Making human immune systems more interpretable through systems immunology

Microvascular immunity is organ-specific and remodeled after kidney injury in mice

Many studies analyze tissue-resident or blood-borne leukocytes to monitor disease progression. We hypothesized that the microvasculature serves as a distinct site for immune cell activity. Here, we investigate microvascular leukocyte phenotypes before, during and after acute kidney injury (AKI) in mice, uncovering unique characteristics in the kidney, liver, and lung. Using single-cell sequencing, we identify several immune cells that were up to 100-fold expanded in the kidney vasculature, including macrophages, dendritic cells (DC), and B cells. Regeneration after AKI is characterized by sustained remodeling of the renal microvascular interface. Homeostatic microvascular C1q+ macrophages withdraw from the vascular barrier which is subsequently repopulated by new subsets, including CD11c+F480+ and CD11c+F480- cells. These newly arrived macrophages exhibit enhanced phagocytic activity toward circulating bacteria and secretion of tumor necrosis factor, pointing to maladaptive repair mechanisms after AKI. These data suggest organ- and disease-specific microvascular immune dynamics which are not detectable through conventional blood and tissue analysis.

Systems immunology analysis of human immune organoids identifies host-specific correlates of protection to different influenza vaccines

Vaccines are an essential tool to significantly reduce pathogen-related morbidity and mortality. However, our ability to rationally design vaccines and identify correlates of protection remains limited. Here, we employed an immune organoid approach to capture human adaptive immune response diversity to influenza vaccines and systematically identify host and antigen features linked to vaccine response variability. Our investigation identified established and unique immune signatures correlated with neutralizing antibody responses across seven different influenza vaccines and antigens. Unexpectedly, heightened ex vivo tissue frequencies of T helper (Th)1 cells emerged as both a predictor and a correlate of neutralizing antibody responses to inactivated influenza vaccines (IIVs). Secondary analysis of human public data confirmed that elevated Th1 signatures are associated with antibody responses following in vivo vaccination. These findings demonstrate the utility of human in vitro models for identifying in vivo correlates of protection and establish a role for Th1 functions in influenza vaccination.

Tonsils weigh in on flu-specific immunity

Wagoner et al.1 use human tonsil organoids to uncover key immune mechanisms driving influenza vaccine responses. They identify Th1 cell frequencies as a critical predictor of neutralizing antibody responses to inactivated vaccines, providing new insights into vaccine effectiveness and paving the way for more targeted vaccine development in the future.

Systems Human Immunology and AI: Immune Setpoint and Immune Health

The immune system, critical for human health and implicated in many diseases, defends against pathogens, monitors physiological stress, and maintains tissue and organismal homeostasis. It exhibits substantial variability both within and across individuals and populations. Recent technological and conceptual progress in systems human immunology has provided predictive insights that link personal immune states to intervention responses and disease susceptibilities. Artificial intelligence (AI), particularly machine learning (ML), has emerged as a powerful tool for analyzing complex immune data sets, revealing hidden patterns across biological scales, and enabling predictive models for individualistic immune responses and potentially personalized interventions. This review highlights recent advances in deciphering human immune variation and predicting outcomes, particularly through the concepts of immune setpoint, immune health, and use of the immune system as a window for measuring health. We also provide a brief history of AI; review ML modeling approaches, including their applications in systems human immunology; and explore the potential of AI to develop predictive models and personal immune state embeddings to detect early signs of disease, forecast responses to interventions, and guide personalized health strategies.

Organismal mucosal immunology: A perspective through the eyes of game theory

In complex organisms, functional units must interact cohesively to maintain homeostasis, especially within mucosal barriers that house diverse, specialized cell exposed to constant environmental challenges. Understanding how homeostasis at mucosal barriers is maintained and how its disruption can lead to autoimmune diseases or cancer, requires a holistic view. Although omics approaches and systems immunology have become powerful tools, they are not without limitations; interpretations may reflect researchers' assumptions, even if other explanations exist. In this perspective, I propose that applying game theory concepts to mucosal immunology could help interpret complex data, offering fresh perspectives and supporting the exploration of alternative scenarios. By framing the mucosal immune system as a network of strategic interactions with multiple possible outcomes, game theory, which analyzes strategic interactions and decision-making processes, could illuminate novel cell types and functions, cell interactions, and responses to pathogens and commensals, leading to a more comprehensive understanding of immune homeostasis and diseases. In addition, game theory might encourage researchers to consider a broader range of possibilities, reduce the risk of myopic thinking, and ultimately enable a more refined and comprehensive understanding of the complexity of the immune system at mucosal barriers. This perspective aims to introduce game theory as a complementary framework for mucosal immunologists, encouraging them to incorporate these concepts into data interpretation and system modeling.

The regulatory network that controls lymphopoiesis

Lymphopoiesis is the generation of the T, B and NK cell lineages from a common lymphoid-biased haematopoietic stem cell. The experimental study of this process has generated a large amount of cellular and molecular data. As a result, there is a considerable number of mathematical and computational models regarding different aspects of lymphopoiesis. We hereby present a regulatory network consisting of 95 nodes and 202 regulatory interactions among them. The network is studied as a qualitative dynamical system, which has as stationary states the molecular patterns reported for CLP, pre-B, B naive, PC, pNK, iNK, NK, DP, CD8 naive, CTL, CD4 naive, Th1, Th2, Th17 and Treg cells. Also, we show that the system is able to respond to specific stimuli to reproduce the ontogeny of the T, B and NK cell lineages.

The Interplay of Nutrition, the Gut Microbiota and Immunity and Its Contribution to Human Disease

Nutrition, the gut microbiota and immunity are all important factors in the maintenance of health. However, there is a growing realization of the complex interplay between these elements coalescing in a nutrition-gut microbiota-immunity axis. This regulatory axis is critical for health with disruption being implicated in a broad range of diseases, including autoimmune disorders, allergies and mental health disorders. This new perspective continues to underpin a growing number of innovative therapeutic strategies targeting different elements of this axis to treat relevant diseases. This review describes the inter-relationships between nutrition, the gut microbiota and immunity. It then details several human diseases where disruption of the nutrition-gut microbiota-immunity axis has been identified and presents examples of how the various elements may be targeted therapeutically as alternate treatment strategies for these diseases.

Transcriptional Systems Vaccinology Approaches for Vaccine Adjuvant Profiling

Adjuvants are a diverse group of substances that can be added to vaccines to enhance antigen-specific immune responses and improve vaccine efficacy. The first adjuvants, discovered almost a century ago, were soluble crystals of aluminium salts. Over the following decades, oil emulsions, vesicles, oligodeoxynucleotides, viral capsids, and other complex organic structures have been shown to have adjuvant potential. However, the detailed mechanisms of how adjuvants enhance immune responses remain poorly understood and may be a barrier that reduces the rational selection of vaccine components. Previous studies on mechanisms of action of adjuvants have focused on how they activate innate immune responses, including the regulation of cell recruitment and activation, cytokine/chemokine production, and the regulation of some "immune" genes. This approach provides a narrow perspective on the complex events involved in how adjuvants modulate antigen-specific immune responses. A comprehensive and efficient way to investigate the molecular mechanism of action for adjuvants is to utilize systems biology approaches such as transcriptomics in so-called "systems vaccinology" analysis. While other molecular biology methods can verify if one or few genes are differentially regulated in response to vaccination, systems vaccinology provides a more comprehensive picture by simultaneously identifying the hundreds or thousands of genes that interact with complex networks in response to a vaccine. Transcriptomics tools such as RNA sequencing (RNA-Seq) allow us to simultaneously quantify the expression of practically all expressed genes, making it possible to make inferences that are only possible when considering the system as a whole. Here, we review some of the challenges in adjuvant studies, such as predicting adjuvant activity and toxicity when administered alone or in combination with antigens, or classifying adjuvants in groups with similar properties, while underscoring the significance of transcriptomics in systems vaccinology approaches to propel vaccine development forward.

Why PNI scientists need to engage in exploratory hypothesis-generating biomarker studies

Multi-omics research is developing rapidly, offering extensive sample analysis options and advanced statistical solutions to identify and understand complex networks of biomarkers. This review encourages groups in the psychoneuroimmunology field with limited experience in omics research to embrace these advances. Cross-sectional studies can leverage existing sample collections to provide unique information that complements longitudinal studies, providing insights into which biological systems may warrant further investigation and building fundamental mechanistic knowledge of biological networks. The understanding of immune-brain interactions should inform ongoing developments in exploratory, hypothesis-generating research. Disregarding psychoneuroimmunological aspects may have led to challenges in some prior biomarker research. Moving forward, a more nuanced perspective on inflammation and psychological comorbidity is needed. The first steps in the conceptualization of an explorative cross-sectional omics study are discussed from a pragmatic perspective, highlighting who we choose to study and what we choose to measure.

Serodynamics: A primer and synthetic review of methods for epidemiological inference using serological data

We present a review and primer of methods to understand epidemiological dynamics and identify past exposures from serological data, referred to as serodynamics. We discuss processing and interpreting serological data prior to fitting serodynamical models, and review approaches for estimating epidemiological trends and past exposures, ranging from serocatalytic models applied to binary serostatus data, to more complex models incorporating quantitative antibody measurements and immunological understanding. Although these methods are seemingly disparate, we demonstrate how they are derived within a common mathematical framework. Finally, we discuss key areas for methodological development to improve scientific discovery and public health insights in seroepidemiology.

The Microbe, the Infection Enigma, and the Host

Human infectious diseases are unique in that the discovery of their environmental trigger, the microbe, was sufficient to drive the development of extraordinarily effective principles and tools for their prevention or cure. This unique medical prowess has outpaced, and perhaps even hindered, the development of scientific progress of equal magnitude in the biological understanding of infectious diseases. Indeed, the hope kindled by the germ theory of disease was rapidly subdued by the infection enigma, in need of a host solution, when it was realized that most individuals infected with most infectious agents continue to do well. The root causes of disease and death in the unhappy few remained unclear. While canonical approaches in vitro (cellular microbiology), in vivo (animal models), and in natura (clinical studies) analyzed the consequences of infection with a microbe, considered to be the cause of disease, in cells, tissues, or organisms seen as a uniform host, alternative approaches searched for preexisting causes of disease, particularly human genetic and immunological determinants in populations of diverse individuals infected with a trigger microbe.

The Promise of a Pointillist Perspective for Comparative Immunology

Most studies in comparative immunology involve investigations into the detailed mechanisms of the immune system of a nonmodel organism. Although this approach has been insightful, it has promoted a deep understanding of only a handful of species, thus inhibiting the recognition of broad taxonomic patterns. Here, we call for investigating the immune defenses of numerous species within a pointillist framework, that is, the meticulous, targeted collection of data from dozens of species and investigation of broad patterns of organismal, ecological, and evolutionary forces shaping those patterns. Without understanding basic immunological patterns across species, we are limited in our ability to extrapolate and/or translate our findings to other organisms, including humans. We illustrate this point by focusing predominantly on the biological scaling literature with some integrations of the pace of life literature, as these perspectives have been the most developed within this framework. We also highlight how the more traditional approach in comparative immunology works synergistically with a pointillist approach, with each approach feeding back into the other. We conclude that the pointillist approach promises to illuminate comprehensive theories about the immune system and enhance predictions in a wide variety of domains, including host-parasite dynamics and disease ecology.

Complementing Cell Taxonomies with a Multicellular Analysis of Tissues

The application of single-cell molecular profiling coupled with spatial technologies has enabled charting of cellular heterogeneity in reference tissues and in disease. This new wave of molecular data has highlighted the expected diversity of single-cell dynamics upon shared external queues and spatial organizations. However, little is known about the relationship between single-cell heterogeneity and the emergence and maintenance of robust multicellular processes in developed tissues and its role in (patho)physiology. Here, we present emerging computational modeling strategies that use increasingly available large-scale cross-condition single-cell and spatial datasets to study multicellular organization in tissues and complement cell taxonomies. This perspective should enable us to better understand how cells within tissues collectively process information and adapt synchronized responses in disease contexts and to bridge the gap between structural changes and functions in tissues.

The Impact of Immune System Aging on Infectious Diseases

Immune system aging is becoming a field of increasing public health interest because of prolonged life expectancy, which is not paralleled by an increase in health expectancy. As age progresses, innate and adaptive immune systems undergo changes, which are defined, respectively, as inflammaging and immune senescence. A wealth of available data demonstrates that these two conditions are closely linked, leading to a greater vulnerability of elderly subjects to viral, bacterial, and opportunistic infections as well as lower post-vaccination protection. To face this novel scenario, an in-depth assessment of the immune players involved in this changing epidemiology is demanded regarding the individual and concerted involvement of immune cells and mediators within endogenous and exogenous factors and co-morbidities. This review provides an overall updated description of the changes affecting the aging immune system, which may be of help in understanding the underlying mechanisms associated with the main age-associated infectious diseases.

Immune system perturbations in patients with long COVID

Klein et al. report multimodal analyses of immune cells, proteins, and physiological parameters in patients with long COVID (LC). At the group level, LC subjects exhibited elevated antibody responses to SARS-CoV-2, but also to herpes viruses, pointing to a general suppression of viral control mechanisms in LC.

Delineating immune variation between adult and children COVID-19 cases and associations with disease severity

The SARS-CoV-2 pandemic has emphasized the need to explore how variations in the immune system relate to the severity of the disease. This study aimed to explore inter-individual variation in response to SARS-CoV-2 infection by comparing T cell, B cell, and innate cell immune subsets among primary infected children and adults (i.e., those who had never experienced SARS-CoV-2 infection nor received vaccination previously), with varying disease severity after infection. We also examined immune subset kinetics in convalescent individuals compared to those with persistent infection to identify possible markers of immune dysfunction. Distinct immune subset differences were observed between infected adults and children, as well as among adult cases with mild, moderate, and severe disease. IgM memory B cells were absent in moderate and severe cases whereas frequencies of B cells with a lack of surface immunoglobulin expression were significantly higher in severe cases. Interestingly, these immune subsets remained stable during recovery implying that these subsets could be associated with underlying baseline immune variation. Our results offer insights into the potential immune markers associated with severe COVID-19 and provide a foundation for future research in this area.

Increased glycolysis and cellular crosstalk in eosinophilic chronic rhinosinusitis with nasal polyps

Introduction

Chronic rhinosinusitis (CRS) is a chronic inflammatory disease of the sinonasal mucosa with distinct endotypes including type 2 (T2) high eosinophilic CRS with nasal polyps (eCRSwNP), T2 low non-eosinophilic CRS with nasal polyps (neCRSwNP), and CRS without nasal polyps (CRSsNP).

Methods

Given the heterogeneity of disease, we hypothesized that assessment of single cell RNA sequencing (scRNA-seq) across this spectrum of disease would reveal connections between infiltrating and activated immune cells and the epithelial and stromal populations that reside in sinonasal tissue.

Results

Here we find increased expression of genes encoding glycolytic enzymes in epithelial cells (EpCs), stromal cells, and memory T-cell subsets from patients with eCRSwNP, as compared to healthy controls. In basal EpCs, this is associated with a program of cell motility and Rho GTPase effector expression. Across both stromal and immune subsets, glycolytic programming was associated with extracellular matrix interactions, proteoglycan generation, and collagen formation. Furthermore, we report increased cell-cell interactions between EpCs and stromal/immune cells in eCRSwNP compared to healthy control tissue, and we nominate candidate receptor-ligand pairs that may drive tissue remodeling.

Discussion

These findings support a role for glycolytic reprograming in T2-elicited tissue remodeling and implicate increased cellular crosstalk in eCRSwNP.

Pre-vaccination immunotypes reveal weak and robust antibody responders to influenza vaccination

Effective vaccine-induced immune responses are particularly essential in older adults who face an increased risk of immunosenescence. However, the complexity and variability of the human immune system make predicting vaccine responsiveness challenging. To address this knowledge gap, our study aimed to characterize immune profiles that are predictive of vaccine responsiveness using "immunotypes" as an innovative approach. We analyzed an extensive set of innate and adaptive immune cell subsets in the whole blood of 307 individuals (aged 25-92) pre- and post-influenza vaccination which we associated with day 28 hemagglutination inhibition (HI) antibody titers. Building on our previous work that stratified individuals into nine immunotypes based on immune cell subsets, we identified two pre-vaccination immunotypes associated with weak and one showing robust day 28 antibody response. Notably, the weak responders demonstrated HLA-DR+ T-cell signatures, while the robust responders displayed a high naïve-to-memory T-cell ratio and percentage of nonclassical monocytes. These specific signatures deepen our understanding of the relationship between the baseline of the immune system and its functional potential. This approach could enhance our ability to identify individuals at risk of immunosenescence. Our findings highlight the potential of pre-vaccination immunotypes as an innovative tool for informing personalized vaccination strategies and improving health outcomes, particularly for aging populations.

Variability of vaccine responsiveness in early life

Vaccinations in early life elicit variable antibody and cellular immune responses, sometimes leaving fully vaccinated children unprotected against life-threatening infectious diseases. Specific immune cell populations and immune networks may have a critical period of development and calibration in a window of opportunity occurring during the first 100 days of early life. Among the early life determinants of vaccine responses, this review will focus on modifiable factors involving development of the infant microbiota and metabolome: antibiotic exposure, breast versus formula feeding, and Caesarian section versus vaginal delivery of newborns. How microbiota may serve as natural adjuvants for vaccine responses and how microbiota-derived metabolites influence vaccine responses are also reviewed. Early life poor vaccine responsiveness can be linked to increased infection susceptibility because both phenotypes share similar immunity dysregulation profiles. An early life pre-vaccination endotype, when interventions have the highest potential for success, should be sought that predicts vaccine response trajectories.