The relationship between cytokine and neutrophil gene network distinguishes SARS-CoV-2-infected patients by sex and age

Dysregulated autoantibodies targeting AGTR1 are associated with the accumulation of COVID-19 symptoms

Coronavirus disease 2019 (COVID-19) presents a wide spectrum of symptoms, the causes of which remain poorly understood. This study explored the associations between autoantibodies (AABs), particularly those targeting G protein-coupled receptors (GPCRs) and renin‒angiotensin system (RAS) molecules, and the clinical manifestations of COVID-19. Using a cross-sectional analysis of 244 individuals, we applied multivariate analysis of variance, principal component analysis, and multinomial regression to examine the relationships between AAB levels and key symptoms. Significant correlations were identified between specific AABs and symptoms such as fever, muscle aches, anosmia, and dysgeusia. Notably, anti-AGTR1 antibodies, which contribute to endothelial glycocalyx (eGC) degradation, a process reversed by losartan, have emerged as strong predictors of core symptoms. AAB levels increased with symptom accumulation, peaking in patients exhibiting all four key symptoms. These findings highlight the role of AABs, particularly anti-AGTR1 antibodies, in determining symptom severity and suggest their involvement in the pathophysiology of COVID-19, including vascular complications.

Spatial maps in piriform cortex during olfactory navigation

Odors are a fundamental part of the sensory environment used by animals to inform behaviors such as foraging and navigation1,2. Primary olfactory (piriform) cortex is thought to be dedicated to encoding odor identity3-8. Here, using neural ensemble recordings in freely moving rats performing a novel odor-cued spatial choice task, we show that posterior piriform cortex neurons also carry a robust spatial map of the environment. Piriform spatial maps were stable across behavioral contexts independent of olfactory drive or reward availability, and the accuracy of spatial information carried by individual neurons depended on the strength of their functional coupling to the hippocampal theta rhythm. Ensembles of piriform neurons concurrently represented odor identity as well as spatial locations of animals, forming an "olfactory-place map". Our results reveal a previously unknown function for piriform cortex in spatial cognition and suggest that it is well-suited to form odor-place associations and guide olfactory cued spatial navigation.

Chemokine receptors in COVID-19 infection

Chemokine receptors play diverse roles in the immune response against pathogens by recruiting innate and adaptive immune cells to sites of infection. However, their involvement could also be detrimental, causing tissue damage and exacerbating respiratory diseases by triggering histological alterations such as fibrosis and remodeling. This chapter reviews the role of chemokine receptors in the immune defense against SARS-CoV-2 infection. In COVID-19, CXCR3 is expressed mainly in T cells, and its upregulation is related to an increase in SARS-CoV-2-specific antibodies but also to COVID-19 severity. CCR5 is a key player in T-cell recruitment, and its suppression leads to reduced inflammation and viremia levels. Conversely, CXCR6 is implicated in the aberrant migration of memory T cells within airways. On the other hand, increased CCR4+ cells in the blood and decreased CCR4+ cells in lung cells are associated with severe COVID-19. Additionally, CCR2 is associated with an increase in macrophage recruitment to lung tissues. Elevated levels of CXCR1 and CXCR2, which are predominantly expressed in neutrophils, are associated with the severity of the disease, and finally, the expression of CX3CR1 in cytotoxic T lymphocytes affects the retention of these cells in lung tissues, thereby impacting the severity of COVID-19. Despite the efforts of many clinical trials to find effective therapies for COVID-19 using chemokine receptor inhibitors, no conclusive results have been found due to the small number of patients, redundancy, and co-expression of chemokine receptors by immune cells, which explains the difficulty in finding a single therapeutic target or effective treatment.

Differences between human male and female neutrophils in mRNA, translation efficiency, protein, and phosphoprotein profiles

Background

Human males and females show differences in the incidence of neutrophil-associated diseases such as systemic lupus erythematosus, rheumatoid arthritis, and reactive arthritis, and differences in neutrophil physiological responses such as a faster response to the chemorepellent SLIGKV. Little is known about the basis of sex-based differences in human neutrophils.

Methods

Starting with human neutrophils from healthy donors, we used RNA-seq to examine total mRNA profiles, mRNAs not associated with ribosomes and thus not being translated, mRNAs in monosomes, and mRNAs in polysomes and thus heavily translated. We used mass spectrometry systems to identify proteins and phosphoproteins.

Results

There were sex-based differences in the translation of 24 mRNAs. There were 132 proteins with higher levels in male neutrophils; these tended to be associated with RNA regulation, ribosome, and phosphoinositide signaling pathways, whereas 30 proteins with higher levels in female neutrophils were associated with metabolic processes, proteosomes, and phosphatase regulatory proteins. Male neutrophils had increased phosphorylation of 32 proteins. After exposure to SLIGKV, male neutrophils showed a faster response in terms of protein phosphorylation compared to female neutrophils.

Conclusions

Male neutrophils have higher levels of proteins and higher phosphorylation of proteins associated with RNA processing and signaling pathways, while female neutrophils have higher levels of proteins associated with metabolism and proteolytic pathways. This suggests that male neutrophils might be more ready to adapt to a new environment, and female neutrophils might be more effective at responding to pathogens. This may contribute to the observed sex-based differences in neutrophil behavior and neutrophil-associated disease incidence and severity.

Blocking the CTLA-4 and PD-1 pathways during pulmonary paracoccidioidomycosis improves immunity, reduces disease severity, and increases the survival of infected mice

Immune checkpoint pathways, i.e., coinhibitory pathways expressed as feedback following immune activation, are crucial for controlling an excessive immune response. Cytotoxic T lymphocyte antigen-4 (CTLA-4) and programmed cell death protein-1 (PD-1) are the central classical checkpoint inhibitory (CPI) molecules used for the control of neoplasms and some infectious diseases, including some fungal infections. As the immunosuppression of severe paracoccidioidomycosis (PCM), a chronic granulomatous fungal disease, was shown to be associated with the expression of coinhibitory molecules, we hypothesized that the inhibition of CTLA-4 and PD-1 could have a beneficial effect on pulmonary PCM. To this end, C57BL/6 mice were infected with Paracoccidioides brasiliensis yeasts and treated with monoclonal antibodies (mAbs) α-CTLA-4, α-PD-1, control IgG, or PBS. We verified that blockade of CTLA-4 and PD-1 reduced the fungal load in the lungs and fungal dissemination to the liver and spleen and decreased the size of pulmonary lesions, resulting in increased survival of mice. Compared with PBS-treated infected mice, significantly increased levels of many pro- and anti-inflammatory cytokines were observed in the lungs of α-CTLA-4-treated mice, but a drastic reduction in the liver was observed following PD-1 blockade. In the lungs of α-CPI and IgG-treated mice, there were no changes in the frequency of inflammatory leukocytes, but a significant reduction in the total number of these cells was observed. Compared with PBS-treated controls, α-CPI- and IgG-treated mice exhibited reduced pulmonary infiltration of several myeloid cell subpopulations and decreased expression of costimulatory molecules. In addition, a decreased number of CD4+ and CD8+ T cells but sustained numbers of Th1, Th2, and Th17 T cells were detected. An expressive reduction in several Treg subpopulations and their maturation and suppressive molecules, in addition to reduced numbers of Treg, TCD4+, and TCD8+ cells expressing costimulatory and coinhibitory molecules of immunity, were also detected. The novel cellular and humoral profiles established in the lungs of α-CTLA-4 and α-PD-1-treated mice but not in control IgG-treated mice were more efficient at controlling fungal growth and dissemination without causing increased tissue pathology due to excessive inflammation. This is the first study demonstrating the efficacy of CPI blockade in the treatment of pulmonary PCM, and further studies combining the use of immunotherapy with antifungal drugs are encouraged.

Immunological signatures unveiled by integrative systems vaccinology characterization of dengue vaccination trials and natural infection

Introduction

Dengue virus infection is a global health problem lacking specific therapy, requiring an improved understanding of DENV immunity and vaccine responses. Considering the recent emerging of new dengue vaccines, here we performed an integrative systems vaccinology characterization of molecular signatures triggered by the natural DENV infection (NDI) and attenuated dengue virus infection models (DVTs).

Methods and results

We analyzed 955 samples of transcriptomic datasets of patients with NDI and attenuated dengue virus infection trials (DVT1, DVT2, and DVT3) using a systems vaccinology approach. Differential expression analysis identified 237 common differentially expressed genes (DEGs) between DVTs and NDI. Among them, 28 and 60 DEGs were up or downregulated by dengue vaccination during DVT2 and DVT3, respectively, with 20 DEGs intersecting across all three DVTs. Enriched biological processes of these genes included type I/II interferon signaling, cytokine regulation, apoptosis, and T-cell differentiation. Principal component analysis based on 20 common DEGs (overlapping between DVTs and our NDI validation dataset) distinguished dengue patients by disease severity, particularly in the late acute phase. Machine learning analysis ranked the ten most critical predictors of disease severity in NDI, crucial for the anti-viral immune response.

Conclusion

This work provides insights into the NDI and vaccine-induced overlapping immune response and suggests molecular markers (e.g., IFIT5, ISG15, and HERC5) for anti-dengue-specific therapies and effective vaccination development.

CXCR2 chemokine receptor - a master regulator in cancer and physiology

Recent findings have modified our understanding of the roles of chemokine receptor CXCR2 and its ligands in cancer, inflammation, and immunity. Studies in Cxcr2 tissue-specific knockout mice show that this receptor is involved in, among other things, cancer, central nervous system (CNS) function, metabolism, reproduction, COVID-19, and the response to circadian cycles. Moreover, CXCR2 involvement in neutrophil function has been revisited not only in physiology but also for its major contribution to cancers. The recent unfolding of the role of CXCR2 in numerous cancers has led to extensive evaluation of multiple CXCR2 antagonists in preclinical and clinical studies. In this review we discuss the potential of targeting CXCR2 for cancer treatment.

From Microcosm to Macrocosm: The -Omics, Multiomics, and Sportomics Approaches in Exercise and Sports

This article explores the progressive integration of -omics methods, including genomics, metabolomics, and proteomics, into sports research, highlighting the development of the concept of "sportomics." We discuss how sportomics can be used to comprehend the multilevel metabolism during exercise in real-life conditions faced by athletes, enabling potential personalized interventions to improve performance and recovery and reduce injuries, all with a minimally invasive approach and reduced time. Sportomics may also support highly personalized investigations, including the implementation of n-of-1 clinical trials and the curation of extensive datasets through long-term follow-up of athletes, enabling tailored interventions for athletes based on their unique physiological responses to different conditions. Beyond its immediate sport-related applications, we delve into the potential of utilizing the sportomics approach to translate Big Data regarding top-level athletes into studying different human diseases, especially with nontargeted analysis. Furthermore, we present how the amalgamation of bioinformatics, artificial intelligence, and integrative computational analysis aids in investigating biochemical pathways, and facilitates the search for various biomarkers. We also highlight how sportomics can offer relevant information about doping control analysis. Overall, sportomics offers a comprehensive approach providing novel insights into human metabolism during metabolic stress, leveraging cutting-edge systems science techniques and technologies.

Neuroimmunology of rabies: New insights into an ancient disease

Rabies is an ancient neuroinvasive viral (genus Lyssavirus, family Rhabdoviridae) disease affecting approximately 59,000 people worldwide. The central nervous system (CNS) is targeted, and rabies has a case fatality rate of almost 100% in humans and animals. Rabies is entirely preventable through proper vaccination, and thus, the highest incidence is typically observed in developing countries, mainly in Africa and Asia. However, there are still cases in European countries and the United States. Recently, demographic, increasing income levels, and the coronavirus disease 2019 (COVID-19) pandemic have caused a massive raising in the animal population, enhancing the need for preventive measures (e.g., vaccination, surveillance, and animal control programs), postexposure prophylaxis, and a better understanding of rabies pathophysiology to identify therapeutic targets, since there is no effective treatment after the onset of clinical manifestations. Here, we review the neuroimmune biology and mechanisms of rabies. Its pathogenesis involves a complex and poorly understood modulation of immune and brain functions associated with metabolic, synaptic, and neuronal impairments, resulting in fatal outcomes without significant histopathological lesions in the CNS. In this context, the neuroimmunological and neurochemical aspects of excitatory/inhibitory signaling (e.g., GABA/glutamate crosstalk) are likely related to the clinical manifestations of rabies infection. Uncovering new links between immunopathological mechanisms and neurochemical imbalance will be essential to identify novel potential therapeutic targets to reduce rabies morbidity and mortality.

Integrated Metabolic and Inflammatory Signatures Associated with Severity of, Fatality of, and Recovery from COVID-19

Severe manifestations of coronavirus disease 2019 (COVID-19) and mortality have been associated with physiological alterations that provide insights into the pathogenesis of the disease. Moreover, factors that drive recovery from COVID-19 can be explored to identify correlates of protection. The cellular metabolism represents a potential target to improve survival upon severe disease, but the associations between the metabolism and the inflammatory response during COVID-19 are not well defined. We analyzed blood laboratorial parameters, cytokines, and metabolomes of 150 individuals with mild to severe disease, of which 33 progressed to a fatal outcome. A subset of 20 individuals was followed up after hospital discharge and recovery from acute disease. We used hierarchical community networks to integrate metabolomics profiles with cytokines and markers of inflammation, coagulation, and tissue damage. Infection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) promotes significant alterations in the plasma metabolome, whose activity varies according to disease severity and correlates with oxygen saturation. Differential metabolism underlying death was marked by amino acids and related metabolites, such as glutamate, glutamyl-glutamate, and oxoproline, and lipids, including progesterone, phosphocholine, and lysophosphatidylcholines (lysoPCs). Individuals who recovered from severe disease displayed persistent alterations enriched for metabolism of purines and phosphatidylinositol phosphate and glycolysis. Recovery of mild disease was associated with vitamin E metabolism. Data integration shows that the metabolic response is a hub connecting other biological features during disease and recovery. Infection by SARS-CoV-2 induces concerted activity of metabolic and inflammatory responses that depend on disease severity and collectively predict clinical outcomes of COVID-19. IMPORTANCE COVID-19 is characterized by diverse clinical outcomes that include asymptomatic to mild manifestations or severe disease and death. Infection by SARS-CoV-2 activates inflammatory and metabolic responses that drive protection or pathology. How inflammation and metabolism communicate during COVID-19 is not well defined. We used high-resolution mass spectrometry to investigate small biochemical compounds (<1,500 Da) in plasma of individuals with COVID-19 and controls. Age, sex, and comorbidities have a profound effect on the plasma metabolites of individuals with COVID-19, but we identified significant activity of pathways and metabolites related to amino acids, lipids, nucleotides, and vitamins determined by disease severity, survival outcome, and recovery. Furthermore, we identified metabolites associated with acute-phase proteins and coagulation factors, which collectively identify individuals with severe disease or individuals who died of severe COVID-19. Our study suggests that manipulating specific metabolic pathways can be explored to prevent hyperinflammation, organ dysfunction, and death.

Discovering common pathogenetic processes between COVID-19 and sepsis by bioinformatics and system biology approach

Corona Virus Disease 2019 (COVID-19), an acute respiratory infectious disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has spread rapidly worldwide, resulting in a pandemic with a high mortality rate. In clinical practice, we have noted that many critically ill or critically ill patients with COVID-19 present with typical sepsis-related clinical manifestations, including multiple organ dysfunction syndrome, coagulopathy, and septic shock. In addition, it has been demonstrated that severe COVID-19 has some pathological similarities with sepsis, such as cytokine storm, hypercoagulable state after blood balance is disrupted and neutrophil dysfunction. Considering the parallels between COVID-19 and non-SARS-CoV-2 induced sepsis (hereafter referred to as sepsis), the aim of this study was to analyze the underlying molecular mechanisms between these two diseases by bioinformatics and a systems biology approach, providing new insights into the pathogenesis of COVID-19 and the development of new treatments. Specifically, the gene expression profiles of COVID-19 and sepsis patients were obtained from the Gene Expression Omnibus (GEO) database and compared to extract common differentially expressed genes (DEGs). Subsequently, common DEGs were used to investigate the genetic links between COVID-19 and sepsis. Based on enrichment analysis of common DEGs, many pathways closely related to inflammatory response were observed, such as Cytokine-cytokine receptor interaction pathway and NF-kappa B signaling pathway. In addition, protein-protein interaction networks and gene regulatory networks of common DEGs were constructed, and the analysis results showed that ITGAM may be a potential key biomarker base on regulatory analysis. Furthermore, a disease diagnostic model and risk prediction nomogram for COVID-19 were constructed using machine learning methods. Finally, potential therapeutic agents, including progesterone and emetine, were screened through drug-protein interaction networks and molecular docking simulations. We hope to provide new strategies for future research and treatment related to COVID-19 by elucidating the pathogenesis and genetic mechanisms between COVID-19 and sepsis.

Cytokine Profiles Associated With Acute COVID-19 and Long COVID-19 Syndrome

The duration and severity of COVID-19 are related to age, comorbidities, and cytokine synthesis. This study evaluated the impact of these factors on patients with clinical presentations of COVID-19 in a Brazilian cohort. A total of 317 patients diagnosed with COVID-19 were included; cases were distributed according to clinical status as severe (n=91), moderate (n=56) and mild (n=170). Of these patients, 92 had acute COVID-19 at sample collection, 90 had already recovered from COVID-19 without sequelae, and 135 had sequelae (long COVID syndrome). In the acute COVID-19 group, patients with the severe form had higher IL-6 levels (p=0.0260). In the post-COVID-19 group, there was no significant difference in cytokine levels between groups with different clinical conditions. In the acute COVID-19 group, younger patients had higher levels of TNF-α, and patients without comorbidities had higher levels of TNF-α, IL-4 and IL-2 (p<0.05). In contrast, patients over age 60 with comorbidities had higher levels of IL-6. In the post-COVID-19 group, subjects with long COVID-19 had higher levels of IL-17 and IL-2 (p<0.05), and subjects without sequelae had higher levels of IL-10, IL-6 and IL- 4 (p<0.05). Our results suggest that advanced age, comorbidities and elevated serum IL-6 levels are associated with severe COVID-19 and are good markers to differentiate severe from mild cases. Furthermore, high serum levels of IL-17 and IL-2 and low levels of IL-4 and IL-10 appear to constitute a cytokine profile of long COVID-19, and these markers are potential targets for COVID-19 treatment and prevention strategies.

Autoantibodies targeting GPCRs and RAS-related molecules associate with COVID-19 severity

COVID-19 shares the feature of autoantibody production with systemic autoimmune diseases. In order to understand the role of these immune globulins in the pathogenesis of the disease, it is important to explore the autoantibody spectra. Here we show, by a cross-sectional study of 246 individuals, that autoantibodies targeting G protein-coupled receptors (GPCR) and RAS-related molecules associate with the clinical severity of COVID-19. Patients with moderate and severe disease are characterized by higher autoantibody levels than healthy controls and those with mild COVID-19 disease. Among the anti-GPCR autoantibodies, machine learning classification identifies the chemokine receptor CXCR3 and the RAS-related molecule AGTR1 as targets for antibodies with the strongest association to disease severity. Besides antibody levels, autoantibody network signatures are also changing in patients with intermediate or high disease severity. Although our current and previous studies identify anti-GPCR antibodies as natural components of human biology, their production is deregulated in COVID-19 and their level and pattern alterations might predict COVID-19 disease severity.

Severe COVID-19 Shares a Common Neutrophil Activation Signature with Other Acute Inflammatory States

Severe COVID-19 patients present a clinical and laboratory overlap with other hyperinflammatory conditions such as hemophagocytic lymphohistiocytosis (HLH). However, the underlying mechanisms of these conditions remain to be explored. Here, we investigated the transcriptome of 1596 individuals, including patients with COVID-19 in comparison to healthy controls, other acute inflammatory states (HLH, multisystem inflammatory syndrome in children [MIS-C], Kawasaki disease [KD]), and different respiratory infections (seasonal coronavirus, influenza, bacterial pneumonia). We observed that COVID-19 and HLH share immunological pathways (cytokine/chemokine signaling and neutrophil-mediated immune responses), including gene signatures that stratify COVID-19 patients admitted to the intensive care unit (ICU) and COVID-19_nonICU patients. Of note, among the common differentially expressed genes (DEG), there is a cluster of neutrophil-associated genes that reflects a generalized hyperinflammatory state since it is also dysregulated in patients with KD and bacterial pneumonia. These genes are dysregulated at the protein level across several COVID-19 studies and form an interconnected network with differentially expressed plasma proteins that point to neutrophil hyperactivation in COVID-19 patients admitted to the intensive care unit. scRNAseq analysis indicated that these genes are specifically upregulated across different leukocyte populations, including lymphocyte subsets and immature neutrophils. Artificial intelligence modeling confirmed the strong association of these genes with COVID-19 severity. Thus, our work indicates putative therapeutic pathways for intervention.

Temporal transcriptomic analysis using TrendCatcher identifies early and persistent neutrophil activation in severe COVID-19

Studying temporal gene expression shifts during disease progression provides important insights into the biological mechanisms that distinguish adaptive and maladaptive responses. Existing tools for the analysis of time course transcriptomic data are not designed to optimally identify distinct temporal patterns when analyzing dynamic differentially expressed genes (DDEGs). Moreover, there are not enough methods to assess and visualize the temporal progression of biological pathways mapped from time course transcriptomic data sets. In this study, we developed an open-source R package TrendCatcher (https://github.com/jaleesr/TrendCatcher), which applies the smoothing spline ANOVA model and break point searching strategy, to identify and visualize distinct dynamic transcriptional gene signatures and biological processes from longitudinal data sets. We used TrendCatcher to perform a systematic temporal analysis of COVID-19 peripheral blood transcriptomes, including bulk and single-cell RNA-Seq time course data. TrendCatcher uncovered the early and persistent activation of neutrophils and coagulation pathways, as well as impaired type I IFN (IFN-I) signaling in circulating cells as a hallmark of patients who progressed to severe COVID-19, whereas no such patterns were identified in individuals receiving SARS-CoV-2 vaccinations or patients with mild COVID-19. These results underscore the importance of systematic temporal analysis to identify early biomarkers and possible pathogenic therapeutic targets.

Systematic temporal analysis of peripheral blood transcriptomes using TrendCatcher identifies early and persistent neutrophil activation as a hallmark of severe COVID-19

Studying temporal gene expression shifts during disease progression provides important insights into the biological mechanisms that distinguish adaptive and maladaptive responses. Existing tools for the analysis of time course transcriptomic data are not designed to optimally identify distinct temporal patterns when analyzing dynamic differentially expressed genes (DDEGs). Moreover, there is a lack of methods to assess and visualize the temporal progression of biological pathways mapped from time course transcriptomic datasets. In this study, we developed an open-source R package TrendCatcher (https://github.com/jaleesr/TrendCatcher), which applies the smoothing spline ANOVA model and break point searching strategy to identify and visualize distinct dynamic transcriptional gene signatures and biological processes from longitudinal datasets. We used TrendCatcher to perform a systematic temporal analysis of COVID-19 peripheral blood transcriptomes, including bulk RNA-seq and scRNA-seq time course data. TrendCatcher uncovered the early and persistent activation of neutrophils and coagulation pathways as well as impaired type I interferon (IFN-I) signaling in circulating cells as a hallmark of patients who progressed to severe COVID-19, whereas no such patterns were identified in individuals receiving SARS-CoV-2 vaccinations or patients with mild COVID-19. These results underscore the importance of systematic temporal analysis to identify early biomarkers and possible pathogenic therapeutic targets.

Application of omics technology to combat the COVID-19 pandemic

As of August 27, 2021, the ongoing pandemic of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread to over 220 countries, areas, and territories. Thus far, 214,468,601 confirmed cases, including 4,470,969 deaths, have been reported to the World Health Organization. To combat the COVID-19 pandemic, multiomics-based strategies, including genomics, transcriptomics, proteomics, and metabolomics, have been used to study the diagnosis methods, pathogenesis, prognosis, and potential drug targets of COVID-19. In order to help researchers and clinicians to keep up with the knowledge of COVID-19, we summarized the most recent progresses reported in omics-based research papers. This review discusses omics-based approaches for studying COVID-19, summarizing newly emerged SARS-CoV-2 variants as well as potential diagnostic methods, risk factors, and pathological features of COVID-19. This review can help researchers and clinicians gain insight into COVID-19 features, providing direction for future drug development and guidance for clinical treatment, so that patients can receive appropriate treatment as soon as possible to reduce the risk of disease progression.