. - 27 biomarkers are differentially expressed between WHO severity grades for COVID-19. - The study highlights potential therapeutic targets that include complement factors, the coagulation system, inflammation modulators as well as pro-inflammatory signalling both upstream and downstream of interleukin 6.