CD74 is a functional MIF receptor on activated CD4+ T cells.

Next to its classical role in MHC II-mediated antigen presentation, CD74 was identified as a high-affinity receptor for macrophage migration inhibitory factor (MIF), a pleiotropic cytokine and major determinant of various acute and chronic inflammatory conditions, cardiovascular diseases and cancer. Recent evidence suggests that CD74 is expressed in T cells, but the functional relevance of this observation is poorly understood. Here, we characterized the regulation of CD74 expression and that of the MIF chemokine receptors during activation of human CD4+ T cells and studied links to MIF-induced T-cell migration, function, and COVID-19 disease stage. MIF receptor profiling of resting primary human CD4+ T cells via flow cytometry revealed high surface expression of CXCR4, while CD74, CXCR2 and ACKR3/CXCR7 were not measurably expressed. However, CD4+ T cells constitutively expressed CD74 intracellularly, which upon T-cell activation was significantly upregulated, post-translationally modified by chondroitin sulfate and could be detected on the cell surface, as determined by flow cytometry, Western blot, immunohistochemistry, and re-analysis of available RNA-sequencing and proteomic data sets. Applying 3D-matrix-based live cell-imaging and receptor pathway-specific inhibitors, we determined a causal involvement of CD74 and CXCR4 in MIF-induced CD4+ T-cell migration. Mechanistically, proximity ligation assay visualized CD74/CXCR4 heterocomplexes on activated CD4+ T cells, which were significantly diminished after MIF treatment, pointing towards a MIF-mediated internalization process. Lastly, in a cohort of 30 COVID-19 patients, CD74 surface expression was found to be significantly upregulated on CD4+ and CD8+ T cells in patients with severe compared to patients with only mild disease course. Together, our study characterizes the MIF receptor network in the course of T-cell activation and reveals CD74 as a novel functional MIF receptor and MHC II-independent activation marker of primary human CD4+ T cells.

[Current Standards in the Treatment of Hodgkin Lymphoma]. / Aktuelle Standards in der Behandlung des Hodgkin Lymphoms.

This review discusses current trends in the treatment of Hodgkin lymphoma, focusing on optimizing therapy outcomes while minimizing toxicity. We summarize advances made by the incorporation of Brentuximab Vedotin into first line therapy for advanced stage Hodgkin lymphoma. Similarly, the incorporation of checkpoint-inhibition into first-line therapy holds great promise and early results suggest superior efficacy with reduced toxicity. In relapsed or refractory Hodgkin lymphoma, salvage chemotherapy followed by high-dose chemotherapy and autologous stem cell transplantation remains the standard approach. However, the remarkable efficacy of checkpoint inhibition in this setting has the potential to redefine treatment paradigms and obviate the need for HD-ASCT in select patients. Finally, we discuss the evolving landscape of nodular lymphocyte predominant Hodgkin lymphoma and reclassification to nodular lymphocyte predominant B-cell lymphoma, with increasing recognition of its distinct characteristics and treatment strategies.

[Targeted therapies in the management of malignant lymphoma - is the end of conventional chemotherapy near?] / Molekular zielgerichtete Therapien ­ brauchen wir überhaupt noch Chemotherapie?

Advances in the understanding of the biology of malignant lymphoma has facilitated the development of numerous molecularly targeted therapies. The incorporation of these precision therapeutics has produced more effective and often less-toxic treatment regimens leading to a significant improvement of treatment outcomes for individuals with lymphoid malignancies.In relapsed diseases, molecularly targeted therapeutic approaches have demonstrated superior outcomes compared to conventional chemotherapy, leading to a growing number of patients being treated entirely chemotherapy-free. This review outlines the current landscape of targeted therapies for both B-cell (B-NHL) and T-cell non-Hodgkin lymphomas (T-NHL) and provides an overview of targeted agents currently approved for the treatment of malignant lymphoma.

Analysis of acute COVID-19 including chronic morbidity: protocol for the deep phenotyping National Pandemic Cohort Network in Germany (NAPKON-HAP).

BACKGROUND: The severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) pandemic causes a high burden of acute and long-term morbidity and mortality worldwide despite global efforts in containment, prophylaxis, and therapy. With unprecedented speed, the global scientific community has generated pivotal insights into the pathogen and the host response evoked by the infection. However, deeper characterization of the pathophysiology and pathology remains a high priority to reduce morbidity and mortality of coronavirus disease 2019 (COVID-19). METHODS: NAPKON-HAP is a multi-centered prospective observational study with a long-term follow-up phase of up to 36 months post-SARS-CoV-2 infection. It constitutes a central platform for harmonized data and biospecimen for interdisciplinary characterization of acute SARS-CoV-2 infection and long-term outcomes of diverging disease severities of hospitalized patients. RESULTS: Primary outcome measures include clinical scores and quality of life assessment captured during hospitalization and at outpatient follow-up visits to assess acute and chronic morbidity. Secondary measures include results of biomolecular and immunological investigations and assessment of organ-specific involvement during and post-COVID-19 infection. NAPKON-HAP constitutes a national platform to provide accessibility and usability of the comprehensive data and biospecimen collection to global research. CONCLUSION: NAPKON-HAP establishes a platform with standardized high-resolution data and biospecimen collection of hospitalized COVID-19 patients of different disease severities in Germany. With this study, we will add significant scientific insights and provide high-quality data to aid researchers to investigate COVID-19 pathophysiology, pathology, and chronic morbidity.

Impaired immune responses and prolonged viral replication in lung allograft recipients infected with SARS-CoV-2 in the early phase after transplantation.

PURPOSE: Lung transplant recipients are at increased risk of severe disease following infection with severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) due to high-dose immunosuppressive drugs and the lung is the main organ affected by Coronavirus disease 2019 (COVID-19). Several studies have confirmed increased SARS-CoV-2-related mortality and morbidity in patients living with lung allografts; however, detailed immunological studies of patients with SARS-CoV-2 infection in the early phase following transplantation remain scarce. METHODS: We investigated patients who were infected with SARS-CoV-2 in the early phase (18-103 days) after receiving double-lung allografts (n = 4, LuTx) in comparison to immunocompetent patients who had not received solid organ transplants (n = 88, noTx). We analyzed SARS-CoV-2-specific antibody responses against the SARS-CoV-2 spike and nucleocapsid proteins using enzyme-linked immunosorbent assays (ELISA), chemiluminescence immunoassays (CLIA), and immunoblot assays. T cell responses were investigated using Elispot assays. RESULTS: One LuTx patient suffered from persistent infection with fatal outcome 122 days post-infection despite multiple interventions including remdesivir, convalescent plasma, and the monoclonal antibody bamlanivimab. Two patients experienced clinically mild disease with prolonged viral shedding (47 and 79 days), and one patient remained asymptomatic. Antibody and T cell responses were significantly reduced or undetectable in all LuTx patients compared to noTx patients. CONCLUSION: Patients in the early phase following lung allograft transplantation are vulnerable to infection with SARS-CoV-2 due to impaired immune responses. This patient population should be vaccinated before LuTx, protected from infection post-LuTx, and in case of infection treated generously with currently available interventions.

How to exclude pulmonary embolism in patients hospitalized with COVID-19: a comparison of predictive scores.

BACKGROUND: Pulmonary embolism (PE) is an important complication of Coronavirus disease 2019 (COVID-19). COVID-19 is associated with respiratory impairment and a pro-coagulative state, rendering PE more likely and difficult to recognize. Several decision algorithms relying on clinical features and D-dimer have been established. High prevalence of PE and elevated Ddimer in patients with COVID-19 might impair the performance of common decision algorithms. Here, we aimed to validate and compare five common decision algorithms implementing age adjusted Ddimer, the GENEVA, and Wells scores as well as the PEGeD- and YEARS-algorithms in patients hospitalized with COVID-19. METHODS: In this single center study, we included patients who were admitted to our tertiary care hospital in the COVID-19 Registry of the LMU Munich. We retrospectively selected patients who received a computed tomography pulmonary angiogram (CTPA) or pulmonary ventilation/perfusion scintigraphy (V/Q) for suspected PE. The performances of five commonly used diagnostic algorithms (age-adjusted D-dimer, GENEVA score, PEGeD-algorithm, Wells score, and YEARS-algorithm) were compared. RESULTS: We identified 413 patients with suspected PE who received a CTPA or V/Q confirming 62 PEs (15%). Among them, 358 patients with 48 PEs (13%) could be evaluated for performance of all algorithms. Patients with PE were older and their overall outcome was worse compared to patients without PE. Of the above five diagnostic algorithms, the PEGeD- and YEARS-algorithms performed best, reducing diagnostic imaging by 14% and 15% respectively with a sensitivity of 95.7% and 95.6%. The GENEVA score was able to reduce CTPA or V/Q by 32.2% but suffered from a low sensitivity (78.6%). Age-adjusted D-dimer and Wells score could not significantly reduce diagnostic imaging. CONCLUSION: The PEGeD- and YEARS-algorithms outperformed other tested decision algorithms and worked well in patients admitted with COVID-19. These findings need independent validation in a prospective study.

Vitronectin promotes immunothrombotic dysregulation in the venular microvasculature.

Microvascular immunothrombotic dysregulation is a critical process in the pathogenesis of severe systemic inflammatory diseases. The mechanisms controlling immunothrombosis in inflamed microvessels, however, remain poorly understood. Here, we report that under systemic inflammatory conditions the matricellular glycoproteinvitronectin (VN) establishes an intravascular scaffold, supporting interactions of aggregating platelets with immune cells and the venular endothelium. Blockade of the VN receptor glycoprotein (GP)IIb/IIIa interfered with this multicellular interplay and effectively prevented microvascular clot formation. In line with these experimental data, particularly VN was found to be enriched in the pulmonary microvasculature of patients with non-infectious (pancreatitis-associated) or infectious (coronavirus disease 2019 (COVID-19)-associated) severe systemic inflammatory responses. Targeting the VN-GPIIb/IIIa axis hence appears as a promising, already feasible strategy to counteract microvascular immunothrombotic dysregulation in systemic inflammatory pathologies.

Consistency as a Data Quality Measure for German Corona Consensus Items Mapped from National Pandemic Cohort Network Data Collections.

BACKGROUND: As a national effort to better understand the current pandemic, three cohorts collect sociodemographic and clinical data from coronavirus disease 2019 (COVID-19) patients from different target populations within the German National Pandemic Cohort Network (NAPKON). Furthermore, the German Corona Consensus Dataset (GECCO) was introduced as a harmonized basic information model for COVID-19 patients in clinical routine. To compare the cohort data with other GECCO-based studies, data items are mapped to GECCO. As mapping from one information model to another is complex, an additional consistency evaluation of the mapped items is recommended to detect possible mapping issues or source data inconsistencies. OBJECTIVES: The goal of this work is to assure high consistency of research data mapped to the GECCO data model. In particular, it aims at identifying contradictions within interdependent GECCO data items of the German national COVID-19 cohorts to allow investigation of possible reasons for identified contradictions. We furthermore aim at enabling other researchers to easily perform data quality evaluation on GECCO-based datasets and adapt to similar data models. METHODS: All suitable data items from each of the three NAPKON cohorts are mapped to the GECCO items. A consistency assessment tool (dqGecco) is implemented, following the design of an existing quality assessment framework, retaining their-defined consistency taxonomies, including logical and empirical contradictions. Results of the assessment are verified independently on the primary data source. RESULTS: Our consistency assessment tool helped in correcting the mapping procedure and reveals remaining contradictory value combinations within COVID-19 symptoms, vital signs, and COVID-19 severity. Consistency rates differ between the different indicators and cohorts ranging from 95.84% up to 100%. CONCLUSION: An efficient and portable tool capable of discovering inconsistencies in the COVID-19 domain has been developed and applied to three different cohorts. As the GECCO dataset is employed in different platforms and studies, the tool can be directly applied there or adapted to similar information models.

Thyroidal Angiotensin-Converting Enzyme 2 Protein Expression and Thyroid Function Tests in Patients with COVID-19: Results from a Retrospective Case Series and a Prospective Cohort Study.

Background: Infection with SARS-CoV-2 has initially been known as a respiratory disease but in the course of the pandemic the understanding has emerged that severity is owing to fatal inflammatory responses apart from lung injury. In this context, endocrine disorders such as thyroiditis as well as pituitary dysfunction in addition to nonthyroidal illness syndrome have been described. Furthermore, angiotensin-converting enzyme 2 (ACE2), the SARS-CoV-2 cell receptor, has been detected in most endocrine tissues, including the thyroid gland. Objective: To evaluate histopathologic changes and compare thyroidal ACE2 protein expression in thyroid tissue from patients who died from severe COVID-19 with thyroid tissue from patients without SARS-CoV-2 infection in a retrospective case series. Furthermore, to assess and compare alterations in thyroid function tests (TFTs) between patients with or without SARS-CoV-2 infection as well as association of TFTs with the severity of the disease in a prospective cohort study. Methods: Thyroid tissue of deceased COVID-19 patients (n = 23) was analyzed for histopathology and ACE2 expression by immunohistochemical staining. A total of 153 patients with confirmed SARS-CoV-2 were evaluated regarding TFTs and divided into a severe (intubation, intensive care treatment) and an intermediate group. Results: Thyroidal ACE2 expression was detected in 87% of the deceased COVID-19 patients. Normal thyroid tissue from patients without SARS-CoV-2 infection showed no ACE2 protein expression. Half of the severely ill COVID-19 patients had low free triiodothyronine (fT3) levels. Combination of low fT3 and thyrotropin (TSH) was associated significantly with deadly disease. Conclusion: The high percentage of positive ACE2 immunostaining in deceased patients compared with normal thyroid tissue of patients without SARS-CoV-2 infection suggests involvement of the thyroid in COVID-19, although further research will have to show the pathogenic role of thyroidal ACE2 in COVID-19. Abnormal fT3 and a TSH of ≤0.5 mU/L were associated with a fatal outcome in our severely ill SARS-CoV-2 patient cohort. Therefore, assessment of TFTs is crucial in the treatment of severely ill COVID-19 patients. Trial Registration: COVID-19 Registry of the LMU University Hospital Munich (CORKUM), WHO trial ID DRKS00021225.

Distinct and dynamic activation profiles of circulating dendritic cells and monocytes in mild COVID-19 and after yellow fever vaccination.

Dysregulation of the myeloid cell compartment is a feature of severe disease in hospitalized COVID-19 patients. Here, we investigated the response of circulating dendritic cell (DC) and monocyte subpopulations in SARS-CoV-2 infected outpatients with mild disease and compared it to the response of healthy individuals to yellow fever vaccine virus YF17D as a model of a well-coordinated response to viral infection. In SARS-CoV-2-infected outpatients circulating DCs were persistently reduced for several weeks whereas after YF17D vaccination DC numbers were decreased temporarily and rapidly replenished by increased proliferation until 14 days after vaccination. The majority of COVID-19 outpatients showed high expression of CD86 and PD-L1 in monocytes and DCs early on, resembling the dynamic after YF17D vaccination. In a subgroup of patients, low CD86 and high PD-L1 expression were detected in monocytes and DCs coinciding with symptoms, higher age, and lower lymphocyte counts. This phenotype was similar to that observed in severely ill COVID-19 patients, but less pronounced. Thus, prolonged reduction and dysregulated activation of blood DCs and monocytes were seen in a subgroup of symptomatic non-hospitalized COVID-19 patients while a transient coordinated activation was characteristic for the majority of patients with mild COVID-19 and the response to YF17D vaccination.

Proteomics reveals antiviral host response and NETosis during acute COVID-19 in high-risk patients.

SARS-CoV-2 remains an acute threat to human health, endangering hospital capacities worldwide. Previous studies have aimed at informing pathophysiologic understanding and identification of disease indicators for risk assessment, monitoring, and therapeutic guidance. While findings start to emerge in the general population, observations in high-risk patients with complex pre-existing conditions are limited. We addressed the gap of existing knowledge with regard to a differentiated understanding of disease dynamics in SARS-CoV-2 infection while specifically considering disease stage and severity. We biomedically characterized quantitative proteomics in a hospitalized cohort of COVID-19 patients with mild to severe symptoms suffering from different (co)-morbidities in comparison to both healthy individuals and patients with non-COVID related inflammation. Deep clinical phenotyping enabled the identification of individual disease trajectories in COVID-19 patients. By the use of the individualized disease phase assignment, proteome analysis revealed a severity dependent general type-2-centered host response side-by-side with a disease specific antiviral immune reaction in early disease. The identification of phenomena such as neutrophil extracellular trap (NET) formation and a pro-coagulatory response characterizing severe disease was successfully validated in a second cohort. Together with the regulation of proteins related to SARS-CoV-2-specific symptoms identified by proteome screening, we not only confirmed results from previous studies but provide novel information for biomarker and therapy development.

Statistical biases due to anonymization evaluated in an open clinical dataset from COVID-19 patients.

Anonymization has the potential to foster the sharing of medical data. State-of-the-art methods use mathematical models to modify data to reduce privacy risks. However, the degree of protection must be balanced against the impact on statistical properties. We studied an extreme case of this trade-off: the statistical validity of an open medical dataset based on the German National Pandemic Cohort Network (NAPKON), which was prepared for publication using a strong anonymization procedure. Descriptive statistics and results of regression analyses were compared before and after anonymization of multiple variants of the original dataset. Despite significant differences in value distributions, the statistical bias was found to be small in all cases. In the regression analyses, the median absolute deviations of the estimated adjusted odds ratios for different sample sizes ranged from 0.01 [minimum = 0, maximum = 0.58] to 0.52 [minimum = 0.25, maximum = 0.91]. Disproportionate impact on the statistical properties of data is a common argument against the use of anonymization. Our analysis demonstrates that anonymization can actually preserve validity of statistical results in relatively low-dimensional data.

Quantitation of SARS-CoV-2 neutralizing antibodies with a virus-free, authentic test.

Neutralizing antibodies (NAbs), and their concentration in sera of convalescents and vaccinees are a correlate of protection from COVID-19. The antibody concentrations in clinical samples that neutralize SARS-CoV-2 are difficult and very cumbersome to assess with conventional virus neutralization tests (cVNTs), which require work with the infectious virus and biosafety level 3 containment precautions. Alternative virus neutralization tests currently in use are mostly surrogate tests based on direct or competitive enzyme immunoassays or use viral vectors with the spike protein as the single structural component of SARS-CoV-2. To overcome these obstacles, we developed a virus-free, safe and very fast (4.5 h) in vitro diagnostic test based on engineered yet authentic SARS-CoV-2 virus-like-particles (VLPs). They share all features of the original SARS-CoV-2 but lack the viral RNA genome and thus are non-infectious. NAbs induced by infection or vaccination, but also potentially neutralizing monoclonal antibodies can be reliably quantified and assessed with ease and within hours with our test, because they interfere and block the ACE2-mediated uptake of VLPs by recipient cells. Results from the VLP neutralization test (VLPNT) showed excellent specificity and sensitivity and correlated very well with a cVNT using fully infectious SARS-CoV-2. The results also demonstrated the reduced neutralizing capacity of COVID-19 vaccinee sera against variants of concern of SARS-CoV-2 including omicron B.1.1.529, BA.1.

Risk Stratification Based on a Pattern of Immunometabolic Host Factors Is Superior to Body Mass Index-Based Prediction of COVID-19-Associated Respiratory Failure.

Overweight and obesity are associated with chronic low-grade inflammation and represent risk factors for various diseases, including COVID-19. However, most published studies on COVID-19 defined obesity by the body mass index (BMI), which does not encounter adipose tissue distribution, thus neglecting immunometabolic high-risk patterns. Therefore, we comprehensively analyzed baseline anthropometry (BMI, waist-to-height-ratio (WtHR), visceral (VAT), epicardial (EAT), subcutaneous (SAT) adipose tissue masses and liver fat, inflammation markers (CRP, ferritin, interleukin-6), and immunonutritional scores (CRP-to-albumin ratio (CAR), modified Glasgow prognostic score, neutrophile-to-lymphocyte ratio, prognostic nutritional index)) in 58 consecutive COVID-19 patients of the early pandemic phase with regard to the necessity of invasive mechanical ventilation (IMV). Here, metabolically high-risk adipose tissues represented by increased VAT, liver fat, and WtHR strongly correlated with higher levels of inflammation, pathologic immunonutritional scores, and the need for IMV. In contrast, the prognostic value of BMI was inferior and absent with regard to SAT. Multivariable logistic regression analysis identified an optimized IMV risk prediction model employing liver fat, WtHR, and CAR. In summary, we suggest an immunometabolically risk-adjusted model to predict COVID-19-induced respiratory failure better than BMI-based stratification, which warrants prospective validation.

Accumulation of mutations in antibody and CD8 T cell epitopes in a B cell depleted lymphoma patient with chronic SARS-CoV-2 infection.

Antibodies against the spike protein of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) can drive adaptive evolution in immunocompromised patients with chronic infection. Here we longitudinally analyze SARS-CoV-2 sequences in a B cell-depleted, lymphoma patient with chronic, ultimately fatal infection, and identify three mutations in the spike protein that dampen convalescent plasma-mediated neutralization of SARS-CoV-2. Additionally, four mutations emerge in non-spike regions encoding three CD8 T cell epitopes, including one nucleoprotein epitope affected by two mutations. Recognition of each mutant peptide by CD8 T cells from convalescent donors is reduced compared to its ancestral peptide, with additive effects resulting from double mutations. Querying public SARS-CoV-2 sequences shows that these mutations have independently emerged as homoplasies in circulating lineages. Our data thus suggest that potential impacts of CD8 T cells on SARS-CoV-2 mutations, at least in those with humoral immunodeficiency, warrant further investigation to inform on vaccine design.

Protective immune trajectories in early viral containment of non-pneumonic SARS-CoV-2 infection.

The antiviral immune response to SARS-CoV-2 infection can limit viral spread and prevent development of pneumonic COVID-19. However, the protective immunological response associated with successful viral containment in the upper airways remains unclear. Here, we combine a multi-omics approach with longitudinal sampling to reveal temporally resolved protective immune signatures in non-pneumonic and ambulatory SARS-CoV-2 infected patients and associate specific immune trajectories with upper airway viral containment. We see a distinct systemic rather than local immune state associated with viral containment, characterized by interferon stimulated gene (ISG) upregulation across circulating immune cell subsets in non-pneumonic SARS-CoV2 infection. We report reduced cytotoxic potential of Natural Killer (NK) and T cells, and an immune-modulatory monocyte phenotype associated with protective immunity in COVID-19. Together, we show protective immune trajectories in SARS-CoV2 infection, which have important implications for patient prognosis and the development of immunomodulatory therapies.

Pulmonary function impairment of asymptomatic and persistently symptomatic patients 4 months after COVID-19 according to disease severity.

OBJECTIVE: Evaluation of pulmonary function impairment after COVID-19 in persistently symptomatic and asymptomatic patients of all disease severities and characterisation of risk factors. METHODS: Patients with confirmed SARS-CoV-2 infection underwent prospective follow-up with pulmonary function testing and blood gas analysis during steady-state cycle exercise 4 months after acute illness. Pulmonary function impairment (PFI) was defined as reduction below 80% predicted of DLCOcSB, TLC, FVC, or FEV1. Clinical data were analyzed to identify risk factors for impaired pulmonary function. RESULTS: 76 patients were included, hereof 35 outpatients with mild disease and 41 patients hospitalized due to COVID-19. Sixteen patients had critical disease requiring mechanical ventilation, 25 patients had moderate-severe disease. After 4 months, 44 patients reported persisting respiratory symptoms. Significant PFI was prevalent in 40 patients (52.6%) occurring among all disease severities. The most common cause for PFI was reduced DLCOcSB (n = 39, 51.3%), followed by reduced TLC and FVC. The severity of PFI was significantly associated with mechanical ventilation (p < 0.001). Further risk factors for DLCO impairment were COPD (p < 0.001), SARS-CoV-2 antibody-Titer (p = 0.014) and in hospitalized patients CT score. A decrease of paO2 > 3 mmHg during cycle exercise occurred in 1/5 of patients after mild disease course. CONCLUSION: We characterized pulmonary function impairment in asymptomatic and persistently symptomatic patients of different severity groups of COVID-19 and identified further risk factors associated with persistently decreased pulmonary function. Remarkably, gas exchange abnormalities were revealed upon cycle exercise in some patients with mild disease courses and no preexisting pulmonary condition.

Dynamics of urinary and respiratory shedding of Severe acute respiratory syndrome virus 2 (SARS-CoV-2) RNA excludes urine as a relevant source of viral transmission.

PURPOSE: To investigate the expression of the receptor protein ACE-2 alongside the urinary tract, urinary shedding and urinary stability of SARS-CoV-2 RNA. METHODS: Immunohistochemical staining was performed on tissue from urological surgery of 10 patients. Further, patients treated for coronavirus disease (COVID-19) at specialized care-units of a university hospital were assessed for detection of SARS-CoV-2 RNA in urinary samples via PCR, disease severity (WHO score), inflammatory response of patients. Finally, the stability of SARS-CoV-2 RNA in urine was analyzed. RESULTS: High ACE-2 expression (3/3) was observed in the tubules of the kidney and prostate glands, moderate expression in urothelial cells of the bladder (0-2/3) and no expression in kidney glomeruli, muscularis of the bladder and stroma of the prostate (0/3). SARS-CoV-2 RNA was detected in 5/199 urine samples from 64 patients. Viral RNA was detected in the first urinary sample of sequential samples. Viral RNA load from other specimen as nasopharyngeal swabs (NPS) or endotracheal aspirates revealed higher levels than from urine. Detection of SARS-CoV-2 RNA in urine was not associated with impaired WHO score (median 5, range 3-8 vs median 4, range 1-8, p = 0.314), peak white blood cell count (median 24.1 × 1000/ml, range 5.19-48.1 versus median 11.9 × 1000/ml, range 2.9-60.3, p = 0.307), peak CRP (median 20.7 mg/dl, 4.2-40.2 versus median 11.9 mg/dl, range 0.1-51.9, p = 0.316) or peak IL-6 levels (median: 1442 ng/ml, range 26.7-3918 versus median 140 ng/ml, range 3.0-11,041, p = 0.099). SARS-CoV-2 RNA was stable under different storage conditions and after freeze-thaw cycles. CONCLUSIONS: SARS-CoV-2 RNA in the urine of COVID-19 patients occurs infrequently. The viral RNA load and dynamics of SARS-CoV-2 RNA shedding suggest no relevant route of transmission through the urinary tract.

Binding of phosphatidylserine-positive microparticles by PBMCs classifies disease severity in COVID-19 patients.

Infection with SARS-CoV-2 is associated with thromboinflammation, involving thrombotic and inflammatory responses, in many COVID-19 patients. In addition, immune dysfunction occurs in patients characterised by T cell exhaustion and severe lymphopenia. We investigated the distribution of phosphatidylserine (PS), a marker of dying cells, activated platelets and platelet-derived microparticles (PMP), during the clinical course of COVID-19. We found an unexpectedly high amount of blood cells loaded with PS+ PMPs for weeks after the initial COVID-19 diagnosis. Elevated frequencies of PS+ PMP+ PBMCs correlated strongly with increasing disease severity. As a marker, PS outperformed established laboratory markers for inflammation, leucocyte composition and coagulation, currently used for COVID-19 clinical scoring. PS+ PMPs preferentially bound to CD8+ T cells with gene expression signatures of proliferating effector rather than memory T cells. As PS+ PMPs carried programmed death-ligand 1 (PD-L1), they may affect T cell expansion or function. Our data provide a novel marker for disease severity and show that PS, which can trigger the blood coagulation cascade, the complement system, and inflammation, resides on activated immune cells. Therefore, PS may serve as a beacon to attract thromboinflammatory processes towards lymphocytes and cause immune dysfunction in COVID-19.