Basophils and Mast Cells in COVID-19 Pathogenesis

The role of hematological parameters in asymptomatic and non-severe cases of Omicron variant infection

BACKGROUND

Omicron variants are currently the predominant circulating lineage worldwide and most cases are mild or asymptomatic. The Omicron variant is characterized by high transmissibility and immune evasion. Early identification of Omicron cases in clinical settings is crucial for controlling its spread. Previous studies have indicated that changes in hematological parameters can be used to predict the severity of coronavirus disease 2019 (COVID-19). However, the role of hematological parameters in non-severe and asymptomatic cases remains unknown. This study aimed to investigate the role of hematological parameters in non-severe and asymptomatic Omicron variant infections.

METHODS

Hematological parameters and results were analyzed and compared in symptomatic (n = 356) and asymptomatic (n = 171) groups respectively, and between these two groups with positive COVID-19 tests. The utility of hematological parameters for predicting positive COVID-19 tests was analyzed using receiver operating characteristic curves.

RESULTS

Individuals with non-severe cases exhibited decreased levels of platelets, lymphocytes, eosinophils, basophils, lymphocytes (%), eosinophils (%), and basophils (%), while exhibiting elevated counts of monocytes, neutrophils (%), monocytes (%), neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio (PLR), and C-reactive protein (CRP) when compared to suspected cases or asymptomatic carriers. In asymptomatic patients, positive carriers had lower leukocyte, neutrophil, and lymphocyte counts but higher monocyte, monocyte (%), PLR, and CRP levels than negative carriers. Basophil counts combined with lymphocytes or the PLR demonstrated a more significant predictive value in screening non-severe cases earlier compared to other parameters. The combined assessment of the monocyte (%) and the PLR had the highest area under the curve for diagnosing asymptomatic carriers.

CONCLUSIONS

Circulating basophils, alone or in combination with other hematological parameters, may be used as efficient biomarkers for early screening of non-severe Omicron cases.

Innate Immunity in Protection and Pathogenesis During Coronavirus Infections and COVID-19

The COVID-19 pandemic was caused by the recently emerged β-coronavirus SARS-CoV-2. SARS-CoV-2 has had a catastrophic impact, resulting in nearly 7 million fatalities worldwide to date. The innate immune system is the first line of defense against infections, including the detection and response to SARS-CoV-2. Here, we discuss the innate immune mechanisms that sense coronaviruses, with a focus on SARS-CoV-2 infection and how these protective responses can become detrimental in severe cases of COVID-19, contributing to cytokine storm, inflammation, long-COVID, and other complications. We also highlight the complex cross talk among cytokines and the cellular components of the innate immune system, which can aid in viral clearance but also contribute to inflammatory cell death, cytokine storm, and organ damage in severe COVID-19 pathogenesis. Furthermore, we discuss how SARS-CoV-2 evades key protective innate immune mechanisms to enhance its virulence and pathogenicity, as well as how innate immunity can be therapeutically targeted as part of the vaccination and treatment strategy. Overall, we highlight how a comprehensive understanding of innate immune mechanisms has been crucial in the fight against SARS-CoV-2 infections and the development of novel host-directed immunotherapeutic strategies for various diseases.

Bronchial Asthma and COVID-19: Etiology, Pathological Triggers, and Therapeutic Considerations

Bronchial asthma (BA) continues to be a difficult disease to diagnose. Various factors have been described in the development of BA, but to date, there is no clear evidence for the etiology of this chronic disease. The emergence of COVID-19 has contributed to the pandemic course of asthma and immunologic features. However, there are no unambiguous data on asthma on the background and after COVID-19. There is correlation between various trigger factors that provoke the development of bronchial asthma. It is now obvious that the SARS-CoV-2 virus is one of the provoking factors. COVID-19 has affected the course of asthma. Currently, there is no clear understanding of whether asthma progresses during or after COVID-19 infection. According to the results of some studies, a significant difference was identified between the development of asthma in people after COVID-19. Mild asthma and moderate asthma do not increase the severity of COVID-19 infection. Nevertheless, oral steroid treatment and hospitalization for severe BA were associated with higher COVID-19 severity. The influence of SARS-CoV-2 infection is one of the protective factors. It causes the development of severe bronchial asthma. The accumulated experience with omalizumab in patients with severe asthma during COVID-19, who received omalizumab during the pandemic, has strongly suggested that continued treatment with omalizumab is safe and may help prevent the severe course of COVID-19. Targeted therapy for asthma with the use of omalizumab may also help to reduce severe asthma associated with COVID-19. However, further studies are needed to prove the effect of omalizumab. Data analysis should persist, based on the results of the course of asthma after COVID-19 with varying degrees of severity.

Increase in venous thromboembolism in SARS-CoV-2 infected lung tissue: proteome analysis of lung parenchyma, isolated endothelium, and thrombi

AIMS

COVID-19 pneumonia is characterized by an increased rate of deep venous thrombosis and pulmonary embolism. To better understand the pathophysiology behind thrombosis in COVID-19, we performed proteomics analysis on SARS-CoV-2 infected lung tissue.

METHODS

Liquid chromatography mass spectrometry was performed on SARS-CoV-2 infected postmortem lung tissue samples. Five protein profiling analyses were performed: whole slide lung parenchyma analysis, followed by analysis of isolated thrombi and endothelium, both stratified by disease (COVID-19 versus influenza) and thrombus morphology (embolism versus in situ). Influenza autopsy cases with pulmonary thrombi were used as controls.

RESULTS

Compared to influenza controls, both analyses of COVID-19 whole-tissue and isolated endothelium showed upregulation of proteins and pathways related to liver metabolism including urea cycle activation, with arginase being among the top upregulated proteins in COVID-19 lung tissue. Analysis of isolated COVID-19 thrombi showed significant downregulation of pathways related to platelet activation compared to influenza thrombi. Analysis of isolated thrombi based on histomorphology shows that in situ thrombi have significant upregulation of coronavirus pathogenesis proteins.

CONCLUSIONS

The decrease in platelet activation pathways in severe COVID-19 thrombi suggests a relative increase in venous thromboembolism, as thrombi from venous origin tend to contain fewer platelets than arterial thrombi. Based on histomorphology, in situ thrombi show upregulation of various proteins related to SARS-CoV-2 pathogenesis compared to thromboemboli, which may indicate increased in situ pulmonary thrombosis in COVID-19. Therefore, this study supports the increase of venous thromboembolism without undercutting the involvement of in situ thrombosis in severe COVID-19.

Mast cells in the autonomic nervous system and potential role in disorders with dysautonomia and neuroinflammation

Mast cells (MC) are ubiquitous in the body, and they are critical for not only in allergic diseases but also in immunity and inflammation, including having potential involvement in the pathophysiology of dysautonomias and neuroinflammatory disorders. MC are located perivascularly close to nerve endings and sites such as the carotid bodies, heart, hypothalamus, the pineal gland, and the adrenal gland that would allow them not only to regulate but also to be affected by the autonomic nervous system (ANS). MC are stimulated not only by allergens but also many other triggers including some from the ANS that can affect MC release of neurosensitizing, proinflammatory, and vasoactive mediators. Hence, MC may be able to regulate homeostatic functions that seem to be dysfunctional in many conditions, such as postural orthostatic tachycardia syndrome, autism spectrum disorder, myalgic encephalomyelitis/chronic fatigue syndrome, and Long-COVID syndrome. The evidence indicates that there is a possible association between these conditions and diseases associated with MC activation. There is no effective treatment for any form of these conditions other than minimizing symptoms. Given the many ways MC could be activated and the numerous mediators released, it would be important to develop ways to inhibit stimulation of MC and the release of ANS-relevant mediators.

Characterization and trajectories of hematological parameters prior to severe COVID-19 based on a large-scale prospective health checkup cohort in western China: a longitudinal study of 13-year follow-up

BACKGROUND

The relaxation of the "zero-COVID" policy on Dec. 7, 2022, in China posed a major public health threat recently. Complete blood count test was discovered to have complicated relationships with COVID-19 after the infection, while very few studies could track long-term monitoring of the health status and identify the characterization of hematological parameters prior to COVID-19.

METHODS

Based on a 13-year longitudinal prospective health checkup cohort of ~ 480,000 participants in West China Hospital, the largest medical center in western China, we documented 998 participants with a laboratory-confirmed diagnosis of COVID-19 during the 1 month after the policy. We performed a time-to-event analysis to explore the associations of severe COVID-19 patients diagnosed, with 34 different hematological parameters at the baseline level prior to COVID-19, including the whole and the subtypes of white and red blood cells.

RESULTS

A total of 998 participants with a positive SARS-CoV-2 test were documented in the cohort, 42 of which were severe cases. For white blood cell-related parameters, a higher level of basophil percentage (HR = 6.164, 95% CI = 2.066-18.393, P = 0.001) and monocyte percentage (HR = 1.283, 95% CI = 1.046-1.573, P = 0.017) were found associated with the severe COVID-19. For lymphocyte-related parameters, a lower level of lymphocyte count (HR = 0.571, 95% CI = 0.341-0.955, P = 0.033), and a higher CD4/CD8 ratio (HR = 2.473, 95% CI = 1.009-6.059, P = 0.048) were found related to the risk of severe COVID-19. We also observed that abnormality of red cell distribution width (RDW), mean corpuscular hemoglobin concentration (MCHC), and hemoglobin might also be involved in the development of severe COVID-19. The different trajectory patterns of RDW-SD and white blood cell count, including lymphocyte and neutrophil, prior to the infection were also discovered to have significant associations with the risk of severe COVID-19 (all P < 0.05).

CONCLUSIONS

Our findings might help decision-makers and clinicians to classify different risk groups of population due to outbreaks including COVID-19. They could not only optimize the allocation of medical resources, but also help them be more proactive instead of reactive to long COVID-19 or even other outbreaks in the future.

Approaching Personalized Medicine: The Use of Machine Learning to Determine Predictors of Mortality in a Population with SARS-CoV-2 Infection

The COVID-19 pandemic demonstrated the need to develop strategies to control a new viral infection. However, the different characteristics of the health system and population of each country and hospital would require the implementation of self-systems adapted to their characteristics. The objective of this work was to determine predictors that should identify the most severe patients with COVID-19 infection. Given the poor situation of the hospitals in the first wave, the analysis of the data from that period with an accurate and fast technique can be an important contribution. In this regard, machine learning is able to objectively analyze data in hourly sets and is used in many fields. This study included 291 patients admitted to a hospital in Spain during the first three months of the pandemic. After screening seventy-one features with machine learning methods, the variables with the greatest influence on predicting mortality in this population were lymphocyte count, urea, FiO2, potassium, and serum pH. The XGB method achieved the highest accuracy, with a precision of >95%. Our study shows that the machine learning-based system can identify patterns and, thus, create a tool to help hospitals classify patients according to their severity of illness in order to optimize admission.

Coronavirus Receptor Expression Profiles in Human Mast Cells, Basophils, and Eosinophils

A major problem in SARS-CoV-2-infected patients is the massive tissue inflammation in certain target organs, including the lungs. Mast cells (MC), basophils (BA), and eosinophils (EO) are key effector cells in inflammatory processes. These cells have recently been implicated in the pathogenesis of SARS-CoV-2 infections. We explored coronavirus receptor (CoV-R) expression profiles in primary human MC, BA, and EO, and in related cell lines (HMC-1, ROSA, MCPV-1, KU812, and EOL-1). As determined using flow cytometry, primary MC, BA, and EO, and their corresponding cell lines, displayed the CoV-R CD13 and CD147. Primary skin MC and BA, as well as EOL-1 cells, also displayed CD26, whereas primary EO and the MC and BA cell lines failed to express CD26. As assessed using qPCR, most cell lines expressed transcripts for CD13, CD147, and ABL2, whereas ACE2 mRNA was not detectable, and CD26 mRNA was only identified in EOL-1 cells. We also screened for drug effects on CoV-R expression. However, dexamethasone, vitamin D, and hydroxychloroquine did not exert substantial effects on the expression of CD13, CD26, or CD147 in the cells. Together, MC, BA, and EO express distinct CoV-R profiles. Whether these receptors mediate virus-cell interactions and thereby virus-induced inflammation remains unknown at present.

The SARS-CoV-2 pandemic and asthma: What we have learned and what is still unknown

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has brought new insights into the immunologic intricacies of asthma. In this review, we discuss the epidemiology of asthma in patients infected with SARS-CoV-2 and the risk of severe infection. Type 2 inflammation had an overall protective effect against SARS-CoV-2 infection by various mechanisms summarized in this review. Asthma, intranasal, and inhaled corticosteroids decreased the angiotensin-converting enzyme 2 receptor, an important receptor for SARS-CoV-2 entry into host cells. We summarize the nuances of the treatment of type 2 inflammation despite its underlying protective effects. Research to date has shown that patients on various allergen immunotherapies and biologics do benefit from being vaccinated.

Fangchinoline inhibits SARS-CoV-2 and MERS-CoV entry

The COVID-19 pandemic caused by SARS-CoV-2, lead to mild to severe respiratory illness and resulted in 6.9 million deaths worldwide. Although vaccines are effective in preventing COVID-19, they may not be sufficient to protect immunocompromised individuals from this respiratory illness. Moreover, novel emerging variants of SARS-CoV-2 pose a risk of new COVID-19 waves. Therefore, identification of effective antivirals is critical in controlling SARS and other coronaviruses, such as MERS-CoV. We show that Fangchinoline (Fcn), a bisbenzylisoquinoline alkaloid, inhibits replication of SARS-CoV, SARS-CoV-2, and MERS-CoV in a range of in vitro assays, by blocking entry. Therapeutic use of Fcn inhibited viral loads in the lungs, and suppressed associated airway inflammation in hACE2. Tg mice and Syrian hamster infected with SARS-CoV-2. Combination of Fcn with remdesivir (RDV) or an anti-leprosy drug, Clofazimine, exhibited synergistic antiviral activity. Compared to Fcn, its synthetic derivative, MK-04-003, more effectively inhibited SARS-CoV-2 and its variants B.1.617.2 and BA.5 in mice. Taken together these data demonstrate that Fcn is a pan beta coronavirus inhibitor, which possibly can be used to combat novel emerging coronavirus diseases.

Novel machine-learning analysis of SARS-CoV-2 infection in a subclinical nonhuman primate model using radiomics and blood biomarkers

Detection of the physiological response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is challenging in the absence of overt clinical signs but remains necessary to understand a full subclinical disease spectrum. In this study, our objective was to use radiomics (from computed tomography images) and blood biomarkers to predict SARS-CoV-2 infection in a nonhuman primate model (NHP) with inapparent clinical disease. To accomplish this aim, we built machine-learning models to predict SARS-CoV-2 infection in a NHP model of subclinical disease using baseline-normalized radiomic and blood sample analyses data from SARS-CoV-2-exposed and control (mock-exposed) crab-eating macaques. We applied a novel adaptation of the minimum redundancy maximum relevance (mRMR) feature-selection technique, called mRMR-permute, for statistically-thresholded and unbiased feature selection. Through performance comparison of eight machine-learning models trained on 14 feature sets, we demonstrated that a logistic regression model trained on the mRMR-permute feature set can predict SARS-CoV-2 infection with very high accuracy. Eighty-nine percent of mRMR-permute selected features had strong and significant class effects. Through this work, we identified a key set of radiomic and blood biomarkers that can be used to predict infection status even in the absence of clinical signs. Furthermore, we proposed and demonstrated the utility of a novel feature-selection technique called mRMR-permute. This work lays the foundation for the prediction and classification of SARS-CoV-2 disease severity.

Mast Cell Activation Syndrome Update-A Dermatological Perspective

Mast cells (MCs) are infamous for their role in potentially fatal anaphylaxis reactions. In the last two decades, a more complex picture has emerged, as it has become obvious that MCs are much more than just IgE effectors of anaphylaxis. MCs are defenders against a host of infectious and toxic aggressions (their interactions with other components of the immune system are not yet fully understood) and after the insult has ended, MCs continue to play a role in inflammation regulation and tissue repair. Unfortunately, MC involvement in pathology is also significant. Apart from their role in allergies, MCs can proliferate clonally to produce systemic mastocytosis. They have also been implicated in excessive fibrosis, keloid scaring, graft rejection and chronic inflammation, especially at the level of the skin and gut. In recent years, the term MC activation syndrome (MCAS) was proposed to account for symptoms caused by MC activation, and clear diagnostic criteria have been defined. However, not all authors agree with these criteria, as some find them too restrictive, potentially leaving much of the MC-related pathology unaccounted for. Here, we review the current knowledge on the physiological and pathological roles of MCs, with a dermatological emphasis, and discuss the MCAS classification.

Recombinant SARS-CoV-2 Spike Protein Stimulates Secretion of Chymase, Tryptase, and IL-1β from Human Mast Cells, Augmented by IL-33

SARS-CoV-2 infects cells via its spike (S) protein binding to its surface receptor angiotensin-converting enzyme 2 (ACE2) and results in the production of multiple proinflammatory cytokines, especially in the lungs, leading to what is known as COVID-19. However, the cell source and the mechanism of secretion of such cytokines have not been adequately characterized. In this study, we used human cultured mast cells that are plentiful in the lungs and showed that recombinant SARS-CoV-2 full-length S protein (1-10 ng/mL), but not its receptor-binding domain (RBD), stimulates the secretion of the proinflammatory cytokine interleukin-1β (IL-1β) as well as the proteolytic enzymes chymase and tryptase. The secretion of IL-1β, chymase, and tryptase is augmented by the co-administration of interleukin-33 (IL-33) (30 ng/mL). This effect is mediated via toll-like receptor 4 (TLR4) for IL-1β and via ACE2 for chymase and tryptase. These results provide evidence that the SARS-CoV-2 S protein contributes to inflammation by stimulating mast cells through different receptors and could lead to new targeted treatment approaches.

Application and utility of boosting machine learning model based on laboratory test in the differential diagnosis of non-COVID-19 pneumonia and COVID-19

BACKGROUND

Non-Coronavirus disease 2019 (COVID-19) pneumonia and COVID-19 have similar clinical features but last for different periods, and consequently, require different treatment protocols. Therefore, they must be differentially diagnosed. This study uses artificial intelligence (AI) to classify the two forms of pneumonia using mainly laboratory test data.

METHODS

Various AI models are applied, including boosting models known for deftly solving classification problems. In addition, important features that affect the classification prediction performance are identified using the feature importance technique and SHapley Additive exPlanations method. Despite the data imbalance, the developed model exhibits robust performance.

RESULTS

eXtreme gradient boosting, category boosting, and light gradient boosted machine yield an area under the receiver operating characteristic of 0.99 or more, accuracy of 0.96-0.97, and F1-score of 0.96-0.97. In addition, D-dimer, eosinophil, glucose, aspartate aminotransferase, and basophil, which are rather nonspecific laboratory test results, are demonstrated to be important features in differentiating the two disease groups.

CONCLUSIONS

The boosting model, which excels in producing classification models using categorical data, excels in developing classification models using linear numerical data, such as laboratory tests. Finally, the proposed model can be applied in various fields to solve classification problems.

Basophils beyond allergic and parasitic diseases

Basophils bind IgE via FcεRI-αβγ2, which they uniquely share only with mast cells. In doing so, they can rapidly release mediators that are hallmark of allergic disease. This fundamental similarity, along with some morphological features shared by the two cell types, has long brought into question the biological significance that basophils mediate beyond that of mast cells. Unlike mast cells, which mature and reside in tissues, basophils are released into circulation from the bone marrow (constituting 1% of leukocytes), only to infiltrate tissues under specific inflammatory conditions. Evidence is emerging that basophils mediate non-redundant roles in allergic disease and, unsuspectingly, are implicated in a variety of other pathologies [e.g., myocardial infarction, autoimmunity, chronic obstructive pulmonary disease, fibrosis, cancer, etc.]. Recent findings strengthen the notion that these cells mediate protection from parasitic infections, whereas related studies implicate basophils promoting wound healing. Central to these functions is the substantial evidence that human and mouse basophils are increasingly implicated as important sources of IL-4 and IL-13. Nonetheless, much remains unclear regarding the role of basophils in pathology vs. homeostasis. In this review, we discuss the dichotomous (protective and/or harmful) roles of basophils in a wide spectrum of non-allergic disorders.

Mixed storm in SARS-CoV-2 infection: A narrative review and new term in the Covid-19 era

Coronavirus disease 2019 (Covid-19) is caused by a novel severe acute respiratory syndrome coronavirus virus type 2 (SARS-CoV-2) leading to the global pandemic worldwide. Systemic complications in Covid-19 are mainly related to the direct SARS-CoV-2 cytopathic effects, associated hyperinflammation, hypercytokinemia, and the development of cytokine storm (CS). As well, Covid-19 complications are developed due to the propagation of oxidative and thrombotic events which may progress to a severe state called oxidative storm and thrombotic storm (TS), respectively. In addition, inflammatory and lipid storms are also developed in Covid-19 due to the activation of inflammatory cells and the release of bioactive lipids correspondingly. Therefore, the present narrative review aimed to elucidate the interrelated relationship between different storm types in Covid-19 and the development of the mixed storm (MS). In conclusion, SARS-CoV-2 infection induces various storm types including CS, inflammatory storm, lipid storm, TS and oxidative storm. These storms are not developing alone since there is a close relationship between them. Therefore, the MS seems to be more appropriate to be related to severe Covid-19 than CS, since it develops in Covid-19 due to the intricate interface between reactive oxygen species, proinflammatory cytokines, complement activation, coagulation disorders, and activated inflammatory signaling pathway.

A Decision Support System for Diagnosis of COVID-19 from Non-COVID-19 Influenza-like Illness Using Explainable Artificial Intelligence

The coronavirus pandemic emerged in early 2020 and turned out to be deadly, killing a vast number of people all around the world. Fortunately, vaccines have been discovered, and they seem effectual in controlling the severe prognosis induced by the virus. The reverse transcription-polymerase chain reaction (RT-PCR) test is the current golden standard for diagnosing different infectious diseases, including COVID-19; however, it is not always accurate. Therefore, it is extremely crucial to find an alternative diagnosis method which can support the results of the standard RT-PCR test. Hence, a decision support system has been proposed in this study that uses machine learning and deep learning techniques to predict the COVID-19 diagnosis of a patient using clinical, demographic and blood markers. The patient data used in this research were collected from two Manipal hospitals in India and a custom-made, stacked, multi-level ensemble classifier has been used to predict the COVID-19 diagnosis. Deep learning techniques such as deep neural networks (DNN) and one-dimensional convolutional networks (1D-CNN) have also been utilized. Further, explainable artificial techniques (XAI) such as Shapley additive values (SHAP), ELI5, local interpretable model explainer (LIME), and QLattice have been used to make the models more precise and understandable. Among all of the algorithms, the multi-level stacked model obtained an excellent accuracy of 96%. The precision, recall, f1-score and AUC obtained were 94%, 95%, 94% and 98% respectively. The models can be used as a decision support system for the initial screening of coronavirus patients and can also help ease the existing burden on medical infrastructure.

Immunometabolic interference between cancer and COVID-19

Even though cancer patients are generally considered more susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, the mechanisms driving their predisposition to severe forms of coronavirus disease 2019 (COVID-19) have not yet been deciphered. Since metabolic disorders are associated with homeostatic frailty, which increases the risk of infection and cancer, we asked whether we could identify immunometabolic pathways intersecting with cancer and SARS-CoV-2 infection. Thanks to a combined flow cytometry and multiomics approach, here we show that the immunometabolic traits of COVID-19 cancer patients encompass alterations in the frequency and activation status of circulating myeloid and lymphoid subsets, and that these changes are associated with i) depletion of tryptophan and its related neuromediator tryptamine, ii) accumulation of immunosuppressive tryptophan metabolites (i.e., kynurenines), and iii) low nicotinamide adenine dinucleotide (NAD+) availability. This metabolic imbalance is accompanied by altered expression of inflammatory cytokines in peripheral blood mononuclear cells (PBMCs), with a distinctive downregulation of IL-6 and upregulation of IFNγ mRNA expression levels. Altogether, our findings indicate that cancer not only attenuates the inflammatory state in COVID-19 patients but also contributes to weakening their precarious metabolic state by interfering with NAD+-dependent immune homeostasis.

Role of SARS-CoV-2 Spike-Protein-Induced Activation of Microglia and Mast Cells in the Pathogenesis of Neuro-COVID

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19). About 45% of COVID-19 patients experience several symptoms a few months after the initial infection and develop post-acute sequelae of SARS-CoV-2 (PASC), referred to as "Long-COVID," characterized by persistent physical and mental fatigue. However, the exact pathogenetic mechanisms affecting the brain are still not well-understood. There is increasing evidence of neurovascular inflammation in the brain. However, the precise role of the neuroinflammatory response that contributes to the disease severity of COVID-19 and long COVID pathogenesis is not clearly understood. Here, we review the reports that the SARS-CoV-2 spike protein can cause blood-brain barrier (BBB) dysfunction and damage neurons either directly, or via activation of brain mast cells and microglia and the release of various neuroinflammatory molecules. Moreover, we provide recent evidence that the novel flavanol eriodictyol is particularly suited for development as an effective treatment alone or together with oleuropein and sulforaphane (ViralProtek®), all of which have potent anti-viral and anti-inflammatory actions.

Increase of mast cells in COVID-19 pneumonia may contribute to pulmonary fibrosis and thrombosis

AIMS

Lung tissue from COVID-19 patients shares similar histomorphological features with chronic lung allograft disease, also suggesting activation of autoimmune-related pathways in COVID-19. To more clearly understand the underlying spectrum of pathophysiology in COVID-19 pneumonia, we analysed mRNA expression of autoimmune-related genes in post-mortem lung tissue from COVID-19 patients.

METHODS AND RESULTS

Formalin-fixed, paraffin-embedded lung tissue samples of 18 COVID-19 patients and eight influenza patients were used for targeted gene expression profiling using NanoString technology. Multiplex immunofluorescence for tryptase and chymase was applied for validation. Genes related to mast cells were significantly increased in COVID-19. This finding was strengthened by multiplex immunofluorescence also showing a significant increase of tryptase- and chymase-positive cells in COVID-19. Furthermore, receptors for advanced glycation end-products (RAGE) and pro-platelet basic protein (PPBP) were up-regulated in COVID-19 compared to influenza. Genes associated with Type I interferon signalling showed a significant correlation to detected SARS-CoV2 pathway-related genes. The comparison of lung tissue samples from both groups based on the presence of histomorphological features indicative of acute respiratory distress syndrome did not result in finding any specific gene or pathways.

CONCLUSION

Two separate means of measuring show a significant increase of mast cells in SARS-CoV-2-infected lung tissue compared to influenza. Additionally, several genes involved in fibrosis and thrombosis, among which are RAGE and PPBP, are up-regulated in COVID-19. As mast cells are able to induce thrombosis and fibrosis, they may play an important role in the pathogenesis of COVID-19.

Blood leukocyte transcriptional modules and differentially expressed genes associated with disease severity and age in COVID-19 patients

Since the molecular mechanisms determining COVID-19 severity are not yet well understood, there is a demand for biomarkers derived from comparative transcriptome analyses of mild and severe cases, combined with patients' clinico-demographic and laboratory data. Here the transcriptomic response of human leukocytes to SARS-CoV-2 infection was investigated by focusing on the differences between mild and severe cases and between age subgroups (younger and older adults). Three transcriptional modules correlated with these traits were functionally characterized, as well as 23 differentially expressed genes (DEGs) associated to disease severity. One module, correlated with severe cases and older patients, had an overrepresentation of genes involved in innate immune response and in neutrophil activation, whereas two other modules, correlated with disease severity and younger patients, harbored genes involved in the innate immune response to viral infections, and in the regulation of this response. This transcriptomic mechanism could be related to the better outcome observed in younger COVID-19 patients. The DEGs, all hyper-expressed in the group of severe cases, were mostly involved in neutrophil activation and in the p53 pathway, therefore related to inflammation and lymphopenia. These biomarkers may be useful for getting a better stratification of risk factors in COVID-19.

The mast cell exosome-fibroblast connection: A novel pro-fibrotic pathway

Introduction

In addition to the traditional activation of resident receptors by release of local mediators, new evidence favors the existence of exosomes in cell-to-cell communication that mediates delivery of specific cargo to modulate recipient cell function. We report that mast cell exosomes are an additional source of pro-fibrotic substances and constitute a unique pathway for the generation of excess collagen.

Methods

We use primary human lung fibroblasts (HLFs) to demonstrate the uptake of labeled exosomes isolated from the human mast cell line HMC-1 (MC-EXOs), previously shown to contain protein cargo in common with human mast cell exosomes.

Results

The MC-EXO uptake by HLF is to the cytosol and increases both proline hydroxylation in HLF lysate and secreted collagen, within 24 h, which is sustained over 72 h, the same time required for transforming growth factor-β (TGF-β) to activate collagen synthesis in the HLFs. Unlike TGF-β, MC-EXO uptake does not induce fibrillar gene activation or invoke the Smad-nuclear transcription pathway. We show that MC-EXO uptake and TGF-β have an additive effect on collagen synthesis in HLF and postulate that MC-EXO uptake by HLFs is a contributing factor to excess collagen synthesis and represents a unique paradigm for understanding fibrosis.

Discussion

It is known that, in the lungs, mast cells are more activated and increase in number with inflammation, injury and viral infection associated with fibrosis. With the reported increased incidence of post-COVID-pulmonary fibrosis (PCPF), data from patients with severe COVID-19 are presented that show an increase in the mast cell number in lung parenchyma, the site of PCPF. Our findings provide a rationale for targeting multiple fibrogenic pathways in the management of lung fibrosis and the use of mast cell exosomes as a biomarker for the prognostic and diagnostic management of evolving fibrotic lung disease.

Cellular immune states in SARS-CoV-2-induced disease

The general immune state plays important roles against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Cells of the immune system are encountering rapid changes during the acute phase of SARS-CoV-2-induced disease. Reduced fraction of functional CD8⁺ T cells, disrupted cross-talking between CD8⁺ T cells with dendritic cells (DCs), and impaired immunological T-cell memory, along with the higher presence of hyperactive neutrophils, high expansion of myeloid-derived suppressor cells (MDSCs) and non-classical monocytes, and attenuated cytotoxic capacity of natural killer (NK) cells, are all indicative of low efficient immunity against viral surge within the body. Immune state and responses from pro- or anti-inflammatory cells of the immune system to SARS-CoV-2 are discussed in this review. We also suggest some strategies to enhance the power of immune system against SARS-CoV-2-induced disease.

IL-33 and the Cytokine Storm in COVID-19: From a Potential Immunological Relationship towards Precision Medicine

Coronavirus SARS-CoV-2 has represented, and still represents, a real challenge from a clinical, diagnostic and therapeutic point of view. During acute infection, the increased levels of pro-inflammatory cytokines, which are involved in the pathology of disease and the development of SARS-CoV-2-induced acute respiratory disease syndrome, the life-threatening form of this infection, are correlated with patient survival and disease severity. IL-33, a key cytokine involved in both innate and adaptive immune responses in mucosal organs, can increase airway inflammation, mucus secretion and Th2 cytokine synthesis in the lungs, following respiratory infections. Similar to cases of exposure to known respiratory virus infections, exposure to SARS-CoV-2 induces the expression of IL-33, correlating with T-cell activation and lung disease severity. In this work, we analyse current evidence regarding the immunological role of IL-33 in patients affected by COVID-19, to evaluate not only the clinical impact correlated to its production but also to identify possible future immunological therapies that can block the most expressed inflammatory molecules, preventing worsening of the disease and saving patient lives.

The machine learning model based on trajectory analysis of ribonucleic acid test results predicts the necessity of quarantine in recurrently positive patients with SARS-CoV-2 infection

Background

SARS-CoV-2 patients re-experiencing positive nucleic acid test results after recovery is a concerning phenomenon. Current pandemic prevention strategy demands the quarantine of all recurrently positive patients. This study provided evidence on whether quarantine is required in those patients, and predictive algorithms to detect subjects with infectious possibility.

Methods

This observational study recruited recurrently positive patients who were admitted to our shelter hospital between May 12 and June 10, 2022. The demographic and epidemiologic data was collected, and nucleic acid tests were performed daily. virus isolation was done in randomly selected cases. The group-based trajectory model was developed based on the cycle threshold (Ct) value variations. Machine learning models were validated for prediction accuracy.

Results

Among the 494 subjects, 72.04% were asymptomatic, and 23.08% had a Ct value under 30 at recurrence. Two trajectories were identified with either rapid (92.24%) or delayed (7.76%) recovery of Ct values. The latter had significantly higher incidence of comorbidities; lower Ct value at recurrence; more persistent cough; and more frequently reported close contacts infection compared with those recovered rapidly. However, negative virus isolation was reported in all selected samples. Our predictive model can efficiently discriminate those with delayed Ct value recovery and infectious potentials.

Conclusion

Quarantine seems to be unnecessary for the majority of re-positive patients who may have low transmission risks. Our predictive algorithm can screen out the suspiciously infectious individuals for quarantine. These findings may assist the enaction of SARS-CoV-2 pandemic prevention strategies regarding recurrently positive patients in the future.

Predictive markers for clinical outcomes in a cohort of diabetic patients hospitalized for COVID-19

INTRODUCTION

The role of glycemic control, both prior and during hospitalization, on mortality from COVID-19 in diabetic patients is debated. Furthermore, it is not clear whether hyperglycemia has a direct effect or requires inflammatory mechanisms.

OBJECTIVE

To identify predictors of clinical outcomes (in-hospital mortality, length of hospitalization, respiratory failure, need for intensive care), considering hyperglycemia, inflammation markers and clinical history.

METHODS

Retrospective observational study of 291 diabetic patients hospitalized with COVID-19 in the Spedali Civili di Brescia from February 1th 2020 to March 31th 2021, with also outpatient electronic records. Glucose, inflammatory parameters, creatinine were collected within 24 h after admission to the hospital. A causal mediation analysis allowed the estimation of the direct and indirect effects of hyperglycemia on mortality.

RESULTS

Glucose at admission ≥ 165 mg/dL and reduced renal function were associated with an increased risk of in-hospital mortality and length of hospitalization (all p < 0.001), while an increase in inflammatory parameters was significantly associated with an increased risk of all outcomes. High basophil count was associated with reduced mortality (p < 0.001). Hyperglycemia had a direct effect on mortality (p < 0.001); the indirect, through inflammatory markers, was significant only for absolute neutrophil count, C-Reactive protein and procalcitonin (p = 0.007, p = 0.029, p = 0.042). Patients with microvascular complications and with chronic kidney disease showed higher mortality (p = 0.03, p = 0.01).

CONCLUSIONS

Hyperglycemia at admission, renal function and inflammatory parameters were found to be predictors of in-hospital mortality, while an increased basophil count was protective. Hyperglycemia had a direct effect on mortality, the indirect effect was only through few markers and markedly lower than the direct one.

Mast Cell's Role in Cytokine Release Syndrome and Related Manifestations of COVID-19 Disease

In this narrative review, firstly, we describe the characteristics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the pathogenesis of its infection in humans. Later, the importance of mast cells in SARS-CoV-2 infection and their role in Coronavirus Disease 2019 (COVID-19) will be discussed. SARS-CoV-2 is a transmissible agent frequently detected in some mammalian species and also in humans. Literature data published in PubMed that covered mast cells' role in cytokine release syndrome and related manifestations of COVID-19 disease were reviewed by the authors independently and collectively. Recommendations for the management of cytokine release syndrome and related manifestations were made by the authors. Mast cells are concentrated in environments where they encounter viruses, bacteria, and toxins, especially in the skin, nasal mucosa, lungs, airways, gastrointestinal tract, and meninges, to prevent their entry into the human body. Once SARS-CoV-2 enters the host, it stimulates one of the mast cells, together with pre-existing innate immune cells that form a defensive barrier in the submucosa of the respiratory tract and nasal cavities against pathogenic microorganisms. The roles of mast cells in SARS-CoV-2-induced hyperinflammation and cytokine storms have recently been one of the hot topics in the literature. Physicians should keep in mind the mast cells' role in cytokine release syndrome and related manifestations of COVID-19 disease. Mast cell-targeting therapies (e.g., H1 and H2 receptor antagonists) can reduce the severity and course of the disease when used after complications associated with COVID-19 are suspected or seen.

Genetics of COVID-19 and myalgic encephalomyelitis/chronic fatigue syndrome: a systematic review

COVID‐19 and ME/CFS present with some similar symptoms, especially physical and mental fatigue. In order to understand the basis of these similarities and the possibility of underlying common genetic components, we performed a systematic review of all published genetic association and cohort studies regarding COVID‐19 and ME/CFS and extracted the genes along with the genetic variants investigated. We then performed gene ontology and pathway analysis of those genes that gave significant results in the individual studies to yield functional annotations of the studied genes using protein analysis through evolutionary relationships (PANTHER) VERSION 17.0 software. Finally, we identified the common genetic components of these two conditions. Seventy‐one studies for COVID‐19 and 26 studies for ME/CFS were included in the systematic review in which the expression of 97 genes for COVID‐19 and 429 genes for ME/CFS were significantly affected. We found that ACE, HLA‐A, HLA‐C, HLA‐DQA1, HLA‐DRB1, and TYK2 are the common genes that gave significant results. The findings of the pathway analysis highlight the contribution of inflammation mediated by chemokine and cytokine signaling pathways, and the T cell activation and Toll receptor signaling pathways. Protein class analysis revealed the contribution of defense/immunity proteins, as well as protein‐modifying enzymes. Our results suggest that the pathogenesis of both syndromes could involve some immune dysfunction.

COVID-19, obesity, and immune response 2 years after the pandemic: A timeline of scientific advances

In the 2 years since the COVID-19 pandemic was officially declared, science has made considerable strides in understanding the disease's pathophysiology, pharmacological treatments, immune response, and vaccination, but there is still much room for further advances, especially in comprehending its relationship with obesity. Science has not yet described the mechanisms that explain how obesity is directly associated with a poor prognosis. This paper gathers all published studies over the past 2 years that have described immune response, obesity, and COVID-19, a historical and chronological record for researchers and the general public alike. In summary, these studies describe how the cytokine/adipokine levels and inflammatory markers, such as the C-reactive protein, are associated with a higher body mass index in COVID-19-positive patients, suggesting that the inflammatory background and immune dysregulation in individuals with obesity may be expressed in the results and that adiposity may influence the immune response. The timeline presented here is a compilation of the results of 2 years of scientific inquiry, describing how the science has progressed, the principal findings, and the challenges ahead regarding SARS-CoV-2, COVID-19, and emerging variants, especially in patients with obesity.

Uncovering the Mast Cell Response to Mycobacterium tuberculosis

The immunologic mechanisms that contribute to the response to Mycobacterium tuberculosis infection still represent a challenge in the clinical management and scientific understanding of tuberculosis disease. In this scenario, the role of the different cells involved in the host response, either in terms of innate or adaptive immunity, remains key for defeating this disease. Among this coordinated cell response, mast cells remain key for defeating tuberculosis infection and disease. Together with its effector’s molecules, membrane receptors as well as its anatomical locations, mast cells play a crucial role in the establishment and perpetuation of the inflammatory response that leads to the generation of the granuloma during tuberculosis. This review highlights the current evidences that support the notion of mast cells as key link to reinforce the advancements in tuberculosis diagnosis, disease progression, and novel therapeutic strategies. Special focus on mast cells capacity for the modulation of the inflammatory response among patients suffering multidrug resistant tuberculosis or in co-infections such as current COVID-19 pandemic.

Role of Basophils in a Broad Spectrum of Disorders

Basophils are the rarest granulocytes and have long been overlooked in immunological research due to their rarity and similarities with tissue-resident mast cells. In the last two decades, non-redundant functions of basophils have been clarified or implicated in a broad spectrum of immune responses, particularly by virtue of the development of novel analytical tools for basophils. Basophils infiltrate inflamed tissues of patients with various disorders, even though they circulate in the bloodstream under homeostatic conditions. Depletion of basophils results in the amelioration or exaggeration of inflammation, depending on models of disease, indicating basophils can play either beneficial or deleterious roles in a context-dependent manner. In this review, we summarize the recent findings of basophil pathophysiology under various conditions in mice and humans, including allergy, autoimmunity, tumors, tissue repair, fibrosis, and COVID-19. Further mechanistic studies on basophil biology could lead to the identification of novel biomarkers or therapeutic targets in a broad range of diseases.

Supporting Clinical COVID-19 Diagnosis with Routine Blood Tests Using Tree-Based Entropy Structured Self-Organizing Maps

Data classification is an automatic or semi-automatic process that, utilizing artificial intelligence algorithms, learns the variable and class relationships of a dataset for use a posteriori in situations where the class result is unknown. For many years, work on this topic has been aimed at increasing the hit rates of algorithms. However, when the problem is restricted to applications in healthcare, besides the concern with performance, it is also necessary to design algorithms whose results are understandable by the specialists responsible for making the decisions. Among the problems in the field of medicine, a current focus is related to COVID-19: AI algorithms may contribute to early diagnosis. Among the available COVID-19 data, the blood test is a typical procedure performed when the patient seeks the hospital, and its use in the diagnosis allows reducing the need for other diagnostic tests that can impact the detection time and add to costs. In this work, we propose using self-organizing map (SOM) to discover attributes in blood test examinations that are relevant for COVID-19 diagnosis. We applied SOM and an entropy calculation in the definition of a hierarchical, semi-supervised and explainable model named TESSOM (tree-based entropy-structured self-organizing maps), in which the main feature is enhancing the investigation of groups of cases with high levels of class overlap, as far as the diagnostic outcome is concerned. Framing the TESSOM algorithm in the context of explainable artificial intelligence (XAI) makes it possible to explain the results to an expert in a simplified way. It is demonstrated in the paper that the use of the TESSOM algorithm to identify attributes of blood tests can help with the identification of COVID-19 cases. It providing a performance increase in 1.489% in multiple scenarios when analyzing 2207 cases from three hospitals in the state of São Paulo, Brazil. This work is a starting point for researchers to identify relevant attributes of blood tests for COVID-19 and to support the diagnosis of other diseases.

Combinational benefit of antihistamines and remdesivir for reducing SARS-CoV-2 replication and alleviating inflammation-induced lung injury in mice

COVID-19 is an immune-mediated inflammatory disease caused by SARS-CoV-2 infection, the combination of anti-inflammatory and antiviral therapy is predicted to provide clinical benefits. We recently demonstrated that mast cells (MCs) are an essential mediator of SARS-CoV-2-initiated hyperinflammation. We also showed that spike protein-induced MC degranulation initiates alveolar epithelial inflammation for barrier disruption and suggested an off-label use of antihistamines as MC stabilizers to block degranulation and consequently suppress inflammation and prevent lung injury. In this study, we emphasized the essential role of MCs in SARS-CoV-2-induced lung lesions in vivo, and demonstrated the benefits of co-administration of antihistamines and antiviral drug remdesivir in SARS-CoV-2-infected mice. Specifically, SARS-CoV-2 spike protein-induced MC degranulation resulted in alveolar-capillary injury, while pretreatment of pulmonary microvascular endothelial cells with antihistamines prevented adhesion junction disruption; predictably, the combination of antiviral drug remdesivir with the antihistamine loratadine, a histamine receptor 1 (HR1) antagonist, dampened viral replication and inflammation, thereby greatly reducing lung injury. Our findings emphasize the crucial role of MCs in SARS-CoV-2-induced inflammation and lung injury and provide a feasible combination antiviral and anti-inflammatory therapy for COVID-19 treatment.

SARS-CoV-2 Infection and Lung Regeneration

The lung is the primary site of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-induced immunopathology whereby the virus enters the host cells by binding to angiotensin-converting enzyme 2 (ACE2). Sophisticated regeneration and repair programs exist in the lungs to replenish injured cell populations. However, known resident stem/progenitor cells have been demonstrated to express ACE2, raising a substantial concern regarding the long-term consequences of impaired lung regeneration after SARS-CoV-2 infection. Moreover, clinical treatments may also affect lung repair from antiviral drug candidates to mechanical ventilation. In this review, we highlight how SARS-CoV-2 disrupts a program that governs lung homeostasis. We also summarize the current efforts of targeted therapy and supportive treatments for COVID-19 patients. In addition, we discuss the pros and cons of cell therapy with mesenchymal stem cells or resident lung epithelial stem/progenitor cells in preventing post-acute sequelae of COVID-19. We propose that, in addition to symptomatic treatments being developed and applied in the clinic, targeting lung regeneration is also essential to restore lung homeostasis in COVID-19 patients.

Comprehensive Analysis of the ILCs and Unconventional T Cells in Virus Infection: Profiling and Dynamics Associated with COVID-19 Disease for a Future Monitoring System and Therapeutic Opportunities

This review is a comprehensive analysis of the effects of SARS-CoV-2 infection on Unconventional T cells and innate lymphoid cells (ILCs). COVID-19 affected patients show dysregulation of their adaptive immune systems, but many questions remain unsolved on the behavior of Unconventional cells and ILCs during infection, considering their role in maintaining homeostasis in tissue. Therefore, we highlight the differences that exist among the studies in cohorts of patients who in general were categorized considering symptoms and hospitalization. Moreover, we make a critical analysis of the presence of particular clusters of cells that express activation and exhausted markers for each group in order to bring out potential diagnostic factors unconsidered before now. We also focus our attention on studies that take into consideration recovered patients. Indeed, it could be useful to determine Unconventional T cells’ and ILCs’ frequencies and functions in longitudinal studies because it could represent a way to monitor the immune status of SARS-CoV-2-infected subjects. Possible changes in cell frequencies or activation profiles could be potentially useful as prognostic biomarkers and for future therapy. Currently, there are no efficacious therapies for SARS-CoV-2 infection, but deep studies on involvement of Unconventional T cells and ILCs in the pathogenesis of COVID-19 could be promising for targeted therapies.

Role of mast cells in the pathogenesis of severe lung damage in COVID-19 patients

BACKGROUND

There is still insufficient knowledge with regard to the potential involvement of mast cells (MCs) and their mediators in the pathology of coronavirus disease-2019 (COVID-19). Therefore, our study aimed to investigate the role of MCs, their activation and protease profiles in the pathogenesis of early and late lung damage in COVID-19 patients.

METHODS

Formalin-fixed and paraffin embedded lung specimens from 30 patients who died from COVID-19 and 9 controls were used for histological detection of MCs and their proteases (tryptase, chymase) followed by morphometric quantification.

RESULTS

Our results demonstrated increased numbers of MCs at early stage and further augmentation of MCs number during the late stage of alveolar damage in COVID-19 patients, as compared to the control group. Importantly, the percentage of degranulated (activated) MCs was higher during both stages of alveolar lesions in comparison to the controls. While there was no prominent alteration in the profile of tryptase-positive MCs, our data revealed a significant elevation in the number of chymase-positive MCs in the lungs of COVID-19 patients, compared to the controls.

CONCLUSIONS

MCs are characterized by dysregulated accumulation and increased activation in the lungs of patients suffering from COVID-19. However, future profound studies are needed for precise analysis of the role of these immune cells in the context of novel coronavirus disease.

Impact of Anti-Type 2 Inflammation Biologic Therapy on COVID-19 Clinical Course and Outcome

SARS-CoV-2 pandemic had a general and deep impact on the clinical management of chronic diseases, including respiratory and allergic disorders. At the beginning of the pandemic, one of the main concerns was the potential impact of immunosuppressive/immunomodulatory drugs on COVID-19 clinical course. In this review, we aim to summarize and analyze the available clinical evidence from patients treated with anti-type 2 inflammation biologics (including anti-IgE, anti-IL-5 and anti-IL-4 agents), who developed COVID-19. Overall, the treatment with anti-Th2 biologics can be considered safe during COVID-19. It does not worsen the clinical course and outcome of COVID-19, and it may be actually protective somehow from developing severe forms. Moreover, patients treated with these biological agents do not seem to be more prone to get infected by SARS-CoV-2.

The Potential Role of Cytokine Storm Pathway in the Clinical Course of Viral Respiratory Pandemic

The "cytokine storm" (CS) consists of a spectrum of different immune dysregulation disorders characterized by constitutional symptoms, systemic inflammation and multiorgan dysfunction triggered by an uncontrolled immune response. Particularly in respiratory virus infections, the cytokine storm plays a primary role in the pathogenesis of respiratory disease and the clinical outcome of respiratory diseases, leading to complications such as alveolar edema and hypoxia. In this review, we wanted to analyze the different pathogenetic mechanisms involved in the various respiratory viral pandemics (COVID-19; SARS; MERS; H1N1 influenza A and Spanish flu) which have affected humans in this and last century, with particular attention to the phenomenon of the "cytokine storm" which determines the clinical severity of the respiratory disease and consequently its lethality.