Highlights d Low avidity and broad cross-reactivities of pre-existing SARS-CoV-2 memory T cells d Strong CCCoV-specific memory CD4 + T cell responses in all analyzed individuals d SARS-CoV-2-specific CD4 + T cells in COVID-19 patients lack cross-reactivity to CCCoVs d Low avidity and clonality of SARS-CoV-2-specific T cell responses in severe COVID-19

Cardiac symptoms are increasingly recognized as late complications of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in previously well individuals with mild initial illness, but the underlying pathophysiology leading to long-term cardiac symptoms remains unclear. In this study, we conducted serial cardiac assessments in a selected population of individuals with Coronavirus Disease 2019 (COVID-19) with no previous cardiac disease or notable comorbidities by measuring blood biomarkers of heart injury or dysfunction and by performing magnetic resonance imaging. Baseline measurements from 346 individuals with COVID-19 (52% females) were obtained at a median of 109 days (interquartile range (IQR), 77–177 days) after infection, when 73% of participants reported cardiac symptoms, such as exertional dyspnea (62%), palpitations (28%), atypical chest pain (27%) and syncope (3%). Symptomatic individuals had higher heart rates and higher imaging values or contrast agent accumulation, denoting inflammatory cardiac involvement, compared to asymptomatic individuals. Structural heart disease or high levels of biomarkers of cardiac injury or dysfunction were rare in symptomatic individuals. At follow-up (329 days (IQR, 274–383 days) after infection), 57% of participants had persistent cardiac symptoms. Diffuse myocardial edema was more pronounced in participants who remained symptomatic at follow-up as compared to those who improved. Female gender and diffuse myocardial involvement on baseline imaging independently predicted the presence of cardiac symptoms at follow-up. Ongoing inflammatory cardiac involvement may, at least in part, explain the lingering cardiac symptoms in previously well individuals with mild initial COVID-19 illness.

Coronavirus disease 2019 (COVID-19) displays high clinical variability but the parameters that determine disease severity are still unclear. Pre-existing T cell memory has been hypothesized as a protective mechanism but conclusive evidence is lacking. Here we demonstrate that all unexposed individuals harbor SARS-CoV-2-specific memory T cells with marginal cross-reactivity to common cold corona and other unrelated viruses. They display low functional avidity and broad protein target specificities and their frequencies correlate with the overall size of the CD4+ memory compartment reflecting the immunological age of an individual. COVID-19 patients have strongly increased SARS-CoV-2-specific inflammatory T cell responses that are correlated with severity. Strikingly however, patients with severe COVID-19 displayed lower TCR functional avidity and less clonal expansion. Our data suggest that a low avidity pre-existing T cell memory negatively impacts on the T cell response quality against neoantigens such as SARS-CoV-2, which may predispose to develop inappropriate immune reactions especially in the elderly. We propose the immunological age as an independent risk factor to develop severe COVID-19.

Background Antibody detection of SARS-CoV-2 requires an understanding of its variation, course, and duration. Methods Antibody response to SARS-CoV-2 was evaluated over 5-430 days on 828 samples across COVID-19 severity levels, for total antibody (TAb), IgG, IgA, IgM, neutralizing antibody (NAb), antibody avidity, and for receptor-binding-domain (RBD), spike (S), or nucleoprotein (N). Specificity was determined on 676 pre-pandemic samples. Results Sensitivity at 30-60 days post symptom onset (pso) for TAb-S/RBD, TAb-N, IgG-S, IgG-N, IgA-S, IgM-RBD, and NAb was 96.6%, 99.5%, 89.7%, 94.3%, 80.9%, 76.9% and 92.8%, respectively. Follow-up 430 days pso revealed: TAb-S/RBD increased slightly (100.0%); TAb-N decreased slightly (97.1%); IgG-S and IgA-S decreased moderately (81.4%, 65.7%); NAb remained positive (94.3%), slightly decreasing in activity after 300 days; there was correlation with IgG-S (Rs=0.88) and IgA-S (Rs=0.71); IgG-N decreased significantly from day 120 (15.7%); IgM-RBD dropped after 30-60 days (22.9%). High antibody avidity developed against S/RBD steadily with time in 94.3% of patients after 430 days. This correlated with persistent antibody detection depending on antibody-binding efficiency of the test design. Severe COVID-19 correlated with earlier and higher antibody response, mild COVID-19 was heterogeneous with a wide range of antibody reactivities. Specificity of the tests was ≥99%, except for IgA (96%). Conclusion Sensitivity of anti-SARS-CoV-2 assays was determined by test design, target antigen, antibody avidity, and COVID-19 severity. Sustained antibody detection was mainly determined by avidity progression for RBD and S. Testing by TAb and for S/RBD provided the highest sensitivity and longest detection duration of 14 months so far.

Background At the entry site of respiratory virus infections, the oropharyngeal microbiome has been proposed as a major hub integrating viral and host immune signals. Early studies suggested that infections with Coronavirus 2 (SARS-CoV-2) are associated with changes of the upper and lower airway microbiome, and that specific microbial signatures may predict COVID-19 illness. However, the results are not conclusive, as critical illness can drastically alter a patient’s microbiome through multiple confounders. Methods To study oropharyngeal microbiome profiles in SARS-CoV-2 infection, clinical confounders, and prediction models in COVID-19, we performed a multi-center, cross-sectional clinical study analyzing oropharyngeal microbial metagenomes in healthy adults, patients with non-SARS-CoV-2 infections, or with mild, moderate and severe COVID-19 (n=322 participants). Results In contrast to mild infections, patients admitted to a hospital with moderate or severe COVID-19 showed dysbiotic microbial configurations, which were significantly pronounced in patients treated with broad-spectrum antibiotics, receiving invasive mechanical ventilation, or when sampling was performed during prolonged hospitalization. In contrast, specimens collected early after admission allowed us to segregate microbiome features predictive of hospital COVID-19 mortality utilizing machine learning models. Taxonomic signatures were found to perform better than models utilizing clinical variables with Neisseria and Haemophilus species abundances as most important features. Conclusion In addition to the infection per se, several factors shape the oropharyngeal microbiome of severely affected COVID-19 patients and deserve consideration in the interpretation of the role of the microbiome in severe COVID-19. Nevertheless, we were able to extract microbial features that can help to predict clinical outcomes.

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Since its first detection in China in late 2019 the novel coronavirus SARS-CoV-2 and the associated infectious disease COVID-19 continue to have a major impact on global health care and clinical practice. Cancer patients, in particular those with haematological malignancies, seem to be at an increased risk for a severe course of infection. Deliberations to avoid or defer potentially immunosuppressive therapies in these patients need to be balanced against the overarching goal of providing optimal antineoplastic treatment. This poses a unique challenge to treating physicians. This guideline provides evidence-based recommendations regarding prevention, diagnostics and treatment of SARS-CoV-2 infection and COVID-19 as well as strategies towards safe antineoplastic care during the COVID-19 pandemic. It was prepared by the Infectious Diseases Working Party (AGIHO) of the German Society for Haematology and Medical Oncology (DGHO) by critically reviewing the currently available data on SARS-CoV-2 and COVID-19 in cancer patients applying evidence-based medicine criteria.

The German government initiated the Network University Medicine (NUM) in early 2020 to improve national research activities on the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic. To this end, 36 German Academic Medical Centers started to collaborate on 13 projects, with the largest being the National Pandemic Cohort Network (NAPKON). The NAPKON’s goal is creating the most comprehensive Coronavirus Disease 2019 (COVID-19) cohort in Germany. Within NAPKON, adult and pediatric patients are observed in three complementary cohort platforms (Cross-Sectoral, High-Resolution and Population-Based) from the initial infection until up to three years of follow-up. Study procedures comprise comprehensive clinical and imaging diagnostics, quality-of-life assessment, patient-reported outcomes and biosampling. The three cohort platforms build on four infrastructure core units (Interaction, Biosampling, Epidemiology, and Integration) and collaborations with NUM projects. Key components of the data capture, regulatory, and data privacy are based on the German Centre for Cardiovascular Research. By April 01, 2022, 34 university and 40 non-university hospitals have enrolled 5298 patients with local data quality reviews performed on 4727 (89%). 47% were female, the median age was 52 (IQR 36–62-) and 50 pediatric cases were included. 44% of patients were hospitalized, 15% admitted to an intensive care unit, and 12% of patients deceased while enrolled. 8845 visits with biosampling in 4349 patients were conducted by April 03, 2022. In this overview article, we summarize NAPKON’s design, relevant milestones including first study population characteristics, and outline the potential of NAPKON for German and international research activities.Trial registrationhttps://clinicaltrials.gov/ct2/show/NCT04768998.https://clinicaltrials.gov/ct2/show/NCT04747366.https://clinicaltrials.gov/ct2/show/NCT04679584