New Insights into the Identification of Metabolites and Cytokines Predictive of Outcome for Patients with Severe SARS-CoV-2 Infection Showed Similarity with Cancer

SARS-CoV-2 infection is characterized by several clinical manifestations, ranging from the absence of symptoms to severe forms that necessitate intensive care treatment. It is known that the patients with the highest rate of mortality develop increased levels of proinflammatory cytokines, called the "cytokine storm”, which is similar to inflammatory processes that occur in cancer. Additionally, SARS-CoV-2 infection induces modifications in host metabolism leading to metabolic reprogramming, which is closely linked to metabolic changes in cancer. A better understanding of the correlation between perturbed metabolism and inflammatory responses is necessary. We evaluated untargeted plasma metabolomics and cytokine profiling via 1H-NMR (proton nuclear magnetic resonance) and multiplex Luminex assay, respectively, in a training set of a limited number of patients with severe SARS-CoV-2 infection classified on the basis of their outcome. Univariate analysis and Kaplan–Meier curves related to hospitalization time showed that lower levels of several metabolites and cytokines/growth factors, correlated with a good outcome in these patients and these data were confirmed in a validation set of patients with similar characteristics. However, after the multivariate analysis, only the growth factor HGF, lactate and phenylalanine retained a significant prediction of survival. Finally, the combined analysis of lactate and phenylalanine levels correctly predicted the outcome of 83.3% of patients in both the training and the validation set. We highlighted that the cytokines and metabolites involved in COVID-19 patients' poor outcomes are similar to those responsible for cancer development and progression, suggesting the possibility of targeting them by repurposing anticancer drugs as a therapeutic strategy against severe SARS-CoV-2 infection.

New Insights into the Identification of Metabolites and Cytokines Predictive of Outcome for Patients with Severe SARS-CoV-2 Infection Showed Similarity with Cancer.

SARS-CoV-2 infection is characterized by several clinical manifestations, ranging from the absence of symptoms to severe forms that necessitate intensive care treatment. It is known that the patients with the highest rate of mortality develop increased levels of proinflammatory cytokines, called the "cytokine storm", which is similar to inflammatory processes that occur in cancer. Additionally, SARS-CoV-2 infection induces modifications in host metabolism leading to metabolic reprogramming, which is closely linked to metabolic changes in cancer. A better understanding of the correlation between perturbed metabolism and inflammatory responses is necessary. We evaluated untargeted plasma metabolomics and cytokine profiling via 1H-NMR (proton nuclear magnetic resonance) and multiplex Luminex assay, respectively, in a training set of a limited number of patients with severe SARS-CoV-2 infection classified on the basis of their outcome. Univariate analysis and Kaplan-Meier curves related to hospitalization time showed that lower levels of several metabolites and cytokines/growth factors, correlated with a good outcome in these patients and these data were confirmed in a validation set of patients with similar characteristics. However, after the multivariate analysis, only the growth factor HGF, lactate and phenylalanine retained a significant prediction of survival. Finally, the combined analysis of lactate and phenylalanine levels correctly predicted the outcome of 83.3% of patients in both the training and the validation set. We highlighted that the cytokines and metabolites involved in COVID-19 patients' poor outcomes are similar to those responsible for cancer development and progression, suggesting the possibility of targeting them by repurposing anticancer drugs as a therapeutic strategy against severe SARS-CoV-2 infection.

Immune profiling of SARS-CoV-2 epitopes in asymptomatic and symptomatic pediatric and adult patients.

BACKGROUND: The infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has unpredictable manifestations of coronavirus disease (COVID-19) and variable clinical course with some patients being asymptomatic whereas others experiencing severe respiratory distress, or even death. We aimed to evaluate the immunoglobulin G (IgG) response towards linear peptides on a peptide array containing sequences from SARS-CoV-2, Middle East respiratory syndrome-related coronavirus (MERS) and common-cold coronaviruses 229E, OC43, NL63 and HKU1 antigens, in order to identify immunological indicators of disease outcome in SARS-CoV-2 infected patients. METHODS: We included in the study 79 subjects, comprising 19 pediatric and 30 adult SARS-CoV-2 infected patients with increasing disease severity, from mild to critical illness, and 30 uninfected subjects who were vaccinated with one dose of SARS-CoV-2 spike mRNA BNT162b2 vaccine. Serum samples were analyzed by a peptide microarray containing 5828 overlapping 15-mer synthetic peptides corresponding to the full SARS-CoV-2 proteome and selected linear epitopes of spike (S), envelope (E) and membrane (M) glycoproteins as well as nucleoprotein (N) of MERS, SARS and coronaviruses 229E, OC43, NL63 and HKU1 (isolates 1, 2 and 5). RESULTS: All patients exhibited high IgG reactivity against the central region and C-terminus peptides of both SARS-CoV-2 N and S proteins. Setting the threshold value for serum reactivity above 25,000 units, 100% and 81% of patients with severe disease, 36% and 29% of subjects with mild symptoms, and 8% and 17% of children younger than 8-years reacted against N and S proteins, respectively. Overall, the total number of peptides in the SARS-CoV-2 proteome targeted by serum samples was much higher in children compared to adults. Notably, we revealed a differential antibody response to SARS-CoV-2 peptides of M protein between adults, mainly reacting against the C-terminus epitopes, and children, who were highly responsive to the N-terminus of M protein. In addition, IgG signals against NS7B, NS8 and ORF10 peptides were found elevated mainly among adults with mild (63%) symptoms. Antibodies towards S and N proteins of other coronaviruses (MERS, 229E, OC43, NL63 and HKU1) were detected in all groups without a significant correlation with SARS-CoV-2 antibody levels. CONCLUSIONS: Overall, our results showed that antibodies elicited by specific linear epitopes of SARS-CoV-2 proteome are age dependent and related to COVID-19 clinical severity. Cross-reaction of antibodies to epitopes of other human coronaviruses was evident in all patients with distinct profiles between children and adult patients. Several SARS-CoV-2 peptides identified in this study are of particular interest for the development of vaccines and diagnostic tests to predict the clinical outcome of SARS-CoV-2 infection.

Cytokine signature and COVID-19 prediction models in the two waves of pandemics.

In Europe, multiple waves of infections with SARS-CoV-2 (COVID-19) have been observed. Here, we have investigated whether common patterns of cytokines could be detected in individuals with mild and severe forms of COVID-19 in two pandemic waves, and whether machine learning approach could be useful to identify the best predictors. An increasing trend of multiple cytokines was observed in patients with mild or severe/critical symptoms of COVID-19, compared with healthy volunteers. Linear Discriminant Analysis (LDA) clearly recognized the three groups based on cytokine patterns. Classification and Regression Tree (CART) further indicated that IL-6 discriminated controls and COVID-19 patients, whilst IL-8 defined disease severity. During the second wave of pandemics, a less intense cytokine storm was observed, as compared with the first. IL-6 was the most robust predictor of infection and discriminated moderate COVID-19 patients from healthy controls, regardless of epidemic peak curve. Thus, serum cytokine patterns provide biomarkers useful for COVID-19 diagnosis and prognosis. Further definition of individual cytokines may allow to envision novel therapeutic options and pave the way to set up innovative diagnostic tools.

Clinical Outcome Prediction in COVID-19 Patients by Lymphocyte Subsets Analysis and Monocytes' iTNF-α Expression.

In December 2019, a novel coronavirus, "SARS-CoV-2", was recognized as the cause of coronavirus disease 2019 (COVID-19). Several studies have explored the changes and the role of inflammatory cells and cytokines in the immunopathogenesis of the disease, but until today, the results have been controversial. Based on these premises, we conducted a retrospective assessment of monocyte intracellular TNF-α expression (iTNF-α) and on the frequencies of lymphocyte sub-populations in twenty-five patients with moderate/severe COVID-19. We found lymphopenia in all COVID-19 infected subjects compared to healthy subjects. On initial observation, in patients with favorable outcomes, we detected a high absolute eosinophil count and a high CD4+/CD8+ T lymphocytes ratio, while in the Exitus Group, we observed high neutrophil and CD8+ T lymphocyte counts. During infection, in patients with favorable outcomes, we observed a rise in the lymphocyte count, in the monocyte and in Treg lymphocyte counts, and in the CD4+ and in CD8+ T lymphocytes count but a reduction in the CD4+/CD8+ T lymphocyte ratio. Instead, in the Exitus Group, we observed a reduction in the Treg lymphocyte counts and a decrease in iTNF-α expression. Our preliminary findings point to a modulation of the different cellular mediators of the immune system, which probably play a key role in the outcomes of COVID-19.

An observational study of a cohort of citizens receiving the AZD1222 vaccine against SARS-CoV-2.

In this retrospective study, a cohort of 67 subjects vaccinated with AZD1222 was retrospectively observed. Consistently with published findings, no serious adverse event was reported, and all adverse events reported (fever, muscle ache and/or pain in the site of injection) had resolved by day 8. Of note, some citizens were prescribed low-dose aspirin and even heparin for thrombosis prevention. We also found variations in laboratory test results (full blood count and chemistry) on day 1 compared with day 8. Physicians should be aware that no prevention therapy for thrombosis is currently recommended, given the very low incidence of this side effect. Additional studies are warranted to interpret our findings.