Common determinants of severe Covid-19 infection are explicable by SARS-CoV-2 secreted glycoprotein interaction with the CD33-related Siglecs, Siglec-3 and Siglec-5/14

Coupling of Alzheimer's Disease Genetic Risk Factors with Viral Susceptibility and Inflammation

Alzheimer's disease (AD) is a neurodegenerative disease characterized by persistent cognitive decline. Amyloid plaque deposition and neurofibrillary tangles are the main pathological features of AD brain, though mechanisms leading to the formation of lesions remain to be understood. Genetic efforts through genome-wide association studies (GWAS) have identified dozens of risk genes influencing the pathogenesis and progression of AD, some of which have been revealed in close association with increased viral susceptibilities and abnormal inflammatory responses in AD patients. In the present study, we try to present a list of AD candidate genes that have been shown to affect viral infection and inflammatory responses. Understanding of how AD susceptibility genes interact with the viral life cycle and potential inflammatory pathways would provide possible therapeutic targets for both AD and infectious diseases.

Multifactorial Causation of Alzheimer's Disease Due to COVID-19

There are several implications of the surge in the incidence of pandemics and epidemics in the last decades. COVID-19 being the most remarkable one, showed the vulnerability of patients with neurodegenerative diseases like Alzheimer's disease (AD). This review studies the pathological interlinks and triggering factors between the two illnesses and proposes a multifactorial pathway of AD causation due to COVID-19. The article evaluates and describes all the postulated hypotheses which explain the etiology and possible pathogenesis of the disease in four domains: Inflammation & Neurobiochemical interactions, Oxidative Stress, Genetic Factors, and Social Isolation. We believe that a probable hypothesis of an underlying cause of AD after COVID-19 infection could be the interplay of all these factors.

Development of a multiomics model for identification of predictive biomarkers for COVID-19 severity: a retrospective cohort study

BACKGROUND

COVID-19 is a multi-system disorder with high variability in clinical outcomes among patients who are admitted to hospital. Although some cytokines such as interleukin (IL)-6 are believed to be associated with severity, there are no early biomarkers that can reliably predict patients who are more likely to have adverse outcomes. Thus, it is crucial to discover predictive markers of serious complications.

METHODS

In this retrospective cohort study, we analysed samples from 455 participants with COVID-19 who had had a positive SARS-CoV-2 RT-PCR result between April 14, 2020, and Dec 1, 2020 and who had visited one of three Mayo Clinic sites in the USA (Minnesota, Arizona, or Florida) in the same period. These participants were assigned to three subgroups depending on disease severity as defined by the WHO ordinal scale of clinical improvement (outpatient, severe, or critical). Our control cohort comprised of 182 anonymised age-matched and sex-matched plasma samples that were available from the Mayo Clinic Biorepository and banked before the COVID-19 pandemic. We did a deep profiling of circulatory cytokines and other proteins, lipids, and metabolites from both cohorts. Most patient samples were collected before, or around the time of, hospital admission, representing ideal samples for predictive biomarker discovery. We used proximity extension assays to quantify cytokines and circulatory proteins and tandem mass spectrometry to measure lipids and metabolites. Biomarker discovery was done by applying an AutoGluon-tabular classifier to a multiomics dataset, producing a stacked ensemble of cutting-edge machine learning algorithms. Global proteomics and glycoproteomics on a subset of patient samples with matched pre-COVID-19 plasma samples was also done.

FINDINGS

We quantified 1463 cytokines and circulatory proteins, along with 902 lipids and 1018 metabolites. By developing a machine-learning-based prediction model, a set of 102 biomarkers, which predicted severe and clinical COVID-19 outcomes better than the traditional set of cytokines, were discovered. These predictive biomarkers included several novel cytokines and other proteins, lipids, and metabolites. For example, altered amounts of C-type lectin domain family 6 member A (CLEC6A), ether phosphatidylethanolamine (P-18:1/18:1), and 2-hydroxydecanoate, as reported here, have not previously been associated with severity in COVID-19. Patient samples with matched pre-COVID-19 plasma samples showed similar trends in muti-omics signatures along with differences in glycoproteomics profile.

INTERPRETATION

A multiomic molecular signature in the plasma of patients with COVID-19 before being admitted to hospital can be exploited to predict a more severe course of disease. Machine learning approaches can be applied to highly complex and multidimensional profiling data to reveal novel signatures of clinical use. The absence of validation in an independent cohort remains a major limitation of the study.

FUNDING

Eric and Wendy Schmidt.

SARS-CoV-2 Attacks in the Brain: Focus on the Sialome

The epidemiological observations suggest that respiratory and gastrointestinal symptoms caused by severe acute respiratory coronavirus 2 (SARS-CoV-2) are accompanied by short- and long-term neurological manifestations. There is increasing evidence that the neuroinvasive potential of SARS-CoV-2 is closely related to its capacity to interact with cell membrane sialome. Given the wide expression of sialylated compounds of cell membranes in the brain, the interplay between cell membrane sialoglycans and the virus is crucial for its attachment and cell entry, transport, neuronal damage and brain immunity. Here, we focus on the significance of the brain sialome in the progress of coronavirus disease 2019 (COVID-19) and SARS-CoV-2-induced neuropathology.

The relationship of early- and late-onset Alzheimer’s disease genes with COVID-19

Individuals with Alzheimer’s disease and other neurodegenerative diseases have been exposed to excess risk by the COVID-19 pandemic. COVID-19’s main manifestations include high body temperature, dry cough, and exhaustion. Nevertheless, some affected individuals may have an atypical presentation at diagnosis but suffer neurological signs and symptoms as the first disease manifestation. These findings collectively show the neurotropic nature of SARS-CoV-2 virus and its ability to involve the central nervous system. In addition, Alzheimer’s disease and COVID-19 has a number of common risk factors and comorbid conditions including age, sex, hypertension, diabetes, and the expression of APOE ε4. Until now, a plethora of studies have examined the COVID-19 disease but only a few studies has yet examined the relationship of COVID-19 and Alzheimer’s disease as risk factors of each other. This review emphasizes the recently published evidence on the role of the genes of early- or late-onset Alzheimer’s disease in the susceptibility of individuals currently suffering or recovered from COVID-19 to Alzheimer’s disease or in the susceptibility of individuals at risk of or with Alzheimer’s disease to COVID-19 or increased COVID-19 severity and mortality. Furthermore, the present review also draws attention to other uninvestigated early- and late-onset Alzheimer’s disease genes to elucidate the relationship between this multifactorial disease and COVID-19.

The impact of DAMP-mediated inflammation in severe COVID-19 and related disorders

The host response to SARS-CoV-2, the virus that causes COVID-19, is highly heterogeneous, ranging from mild/asymptomatic to severe. The moderate to severe forms of COVID-19 often require hospitalization, are associated with a high rate of mortality, and appear to be caused by an inappropriately exaggerated inflammatory response to the virus. Emerging data confirm the involvement of both innate and adaptive immune pathways both in protection from SARS-CoV-2, and in driving the pathology of severe COVID-19. In particular, innate immune cells including neutrophils appear to be key players in the inflammation that causes the vicious cycle of damage and inflammation that underlies the symptomatology of severe COVID-19. Several recent studies support a link between damage and inflammation, with damage-associated molecular patterns (DAMPs) playing a key role in the pathology of severe COVID-19. In this review, we put into perspective the role of DAMPs and of components of the DAMP-signaling cascade, including Siglecs and their cognate ligands CD24 and CD52, in COVID-19. Further, we review clinical data on proposed therapeutics targeting DAMP pathways to treat SARS-CoV-2 infection and the regulation of these signaling cascades in COVID-19. We also discuss the potential impact of DAMP-mediated inflammation in other indications related to COVID-19, such as ARDS, endothelial dysfunction, hypercoagulation, and sepsis.

Effects of Bacille Calmette Guerin (BCG) vaccination during COVID-19 infection

The coronavirus disease 2019 (COVID-19) is caused by the infection of highly contagious severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), also known as the novel coronavirus. In most countries, the containment of this virus spread is not controlled, which is driving the pandemic towards a more difficult phase. In this study, we investigated the impact of the Bacille Calmette Guerin (BCG) vaccination on the severity and mortality of COVID-19 by performing transcriptomic analyses of SARS-CoV-2 infected and BCG vaccinated samples in peripheral blood mononuclear cells (PBMC). A set of common differentially expressed genes (DEGs) were identified and seeded into their functional enrichment analyses via Gene Ontology (GO)-based functional terms and pre-annotated molecular pathways databases, and their Protein-Protein Interaction (PPI) network analysis. We further analysed the regulatory elements, possible comorbidities and putative drug candidates for COVID-19 patients who have not been BCG-vaccinated. Differential expression analyses of both BCG-vaccinated and COVID-19 infected samples identified 62 shared DEGs indicating their discordant expression pattern in their respected conditions compared to control. Next, PPI analysis of those DEGs revealed 10 hub genes, namely ITGB2, CXCL8, CXCL1, CCR2, IFNG, CCL4, PTGS2, ADORA3, TLR5 and CD33. Functional enrichment analyses found significantly enriched pathways/GO terms including cytokine activities, lysosome, IL-17 signalling pathway, TNF-signalling pathways. Moreover, a set of identified TFs, miRNAs and potential drug molecules were further investigated to assess their biological involvements in COVID-19 and their therapeutic possibilities. Findings showed significant genetic interactions between BCG vaccination and SARS-CoV-2 infection, suggesting an interesting prospect of the BCG vaccine in relation to the COVID-19 pandemic. We hope it may potentially trigger further research on this critical phenomenon to combat COVID-19 spread.

Role of myeloid-derived suppressor cells in viral respiratory infections; Hints for discovering therapeutic targets for COVID-19

The expansion of myeloid-derived suppressor cells (MDSCs), known as heterogeneous population of immature myeloid cells, is enhanced during several pathological conditions such as inflammatory or viral respiratory infections. It seems that the way MDSCs behave in infection depends on the type and the virulence mechanisms of the invader pathogen, the disease stage, and the infection-related pathology. Increasing evidence showing that in correlation with the severity of the disease, MDSCs are accumulated in COVID-19 patients, in particular in those at severe stages of the disease or ICU patients, contributing to pathogenesis of SARS-CoV2 infection. Based on the involved subsets, MDSCs delay the clearance of the virus through inhibiting T-cell proliferation and responses by employing various mechanisms such as inducing the secretion of anti-inflammatory cytokines, inducible nitric oxide synthase (iNOS)-mediated hampering of IFN-γ production, or forcing arginine shortage. While the immunosuppressive characteristic of MDSCs may help to preserve the tissue homeostasis and prevent hyperinflammation at early stages of the infection, hampering of efficient immune responses proved to exert significant pathogenic effects on severe forms of COVID-19, suggesting the targeting of MDSCs as a potential intervention to reactivate T-cell immunity and thereby prevent the infection from developing into severe stages of the disease. This review tried to compile evidence on the roles of different subsets of MDSCs during viral respiratory infections, which is far from being totally understood, and introduce the promising potential of MDSCs for developing novel diagnostic and therapeutic approaches, especially against COVID-19 disease.

Sialic Acid-Siglec Axis in Human Immune Regulation, Involvement in Autoimmunity and Cancer and Potential Therapeutic Treatments

Siglecs are sialic acid-binding immunoglobulin-like lectins. Most Siglecs function as transmembrane receptors mainly expressed on blood cells in a cell type-specific manner. They recognize and bind sialic acids in specific linkages on glycoproteins and glycolipids. Since Sia is a self-molecule, Siglecs play a role in innate immune responses by distinguishing molecules as self or non-self. Increasing evidence supports the involvement of Siglecs in immune signaling representing immune checkpoints able to regulate immune responses in inflammatory diseases as well as cancer. Although further studies are necessary to fully understand the involvement of Siglecs in pathological conditions as well as their interactions with other immune regulators, the development of therapeutic approaches that exploit these molecules represents a tremendous opportunity for future treatments of several human diseases, as demonstrated by their application in several clinical trials. In the present review, we discuss the involvement of Siglecs in the regulation of immune responses, with particular focus on autoimmunity and cancer and the chance to target the sialic acid-Siglec axis as novel treatment strategy.

Enhanced expression of immune checkpoint receptors during SARS-CoV-2 viral infection

The immune system is tightly regulated by the activity of stimulatory and inhibitory immune receptors. This immune homeostasis is usually disturbed during chronic viral infection. Using publicly available transcriptomic datasets, we conducted in silico analyses to evaluate the expression pattern of 38 selected immune inhibitory receptors (IRs) associated with different myeloid and lymphoid immune cells during coronavirus disease 2019 (COVID-19) infection. Our analyses revealed a pattern of overall upregulation of IR mRNA during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. A large number of IRs expressed on both lymphoid and myeloid cells were upregulated in nasopharyngeal swabs (NPSs), while lymphoid-associated IRs were specifically upregulated in autopsies, reflecting severe, terminal stage COVID-19 disease. Eight genes (BTLA, LAG3, FCGR2B, PDCD1, CEACAM1, CTLA4, CD72, and SIGLEC7), shared by NPSs and autopsies, were more expressed in autopsies and were directly correlated with viral levels. Single-cell data from blood and bronchoalveolar samples also reflected the observed association between IR upregulation and disease severity. Moreover, compared to SARS-CoV-1, influenza, and respiratory syncytial virus infections, the number and intensities of upregulated IRs were higher in SARS-CoV-2 infections. In conclusion, the immunopathology and severity of COVID-19 could be attributed to dysregulation of different immune inhibitors. Targeting one or more of these immune inhibitors could represent an effective therapeutic approach for the treatment of COVID-19 early and late immune dysregulations.

The therapeutic potential of sialylated Fc domains of human IgG

Pathogens frequently use multivalent binding to sialic acid to infect cells or to modulate immunity through interactions with human sialic acid-binding immunoglobulin-type lectins (Siglecs). Molecules that interfere with these interactions could be of interest as diagnostics, anti-infectives or as immune modulators. This review describes the development of molecular scaffolds based on the crystallizable fragment (Fc) region of immunoglobulin (Ig) G that deliver high-avidity binding to innate immune receptors, including sialic acid-dependent receptors. The ways in which the sialylated Fc may be engineered as immune modulators that mimic the anti-inflammatory properties of intravenous polyclonal Ig or as blockers of sialic-acid-dependent infectivity by viruses are also discussed.