Alterations in programmed death ligand expression in whole blood cells in COVID-19 patients

Background: Infections with SARS-CoV- 2 cause the coronavirus disease 2019 (COVID-19) pandemic. Alterations in immune cells of COVID-19 patients may predict the subsequent severity of disease. The changes in composition of immune cells in COVID-19 patients include lymphopenia, lower neutrophil to lymphocyte-ratios and an eosinopenia in about 50 to 80% of hospitalized patients. Eosinophils and neutrophils can interact with T cells via immune checkpoints receptors such as programmed death (PD)-1 on T cells and its counterpart PD-ligand 1 (PD-L1) on eosinophils or neutrophils. There are only limited studies on PD-1 and PD-L1 expressions in viral infections, we aimed to elucidate the interplay of T cells and other peripheral cells by analysing the immune checkpoints PD-1 and PD-L1 in expression during COVID-19. Method(s): Using flow cytometry, we have now analysed the immune checkpoint receptor expressions on whole blood cells from a total of 38 COVID-19 patients. The patient cohort comprises all ages and both sexes with the disease severity ranging from mild, moderate to severe, with ~10% mortality. We have further been investigating 21 biomarkers (G-CSF, GM-CSF, IFN-gamma, TGF-beta1, IL-2, IL-4, IL-5, IL-6, IL-10, IL-12p70, IL-13, IL-17A, IL-18, IL-23, IL-33, IP-10, MCP-1, MIP-1beta, TNF-alpha, and YKL-40) in plasma on a cohort of 76 COVID-19 patients using the MesoScale Multiplex Assay platform, with 48 healthy controls. Result(s): PD-L1 expression on eosinophils was significantly lower in COVID-19 patients in initial stages of infection, relative to healthy controls. There was an inverse relationship between disease progression and the expression of PD-1 on CD8+ T cells. These data suggests that analysis of PD-L1- PD1 cell networks in immune cells of EDTA blood of COVID-19 patients can predict disease outcomes. While most detectable biomarkers are strongly increased in COVID samples overall compared to healthy controls, the more severe the disease the higher the blood biomarker concentration. Conclusion(s): Taken together, the analysis of PD-L1- PD1 cell networks in immune cells together with plasma biomarkers of COVID-19 patients can predict disease outcomes.

Efficient virus detection utilizing chitin-immobilized nanobodies synthesized in Ustilago maydis.

The COVID-19 pandemic has greatly impacted the global economy and health care systems, illustrating the urgent need for timely and inexpensive responses to pandemic threats in the form of vaccines and antigen tests. Currently, antigen testing is mostly conducted by qualitative flow chromatography or via quantitative ELISA-type assays. The latter mostly utilize materials like protein-adhesive polymers and gold or latex particles. Here we present an alternative ELISA approach using inexpensive, biogenic materials and permitting quick detection based on components produced in the microbial model Ustilago maydis. In this fungus, heterologous proteins like biopharmaceuticals can be exported by fusion to unconventionally secreted chitinase Cts1. As a unique feature, the carrier chitinase binds to chitin allowing its additional use as a purification or immobilization tag. Recent work has demonstrated that nanobodies are suitable target proteins. These proteins represent a very versatile alternative antibody format and can quickly be adapted to detect novel antigens by camelidae immunization or synthetic libraries. In this study, we exemplarily produced different mono- and bivalent SARS-CoV-2 nanobodies directed against the spike protein receptor binding domain (RBD) as Cts1 fusions and screened their antigen binding affinity in vitro and in vivo. Functional nanobody-Cts1 fusions were immobilized on chitin forming an RBD tethering surface. This provides a solid base for future development of inexpensive antigen tests utilizing unconventionally secreted nanobodies as antigen trap and a matching ubiquitous and biogenic surface for immobilization.

Analysis of Chitinase-3-Like Protein 1, IL-1-Alpha, and IL-6 as Novel Inflammatory Biomarkers for COVID-19.

The aim of our study was to investigate the potential role of IL-1-alpha, IL-6, and chitinase 3-like protein-1 (CHI3L1) as potential biomarkers for COVID-19. Sixty adult SARS Cov-2 PCR-positive patients (22 mild, 25 moderate, and 13 severe) and 50 healthy controls were included in this study. The serum levels of CHI3L1, IL-1-alpha, and IL-6 for all study participants were measured by protein-specific ELISAs. Mean serum CHI3L1 levels in patients with severe disease (7,185.5 ± 1,109.4) were significantly higher than in the moderate (3,977.4 ± 1,260.3), mild (1,379.5 ± 598.8), and control (329.5 ± 128.4) groups (P = 0.001). There was no difference in IL-1-alpha levels between the patient and control groups (P = 0.083). IL-6 levels differed significantly, being lowest in the control group (35.9 ± 13.7), 89.1 ± 23.4 in the mild group, 156.2 ± 29.6 in the moderate group, and the highest in the severe group (214.9 ± 28.1) (P = 0.001). A strong significant correlation was found between disease severity and serum IL-6 and CHI3L1 values (r = 0.894 and r = 0.905, respectively, and P < 0.001 for both). Serum CHI3L1 and IL-6 levels exhibited a linear correlation with the clinical course of COVID-19 infection. These results indicate that inhibitors of IL-6 and/or CHI3L1 may provide useful treatments for COVID-19.

GDF-15 IS A PREDICTOR OF MORTALITY IN CHRONIC KIDNEY DISEASE PATIENTS WITH COVID-19 INFECTION

BACKGROUND AND AIMS: A cytokine storm drives the pathogenesis of severe coronavirus disease (COVID-19) and several biomarkers with different mechanisms of action have been linked to mortality. Chronic kidney disease (CKD) emerged as a very common risk factor for severe COVID-19. Indeed, CKD patients are at increased risk of premature death from many causes, including, but not limited to, cardiovascular disease (CVD) and infections. In this study, we aimed to investigate the associations between the growth differentiation factor 15 (GDF-15), an established cardiovascular and inflammatory biomarker and outcomes in CKD patients hospitalized for COVID-19. METHOD: A retrospective study on COVID-19 hospitalized subjects in the acute phase of the disease. A broad range of cytokines (CD25, IL-18, TNF-α, TNF RI, TNF RII, GDF-15, IL-7, LIF, IL-6, CHITINASE3-LIKE1, RAGE and Pentraxin-3) were assessed in plasma (Luminex, ELISA) collected upon hospitalization. A total of 77 subjects were divided into two groups according to their estimated glomerular filtration rate (eGFR, by CKD-EPI formula), ≥45 mL/min (n = 44), or <45 mL/min (n = 33). RESULTS: We found no statistical differences between the two groups in terms of demographic features. Among comorbidities, we found a higher percentage of patients with diabetes in the eGFR < 45 group. Likewise, the serum tests upon admission showed in the eGFR < 45 group a higher value of neutrophilic count. Upon hospital admission, the patient groups were comparable in terms of symptoms, time from symptom onset to admission and death or discharge, radiological evidence of pneumonia and respiratory parameters and time of hospitalization. Furthermore, there were no statistical differences between medical therapy during hospitalization, need for respiratory support with Continuous Positive Airways Pressure or Non-Invasive Mechanical Ventilation, or death rather than discharge as the clinical outcome. Serum levels of 20 different compounds were measured in COVID-19 patients admitted to the hospital 4-5 days after the onset of symptoms. Interestingly, we found that patients with lower renal function (eGFR < 45 mL/min) had a significant increase of GDF-15, CD-25 and RAGE and, furthermore, higher serum levels of these molecules were detected in non-survivor patients and in those who needed ventilation. Also, TNFα, TNFR I, TNFR II, IL-7 and LIF had a significant increase in patients with eGFR < 45 mL/min with more elevated levels in non-survivor patients. In univariate analysis low and mid-low GDF-15 quartiles (<4.45 ng/mL) were associated with lower mortality risk, while mid-high and high quartiles (>4.45 ng/mL) were associated with higher mortality risk (Figure 1). Independent association between GDF-15 quartiles and mortality risk was confirmed in Cox model adjusted for eGFR, age, fever, dyspnoea and P/F [hazard ratio (HR) 2.28, 95% confidence interval (CI) 1.53-3.39, P < 0.0001) The strength of association between GDF-15 quartiles and mortality risk was increased in patients with eGFR < 45 mL/min/1.73 m2 (HR 2.53, CI 1.34-4.79) compared with the other eGFR group (HR 1.99, CI 1.17-3.39) (Table 1). CONCLUSION: Our results demonstrate that GDF-15 is an independent predictor of COVID-19 mortality in CKD patients. Given the reported increase of this cytokine with age and its possible mechanistic role in various pathological conditions, our findings suggest that GDF-15 signalling pathway inhibitors may be included as possible therapeutic candidates for COVID-19 in CKD. (Table Presented).

GDF-15 AS A PREDICTOR of MORTALITY in COVID-19: IMPLICATIONS for TREATMENT

Background: A cytokine storm drives the pathogenesis of severe COVID-19 and has therefore prompted the use of cytokine/transduction pathway inhibitors in the treatment of disease. However, numerous markers with different mechanisms of action have been linked to mortality, complicating the understanding of disease pathogenesis and the elaboration of therapeutic strategies. Methods: Retrospective study on COVID-19 hospitalized subjects in the acute phase of disease. A broad range of cytokines (CD25, IL-18, TNF-α, TNF RI, TNF RII, GDF-15, IL-7, LIF, IL-6, CHITINASE3-LIKE1, RAGE and Pentraxin-3) was assessed on plasma samples (Luminex, ELISA) collected upon hospitalization. Subjects were divided into two groups according to their clinical in-hospital death (Survivors: S;Non-Survivors: NS). Comparisons between groups were performed by Fisher's exact test or Mann-Whitney U test as appropriate. The association between each variable and mortality was analysed through univariate and multiple logistic regression models. Subsequently, survival analysis was conducted with Cox proportional hazard models. Results: 77 hospitalised Covid-19 patients were enrolled: 42 S and 35 NS (Figure 1A). As expected, in the NS group we found a higher proportion of subjects with fever and dyspnoea upon admission, development of ARDS and need of PEEP respiratory support (Figure 1A). NS also displayed significantly higher blood neutrophils/lymphocytes, C-reactive protein, LDH and procalcitonin as well as lower PaO2/FiO2 and peripheral O2 saturation values at admission (Figure 1A). In keeping with these findings, CD25, IL-18, IL-6, TNF-α, TNFRI, TNFRII, GDF-15, IL-7, LIF and Chitinase3-Like1, Pentraxin-3 and RAGE were significantly higher in NS than S (Figure 1B) and were associated to mortality in univariate regression models. In the multivariate regression model GDF-15 and fever were the two more relevant features associated with mortality (Figure 1C). In the survival analysis GDF-15 was the strongest predictor of mortality (HR 2,26, 1,55-3,31;p<0,01 reference group bottom quartile Figure 1D, E). Conclusion: Our in-depth characterization of the cytokine storm demonstrates that GDF-15 is an independent predictor of Covid-19 mortality. Given the reported increase of this cytokine with age and its possible mechanistic role in various pathological conditions, our findings suggest that GDF-15 signalling pathway inhibitors may be included as possible therapeutic candidates for Covid-19.

A 'Multiomic' Approach of Saliva Metabolomics, Microbiota, and Serum Biomarkers to Assess the Need of Hospitalization in Coronavirus Disease 2019.

BACKGROUND AND AIMS: The SARS-CoV-2 pandemic has overwhelmed the treatment capacity of the health care systems during the highest viral diffusion rate. Patients reaching the emergency department had to be either hospitalized (inpatients) or discharged (outpatients). Still, the decision was taken based on the individual assessment of the actual clinical condition, without specific biomarkers to predict future improvement or deterioration, and discharged patients often returned to the hospital for aggravation of their condition. Here, we have developed a new combined approach of omics to identify factors that could distinguish coronavirus disease 19 (COVID-19) inpatients from outpatients. METHODS: Saliva and blood samples were collected over the course of two observational cohort studies. By using machine learning approaches, we compared salivary metabolome of 50 COVID-19 patients with that of 270 healthy individuals having previously been exposed or not to SARS-CoV-2. We then correlated the salivary metabolites that allowed separating COVID-19 inpatients from outpatients with serum biomarkers and salivary microbiota taxa differentially represented in the two groups of patients. RESULTS: We identified nine salivary metabolites that allowed assessing the need of hospitalization. When combined with serum biomarkers, just two salivary metabolites (myo-inositol and 2-pyrrolidineacetic acid) and one serum protein, chitinase 3-like-1 (CHI3L1), were sufficient to separate inpatients from outpatients completely and correlated with modulated microbiota taxa. In particular, we found Corynebacterium 1 to be overrepresented in inpatients, whereas Actinomycetaceae F0332, Candidatus Saccharimonas, and Haemophilus were all underrepresented in the hospitalized population. CONCLUSION: This is a proof of concept that a combined omic analysis can be used to stratify patients independently from COVID-19.

Longitudinal changes of neurospecific serum proteins in COVID-19 patients

INTRODUCTION/HYPOTHESIS: COVID-19 has been associated with distinct types of neuronal damage. We hypothesize that the progression of neurological damage will be related to an imbalance between neurodegeneration, neuroinflammatory, and neuroprotective markers, therefore suggesting a potential mechanism for the emergence of adverse, chronic outcomes. METHODS: 105 patients admitted to an urban, academic hospital with a diagnosis of COVID-19 were enrolled. Serum neuroprotective (clusterin, fetuin), neurodegenerative (τ, phosphorylated τ, amyloids, TDP43, NRGN, NCAM-1, and KLK6), and neuroinflammatory (CCL23, YKL40, MIF) markers were collected. These were analyzed longitudinally in conjunction with immune system activators (RAGE, IL-34) using the multiplex platform. Electronic medical records were used to collect demographic and clinical data. RESULTS: Of the 105 patients, 5 were diagnosed with stroke within 28 days of admission, followed by an additional 6 strokes occurring by 6 months, or a 9.5% occurrence of stroke overall. Serum levels of Amyloid β42 declined significantly for the general population 7 days after admission when compared to initial collections (p< 0.001), while Amyloid β40, KLK6, and MIF declined and recovered within the same 7 days (p< 0.001, p< 0.001, p=0.003). The neuroprotective markers fetuin and clusterin were particularly dynamic with fetuin decreasing and restoring in less than 7 days (p=0.02) and clusterin remaining low after admission (p< 0.001). Most patients had persistently elevated CCL23 levels, with the stroke patient cohort having the highest values (p=0.018). The IL-6 levels of stroke patients were significantly higher compared to their non-stroke counterparts one week after admission (p=0.001), while IL-8 levels fluctuated before declining (p< 0.001). CONCLUSIONS: Our data reveals elevations in neuronal damage in the 7 days following hospital admission for COVID-19 patients. The down-regulation of fetuin and clusterin is particularly compelling as their declines may be linked to the elevated neuronal injury seen with increased neuroinflammatory markers, specifically CCL23 and IL-6. Serum levels of neurodegeneration markers proved complex, therefore possibly suggesting a more dynamic relationship to the neural abnormalities seen in COVID-19 patients.

Assessment of Macrophage Inflammatory Biomarkers and Neutrophil Extracellular Traps Associated Proteins in COVID-19 Patients

[Formula presented] Background : The SARS-CoV-2 infection activates both innate and adaptive immune responses and induces an exaggerated cytokine storm leading to causes septic shock, acute respiratory distress syndrome, and/or multiple organ failure in critically ill patients. The knowledge of this dysregulated immune response is not well explained. One hypothesis is that the response of macrophages and neutrophils to infection is disproportionate, resulting in overproduction of cytokines and activation of neutrophils leading to the most severe complications of infection, including the production of multiple microthrombi and endothelial damage. Aim of the study: To evaluate the activation levels of macrophage biomarkers as well as indicators of the development of neutrophil extracellular traps (NET) in the first phase of infection in hospitalized patients with COVID19. Patients and Methods: We selected dry blood spot from a total of 60 previously identified SARS-CoV-2 infected subjects. Plasma samples were provided by the Aragon Health System Biobank's collection and were extracted within 5 days of symptom onset. Plasma from 60 healthy controls were used to stablish the control range for NETosis determination. The study was authorized by the Ethics Committee of the Aragon Health System and complies with the European General Data Protection Regulation (GDPR 2016/679) and LO 3/2018. Demographic characteristics, clinical manifestations, follow-up during hospitalization, associated comorbidities, and thrombotic complications were obtained from the database. Chitotriosidase activity (ChT), YKL40 chitinase and CCL18/PARC cytokine were measured as markers of macrophage activation. Myeloperoxidase (MPO), Neutrophil Elastase (NE), and S100A8/S100A9 Heterodimer (MPR) were immuno-quantified, levels of circulating free DNA (cfDNA) were measured as well as the presence of DNAsases by fluorimetry as indicators of Netosis. For the comparative analysis, we stratified patients by age groups and disease severity and used the Mann-Whitney U test for statistical comparison, considering a p-value < 0.05 as statistically significant. Results : A statistically significant increase in ChT (p=0.032) and CCL18/PARC (p=0.0001) was observed in the patients´ group. A comparative study with clinical variables and other inflammation markers as ferritin, D-dimer will be shown upon acceptance. Concerning NET markers, we found a statistically significant increase in MPO, NE, and MRP in COVID-19 patients (p=0.0001;p=0.0290;p=0.0001 respectively), as well as a statistically significant decrease in DNAsa (p=0.0001). No differences in cfDNA levels were observed. The table shows the median (quartile1-quartile3) for each marker in the control group and in the patient group. Conclusions : In this study, biomarkers of macrophage activation do not appear to be more sensitive than the indicators of inflammation in routine clinical practice (ferritin, D-dimer). Clinical cases of severe COVID-19 disease show an excessive NET formation, which contributes to vascular damage and the development of thrombosis. This work was supported by a research grant from FEETEG [Formula presented] Disclosures: No relevant conflicts of interest to declare.

Chitinase Chit62J4 Essential for Chitin Processing by Human Microbiome Bacterium Clostridium paraputrificum J4.

Commensal bacterium Clostridium paraputrificum J4 produces several extracellular chitinolytic enzymes including a 62 kDa chitinase Chit62J4 active toward 4-nitrophenyl N,N'-diacetyl-ß-d-chitobioside (pNGG). We characterized the crude enzyme from bacterial culture fluid, recombinant enzyme rChit62J4, and its catalytic domain rChit62J4cat. This major chitinase, securing nutrition of the bacterium in the human intestinal tract when supplied with chitin, has a pH optimum of 5.5 and processes pNGG with Km = 0.24 mM and kcat = 30.0 s-1. Sequence comparison of the amino acid sequence of Chit62J4, determined during bacterial genome sequencing, characterizes the enzyme as a family 18 glycosyl hydrolase with a four-domain structure. The catalytic domain has the typical TIM barrel structure and the accessory domains-2x Fn3/Big3 and a carbohydrate binding module-that likely supports enzyme activity on chitin fibers. The catalytic domain is highly homologous to a single-domain chitinase of Bacillus cereus NCTU2. However, the catalytic profiles significantly differ between the two enzymes despite almost identical catalytic sites. The shift of pI and pH optimum of the commensal enzyme toward acidic values compared to the soil bacterium is the likely environmental adaptation that provides C. paraputrificum J4 a competitive advantage over other commensal bacteria.