Trimodal single-cell profiling reveals a novel pediatric CD8αα+ T cell subset and broad age-related molecular reprogramming across the T cell compartment.

Age-associated changes in the T cell compartment are well described. However, limitations of current single-modal or bimodal single-cell assays, including flow cytometry, RNA-seq (RNA sequencing) and CITE-seq (cellular indexing of transcriptomes and epitopes by sequencing), have restricted our ability to deconvolve more complex cellular and molecular changes. Here, we profile >300,000 single T cells from healthy children (aged 11-13 years) and older adults (aged 55-65 years) by using the trimodal assay TEA-seq (single-cell analysis of mRNA transcripts, surface protein epitopes and chromatin accessibility), which revealed that molecular programming of T cell subsets shifts toward a more activated basal state with age. Naive CD4+ T cells, considered relatively resistant to aging, exhibited pronounced transcriptional and epigenetic reprogramming. Moreover, we discovered a novel CD8αα+ T cell subset lost with age that is epigenetically poised for rapid effector responses and has distinct inhibitory, costimulatory and tissue-homing properties. Together, these data reveal new insights into age-associated changes in the T cell compartment that may contribute to differential immune responses.

Beta cell-specific CD8+ T cells maintain stem cell memory-associated epigenetic programs during type 1 diabetes.

The pool of beta cell-specific CD8+ T cells in type 1 diabetes (T1D) sustains an autoreactive potential despite having access to a constant source of antigen. To investigate the long-lived nature of these cells, we established a DNA methylation-based T cell 'multipotency index' and found that beta cell-specific CD8+ T cells retained a stem-like epigenetic multipotency score. Single-cell assay for transposase-accessible chromatin using sequencing confirmed the coexistence of naive and effector-associated epigenetic programs in individual beta cell-specific CD8+ T cells. Assessment of beta cell-specific CD8+ T cell anatomical distribution and the establishment of stem-associated epigenetic programs revealed that self-reactive CD8+ T cells isolated from murine lymphoid tissue retained developmentally plastic phenotypic and epigenetic profiles relative to the same cells isolated from the pancreas. Collectively, these data provide new insight into the longevity of beta cell-specific CD8+ T cell responses and document the use of this methylation-based multipotency index for investigating human and mouse CD8+ T cell differentiation.

PD-L1 and PD-1 Are Associated with Clinical Outcomes and Alveolar Immune Cell Activation in ARDS.

The relationship between the Programmed Death-Ligand 1 (PD-L1)/Programmed Death-1 (PD-1) pathway, lung inflammation, and clinical outcomes in acute respiratory distress syndrome (ARDS) is poorly understood. We sought to determine whether PD-L1/PD-1 in the lung or blood is associated with ARDS and associated severity. We measured soluble PD-L1 (sPD-L1) in plasma and lower respiratory tract samples (ARDS1 (n = 59) and ARDS2 (n = 78)) or plasma samples alone (ARDS3 (n = 149)) collected from subjects with ARDS and tested for associations with mortality using multiple regression. We used mass cytometry to measure PD-L1/PD-1 expression and intracellular cytokine staining in cells isolated from bronchoalveolar lavage fluid (BALF) (n = 18) and blood (n = 16) from critically-ill subjects with or without ARDS enrolled from a fourth cohort. Higher plasma levels of sPD-L1 were associated with mortality in ARDS1, ARDS2, and ARDS3. In contrast, higher levels of sPD-L1 in the lung were either not associated with mortality (ARDS2) or were associated with survival (ARDS1). Alveolar PD-1POS T cells had more intracellular cytokine staining compared with PD-1NEG T cells. Subjects without ARDS had a higher ratio of PD-L1POS alveolar macrophages to PD-1POS T cells compared with subjects with ARDS. We conclude that sPD-L1 may have divergent cellular sources and/or functions in the alveolar vs. blood compartments given distinct associations with mortality. Alveolar leukocyte subsets defined by PD-L1/PD-1 cell-surface expression have distinct cytokine secretion profiles, and the relative proportions of these subsets are associated with ARDS.

The SARS-CoV-2 Delta variant induces an antibody response largely focused on class 1 and 2 antibody epitopes.

Exposure histories to SARS-CoV-2 variants and vaccinations will shape the specificity of antibody responses. To understand the specificity of Delta-elicited antibody immunity, we characterize the polyclonal antibody response elicited by primary or mRNA vaccine-breakthrough Delta infections. Both types of infection elicit a neutralizing antibody response focused heavily on the receptor-binding domain (RBD). We use deep mutational scanning to show that mutations to the RBD's class 1 and class 2 epitopes, including sites 417, 478, and 484-486 often reduce binding of these Delta-elicited antibodies. The anti-Delta antibody response is more similar to that elicited by early 2020 viruses than the Beta variant, with mutations to the class 1 and 2, but not class 3 epitopes, having the largest effects on polyclonal antibody binding. In addition, mutations to the class 1 epitope (e.g., K417N) tend to have larger effects on antibody binding and neutralization in the Delta spike than in the D614G spike, both for vaccine- and Delta-infection-elicited antibodies. These results help elucidate how the antigenic impacts of SARS-CoV-2 mutations depend on exposure history.

Immune markers of severe acute pancreatitis.

PURPOSE OF THE REVIEW: Acute pancreatitis is a common acute inflammatory disorder of the pancreas, and its incidence has been increasing worldwide. Approximately 10% of acute pancreatitis progresses to severe acute pancreatitis (SAP), which carries significant morbidity and mortality. Disordered immune response to pancreatic injury is regarded as a key event that mediates systemic injury in SAP. In this article, we review recent developments in immune biomarkers of SAP and future directions for research. RECENT FINDINGS: Given the importance of the NLRP3-inflammasome pathway in mediating systemic inflammatory response syndrome and systemic injury, recent studies have investigated associations of SAP with systemic levels of activators of NLRP3, such as the damage associated molecular patterns (DAMPs) for the first time in human SAP. For example, circulating levels of histones, mitochondrial DNAs, and cell free DNAs have been associated with SAP. A panel of mechanistically relevant immune markers (e.g., panel of Angiopoeitin-2, hepatocyte growth factor, interleukin-8 (IL-8), resistin and sTNF-α R1) carried higher predictive accuracies than existing clinical scores and individual immune markers. Of the cytokines with established relevance to SAP pathogenesis, phase 2 trials of immunotherapies, including tumor necrosis factor (TNF)-alpha inhibition and stimulation of IL-10 production, are underway to determine if altering the immunologic response can reduce the severity of acute pancreatitis (AP). SUMMARY: Circulating systemic levels of various DAMPs and a panel of immune markers that possibly reflect activities of different pathways that drive SAP appear promising as predictive biomarkers for SAP. But larger multicenter studies are needed for external validation. Studies investigating immune cellular pathways driving SAP using immunophenotyping techniques are scarce. Interdisciplinary efforts are also needed to bring some of the promising biomarkers to the bedside for validation and testing for clinical utility. Studies investigating the role of and characterization of altered gut-lymph and gut-microbiota in severe AP are needed.

Fewer LAG-3+ T Cells in Relapsing-Remitting Multiple Sclerosis and Type 1 Diabetes.

The coinhibitory receptor lymphocyte activation gene 3 (LAG-3) is an immune checkpoint molecule that negatively regulates T cell activation, proliferation, and homeostasis. Blockade or deletion of LAG-3 in autoimmune-prone backgrounds or induced-disease models has been shown to exacerbate disease. We observed significantly fewer LAG-3+ CD4 and CD8 T cells from subjects with relapsing-remitting multiple sclerosis (RRMS) and type 1 diabetes. Low LAG-3 protein expression was linked to alterations in mRNA expression and not cell surface cleavage. Functional studies inhibiting LAG-3 suggest that in subjects with RRMS, LAG-3 retains its ability to suppress T cell proliferation. However, LAG-3 expression was associated with the expression of markers of apoptosis, indicating a role for low LAG-3 in T cell resistance to cell death. In T cells from subjects with RRMS, we observed a global dysregulation of LAG-3 expression stemming from decreased transcription and persisting after T cell stimulation. These findings further support the potential clinical benefits of a LAG-3 agonist in the treatment of human autoimmunity.

Cutting Edge: Effect of Disease-Modifying Therapies on SARS-CoV-2 Vaccine-Induced Immune Responses in Multiple Sclerosis Patients.

Multiple sclerosis (MS) is a demyelinating inflammatory disease of the CNS treated by diverse disease-modifying therapies that suppress the immune system. Severe acute respiratory syndrome coronavirus 2 mRNA vaccines have been very effective in immunocompetent individuals, but whether MS patients treated with modifying therapies are afforded the same protection is not known. This study determined that dimethyl fumarate caused a momentary reduction in anti-Spike (S)-specific Abs and CD8 T cell response. MS patients treated with B cell-depleting (anti-CD20) or sphingosine 1-phosphate receptor agonist (fingolimod) therapies lack significant S-specific Ab response. Whereas S-specific CD4 and CD8 T cell responses were largely compromised by fingolimod treatment, T cell responses were robustly generated in anti-CD20-treated MS patients, but with a reduced proportion of CD4+CXCR5+ circulating follicular Th cells. These data provide novel information regarding vaccine immune response in patients with autoimmunity useful to help improve vaccine effectiveness in these populations.

Guidelines for standardizing T-cell cytometry assays to link biomarkers, mechanisms, and disease outcomes in type 1 diabetes.

Cytometric immunophenotyping is a powerful tool to discover and implement T-cell biomarkers of type 1 diabetes (T1D) progression and response to clinical therapy. Although many discovery-based T-cell biomarkers have been described, to date, no such markers have been widely adopted in standard practice. The heterogeneous nature of T1D and lack of standardized assays and experimental design across studies is a major barrier to the broader adoption of T-cell immunophenotyping assays. There is an unmet need to harmonize the design of immunophenotyping assays, including those that measure antigen-agnostic cell populations, such that data collected from different clinical trial sites and T1D cohorts are comparable, yet account for cohort-specific features and different drug mechanisms of action. In these Guidelines, we aim to provide expert advice on how to unify aspects of study design and practice. We provide recommendations for defining cohorts, method implementation, as well as tools for data analysis and reporting by highlighting and building on selected successes. Harmonization of cytometry-based T-cell assays will allow researchers to better integrate findings across trials, ultimately enabling the identification and validation of biomarkers of disease progression and treatment response in T1D.

Characterising the age-dependent effects of risk factors on type 1 diabetes progression.

AIMS/HYPOTHESIS: Age is known to be one of the most important stratifiers of disease progression in type 1 diabetes. However, what drives the difference in rate of progression between adults and children is poorly understood. Evidence suggests that many type 1 diabetes disease predictors do not have the same effect across the age spectrum. Without a comprehensive analysis describing the varying risk profiles of predictors over the age continuum, researchers and clinicians are susceptible to inappropriate assessment of risk when examining populations of differing ages. We aimed to systematically assess and characterise how the effect of key type 1 diabetes risk predictors changes with age. METHODS: Using longitudinal data from single- and multiple-autoantibody-positive at-risk individuals recruited between the ages of 1 and 45 years in TrialNet's Pathway to Prevention Study, we assessed and visually characterised the age-varying effect of key demographic, immune and metabolic predictors of type 1 diabetes by employing a flexible spline model. Two progression outcomes were defined: participants with single autoantibodies (n=4893) were analysed for progression to multiple autoantibodies or type 1 diabetes, and participants with multiple autoantibodies were analysed (n=3856) for progression to type 1 diabetes. RESULTS: Several predictors exhibited significant age-varying effects on disease progression. Amongst single-autoantibody participants, HLA-DR3 (p=0.007), GAD65 autoantibody positivity (p=0.008), elevated BMI (p=0.007) and HOMA-IR (p=0.002) showed a significant increase in effect on disease progression with increasing age. Insulin autoantibody positivity had a diminishing effect with older age in single-autoantibody-positive participants (p<0.001). Amongst multiple-autoantibody-positive participants, male sex (p=0.002) was associated with an increase in risk for progression, and HLA DR3/4 (p=0.05) showed a decreased effect on disease progression with older age. In both single- and multiple-autoantibody-positive individuals, significant changes in HR with age were seen for multiple measures of islet function. Risk estimation using prediction risk score Index60 was found to be better at a younger age for both single- and multiple-autoantibody-positive individuals (p=0.007 and p<0.001, respectively). No age-varying effect was seen for prediction risk score DPTRS (p=0.861 and p=0.178, respectively). Multivariable analyses suggested that incorporating the age-varying effect of the individual components of these validated risk scores has the potential to enhance the risk estimate. CONCLUSIONS/INTERPRETATION: Analysing the age-varying effect of disease predictors improves understanding and prediction of type 1 diabetes disease progression, and should be leveraged to refine prediction models and guide mechanistic studies.

Severe acute pancreatitis exhibits distinct cytokine signatures and trajectories in humans: a prospective observational study.

Severe acute pancreatitis (SAP) is associated with substantial morbidity and mortality. Several cytokines have been identified to have pathophysiological significance in SAP, but studies characterizing their early trajectories are lacking. Here we characterize the early trajectories of seven key cytokines associated with SAP and compare them with non-SAP subjects. Five proinflammatory cytokines (angiopoietin-2, interleukin-6, interleukin-8, monocyte chemoattractant protein-1, resistin) and two anti-inflammatory cytokines (hepatocyte growth factor, and soluble tumor necrosis factor-α receptor-1A) were measured in a prospective cohort of acute pancreatitis subjects (2012-2016) at the time of enrollment and then every 24 h for 5 days or until discharge. The cytokines' levels and trajectories were calibrated based on date of pain onset and were compared between healthy controls and three severity categories (mild, moderate, and severe). The cohort (n = 170) consisted of 27 healthy controls, 65 mild, 38 moderate, and 40 SAP. From day 1 of symptom onset, SAP subjects exhibited significantly higher levels of both pro- and anti-inflammatory cytokines compared with non-SAP and healthy subjects. But in SAP subjects, all proinflammatory cytokines' levels trended downward after day 2 (except for a flat slope for angiopoeitin-2) whereas for non-SAP subjects, the trajectory was upward: this trajectory difference between SAP versus non-SAP subjects resulted in narrowing of the differences initially seen on day 1 for proinflammatory cytokines. For anti-inflammatory cytokines, the trajectories were uniformly upward for both SAP and non-SAP subjects. Proinflammatory cytokine response is an early and time-sensitive event in SAP that should be accounted for when designing future biomarker studies and/or therapeutic trials.NEW & NOTEWORTHY In this study, we showed that the proinflammatory cytokine response in SAP is an early event, with subsequent downregulation of proinflammatory cytokines beginning at day 1 of symptom onset. Our findings underscore the importance of enrolling subjects very early in the disease course when conducting studies to investigate early immune events of SAP; this current study also serves as an important reference for the design of future biomarker studies and therapeutic trials in SAP.

A simple strategy for sample annotation error detection in cytometry datasets.

Mislabeling samples or data with the wrong participant information can affect study integrity and lead investigators to draw inaccurate conclusions. Quality control to prevent these types of errors is commonly embedded into the analysis of genomic datasets, but a similar identification strategy is not standard for cytometric data. Here, we present a method for detecting sample identification errors in cytometric data using expression of human leukocyte antigen (HLA) class I alleles. We measured HLA-A*02 and HLA-B*07 expression in three longitudinal samples from 41 participants using a 33-marker CyTOF panel designed to identify major immune cell types. 3/123 samples (2.4%) showed HLA allele expression that did not match their longitudinal pairs. Furthermore, these same three samples' cytometric signature did not match qPCR HLA class I allele data, suggesting that they were accurately identified as mismatches. We conclude that this technique is useful for detecting sample-labeling errors in cytometric analyses of longitudinal data. This technique could also be used in conjunction with another method, like GWAS or PCR, to detect errors in cross-sectional data. We suggest widespread adoption of this or similar techniques will improve the quality of clinical studies that utilize cytometry.

Systems scale interactive exploration reveals quantitative and qualitative differences in response to influenza and pneumococcal vaccines.

Systems immunology approaches were employed to investigate innate and adaptive immune responses to influenza and pneumococcal vaccines. These two non-live vaccines show different magnitudes of transcriptional responses at different time points after vaccination. Software solutions were developed to explore correlates of vaccine efficacy measured as antibody titers at day 28. These enabled a further dissection of transcriptional responses. Thus, the innate response, measured within hours in the peripheral blood, was dominated by an interferon transcriptional signature after influenza vaccination and by an inflammation signature after pneumococcal vaccination. Day 7 plasmablast responses induced by both vaccines was more pronounced after pneumococcal vaccination. Together, these results suggest that comparing global immune responses elicited by different vaccines will be critical to our understanding of the immune mechanisms underpinning successful vaccination.

The many faces of islet antigen-specific CD8 T cells: clues to clinical outcome in type 1 diabetes.

Immune monitoring enables a better understanding of disease processes and response to therapy, but has been challenging in the setting of chronic autoimmunity because of unknown etiology, variable and protracted kinetics of the disease process, heterogeneity across patients and the complexity of immune interactions. To begin to parse this complexity, we focus here on type 1 diabetes (T1D) and CD8 T cells as a cell type that has features that are associated with different stages of disease, rates of progression and response to therapy. Specifically, we discuss the current understanding of the role of autoreactive CD8 T cells in disease outcome, which implicates particular CD8 functional subsets, rather than unique antigens or total number of autoreactive T cells. Next, we discuss how autoreactive CD8 T-cell features can be reflected in measures of global CD8 T cells, and then pull these concepts together by highlighting immune therapies recently shown to modulate both CD8 T cells and disease progression. We end by discussing outstanding questions about the role of specific subsets of autoreactive CD8 T cells in disease progression and how they may be optimally modulated to treat and prevent T1D.

Innate immune stimulation of whole blood reveals IFN-1 hyper-responsiveness in type 1 diabetes.

AIMS/HYPOTHESIS: Self-antigen-specific T cell responses drive type 1 diabetes pathogenesis, but alterations in innate immune responses are also critical and not as well understood. Innate immunity in human type 1 diabetes has primarily been assessed via gene-expression analysis of unstimulated peripheral blood mononuclear cells, without the immune activation that could amplify disease-associated signals. Increased responsiveness in each of the two main innate immune pathways, driven by either type 1 IFN (IFN-1) or IL-1, have been detected in type 1 diabetes, but the dominant innate pathway is still unclear. This study aimed to determine the key innate pathway in type 1 diabetes and assess the whole blood immune stimulation assay as a tool to investigate this. METHODS: The TruCulture whole blood ex vivo stimulation assay, paired with gene expression and cytokine measurements, was used to characterise changes in the stimulated innate immune response in type 1 diabetes. We applied specific cytokine-induced signatures to our data, pre-defined from the same assays measured in a separate cohort of healthy individuals. In addition, NOD mice were stimulated with CpG and monocyte gene expression was measured. RESULTS: Monocytes from NOD mice showed lower baseline vs diabetes-resistant B6.g7 mice, but higher induced IFN-1-associated gene expression. In human participants, ex vivo whole blood stimulation revealed higher induced IFN-1 responses in type 1 diabetes, as compared with healthy control participants. In contrast, neither the IL-1-induced gene signature nor response to the adaptive immune stimulant Staphylococcal enterotoxin B were significantly altered in type 1 diabetes samples vs healthy control participants. Targeted gene-expression analysis showed that this enhanced IFN response was specific to IFN-1, as IFN-γ-driven responses were not significantly different. CONCLUSIONS/INTERPRETATION: Our study identifies increased responsiveness to IFN-1 as a feature of both the NOD mouse model of autoimmune diabetes and human established type 1 diabetes. A stimulated IFN-1 gene signature may be a potential biomarker for type 1 diabetes and used to evaluate the effects of therapies targeting this pathway. DATA AVAILABILITY: Mouse gene expression data are found in the gene expression omnibus (GEO) repository, accession GSE146452 ( www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE146452 ). Nanostring count data from the human experiments were deposited in the GEO repository, accession GSE146338 ( www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE146338 ). Data files and R code for all analyses are available at https://github.com/rodriguesk/T1D_truculture_diabetologia . Graphical abstract.

Hyaluronan deposition in islets may precede and direct the location of islet immune-cell infiltrates.

AIMS/HYPOTHESIS: Substantial deposition of the extracellular matrix component hyaluronan (HA) is characteristic of insulitis in overt type 1 diabetes. We investigated whether HA accumulation is detectable in islets early in disease pathogenesis and how this affects the development of insulitis and beta cell mass. METHODS: Pancreas tissue from 15 non-diabetic organ donors who were positive for islet autoantibodies (aAbs) and from 14 similarly aged aAb- control donors were examined for the amount of islet HA staining and the presence of insulitis. The kinetics of HA deposition in islets, along with the onset and progression of insulitis and changes in beta cell mass, were investigated in BioBreeding DRLyp/Lyp rats (a model of spontaneous autoimmune diabetes) from 40 days of age until diabetes onset. RESULTS: Abundant islet HA deposits were observed in pancreas tissues from n = 3 single- and n = 4 double-aAb+ donors (aAb+HAhigh). In these seven tissues, the HA-stained areas in islets measured 1000 ± 240 µm2 (mean ± SEM) and were fourfold larger than those from aAb- control tissues. The aAb+HAhigh tissues also had a greater prevalence of islets that were highly rich in HA (21% of the islets in these tissues contained the largest HA-stained areas [>2000 µm2] vs less than 1% in tissues from aAb- control donors). The amount of HA staining in islets was associated with the number of aAbs (i.e. single- or double-aAb positivity) but not with HLA genotype or changes in beta cell mass. Among the seven aAb+HAhigh tissues, three from single- and one from double-aAb+ donors did not show any islet immune-cell infiltrates, indicating that HA accumulates in aAb+ donors independently of insulitis. The three aAb+HAhigh tissues that exhibited insulitis had the largest HA-stained areas and, in these tissues, islet-infiltrating immune cells co-localised with the most prominent HA deposits (i.e. with HA-stained areas >2000 µm2). Accumulation of HA in islets was evident prior to insulitis in 7-8-week-old presymptomatic DRLyp/Lyp rats, in which the islet HA-stained area measured 2370 ± 170 µm2 (mean ± SEM), which was threefold larger than in 6-week-old rats. This initial islet HA deposition was not concurrent with beta cell loss. Insulitis was first detected in 9-10-week-old rats, in which the HA-stained areas were 4980 ± 500 µm2. At this age, the rats also exhibited a 44% reduction in beta cell mass. Further enlargement of the HA-positive areas (mean ± SEM: 7220 ± 880 µm2) was associated with invasive insulitis. HA deposits remained abundant in the islets of rats with destructive insulitis, which had lost 85% of their beta cells. CONCLUSIONS/INTERPRETATION: This study indicates that HA deposition in islets occurs early in type 1 diabetes and prior to insulitis, and points to a potential role of HA in triggering islet immune-cell infiltration and the promotion of insulitis.

Characterization of regulatory T cells in obese omental adipose tissue in humans.

Obesity-associated visceral adipose tissue (AT) inflammation promotes insulin resistance and type 2 diabetes (T2D). In mice, lean visceral AT is populated with anti-inflammatory cells, notably regulatory T cells (Tregs) expressing the IL-33 receptor ST2. Conversely, obese AT contains fewer Tregs and more proinflammatory cells. In humans, however, there is limited evidence for a similar pattern of obesity-associated immunomodulation. We used flow cytometry and mRNA quantification to characterize human omental AT in 29 obese subjects, 18 of whom had T2D. Patients with T2D had increased proportions of inflammatory cells, including M1 macrophages, with positive correlations to body mass index. In contrast, Treg frequencies negatively correlated to body mass index but were comparable between T2D and non-T2D individuals. Compared to human thymic Tregs, omental AT Tregs expressed similar levels of FOXP3, CD25, IKZF2, and CTLA4, but higher levels of PPARG, CCR4, PRDM1, and CXCL2. ST2, however, was not detectable on omental AT Tregs from lean or obese subjects. This is the first comprehensive investigation into how omental AT immunity changes with obesity and T2D in humans, revealing important similarities and differences to paradigms in mice. These data increase our understanding of how pathways of immune regulation could be targeted to ameliorate AT inflammation in humans.

DRB4*01:01 Has a Distinct Motif and Presents a Proinsulin Epitope That Is Recognized in Subjects with Type 1 Diabetes.

DRB4*01:01 (DRB4) is a secondary HLA-DR product that is part of the high-risk DR4/DQ8 haplotype that is associated with type 1 diabetes (T1D). DRB4 shares considerable homology with HLA-DR4 alleles that predispose to autoimmunity, including DRB1*04:01 and DRB1*04:04. However, the DRB4 protein sequence includes distinct residues that would be expected to alter the characteristics of its binding pockets. To identify high-affinity peptides that are recognized in the context of DRB4, we used an HLA class II tetramer-based approach to identify epitopes within multiple viral Ags. We applied a similar approach to identify antigenic sequences within glutamic acid decarboxylase 65 and pre-proinsulin that are recognized in the context of DRB4. Seven sequences were immunogenic, eliciting high-affinity T cell responses in DRB4+ subjects. DRB1*04:01-restricted responses toward many of these peptides have been previously described, but responses to a novel pre-proinsulin 9-28 peptide were commonly observed in subjects with T1D. Furthermore, T cells that recognized this peptide in the context of DRB4 were present at significantly higher frequencies in patients with T1D than in healthy controls, implicating this as a disease-relevant specificity that may contribute to the breakdown of ß cell tolerance in genetically susceptible individuals. We then deduced a DRB4 motif and confirmed its key features through structural modeling. This modeling suggested that the core epitope within the pre-proinsulin 9-28 peptide has a somewhat unusual binding motif, with tryptophan in the fourth binding pocket of DRB4, perhaps influencing the availability of this complex for T cell selection.

Analysis of pancreatic beta cell specific CD4+ T cells reveals a predominance of proinsulin specific cells.

CD4+ T cell responses are thought to play a role in type 1 diabetes (T1D). However, detection and characterization of T cells that respond to beta cell epitopes in subjects with T1D has been limited by technical obstacles, including the inherently low frequencies in peripheral blood and variable responsiveness of individual subjects to single epitopes. We implemented a multicolor staining approach that allows direct ex vivo characterization of multiple CD4+ T cell specificities in a single sample. Here we demonstrate and apply that multicolor approach to directly measure the frequency and phenotype of beta cell specific CD4+ T cells in T1D patients and HLA matched controls. For this work we utilized five DR0401 restricted peptides from proinsulin, GAD65, IA-2, and IGRP, which were previously reported as disease relevant epitopes. Surprisingly, although responses to each of these peptides can be readily detected after in vitro expansion, our results indicated that only proinsulin specific T cells were consistently detectable at moderate frequencies in subjects with T1D. Characterization of beta cell specific CD4+ T cells revealed only modest differences between subjects with T1D and healthy controls. Subjects with T1D did have higher proportions of CD45RA negative epitope specific T cells than controls. In patients epitope specific T cells were often CXCR3 positive and a substantial proportion were CCR7 negative, suggesting a Th1-like effector phenotype. Finally, we demonstrated that our multicolor staining approach is compatible with class I multimer analysis, facilitating the characterization of self-reactive CD4+ and CD8+ T cells using a single sample.

Antigen-Specific T Cell Analysis Reveals That Active Immune Responses to ß Cell Antigens Are Focused on a Unique Set of Epitopes.

CD38 is an activation marker that is present on recently activated T cells, but absent on resting memory T cells. In this study, we show that CD45RO+CD38+ ß cell Ag-specific CD4+ T cells were present at higher frequencies in type 1 diabetes subjects compared with those in healthy subjects. These results imply an ongoing ß cell immunity years after onset of diabetes and suggest these activated T cells have an active role in the disease process. The Ag specificities of these activated T cells were determined by a novel CD154 T cell epitope mapping assay. Although each patient usually had a unique set of epitopes recognized by these T cells, two epitopes, DR0401-restricted modified preproinsulin peptide 78-90K88S and zinc transport 8 266-285, were repeatedly identified in multiple subjects. Identifying these T cells and their specific antigenic epitopes might provide immunotherapeutic targets for personalized therapies.