The Immune Signatures Data Resource: A compendium of systems vaccinology datasets

Vaccines are among the most cost-effective public health interventions for preventing infection-induced morbidity and mortality, yet much remains to be learned regarding the mechanisms by which vaccines protect. Systems immunology combines traditional immunology with modern 'omic profiling techniques and computational modeling to promote rapid and transformative advances in vaccinology and vaccine discovery. The NIH/NIAID Human Immunology Project Consortium (HIPC) has leveraged systems immunology approaches to identify molecular signatures associated with the immunogenicity of many vaccines, including those targeting seasonal influenza, yellow fever, and hepatitis B. These data are made available to the broader scientific community through the ImmuneSpace data portal and analysis engine leveraging the NIH/NIAID ImmPort repository. However, a barrier to progress in this area is that comparative analyses have been limited by the distributed nature of some data, potential batch effects across studies, and the absence of multiple relevant studies from non-HIPC groups in ImmPort. To support comparative analyses across different vaccines, we have created the Immune Signatures Data Resource, a compendium of standardized systems vaccinology datasets. This data resource is available through ImmuneSpace, along with code to reproduce the processing and batch normalization starting from the underlying study data in ImmPort and the Gene Expression Omnibus (GEO). The current release comprises 1405 participants from 53 cohorts profiling the response to 24 different vaccines and includes transcriptional profiles and antibody response measurements. This novel systems vaccinology data release represents a valuable resource for comparative and meta-analyses that will accelerate our understanding of mechanisms underlying vaccine responses.

High Throughput Human T Cell Receptor Sequencing: A New Window Into Repertoire Establishment and Alloreactivity

Recent advances in high throughput sequencing (HTS) of T cell receptors (TCRs) and in transcriptomic analysis, particularly at the single cell level, have opened the door to a new level of understanding of human immunology and immune-related diseases. In this article, we discuss the use of HTS of TCRs to discern the factors controlling human T cell repertoire development and how this approach can be used in combination with human immune system (HIS) mouse models to understand human repertoire selection in an unprecedented manner. An exceptionally high proportion of human T cells has alloreactive potential, which can best be understood as a consequence of the processes governing thymic selection. High throughput TCR sequencing has allowed assessment of the development, magnitude and nature of the human alloresponse at a new level and has provided a tool for tracking the fate of pre-transplant-defined donor- and host-reactive TCRs following transplantation. New insights into human allograft rejection and tolerance obtained with this method in combination with single cell transcriptional analyses are reviewed here.

Rhesus negative males have an enhanced IFNγ-mediated immune response to influenza A virus

The Rhesus D antigen (RhD) has been associated with susceptibility to several viral infections. Reports suggest that RhD-negative individuals are better protected against infectious diseases and have overall better health. However, potential mechanisms contributing to these associations have not yet been defined. Here, we used transcriptomic and genomic data from the Milieu Interieur cohort of 1000 healthy individuals to explore the effect of RhD on immune responses. We used the rs590787 SNP in the RHD gene to classify the 1000 donors as either RhD-positive or -negative. Whole blood was stimulated with LPS, polyIC, and the live influenza A virus and the NanoString human immunology panel of 560 genes used to assess donor immune response and to investigate sex specific effects. Using regression analysis, we observed no significant differences in responses to polyIC or LPS between RhD-positive and -negative individuals. However, upon sex-specific analysis, we observed over 30 differentially expressed genes (DEGs) between RhD-positive (n=401) and RhD-negative males (n=78). Interestingly these Rhesus-associated differences were not seen in females. Further investigation, using gene set enrichment analysis, revealed enhanced IFNγ signalling in RhD-negative males. This amplified IFNγ signalling axis may explain the increased viral resistance previously described in RhD-negative individuals.

An innate immune activation state prior to vaccination predicts responsiveness to multiple vaccines

Many factors determine whether an individual responding to vaccination will generate an immune response that can lead to protection. Several studies have shown that the pre-vaccination immune state associate with the antibody response to vaccines. However, the generalizability and mechanisms that underlie this association remain poorly defined. Here, we sought to identify a common pre-vaccination signature and mechanisms that could predict the immune response across a wide variety of vaccines. We leveraged the "Immune Signatures Data Resource" created by the NIH Human Immunology Project Consortium (HIPC) to integrate data from 28 studies involving 13 different vaccines and associate the blood transcriptional status of 820 healthy young adults with their responses. An unsupervised analysis of blood transcriptional profiles across studies revealed three distinct pre-vaccination states, characterized by the differential expression of genes associated with a pro-inflammatory response, cell proliferation, and metabolism alterations downstream of NFκB and IRF7. Innate and adaptive immune cell subset-specific genes were also associated with the three pre-vaccination states. Importantly, individuals whose pre-vaccination state was enriched in pro-inflammatory response genes known to be downstream of NFκB tended to have higher serum antibody responses one month after vaccination. A supervised analysis of the same data resulted in a single classifier, also enriched for NFκB regulated genes, that predicted the antibody response across most of the vaccines. Projection into single-cell RNA-sequencing data suggested that this pre-vaccination state was attributable to the signature of activation of non-classical monocytes and myeloid dendritic cells. Transcriptional signatures of recent exposure to bacterial and not viral infections were enriched in the high pro-inflammatory pre-vaccination state and also included NFκB regulated genes. The pro-inflammatory pre-vaccination state was highly reminiscent of the innate activation state triggered by TLR ligands or adjuvants. These results demonstrate that wide variations in the transcriptional state of the immune system in humans can be a key determinant of responsiveness to vaccination. They also define a transcriptional signature NFκB activation at baseline, that is associated with a greater magnitude of antibody response to 13 different vaccines, and suggest that modulation of the innate immune system by next-generation adjuvants targeting NFκB before vaccine administration may improve vaccine responsiveness.

Platelet FcγRIIA-induced serotonin release exacerbates the severity of Transfusion-Related Acute Lung Injury in mice

Transfusion-related acute lung injury (TRALI) remains a major cause of transfusion-related fatalities. The mechanism of human antibody-mediated TRALI, especially the involvement of the Fcγ receptors, is not clearly established. Contrary to mice, human platelets are unique in their expression of the FcγRIIA/CD32A receptor, suggesting that our understanding of the pathogenesis of antibody-mediated TRALI is partial, since the current murine models incompletely recapitulate the human immunology. We evaluated the role of FcγRIIA/CD32A in TRALI using a humanized mouse model expressing the FcγRIIA/CD32A receptor. When challenged with a recombinant chimeric human IgG1/mouse anti-MHC I monoclonal antibody, these mice showed exacerbated alveolar edema and higher mortality compared to WT mice. Unlike in WT mice, monocytes/macrophages were accessory for TRALI initiation in CD32A+ mice pointing to the decisive contribution of another cell type. Platelet activation was dramatically increased in CD32A+ animals resulting in their increased consumption and massive release of their granule contents. Platelet depletion prevented the exacerbation of TRALI in CD32A+ mice but did not affect TRALI in WT animals. By blocking platelet serotonin uptake with fluoxetine, we showed that the severity of TRALI in CD32A+ mice resulted from the serotonin released by activated platelets. Furthermore, inhibition of 5-hydroxytryptamine 2A serotonin receptor with sarpogrelate, before or after the induction of TRALI, abolished the aggravation of lung edema in CD32A+ mice. Our findings demonstrate that platelet FcγRIIA/CD32A activation exacerbates antibody-mediated TRALI and provide a rationale for designing prophylactic and therapeutic strategies targeting the serotonin pathway to attenuate TRALI in patients.

In Vivo Lentiviral Gene Delivery of HLA-DR and Vaccination of Humanized Mice for Improving the Human T and B Cell Immune Reconstitution

Humanized mouse models generated with human hematopoietic stem cells (HSCs) and reconstituting the human immune system (HIS-mice) are invigorating preclinical testing of vaccines and immunotherapies. We have recently shown that human engineered dendritic cells boosted bonafide human T and B cell maturation and antigen-specific responses in HIS-mice. Here, we evaluated a cell-free system based on in vivo co-delivery of lentiviral vectors (LVs) for expression of a human leukocyte antigen (HLA-DRA*01/ HLA-DRB1*0401 functional complex, “DR4”), and a LV vaccine expressing human cytokines (GM-CSF and IFN-α) and a human cytomegalovirus gB antigen (HCMV-gB). Humanized NOD/Rag1null/IL2Rγnull (NRG) mice injected by i.v. with LV-DR4/fLuc showed long-lasting (up to 20 weeks) vector distribution and expression in the spleen and liver. In vivo administration of the LV vaccine after LV-DR4/fLuc delivery boosted the cellularity of lymph nodes, promoted maturation of terminal effector CD4+ T cells, and promoted significantly higher development of IgG+ and IgA+ B cells. This modular lentigenic system opens several perspectives for basic human immunology research and preclinical utilization of LVs to deliver HLAs into HIS-mice.

TLR9- and CD40-Targeting Vaccination Promotes Human B Cell Maturation and IgG Induction via pDC-Dependent Mechanisms in Humanized Mice

Mice reconstituted with a human immune system (humanized mice) provide a robust model to study human immunology, vaccinology, and human infectious diseases. However, the development and function of B cells in humanized mice is impaired. B cells from humanized mice are immature and are impaired in IgM to IgG isotype switch in response to infection or vaccination. In the present study we report that Toll-like receptor 9 (TLR9) agonist CpG-B combined with CD40-targeting vaccination triggered human B cell immunoglobin class-switch from IgM+ to IgG+ B cells in humanized mice. Human B cells from mice vaccinated with CpG-B as adjuvant were more mature in phenotype and produced significant levels of both total IgG and antigen-specific IgG. We found that CpG-B treatment activated human pDCs (plasmacytoid dendritic cells) in vivo to induce interferon-alpha (IFN-α)expression in humanized mice. Pre-depletion of human pDC in vivo abrogated the adjuvant effect of CpG-B. Our results indicate that TLR9 and CD40-targeting vaccination triggers human B cell maturation and immunoglobulin class-switch in a pDC-dependent manner in humanized mice. The findings also shed light on induction of human IgG antibodies in humanized mouse models.

A curated collection of human vaccination response signatures

Recent advances in high-throughput experiments and systems biology approaches have resulted in hundreds of publications identifying “immune signatures”. Unfortunately, these are often described within text, figures, or tables in a format not amenable to computational processing, thus severely hampering our ability to fully exploit this information. Here we present a data model to represent immune signatures, along with the Human Immunology Project Consortium (HIPC) Dashboard (www.hipc-dashboard.org), a web-enabled application to facilitate signature access and querying. The data model captures the biological response components (e.g., genes, proteins or cell types or metabolites) and metadata describing the context under which the signature was identified using standardized terms from established resources (e.g., HGNC, Protein Ontology, Cell Ontology). We have manually curated a collection of >600 immune signatures from >60 published studies profiling human vaccination responses for the current release. The system will aid in building a broader understanding of the human immune response to stimuli by enabling researchers to easily access and interrogate published immune signatures.

CytoGLMM: conditional differential analysis for flow and mass cytometry experiments

Background Flow and mass cytometry are important modern immunology tools for measuring expression levels of multiple proteins on single cells. The goal is to better understand the mechanisms of responses on a single cell basis by studying differential expression of proteins. Most current data analysis tools compare expressions across many computationally discovered cell types. Our goal is to focus on just one cell type. Our narrower field of application allows us to define a more specific statistical model with easier to control statistical guarantees. Results Differential analysis of marker expressions can be difficult due to marker correlations and inter-subject heterogeneity, particularly for studies of human immunology. We address these challenges with two multiple regression strategies: a bootstrapped generalized linear model and a generalized linear mixed model. On simulated datasets, we compare the robustness towards marker correlations and heterogeneity of both strategies. For paired experiments, we find that both strategies maintain the target false discovery rate under medium correlations and that mixed models are statistically more powerful under the correct model specification. For unpaired experiments, our results indicate that much larger patient sample sizes are required to detect differences. We illustrate the R package and workflow for both strategies on a pregnancy dataset. Conclusion Our approach to finding differential proteins in flow and mass cytometry data reduces biases arising from marker correlations and safeguards against false discoveries induced by patient heterogeneity.

Coronavirus disease 2019 (COVID-19) and autoimmunity

The coronavirus 2019 pandemic (coronavirus disease, COVID-19), etiologically related to the SARS-CoV-2 virus (severe acute respiratory syndrome coronavirus-2), has once again reawakened healthcare professionals’ interest towards new clinical and conceptual issues of human immunology and immunopathology. An unprecedented number of clinical trials and fundamental studies of epidemiology, virology, immunology and molecular biology, of the COVID-19 clinical course polymorphism and pharmacotherapy have been conducted within one year since the outbreak of 2019 pandemic, bringing together scientists of almost all biological and physicians of almost all medical specialties. Their joint efforts have resulted in elaboration of several types of vaccines against SARS-CoV-2 infection and, in general, fashioning of more rational approaches to patient management. Also important for COVID-19 management were all clinical trials of biologics and “targeted” anti-inflammatory drugs modulating intracellular cytokine signaling, which have been specifically developed for treatment immune-mediated inflammatory rheumatic disease (IMIRDs) over the past 20 years. It became obvious after a comprehensive analysis of the entire spectrum of clinical manifestations and immunopathological disorders in COVID-19 is accompanied by a wide range of extrapulmonary clinical and laboratory disorders, some of which are characteristic of IMIRDs and other autoimmune and auto-in-flammatory human diseases. All these phenomena substantiated the practice of anti-inflammatory drugs repurposing with off-label use of specific antirheumatic agents for treatment of COVID-19. This paper discusses potential use of glucocorticoids, biologics, JAK inhibitors, etc., blocking the effects of pro-inflammatory cytokines for treatment of COVID-19.