Smoking changes adaptive immunity with persistent effects.

Individuals differ widely in their immune responses, with age, sex and genetic factors having major roles in this inherent variability1-6. However, the variables that drive such differences in cytokine secretion-a crucial component of the host response to immune challenges-remain poorly defined. Here we investigated 136 variables and identified smoking, cytomegalovirus latent infection and body mass index as major contributors to variability in cytokine response, with effects of comparable magnitudes with age, sex and genetics. We find that smoking influences both innate and adaptive immune responses. Notably, its effect on innate responses is quickly lost after smoking cessation and is specifically associated with plasma levels of CEACAM6, whereas its effect on adaptive responses persists long after individuals quit smoking and is associated with epigenetic memory. This is supported by the association of the past smoking effect on cytokine responses with DNA methylation at specific signal trans-activators and regulators of metabolism. Our findings identify three novel variables associated with cytokine secretion variability and reveal roles for smoking in the short- and long-term regulation of immune responses. These results have potential clinical implications for the risk of developing infections, cancers or autoimmune diseases.

In situ tumour arrays reveal early environmental control of cancer immunity.

The immune phenotype of a tumour is a key predictor of its response to immunotherapy1-4. Patients who respond to checkpoint blockade generally present with immune-inflamed5-7 tumours that are highly infiltrated by T cells. However, not all inflamed tumours respond to therapy, and even lower response rates occur among tumours that lack T cells (immune desert) or that spatially exclude T cells to the periphery of the tumour lesion (immune excluded)8. Despite the importance of these tumour immune phenotypes in patients, little is known about their development, heterogeneity or dynamics owing to the technical difficulty of tracking these features in situ. Here we introduce skin tumour array by microporation (STAMP)-a preclinical approach that combines high-throughput time-lapse imaging with next-generation sequencing of tumour arrays. Using STAMP, we followed the development of thousands of arrayed tumours in vivo to show that tumour immune phenotypes and outcomes vary between adjacent tumours and are controlled by local factors within the tumour microenvironment. Particularly, the recruitment of T cells by fibroblasts and monocytes into the tumour core was supportive of T cell cytotoxic activity and tumour rejection. Tumour immune phenotypes were dynamic over time and an early conversion to an immune-inflamed phenotype was predictive of spontaneous or therapy-induced tumour rejection. Thus, STAMP captures the dynamic relationships of the spatial, cellular and molecular components of tumour rejection and has the potential to translate therapeutic concepts into successful clinical strategies.

Defective activation and regulation of type I interferon immunity is associated with increasing COVID-19 severity.

Host immunity to infection with SARS-CoV-2 is highly variable, dictating diverse clinical outcomes ranging from asymptomatic to severe disease and death. We previously reported reduced type I interferon in severe COVID-19 patients preceded clinical worsening. Further studies identified genetic mutations in loci of the TLR3- or TLR7-dependent interferon-I pathways, or neutralizing interferon-I autoantibodies as risk factors for development of COVID-19 pneumonia. Here we show in patient cohorts with different severities of COVID-19, that baseline plasma interferon α measures differ according to the immunoassay used, timing of sampling, the interferon α subtype measured, and the presence of autoantibodies. We also show a consistently reduced induction of interferon-I proteins in hospitalized COVID-19 patients upon immune stimulation, that is not associated with detectable neutralizing autoantibodies against interferon α or interferon ω. Intracellular proteomic analysis shows increased monocyte numbers in hospitalized COVID-19 patients but impaired interferon-I response after stimulation. We confirm this by ex vivo whole blood stimulation with interferon-I which induces transcriptomic responses associated with inflammation in hospitalized COVID-19 patients, that is not seen in controls or non-hospitalized moderate cases. These results may explain the dichotomy of the poor clinical response to interferon-I based treatments in late stage COVID-19, despite the importance of interferon-I in early acute infection and may guide alternative therapeutic strategies.

Early IFNß secretion determines variable downstream IL-12p70 responses upon TLR4 activation.

The interleukin-12 (IL-12) family comprises the only heterodimeric cytokines mediating diverse functional effects. We previously reported a striking bimodal IL-12p70 response to lipopolysaccharide (LPS) stimulation in healthy donors. Herein, we demonstrate that interferon ß (IFNß) is a major upstream determinant of IL-12p70 production, which is also associated with numbers and activation of circulating monocytes. Integrative modeling of proteomic, genetic, epigenomic, and cellular data confirms IFNß as key for LPS-induced IL-12p70 and allowed us to compare the relative effects of each of these parameters on variable cytokine responses. Clinical relevance of our findings is supported by reduced IFNß-IL-12p70 responses in patients hospitalized with acute severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection or chronically infected with hepatitis C (HCV). Importantly, these responses are resolved after viral clearance. Our systems immunology approach defines a better understanding of IL-12p70 and IFNß in healthy and infected persons, providing insights into how common genetic and epigenetic variation may impact immune responses to bacterial infection.

Tuberculosis alters immune-metabolic pathways resulting in perturbed IL-1 responses.

Tuberculosis (TB) remains a major public health problem and we lack a comprehensive understanding of how Mycobacterium tuberculosis (M. tb) infection impacts host immune responses. We compared the induced immune response to TB antigen, BCG and IL-1ß stimulation between latently M. tb infected individuals (LTBI) and active TB patients. This revealed distinct responses between TB/LTBI at transcriptomic, proteomic and metabolomic levels. At baseline, we identified a novel immune-metabolic association between pregnane steroids, the PPARγ pathway and elevated plasma IL-1ra in TB. We observed dysregulated IL-1 responses after BCG stimulation in TB patients, with elevated IL-1ra responses being explained by upstream TNF differences. Additionally, distinct secretion of IL-1α/IL-1ß in LTBI/TB after BCG stimulation was associated with downstream differences in granzyme mediated cleavage. Finally, IL-1ß driven signalling was dramatically perturbed in TB disease but was completely restored after successful treatment. This study improves our knowledge of how immune responses are altered during TB disease, and may support the design of improved preventive and therapeutic tools, including host-directed strategies.

SCHNAPPs - Single Cell sHiNy APPlication(s).

Single-cell RNA-sequencing (scRNAseq) experiments are becoming a standard tool for bench-scientists to explore the cellular diversity present in all tissues. Data produced by scRNAseq is technically complex and requires analytical workflows that are an active field of bioinformatics research, whereas a wealth of biological background knowledge is needed to guide the investigation. Thus, there is an increasing need to develop applications geared towards bench-scientists to help them abstract the technical challenges of the analysis so that they can focus on the science at play. It is also expected that such applications should support closer collaboration between bioinformaticians and bench-scientists by providing reproducible science tools. We present SCHNAPPs, a Graphical User Interface (GUI), designed to enable bench-scientists to autonomously explore and interpret scRNAseq data and associated annotations. The R/Shiny-based application allows following different steps of scRNAseq analysis workflows from Seurat or Scran packages: performing quality control on cells and genes, normalizing the expression matrix, integrating different samples, dimension reduction, clustering, and differential gene expression analysis. Visualization tools for exploring each step of the process include violin plots, 2D projections, Box-plots, alluvial plots, and histograms. An R-markdown report can be generated that tracks modifications and selected visualizations. The modular design of the tool allows it to easily integrate new visualizations and analyses by bioinformaticians. We illustrate the main features of the tool by applying it to the characterization of T cells in a scRNAseq and Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-Seq) experiment of two healthy individuals.

Distinct systemic and mucosal immune responses during acute SARS-CoV-2 infection.

Coordinated local mucosal and systemic immune responses following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection either protect against coronavirus disease 2019 (COVID-19) pathologies or fail, leading to severe clinical outcomes. To understand this process, we performed an integrated analysis of SARS-CoV-2 spike-specific antibodies, cytokines, viral load and bacterial communities in paired nasopharyngeal swabs and plasma samples from a cohort of clinically distinct patients with COVID-19 during acute infection. Plasma viral load was associated with systemic inflammatory cytokines that were elevated in severe COVID-19, and also with spike-specific neutralizing antibodies. By contrast, nasopharyngeal viral load correlated with SARS-CoV-2 humoral responses but inversely with interferon responses, the latter associating with protective microbial communities. Potential pathogenic microorganisms, often implicated in secondary respiratory infections, were associated with mucosal inflammation and elevated in severe COVID-19. Our results demonstrate distinct tissue compartmentalization of SARS-CoV-2 immune responses and highlight a role for the nasopharyngeal microbiome in regulating local and systemic immunity that determines COVID-19 clinical outcomes.

Immune Profiling Enables Stratification of Patients With Active Tuberculosis Disease or Mycobacterium tuberculosis Infection.

BACKGROUND: Tuberculosis (TB) is caused by Mycobacterium tuberculosis (Mtb) infection and is a major public health problem. Clinical challenges include the lack of a blood-based test for active disease. Current blood-based tests, such as QuantiFERON (QFT) do not distinguish active TB disease from asymptomatic Mtb infection. METHODS: We hypothesized that TruCulture, an immunomonitoring method for whole-blood stimulation, could discriminate active disease from latent Mtb infection (LTBI). We stimulated whole blood from patients with active TB and compared with LTBI donors. Mtb-specific antigens and live bacillus Calmette-Guérin (BCG) were used as stimuli, with direct comparison to QFT. Protein analyses were performed using conventional and digital enzyme-linked immunosorbent assay (ELISA), as well as Luminex. RESULTS: TruCulture showed discrimination of active TB cases from LTBI (P < .0001, AUC = .81) compared with QFT (P = .45, AUC = .56), based on an interferon γ (IFNγ) readout after Mtb antigen (Ag) stimulation. This result was replicated in an independent cohort (AUC = .89). In exploratory analyses, TB stratification could be further improved by the Mtb antigen to BCG IFNγ ratio (P < .0001, AUC = .91). Finally, the combination of digital ELISA and transcriptional analysis showed that LTBI donors with high IFNγ clustered with patients with TB, suggesting the possibility to identify subclinical disease. CONCLUSIONS: TruCulture offers a next-generation solution for whole-blood stimulation and immunomonitoring with the possibility to discriminate active and latent infection.

Immune response profiling of patients with spondyloarthritis reveals signalling networks mediating TNF-blocker function in vivo.

OBJECTIVES: Antitumour necrosis factor (TNF) therapy has revolutionised treatment of several chronic inflammatory diseases, including spondyloarthritis (SpA). However, TNF inhibitors (TNFi) are not effective in all patients and the biological basis for treatment failure remains unknown. We have analysed induced immune responses to define the mechanism of action of TNF blockers in SpA and to identify immunological correlates of responsiveness to TNFi. METHODS: Immune responses to microbial and pathway-specific stimuli were analysed in peripheral blood samples from 80 patients with axial SpA before and after TNFi treatment, using highly standardised whole-blood stimulation assays. Cytokines and chemokines were measured in a Clinical Laboratory Improvement Amendments (CLIA)-certified laboratory, and gene expression was monitored using nCounter assays. RESULTS: Anti-TNF therapy induced profound changes in patients' innate immune responses. TNFi action was selective, and had only minor effects on Th1/Th17 immunity. Modular transcriptional repertoire analysis identified prostaglandin E2 synthesis and signalling, leucocyte recirculation, macrophage polarisation, dectin and interleukin (IL)-1 signalling, as well as the nuclear factor kappa B (NF-kB) transcription factor family as key pathways targeted by TNF blockers in vivo. Analysis of induced immune responses before treatment initiation revealed that expression of molecules associated with leucocyte adhesion and invasion, chemotaxis and IL-1 signalling are correlated with therapeutic responses to anti-TNF. CONCLUSIONS: We show that TNFi target multiple immune cell pathways that cooperate to resolve inflammation. We propose that immune response profiling provides new insight into the biology of TNF-blocker action in patients and can identify signalling pathways associated with therapeutic responses to biological therapies.

Polygenic risk for skin autoimmunity impacts immune checkpoint blockade in bladder cancer.

PD-1 and PD-L1 act to restrict T cell responses in cancer and contribute to self-tolerance. Consistent with this role, PD-1 checkpoint inhibitors have been associated with immune-related adverse events (irAEs), immune toxicities thought to be autoimmune in origin. Analyses of dermatological irAEs have identified an association with improved overall survival (OS) following anti-PD-(L)1 therapy, but the factors that contribute to this relationship are poorly understood. We collected germline whole-genome sequencing data from IMvigor211, a recent phase 3 randomized controlled trial comparing atezolizumab (anti-PD-L1) monotherapy to chemotherapy in bladder cancer. We found that high vitiligo, high psoriasis, and low atopic dermatitis polygenic risk scores (PRSs) were associated with longer OS under anti-PD-L1 monotherapy as compared to chemotherapy, reflecting the Th17 polarization of these diseases. PRSs were not correlated with tumor mutation burden, PD-L1 immunohistochemistry, nor T-effector gene signatures. Shared genetic factors impact risk for dermatological autoimmunity and anti-PD-L1 monotherapy in bladder cancer.

Associations between usual diet and gut microbiota composition: results from the Milieu Intérieur cross-sectional study.

BACKGROUND: Diet is widely recognized as one of the main modifiable drivers of gut microbiota variability, and its influence on microbiota composition is an active area of investigation. OBJECTIVE: The present work aimed to explore the associations between usual diet and gut microbiota composition in a large sample of healthy French adults. METHODS: Gut microbiota composition was established through sequencing of the 16S rRNA gene in stool samples from 862 healthy French adults of the Milieu Intérieur study. Usual dietary consumptions were determined through the administration of a food-frequency questionnaire. The associations between dietary variables and α- and ß-diversity indexes and relative taxa abundances were tested using Spearman correlations, permutational ANOVAs, and multivariate analyses with linear models, respectively. RESULTS: Foods generally considered as healthy (raw fruits, fish) were positively associated with α-diversity, whereas food items for which a limited consumption is generally recommended (fried products, sodas or sugary drinks, fatty sweet products, processed meats, ready-cooked meals, and desserts) were negatively associated with α-diversity. Fruits, fried products, ready-cooked meals, and cheese contributed to shifts within microbiota composition (ß-diversity). Our results also highlighted a number of associations between various food group intakes and abundances of specific phyla, genera, and species. For instance, the consumption of cheese was negatively associated with Akkermansia muciniphila abundance. CONCLUSIONS: This large-scale population-based study supports that the usual consumption of certain food items is associated with several gut microbial features, and extends the mechanistic arguments linking Western diet to an altered microbiota composition. These results provide new insights into the understanding of complex diet-gut microbiota relations, and their implications for host health deserve further investigation because altered microbiota diversity was consistently linked to increased risk of several health outcomes. This trial was registered at clinicaltrials.gov as NCT01699893.

Publisher Correction: Natural variation in the parameters of innate immune cells is preferentially driven by genetic factors.

In the version of this article initially published, the name of one author was incorrect (James P. Santo). The correct name is James P. Di Santo. The error has been corrected in the HTML and PDF versions of the article.

Natural variation in the parameters of innate immune cells is preferentially driven by genetic factors.

The quantification and characterization of circulating immune cells provide key indicators of human health and disease. To identify the relative effects of environmental and genetic factors on variation in the parameters of innate and adaptive immune cells in homeostatic conditions, we combined standardized flow cytometry of blood leukocytes and genome-wide DNA genotyping of 1,000 healthy, unrelated people of Western European ancestry. We found that smoking, together with age, sex and latent infection with cytomegalovirus, were the main non-genetic factors that affected variation in parameters of human immune cells. Genome-wide association studies of 166 immunophenotypes identified 15 loci that showed enrichment for disease-associated variants. Finally, we demonstrated that the parameters of innate cells were more strongly controlled by genetic variation than were those of adaptive cells, which were driven by mainly environmental exposure. Our data establish a resource that will generate new hypotheses in immunology and highlight the role of innate immunity in susceptibility to common autoimmune diseases.

Distinctive roles of age, sex, and genetics in shaping transcriptional variation of human immune responses to microbial challenges.

The contribution of host genetic and nongenetic factors to immunological differences in humans remains largely undefined. Here, we generated bacterial-, fungal-, and viral-induced immune transcriptional profiles in an age- and sex-balanced cohort of 1,000 healthy individuals and searched for the determinants of immune response variation. We found that age and sex affected the transcriptional response of most immune-related genes, with age effects being more stimulus-specific relative to sex effects, which were largely shared across conditions. Although specific cell populations mediated the effects of age and sex on gene expression, including CD8+ T cells for age and CD4+ T cells and monocytes for sex, we detected a direct effect of these intrinsic factors for the majority of immune genes. The mapping of expression quantitative trait loci (eQTLs) revealed that genetic factors had a stronger effect on immune gene regulation than age and sex, yet they affected a smaller number of genes. Importantly, we identified numerous genetic variants that manifested their regulatory effects exclusively on immune stimulation, including a Candida albicans-specific master regulator at the CR1 locus. These response eQTLs were enriched in disease-associated variants, particularly for autoimmune and inflammatory disorders, indicating that differences in disease risk may result from regulatory variants exerting their effects only in the presence of immune stress. Together, this study quantifies the respective effects of age, sex, genetics, and cellular heterogeneity on the interindividual variability of immune responses and constitutes a valuable resource for further exploration in the context of different infection risks or disease outcomes.

Standardized whole blood stimulation improves immunomonitoring of induced immune responses in multi-center study.

Functional immune responses are increasingly important for clinical studies, providing in depth biomarker information to assess immunotherapy or vaccination. Incorporating functional immune assays into routine clinical practice has remained limited due to challenges in standardizing sample preparation. We recently described the use of a whole blood syringe-based system, TruCulture®, which permits point-of-care standardized immune stimulation. Here, we report on a multi-center clinical study in seven FOCIS Centers of Excellence to directly compare TruCulture to conventional PBMC methods. Whole blood and PBMCs from healthy donors were exposed to LPS, anti-CD3 anti-CD28 antibodies, or media alone. 55 protein analytes were analyzed centrally by Luminex multi-analyte profiling in a CLIA-certified laboratory. TruCulture responses showed greater reproducibility and improved the statistical power for monitoring differential immune response activation. The use of TruCulture addresses a major unmet need through a robust and flexible method for immunomonitoring that can be reproducibly applied in multi-center clinical studies. ONE SENTENCE SUMMARY: A multi-center study revealed greater reproducibility from whole blood stimulation systems as compared to PBMC stimulation for studying induced immune responses.

Standardized Whole-Blood Transcriptional Profiling Enables the Deconvolution of Complex Induced Immune Responses.

Systems approaches for the study of immune signaling pathways have been traditionally based on purified cells or cultured lines. However, in vivo responses involve the coordinated action of multiple cell types, which interact to establish an inflammatory microenvironment. We employed standardized whole-blood stimulation systems to test the hypothesis that responses to Toll-like receptor ligands or whole microbes can be defined by the transcriptional signatures of key cytokines. We found 44 genes, identified using Support Vector Machine learning, that captured the diversity of complex innate immune responses with improved segregation between distinct stimuli. Furthermore, we used donor variability to identify shared inter-cellular pathways and trace cytokine loops involved in gene expression. This provides strategies for dimension reduction of large datasets and deconvolution of innate immune responses applicable for characterizing immunomodulatory molecules. Moreover, we provide an interactive R-Shiny application with healthy donor reference values for induced inflammatory genes.

The Milieu Intérieur study - an integrative approach for study of human immunological variance.

The Milieu Intérieur Consortium has established a 1000-person healthy population-based study (stratified according to sex and age), creating an unparalleled opportunity for assessing the determinants of human immunologic variance. Herein, we define the criteria utilized for participant enrollment, and highlight the key data that were collected for correlative studies. In this report, we analyzed biological correlates of sex, age, smoking-habits, metabolic score and CMV infection. We characterized and identified unique risk factors among healthy donors, as compared to studies that have focused on the general population or disease cohorts. Finally, we highlight sex-bias in the thresholds used for metabolic score determination and recommend a deeper examination of current guidelines. In sum, our clinical design, standardized sample collection strategies, and epidemiological data analyses have established the foundation for defining variability within human immune responses.

Semi-automated and standardized cytometric procedures for multi-panel and multi-parametric whole blood immunophenotyping.

Immunophenotyping by multi-parametric flow cytometry is the cornerstone technology for enumeration and characterization of immune cell populations in health and disease. Standardized procedures are essential to allow for inter-individual comparisons in the context of population based or clinical studies. Herein we report the approach taken by the Milieu Intérieur Consortium, highlighting the standardized and automated procedures used for immunophenotyping of human whole blood samples. We optimized eight-color antibody panels and procedures for staining and lysis of whole blood samples, and implemented pre-analytic steps with a semi-automated workflow using a robotic system. We report on four panels that were designed to enumerate and phenotype major immune cell populations (PMN, T, B, NK cells, monocytes and DC). This work establishes a foundation for defining reference values in healthy donors. Our approach provides robust protocols for affordable, semi-automated eight-color cytometric immunophenotyping that can be used in population-based studies and clinical trial settings.

Automated flow cytometric analysis across large numbers of samples and cell types.

Multi-parametric flow cytometry is a key technology for characterization of immune cell phenotypes. However, robust high-dimensional post-analytic strategies for automated data analysis in large numbers of donors are still lacking. Here, we report a computational pipeline, called FlowGM, which minimizes operator input, is insensitive to compensation settings, and can be adapted to different analytic panels. A Gaussian Mixture Model (GMM)-based approach was utilized for initial clustering, with the number of clusters determined using Bayesian Information Criterion. Meta-clustering in a reference donor permitted automated identification of 24 cell types across four panels. Cluster labels were integrated into FCS files, thus permitting comparisons to manual gating. Cell numbers and coefficient of variation (CV) were similar between FlowGM and conventional gating for lymphocyte populations, but notably FlowGM provided improved discrimination of "hard-to-gate" monocyte and dendritic cell (DC) subsets. FlowGM thus provides rapid high-dimensional analysis of cell phenotypes and is amenable to cohort studies.