Integrative systems immunology uncovers molecular networks of the cell cycle that stratify COVID-19 severity.

Several perturbations in the number of peripheral blood leukocytes, such as neutrophilia and lymphopenia associated with Coronavirus disease 2019 (COVID-19) severity, point to systemic molecular cell cycle alterations during severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. However, the landscape of cell cycle alterations in COVID-19 remains primarily unexplored. Here, we performed an integrative systems immunology analysis of publicly available proteome and transcriptome data to characterize global changes in the cell cycle signature of COVID-19 patients. We found significantly enriched cell cycle-associated gene co-expression modules and an interconnected network of cell cycle-associated differentially expressed proteins (DEPs) and genes (DEGs) by integrating the molecular data of 1469 individuals (981 SARS-CoV-2 infected patients and 488 controls [either healthy controls or individuals with other respiratory illnesses]). Among these DEPs and DEGs are several cyclins, cell division cycles, cyclin-dependent kinases, and mini-chromosome maintenance proteins. COVID-19 patients partially shared the expression pattern of some cell cycle-associated genes with other respiratory illnesses but exhibited some specific differential features. Notably, the cell cycle signature predominated in the patients' blood leukocytes (B, T, and natural killer cells) and was associated with COVID-19 severity and disease trajectories. These results provide a unique global understanding of distinct alterations in cell cycle-associated molecules in COVID-19 patients, suggesting new putative pathways for therapeutic intervention.

Cross-sectional analysis reveals autoantibody signatures associated with COVID-19 severity.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is associated with increased levels of autoantibodies targeting immunological proteins such as cytokines and chemokines. Reports further indicate that COVID-19 patients may develop a broad spectrum of autoimmune diseases due to reasons not fully understood. Even so, the landscape of autoantibodies induced by SARS-CoV-2 infection remains uncharted territory. To gain more insight, we carried out a comprehensive assessment of autoantibodies known to be linked to diverse autoimmune diseases observed in COVID-19 patients in a cohort of 231 individuals, of which 161 were COVID-19 patients (72 with mild, 61 moderate, and 28 with severe disease) and 70 were healthy controls. Dysregulated IgG and IgA autoantibody signatures, characterized mainly by elevated concentrations, occurred predominantly in patients with moderate or severe COVID-19 infection. Autoantibody levels often accompanied anti-SARS-CoV-2 antibody concentrations while stratifying COVID-19 severity as indicated by random forest and principal component analyses. Furthermore, while young versus elderly COVID-19 patients showed only slight differences in autoantibody levels, elderly patients with severe disease presented higher IgG autoantibody concentrations than young individuals with severe COVID-19. This work maps the intersection of COVID-19 and autoimmunity by demonstrating the dysregulation of multiple autoantibodies triggered during SARS-CoV-2 infection. Thus, this cross-sectional study suggests that SARS-CoV-2 infection induces autoantibody signatures associated with COVID-19 severity and several autoantibodies that can be used as biomarkers of COVID-19 severity, indicating autoantibodies as potential therapeutical targets for these patients.

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.

Interferome signature dynamics during the anti-dengue immune response: a systems biology characterization.

Dengue virus (DENV) infection manifests as a febrile illness with three distinct phases: early acute, late acute, and convalescent. Dengue can result in clinical manifestations with different degrees of severity, dengue fever, dengue hemorrhagic fever, and dengue shock syndrome. Interferons (IFNs) are antiviral cytokines central to the anti-DENV immune response. Notably, the distinct global signature of type I, II, and III interferon-regulated genes (the interferome) remains uncharacterized in dengue patients to date. Therefore, we performed an in-depth cross-study for the integrative analysis of transcriptome data related to DENV infection. Our systems biology analysis shows that the anti-dengue immune response is characterized by the modulation of numerous interferon-regulated genes (IRGs) enriching, for instance, cytokine-mediated signaling (e.g., type I and II IFNs) and chemotaxis, which is then followed by a transcriptional wave of genes associated with cell cycle, also regulated by the IFN cascade. The adjunct analysis of disease stratification potential, followed by a transcriptional meta-analysis of the interferome, indicated genes such as IFI27, ISG15, and CYBRD1 as potential suitable biomarkers of disease severity. Thus, this study characterizes the landscape of the interferome signature in DENV infection, indicating that interferome dynamics are a crucial and central part of the anti-dengue immune response.

Combinatorial multimer staining and spectral flow cytometry facilitate quantification and characterization of polysaccharide-specific B cell immunity.

Bacterial capsular polysaccharides are important vaccine immunogens. However, the study of polysaccharide-specific immune responses has been hindered by technical restrictions. Here, we developed and validated a high-throughput method to analyse antigen-specific B cells using combinatorial staining with fluorescently-labelled capsular polysaccharide multimers. Concurrent staining of 25 cellular markers further enables the in-depth characterization of polysaccharide-specific cells. We used this assay to simultaneously analyse 14 Streptococcus pneumoniae or 5 Streptococcus agalactiae serotype-specific B cell populations. The phenotype of polysaccharide-specific B cells was associated with serotype specificity, vaccination history and donor population. For example, we observed a link between non-class switched (IgM+) memory B cells and vaccine-inefficient S. pneumoniae serotypes 1 and 3. Moreover, B cells had increased activation in donors from South Africa, which has high-incidence of S. agalactiae invasive disease, compared to Dutch donors. This assay allows for the characterization of heterogeneity in B cell immunity that may underlie immunization efficacy.

Severe COVID-19 patients exhibit elevated levels of autoantibodies targeting cardiolipin and platelet glycoprotein with age: a systems biology approach.

Age is a significant risk factor for the coronavirus disease 2019 (COVID-19) severity due to immunosenescence and certain age-dependent medical conditions (e.g., obesity, cardiovascular disorder, and chronic respiratory disease). However, despite the well-known influence of age on autoantibody biology in health and disease, its impact on the risk of developing severe COVID-19 remains poorly explored. Here, we performed a cross-sectional study of autoantibodies directed against 58 targets associated with autoimmune diseases in 159 individuals with different COVID-19 severity (71 mild, 61 moderate, and 27 with severe symptoms) and 73 healthy controls. We found that the natural production of autoantibodies increases with age and is exacerbated by SARS-CoV-2 infection, mostly in severe COVID-19 patients. Multiple linear regression analysis showed that severe COVID-19 patients have a significant age-associated increase of autoantibody levels against 16 targets (e.g., amyloid ß peptide, ß catenin, cardiolipin, claudin, enteric nerve, fibulin, insulin receptor a, and platelet glycoprotein). Principal component analysis with spectrum decomposition and hierarchical clustering analysis based on these autoantibodies indicated an age-dependent stratification of severe COVID-19 patients. Random forest analysis ranked autoantibodies targeting cardiolipin, claudin, and platelet glycoprotein as the three most crucial autoantibodies for the stratification of severe COVID-19 patients ≥50 years of age. Follow-up analysis using binomial logistic regression found that anti-cardiolipin and anti-platelet glycoprotein autoantibodies significantly increased the likelihood of developing a severe COVID-19 phenotype with aging. These findings provide key insights to explain why aging increases the chance of developing more severe COVID-19 phenotypes.

Corrigendum to "Cross-sectional analysis of students and school workers reveals a high number of asymptomatic SARS-CoV-2 infections during school reopening in Brazilian cities" [Heliyon 8 (11) (November 2022) Article e11368].

[This corrects the article DOI: 10.1016/j.heliyon.2022.e11368.].

Dysregulated autoantibodies targeting vaso- and immunoregulatory receptors in Post COVID Syndrome correlate with symptom severity.

Most patients with Post COVID Syndrome (PCS) present with a plethora of symptoms without clear evidence of organ dysfunction. A subset of them fulfills diagnostic criteria of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Symptom severity of ME/CFS correlates with natural regulatory autoantibody (AAB) levels targeting several G-protein coupled receptors (GPCR). In this exploratory study, we analyzed serum AAB levels against vaso- and immunoregulatory receptors, mostly GPCRs, in 80 PCS patients following mild-to-moderate COVID-19, with 40 of them fulfilling diagnostic criteria of ME/CFS. Healthy seronegative (n=38) and asymptomatic post COVID-19 controls (n=40) were also included in the study as control groups. We found lower levels for various AABs in PCS compared to at least one control group, accompanied by alterations in the correlations among AABs. Classification using random forest indicated AABs targeting ADRB2, STAB1, and ADRA2A as the strongest classifiers (AABs stratifying patients according to disease outcomes) of post COVID-19 outcomes. Several AABs correlated with symptom severity in PCS groups. Remarkably, severity of fatigue and vasomotor symptoms were associated with ADRB2 AAB levels in PCS/ME/CFS patients. Our study identified dysregulation of AAB against various receptors involved in the autonomous nervous system (ANS), vaso-, and immunoregulation and their correlation with symptom severity, pointing to their role in the pathogenesis of PCS.

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.

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.

Cross-sectional analysis of students and school workers reveals a high number of asymptomatic SARS-CoV-2 infections during school reopening in Brazilian cities.

Brazil experienced one of the most prolonged periods of school closures, and reopening could have exposed students to high rates of SARS-CoV-2 infection. However, the infection status of students and school workers at the time of the reopening of schools located in Brazilian cities is unknown. Here we evaluated viral carriage by RT-PCR and seroprevalence of anti-SARS-CoV-2 antibodies (IgM and IgG) by immunochromatography in 2259 individuals (1139 students and 1120 school workers) from 28 schools in 28 Brazilian cities. We collected the samples within 30 days after public schools reopened and before the start of vaccination campaigns. Most students (n = 421) and school workers (n = 446) had active (qRT-PCR + IgM- IgG- or qRT-PCR + IgM + IgG-/+) SARS-CoV-2 infection. Regression analysis indicated a strong association between the infection status of students and school workers. Furthermore, while 45% (n = 515) of the students and 37% (n = 415) of the school workers were neither antigen nor antibody positive in laboratory tests, 16% of the participants (169 students and 193 school workers) were oligosymptomatic, including those reinfected. These individuals presented mild symptoms such as headache, sore throat, and cough. Notably, most of the individuals were asymptomatic (83.9%). These results indicate that many SARS-CoV-2 infections in Brazilian cities during school reopening were asymptomatic. Thus, our study highlights the need to promote a coordinated public health effort to guarantee a safe educational environment while avoiding exacerbating pre-existent social inequalities in Brazil, reducing social, mental, and economic losses for students, school workers, and their families.

The network interplay of interferon and Toll-like receptor signaling pathways in the anti-Candida immune response.

Fungal infections represent a major global health problem affecting over a billion people that kills more than 1.5 million annually. In this study, we employed an integrative approach to reveal the landscape of the human immune responses to Candida spp. through meta-analysis of microarray, bulk, and single-cell RNA sequencing (scRNA-seq) data for the blood transcriptome. We identified across these different studies a consistent interconnected network interplay of signaling molecules involved in both Toll-like receptor (TLR) and interferon (IFN) signaling cascades that is activated in response to different Candida species (C. albicans, C. auris, C. glabrata, C. parapsilosis, and C. tropicalis). Among these molecules are several types I IFN, indicating an overlap with antiviral immune responses. scRNA-seq data confirmed that genes commonly identified by the three transcriptomic methods show cell type-specific expression patterns in various innate and adaptive immune cells. These findings shed new light on the anti-Candida immune response, providing putative molecular pathways for therapeutic intervention.