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Acute respiratory distress syndrome (ARDS) has a fibroproliferative phase that may be followed by pulmonary fibrosis. This has been described in patients with COVID-19 pneumonia, but the underlying mechanisms have not been completely defined. We hypothesized that protein mediators of tissue remodeling and monocyte chemotaxis are elevated in the plasma and endotracheal aspirates of critically ill patients with COVID-19 who subsequently develop radiographic fibrosis.We enrolled COVID-19 patients admitted to the ICU who had hypoxemic respiratory failure, were hospitalized and alive for at least 10 days, and had chest imaging done during hospitalization (n= 119). Plasma was collected within 24h of ICU admission and at 7d. In mechanically ventilated patients, endotracheal aspirates (ETA) were collected at 24h and 48-96h. Protein concentrations were measured by immunoassay. We tested for associations between protein concentrations and radiographic evidence of fibrosis using logistic regression adjusting for age, sex, and APACHE score.We identified 39 patients (33%) with features of fibrosis. Within 24h of ICU admission, plasma proteins related to tissue remodeling (MMP-9, Amphiregulin) and monocyte chemotaxis (CCL-2/MCP-1, CCL-13/MCP-4) were associated with the subsequent development of fibrosis whereas markers of inflammation (IL-6, TNF-α) were not. After 1 week, plasma MMP-9 increased in patients without fibrosis. In ETAs, only CCL-2/MCP-1 was associated with fibrosis at the later timepoint.This cohort study identifies proteins of tissue remodeling and monocyte recruitment that may identify early fibrotic remodeling following COVID-19. Measuring changes in these proteins over time may allow for early detection of fibrosis in patients with COVID-19.

OBJECTIVES: The metabolic abnormalities that lead to diabetes mellitus (DM) following an episode of acute pancreatitis (AP) have not been extensively studied. This manuscript describes the objectives, hypotheses, and methods of mechanistic studies of glucose metabolism that comprise secondary outcomes of the Diabetes RElated to Acute pancreatitis and its Mechanisms (DREAM) Study. METHODS: Three months after an index episode of AP, participants without pre-existing DM will undergo baseline testing with an oral glucose tolerance test. Participants will be followed longitudinally in three sub-cohorts with distinct metabolic tests. In the first and largest subcohort, oral glucose tolerance tests will be repeated 12 months after AP and annually to assess changes in β-cell function, insulin secretion, and insulin sensitivity. In the second, mixed meal tolerance tests will be performed at 3 and 12 months, then annually, and following incident DM to assess incretin and pancreatic polypeptide responses. In the third, frequently-sampled intravenous glucose tolerance tests will be performed at 3 months and 12 months to assess the first-phase insulin response and more precisely measure β-cell function and insulin sensitivity. CONCLUSIONS: The DREAM study will comprehensively assess the metabolic and endocrine changes that precede and lead to the development of DM after AP.

Acute pancreatitis (AP) is a disease characterized by an acute inflammatory phase followed by a convalescent phase. Diabetes mellitus (DM) was historically felt to be a transient phenomenon related to acute inflammation; however, it is increasingly recognized as an important late and chronic complication. There are several challenges that have prevented precisely determining the incidence rate of DM following AP and understanding the underlying mechanisms. The Diabetes RElated to Acute Pancreatitis and its Mechanisms (DREAM) Study is a prospective cohort study designed to address these and other knowledge gaps to provide the evidence needed to screen for, prevent, and treat DM following AP. In the following article, we summarize literature regarding the epidemiology of DM following AP, and provide the rationale and an overview of the DREAM study.

Inflammation and oxidative stress in pancreatic islets amplify the appearance of various posttranslational modifications to self-proteins. In this study, we identified a select group of carbonylated islet proteins arising before the onset of hyperglycemia in NOD mice. Of interest, we identified carbonyl modification of the prolyl-4-hydroxylase β subunit (P4Hb) that is responsible for proinsulin folding and trafficking as an autoantigen in both human and murine type 1 diabetes. We found that carbonylated P4Hb is amplified in stressed islets coincident with decreased glucose-stimulated insulin secretion and altered proinsulin-to-insulin ratios. Autoantibodies against P4Hb were detected in prediabetic NOD mice and in early human type 1 diabetes prior to the onset of anti-insulin autoimmunity. Moreover, we identify autoreactive CD4+ T-cell responses toward carbonyl-P4Hb epitopes in the circulation of patients with type 1 diabetes. Our studies provide mechanistic insight into the pathways of proinsulin metabolism and in creating autoantigenic forms of insulin in type 1 diabetes.

BackgroundHeterogeneity exists in type 1 diabetes (T1D) development and presentation. Islet autoantibodies form the foundation for T1D diagnostic and staging efforts. We hypothesized that autoantibodies can be used to identify heterogeneity in T1D before, at, and after diagnosis, and in response to disease modifying therapies. at clinically relevant timepoints throughout T1D progression.MethodsWe performed a systematic review assessing 10 years of original research studies examining relationships between autoantibodies and heterogeneity during disease progression, at the time of diagnosis, after diagnosis, and in response to disease modifying therapies in individuals at risk for T1D or within 1 year of T1D diagnosis.Results10,067 papers were screened. Out of 151 that met data extraction criteria, 90 studies characterized heterogeneity before clinical diagnosis. Autoantibody type/target was most commonly examined, followed by autoantibody number, titer, order of seroconversion, affinity, and novel islet autoantibodies/epitopes. Recurring themes included positive relationships of autoantibody number and specific types and titers with disease progression, differing clinical phenotypes based on the order of autoantibody seroconversion, and interactions with age and genetics. Overall, reporting of autoantibody assay performance was commonly included; however, only 43% (65/151) included information about autoantibody assay standardization efforts. Populations studied were almost exclusively of European ancestry.ConclusionsCurrent evidence most strongly supports the application of autoantibody features to more precisely define T1D before clinical diagnosis. Our findings support continued use of pre-clinical staging paradigms based on autoantibody number and suggest that additional autoantibody features, particularly when considered in relation to age and genetic risk, could offer more precise stratification. Increased participation in autoantibody standardization efforts is a critical step to improving future applicability of autoantibody-based precision medicine in T1D.Plain Language SummaryWe performed a systematic review to ascertain whether islet autoantibodies, biomarkers of autoimmunity against insulin-producing cells, could aid in stratifying individuals with different clinical presentations of type 1 diabetes. We found existing evidence most strongly supporting the application of these biomarkers to the period before clinical diagnosis, when certain autoantibody features (number, type) and the age when they develop, can provide important information for patients and care providers on what to expect for future type 1 diabetes progression.

BackgroundType 1 diabetes (T1D) results from immune-mediated destruction of insulin-producing beta cells. Efforts to prevent T1D have focused on modulating immune responses and supporting beta cell health; however, heterogeneity in disease progression and responses to therapies have made these efforts difficult to translate to clinical practice, highlighting the need for precision medicine approaches to T1D prevention.MethodsTo understand the current state of knowledge regarding precision approaches to T1D prevention, we performed a systematic review of randomized-controlled trials from the past 25 years testing disease-modifying therapies in T1D and/or identifying features linked to treatment response, analyzing bias using a Cochrane-risk-of-bias instrument.ResultsWe identified 75 manuscripts, 15 describing 11 prevention trials for individuals with increased risk for T1D, and 60 describing treatments aimed at preventing beta cell loss in individuals at disease onset. Seventeen agents tested, mostly immunotherapies, showed benefit compared to placebo (only two prior to T1D onset). Fifty-seven studies employed precision analyses to assess features linked to treatment response. Age, measures of beta cell function and immune phenotypes were most frequently tested. However, analyses were typically not prespecified, with inconsistent methods reporting, and tended to report positive findings.ConclusionsWhile the quality of prevention and intervention trials was overall high, low quality of precision analyses made it difficult to draw meaningful conclusions that inform clinical practice. Thus, prespecified precision analyses should be incorporated into the design of future studies and reported in full to facilitate precision medicine approaches to T1D prevention.Plain Language SummaryType 1 diabetes (T1D) results from the destruction of insulin-producing cells in the pancreas, necessitating lifelong insulin dependence. T1D prevention remains an elusive goal, largely due to immense variability in disease progression. Agents tested to date in clinical trials work in a subset of individuals, highlighting the need for precision medicine approaches to prevention. We systematically reviewed clinical trials of disease-modifying therapy in T1D. While age, measures of beta cell function, and immune phenotypes were most commonly identified as factors that influenced treatment response, the overall quality of these studies was low. This review reveals an important need to proactively design clinical trials with well-defined analyses to ensure that results can be interpreted and applied to clinical practice.

mRNA-based vaccines dramatically reduce the occurrence and severity of COVID-19, but are associated with rare vaccine-related adverse effects. These toxicities, coupled with observations that SARS-CoV-2 infection is associated with autoantibody development, raise questions whether COVID-19 vaccines may also promote the development of autoantibodies, particularly in autoimmune patients. Here we used Rapid Extracellular Antigen Profiling to characterize self- and viral-directed humoral responses after SARS-CoV-2 mRNA vaccination in 145 healthy individuals, 38 patients with autoimmune diseases, and 8 patients with mRNA vaccine-associated myocarditis. We confirm that most individuals generated robust virus-specific antibody responses post vaccination, but that the quality of this response is impaired in autoimmune patients on certain modes of immunosuppression. Autoantibody dynamics are remarkably stable in all vaccinated patients compared to COVID-19 patients that exhibit an increased prevalence of new autoantibody reactivities. Patients with vaccine-associated myocarditis do not have increased autoantibody reactivities relative to controls. In summary, our findings indicate that mRNA vaccines decouple SARS-CoV-2 immunity from autoantibody responses observed during acute COVID-19.

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.

IntroductionPrevious studies verify the formation of enzymatically post-translationally modified (PTM) self-peptides and their preferred recognition by T cells in subjects with type 1 diabetes (T1D). However, questions remain about the relative prevalence of T cells that recognize PTM self-peptides derived from different antigens, their functional phenotypes, and whether their presence correlates with a specific disease endotype.MethodsTo address this question, we identified a cohort of subjects with T1D who had diverse levels of residual beta cell function. Using previously developed HLA class II tetramer reagents, we enumerated T cells that recognize PTM GAD epitopes in the context of DRB1*04:01 or PTM IA2 epitopes in the context of DQB1*03:02 (DQ8).ResultsConsistent with prior studies, we observed higher overall frequencies and a greater proportion of memory T cells in subjects with T1D than in HLA matched controls. There were significantly higher numbers of GAD specific T cells than IA2 specific T cells in subjects with T1D. T cells specific for both groups of epitopes could be expanded from the peripheral blood of subjects with established T1D and at-risk subjects. Expanded neo-epitope specific T cells primarily produced interferon gamma in both groups, but a greater proportion of T cells were interferon gamma positive in subjects with T1D, including some poly-functional cells that also produced IL-4. Based on direct surface phenotyping, neo-epitope specific T cells exhibited diverse combinations of chemokine receptors. However, the largest proportion had markers associated with a Th1-like phenotype. Notably, DQ8 restricted responses to PTM IA2 were over-represented in subjects with lower residual beta cell function. Neo-epitope specific T cells were present in at-risk subjects, and those with multiple autoantibodies have higher interferon gamma to IL-4 ratios than those with single autoantibodies, suggesting a shift in polarization during progression.DiscussionThese results reinforce the relevance of PTM neo-epitopes in human disease and suggest that distinct responses to neo-antigens promote a more rapid decline in beta cell function.

Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disorder that causes debilitating swelling and destruction of the joints. People with RA are treated with drugs that actively suppress one or more parts of their immune system, and these may alter their response to vaccination against SARS-CoV-2. In this study, we analyzed blood samples from a cohort of RA subjects after receiving a 2-dose mRNA COVID-19 vaccine regimen. Our data show that individuals on the CTLA4-Ig therapy abatacept have reduced levels of SARS-CoV-2-neutralizing antibodies after vaccination. At a cellular level, these subjects show reduced activation and class-switching of SARS-CoV-2-specific B cells, as well as reduced numbers and impaired helper cytokine production by SARS-CoV-2-specific CD4+T cells. Individuals on methotrexate showed similar but less severe defects in vaccine response, whereas individuals on the B cell-depleting therapy rituximab had a near-total loss of antibody production after vaccination. These data define a specific cellular phenotype associated with impaired response to SARS-CoV-2 vaccination in RA subjects on different immune-modifying therapies, and help inform efforts to improve vaccination strategies in this vulnerable population.

The use of a standardized outcome metric enhances clinical trial conduct, interpretation, and cross-trial comparison. If a disease course is predictable, comparing modeled predictions with outcome data affords the precision and confidence needed to accelerate precision medicine. We demonstrate the power of this approach in type 1 diabetes (T1D) trials aiming to preserve endogenous insulin secretion measured by C-peptide. C-peptide is a predictable outcome given an individual’s age and baseline value; quantitative response (QR) adjusts for these variables and represents the difference between the observed and predicted outcome. Validated across 13 trials, the QR metric reduces each trial’s variance and markedly increases statistical power. As smaller studies are especially subject to random sampling variability, using QR as the outcome metric introduces alternative interpretations of previous clinical trial results analyzed by traditional statistical methods. QR can provide model-based estimates that quantify whether individuals or groups did better or worse than expected. QR also provides a purer metric to associate with biomarker data, enabling improved mechanistic insights. Using data from more than 1,300 participants, we demonstrate the value of QR in advancement of disease-modifying therapy (DMT) in T1D. QR applies to any disease where outcome is predictable by baseline covariates, rendering it useful for defining responders to therapy, comparing the effectiveness of different therapies, and understanding causal pathways in disease.

The naive T cell compartment undergoes multiple changes across age that associate with altered susceptibility to infection and autoimmunity. In addition to the acquisition of naive-like memory T cell subsets, mouse studies describe substantial molecular reprogramming of the naive compartment in adults compared with adolescents. However, these alterations are not well delineated in human aging. Using a new trimodal single cell technology (TEA-seq), we discovered that the composition and transcriptional and epigenetic programming of the naive T cell compartment in children (11-13 yrs) is distinct from that of older adults (55-65 yrs). Naive CD4 T cells, previously considered relatively resistant to aging, exhibited far more pronounced molecular reprogramming than naive CD8 T cells, in which alterations are preferentially driven by shifts in naive-like memory subsets. These data reveal the complex nature of the naive T cell compartment that may contribute to differential immune responses across the spectrum of human age.One Sentence Summary:The naive CD8 and CD4 T cell compartments in humans are heterogeneous and impacted differently with age, in which naive CD8 T cell subsets dramatically shift in composition and true naive CD4 T cells display significant molecular re-programming.

Genome-wide association studies have identified numerous loci with allelic associations to Type 1 Diabetes (T1D) risk. Most disease-associated variants are enriched in regulatory sequences active in lymphoid cell types, suggesting that lymphocyte gene expression is altered in T1D. We assayed gene expression between T1D cases and healthy controls in two autoimmunity-relevant lymphocyte cell types, memory CD4+/CD25+ T-regulatory cells (Treg) and memory CD4+/CD25- T-cells, using a splicing event-based approach to characterize tissue-specific transcriptomes. Limited differences in isoform usage between T1D cases and controls were observed in memory CD4+/CD25- T-cells. In Tregs, 553 genes demonstrated differences in isoform usage between cases and controls, particularly RNA recognition and splicing factor genes. Many of these genes are regulated by the variable inclusion of exons that can trigger nonsense mediated decay. Our results suggest that dysregulation of gene expression, through shifts in alternative splicing in Tregs, contributes to T1D etiology.

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., Studies implicate particular autoreactive CD8 T‐cell functional subsets, rather than certain self‐antigen specificities or the total number of cells, in type 1 diabetes (T1D) outcome. Specifically, more hyporesponsive and terminal subsets (i.e. exhausted cells) are associated with preservation of insulin‐producing beta islet cells while more progenitor, polyfunctional subsets are associated with poor outcome. A better understanding of the development of such CD8 T‐cell subsets in T1D will inform how they may be specifically and optimally modulated to treat and prevent T1D.

Context The presence of islet autoimmunity identifies individuals likely to progress to clinical type 1 diabetes (T1D). In clinical research studies, autoantibody screening followed by regular metabolic monitoring every 6 months reduces incidence of diabetic ketoacidosis (DKA) at diagnosis. Objective We hypothesized that DKA reduction can be achieved on a population basis with a reduced frequency of metabolic monitoring visits. We reasoned that prolonged time between the development of T1D and the time of clinical diagnosis (“undiagnosed time”) would more commonly result in DKA and thus that limiting undiagnosed time would decrease DKA. Methods An analysis was conducted of data from TrialNet's Pathway to Prevention (PTP), a cross-sectional longitudinal study that identifies and follows at-risk relatives of people with T1D. PTP is a population-based study enrolling across multiple countries. A total of 6193 autoantibody (AAB)-positive individuals participated in PTP from March 2004 to April 2019. We developed models of progression to clinical diagnosis for pediatric and adult populations with single or multiple AAB, and summarized results using estimated hazard rate. An optimal monitoring visit schedule was determined for each model to achieve a minimum average level of undiagnosed time for each population. Results Halving the number of monitoring visits usually conducted in research studies is likely to substantially lower the population incidence of DKA at diagnosis of T1D. Conclusion Our study has clinical implications for the metabolic monitoring of at-risk individuals. Fewer monitoring visits would reduce the clinical burden, suggesting a path toward transitioning monitoring beyond the research setting.

Inflammation and oxidative stress in pancreatic islets amplify the appearance of various post-translational modifications (PTMs) to self-proteins. Herein, we identified a select group of carbonylated islet proteins arising before the onset of hyperglycemia in non-obese diabetic mice. Of interest, we identified carbonyl modification of the prolyl-4-hydroxylase beta subunit (P4Hb) that is responsible for proinsulin folding and trafficking as an autoantigen in both human and murine type 1 diabetes. We found the carbonylated P4Hb is amplified in stressed islets coincident with decreased glucose-stimulated insulin secretion and altered proinsulin to insulin ratios. Autoantibodies against P4Hb were detected in prediabetic NOD mice and in early human type 1 diabetes prior to the onset of anti-insulin autoimmunity. Moreover, we identify autoreactive CD4+ T cell responses toward carbonyl-P4Hb epitopes in the circulation of patients with type 1 diabetes. Our studies provide mechanistic insight into the pathways of proinsulin metabolism and in creating autoantigenic forms of insulin in type 1 diabetes.

Diabetic ketoacidosis (DKA) is often the sentinel event to a diagnosis of clinical type 1 diabetes. Research studies involving antibody positive (AAB+) individuals at risk for developing type 1 diabetes have demonstrated that metabolic monitoring every 6 months with oral glucose tolerance testing can dramatically reduce the incidence of DKA at diagnosis. It is unknown whether other schedules can reduce the population level burden of metabolic monitoring in AAB+ individuals while retaining the potential benefit of reducing DKA. We reasoned that the shorter the time time-period during which clinical type 1 diabetes (T1D) remains undetected, the lower the likelihood of DKA. We aimed to develop models of optimized monitoring visit schedules to limit undiagnosed (UnDx) time for the population. Using OGTT data from 6193 islet AAB+ relatives identified in TrialNet’s Pathway to Prevention study, we developed models and an algorithm to optimize visit schedules to limit population-based UnDx time. The results of modeling were presented using estimated hazard rate as a function of age. An "optimal" visit schedule was determined for each model to achieve a minimum average level of UnDx time for the population. This was applied for risk patterns identified by each model thus producing optimal schedules for pediatric and adult populations with single or multiple antibodies. Modeling an optimized visit schedule to keep UnDx time ≤ 6 months at a population level, we find that conducting half the number of metabolic monitoring visits usually done in research studies is likely to be effective in significantly impacting the population incidence of DKA at diagnosis of T1D. Our approach has implications for public health screening and monitoring for T1D risk. Disclosure C. Orourke: None. C. Speake: Advisory Panel; Vertex Pharmaceuticals Incorporated. A. Ylescupidez: None. C. Bender: None. S. Lord: Other Relationship; Pfizer Inc. Funding Helmsley Charitable Trust (2103-05008) ; Helmsley Charitable Trust (2210-05590)

T cells isolated from the pancreatic infiltrates of nonobese diabetic mice have been shown to recognize epitopes formed by the covalent cross-linking of proinsulin and secretory granule peptides. Formation of such hybrid insulin peptides (HIPs) was confirmed through mass spectrometry, and responses to HIPs were observed among the islet-infiltrating T cells of pancreatic organ donors and in the peripheral blood of individuals with type 1 diabetes (T1D). However, questions remain about the prevalence of HIP-specific T cells in humans, the sequences they recognize, and their role in disease. We identified six novel HIPs that are recognized in the context of DRB1*04:01, discovered by using a library of theoretical HIP sequences derived from insulin fragments covalently linked to one another or to fragments of secretory granule proteins or other islet-derived proteins. We demonstrate that T cells that recognize these HIPs are detectable in the peripheral blood of subjects with T1D and exhibit an effector memory phenotype. HIP-reactive T-cell clones produced Th1-associated cytokines and proliferated in response to human islet preparations. These results support the relevance of HIPs in human disease, further establishing a novel posttranslational modification that may contribute to the loss of peripheral tolerance in T1D.

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.

Inflammation, including reactive oxygen species and inflammatory cytokines in tissues amplify various post-translational modifications of self-proteins. A number of post-translational modifications have been identified as autoimmune biomarkers in the initiation and progression of Type 1 diabetes. Here we show the citrullination of pancreatic glucokinase as a result of inflammation, triggering autoimmunity and affecting glucokinase biological functions. Glucokinase is expressed in hepatocytes to regulate glycogen synthesis, and in pancreatic beta cells as a glucose sensor to initiate glycolysis and insulin signaling. We identify autoantibodies and autoreactive CD4+ T cells to glucokinase epitopes in the circulation of Type 1 diabetes patients and NOD mice. Finally, citrullination alters glucokinase biologic activity and suppresses glucose-stimulated insulin secretion. Our study define glucokinase as a Type 1 diabetes biomarker, providing new insights of how inflammation drives post-translational modifications to create both neoautoantigens and affect beta cell metabolism. ispartof: NATURE COMMUNICATIONS vol:13 issue:1 ispartof: location:England status: published

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.

A recent discovery effort resulted in identification of novel splice variant and secretory granule antigens within the HLA class I peptidome of human islets and documentation of their recognition by CD8+ T cells from peripheral blood and human islets. In the current study, we applied a systematic discovery process to identify novel CD4+ T cell epitopes derived from these candidate antigens. We predicted 145 potential epitopes spanning unique splice junctions and within conventional secretory granule antigens and measured their in vitro binding to DRB1*04:01. We generated HLA class II tetramers for the 35 peptides with detectable binding and used these to assess immunogenicity and isolate T cell clones. Tetramers corresponding to peptides with verified immunogenicity were then used to label T cells specific for these putative epitopes in peripheral blood. T cells that recognize distinct epitopes derived from a cyclin I splice variant, neuroendocrine convertase 2, and urocortin-3 were detected at frequencies that were similar to those of an immunodominant proinsulin epitope. Cells specific for these novel epitopes predominantly exhibited a Th1-like surface phenotype. Among the three epitopes, responses to the cyclin I peptide exhibited a distinct memory profile. Responses to neuroendocrine convertase 2 were detected among pancreatic infiltrating T cells. These results further establish the contribution of unconventional antigens to the loss of tolerance in autoimmune diabetes.

Therapeutics that inhibit IL-6 at different points in its signaling pathway are in clinical use, yet whether the immunological effects of these interventions differ based on their molecular target is unknown. We performed short-term interventions in individuals with type 1 diabetes using anti-IL-6 (siltuximab) or anti-IL-6 receptor (IL-6R; tocilizumab) therapies and investigated the impact of this in vivo blockade on T cell fate and function. Immune outcomes were influenced by the target of the therapeutic intervention (IL-6 versus IL-6R) and by peak drug concentration. Tocilizumab reduced ICOS expression on T follicular helper cell populations and T cell receptor-driven (TCR-driven) STAT3 phosphorylation. Siltuximab reversed resistance to Treg-mediated suppression and increased TCR-driven phosphorylated STAT3 and production of IL-10, IL-21, and IL-27 by T effectors. Together, these findings indicate that the context of IL-6 blockade in vivo drives distinct T cell-intrinsic changes that may influence therapeutic outcomes.

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.

Individuals with Down syndrome show cellular and clinical features of dysregulated aging of the immune system, including a shift from naïve to memory T cells and increased incidence of autoimmunity. However, a quantitative understanding of how various immune compartments change with age in Down syndrome remains lacking. Here we performed deep immunophenotyping of a cohort of individuals with Down syndrome across the lifespan, selecting for autoimmunity-free individuals. We simultaneously interrogated age- and sex-matched healthy controls and people with type 1 diabetes as a representative autoimmune disease. We built an analytical software, IMPACD (Iterative Machine-assisted Permutational Analysis of Cytometry Data), that enabled us to rapidly identify many features of immune dysregulation in Down syndrome shared with other autoimmune diseases. We found quantitative and qualitative dysregulation of naïve CD4(+) and CD8(+) T cells in individuals with Down syndrome and identified interleukin (IL)-6 as a candidate driver of some of these changes, thus extending the consideration of immunopathologic cytokines in Down syndrome beyond interferons. We used immune cellular composition to generate three linear models of aging (immune clocks) trained on control participants. All three immune clocks demonstrated advanced immune aging in individuals with Down syndrome. One of these clocks, informed by Down syndrome-relevant biology, also showed advanced immune aging in individuals with type 1 diabetes. Orthologous RNA sequencing-derived immune clocks also demonstrated advanced immune aging in individuals with Down syndrome. Together, our findings demonstrate an approach to studying immune aging in Down syndrome which may have implications in the context of other autoimmune diseases.

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.

Human islet antigen reactive CD4+ memory T cells (IAR T cells) play a key role in the pathogenesis of autoimmune type 1 diabetes (T1D). Using single-cell RNA sequencing (scRNA-Seq) to identify T cell receptors (TCRs) in IAR T cells, we have identified a class of TCRs that share TCRα chains between individuals ("public" chains). We isolated IAR T cells from blood of healthy, new-onset T1D and established T1D donors using multiplexed CD154 enrichment and identified paired TCRαβ sequences from 2767 individual cells. More than a quarter of cells shared TCR junctions between 2 or more cells ("expanded"), and 29/47 (~62%) of expanded TCRs tested showed specificity for islet antigen epitopes. Public TCRs sharing TCRα junctions were most prominent in new-onset T1D. Public TCR sequences were more germline like than expanded unique, or "private," TCRs, and had shorter junction sequences, suggestive of fewer random nucleotide insertions. Public TCRα junctions were often paired with mismatched TCRβ junctions in TCRs; remarkably, a subset of these TCRs exhibited cross-reactivity toward distinct islet antigen peptides. Our findings demonstrate a prevalent population of IAR T cells with diverse specificities determined by TCRs with restricted TCRα junctions and germline-constrained antigen recognition properties. Since these "innate-like" TCRs differ from previously described immunodominant TCRβ chains in autoimmunity, they have implications for fundamental studies of disease mechanisms. Self-reactive restricted TCRα chains and their associated epitopes should be considered in fundamental and translational investigations of TCRs in T1D.

Mislabeling samples or data with the wrong participant information can impact 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 HLA class I alleles. We measured HLA-A*02 and HLA-B*07 expression in 3 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.

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

People with Down syndrome show cellular and clinical features of dysregulated aging of the immune system, including naïve-memory shift in the T cell compartment and increased incidence of autoimmunity. However, a quantitative understanding of how various immune compartments change with age in Down syndrome remains lacking. Here we performed deep immunophenotyping of a cohort of individuals with Down syndrome across the lifespan, selecting for individuals not affected by autoimmunity. We simultaneously interrogated age- and sex-matched healthy neurotypical controls and people with type 1 diabetes, as a representative autoimmune disease. We built a new analytical software, IMPACD, that enabled us to rapidly identify many features of immune dysregulation in Down syndrome that are recapitulated in other autoimmune diseases. We found significant quantitative and qualitative dysregulation of naïve CD4+and CD8+T cells in Down syndrome and identified IL-6 as a candidate driver of some of these changes, thus extending the consideration of immunopathologic cytokines in Down syndrome beyond interferons. Notably, we successfully used immune cellular composition to generate three quantitative models of aging (i.e. immune clocks) trained on control subjects. All three immune clocks demonstrated significantly advanced immune aging in people with Down syndrome. Notably, one of these clocks, informed by Down syndrome-relevant biology, also showed advanced immune aging in people with type 1 diabetes. Together, our findings demonstrate a novel approach to studying immune aging in Down syndrome which may have implications in the context of other autoimmune diseases.One Sentence SummaryPermutational analysis of immune landscape reveals advanced immune aging in people with Down syndrome and in people with type 1 diabetes.

Many host RNA sensors are positioned in the cytosol to detect viral RNA during infection. However, most positive-strand RNA viruses replicate within a modified organelle co-opted from intracellular membranes of the endomembrane system, which shields viral products from cellular innate immune sensors. Targeting innate RNA sensors to the endomembrane system may enhance their ability to sense RNA generated by viruses that use these compartments for replication. Here, we reveal that an isoform of oligoadenylate synthetase 1, OAS1 p46, is prenylated and targeted to the endomembrane system. Membrane localization of OAS1 p46 confers enhanced access to viral replication sites and results in increased antiviral activity against a subset of RNA viruses including flaviviruses, picornaviruses, and SARS-CoV-2. Finally, our human genetic analysis shows that the OAS1 splice-site SNP responsible for production of the OAS1 p46 isoform correlates with protection from severe COVID-19. This study highlights the importance of endomembrane targeting for the antiviral specificity of OAS1 and suggests that early control of SARS-CoV-2 replication through OAS1 p46 is an important determinant of COVID-19 severity.

Context There is an unmet need for biomarkers of pancreatic beta-cell death to improve early diagnosis of type 1 diabetes, enroll subjects into clinical trials, and assess treatment response. To address this need, several groups developed assays measuring insulin deoxyribonucleic acid (DNA) with unmethylated CpG sites in cell-free DNA. Unmethylated insulin DNA should be derived predominantly from beta-cells and indicate ongoing beta-cell death. Objective To assess the performance of three unmethylated insulin DNA assays. Design and Participants Plasma or serum samples from 13 subjects undergoing total pancreatectomy and islet autotransplantation were coded and provided to investigators to measure unmethylated insulin DNA. Samples included a negative control taken post-pancreatectomy but pretransplant, and a positive control taken immediately following islet infusion. We assessed technical reproducibility, linearity, and persistence of detection of unmethylated insulin DNA for each assay. Results All assays discriminated between the negative sample and samples taken directly from the islet transplant bag; 2 of 3 discriminated negative samples from those taken immediately after islet infusion. When high levels of unmethylated insulin DNA were present, technical reproducibility was generally good for all assays. Conclusions The measurement of beta cell cell-free DNA, including insulin, is a promising approach, warranting further testing and development in those with or at-risk for type 1 diabetes, as well as in other settings where understanding the frequency or kinetics of beta cell death could be useful.

Although most patients with type 1 diabetes (T1D) retain some functional insulin-producing islet β cells at the time of diagnosis, the rate of further β cell loss varies across individuals. It is not clear what drives this differential progression rate. CD8+ T cells have been implicated in the autoimmune destruction of β cells. Here, we addressed whether the phenotype and function of autoreactive CD8+ T cells influence disease progression. We identified islet-specific CD8+ T cells using high-content, single-cell mass cytometry in combination with peptide-loaded MHC tetramer staining. We applied a new analytical method, DISCOV-R, to characterize these rare subsets. Autoreactive T cells were phenotypically heterogeneous, and their phenotype differed by rate of disease progression. Activated islet-specific CD8+ memory T cells were prevalent in subjects with T1D who experienced rapid loss of C-peptide; in contrast, slow disease progression was associated with an exhaustion-like profile, with expression of multiple inhibitory receptors, limited cytokine production, and reduced proliferative capacity. This relationship between properties of autoreactive CD8+ T cells and the rate of T1D disease progression after onset make these phenotypes attractive putative biomarkers of disease trajectory and treatment response and reveal potential targets for therapeutic intervention.

Inflammation, including reactive oxygen species and inflammatory cytokines in tissues amplify various post-translational modifications of self-proteins. A number of post-translational modifications have been identified as autoimmune biomarkers in the initiation and progression of Type 1 diabetes. Here we show the citrullination of pancreatic glucokinase as a result of inflammation, triggering autoimmunity and affecting glucokinase biological functions. Glucokinase is expressed in hepatocytes to regulate glycogen synthesis, and in pancreatic beta cells as a glucose sensor to initiate glycolysis and insulin signaling. We identify autoantibodies and autoreactive CD4

Inflammation and oxidative stress in pancreatic islets amplify the appearance of various post-translational modifications (PTMs) to self-proteins. Herein, we identified a select group of carbonylated islet proteins arising before the onset of hyperglycemia in non-obese diabetic (NOD) mice. Of particular interest, we identified carbonyl modification of the prolyl-4-hydroxylase beta subunit (P4Hb) that is responsible for proinsulin folding and trafficking as an autoantigen in both human and murine type 1 diabetes. We found the carbonylated-P4Hb is amplified in stressed islets coincident with decreased glucose-stimulated insulin secretion and altered proinsulin to insulin ratios. Moreover, circulating autoantibodies against P4Hb were detected in prediabetic NOD mice and in early human type 1 diabetes prior to the onset of anti-insulin autoimmunity. Our studies provide mechanistic insight into the pathways of proinsulin metabolism and those creating autoantigenic forms of insulin in type 1 diabetes.

Inflammation, including reactive oxygen species and inflammatory cytokines in tissue microenvironments amplify the appearance of various post-translational modifications (PTMs) of self-proteins. Previously, a number of PTMs have been identified as autoimmune biomarkers in the initiation and progression of Type 1 diabetes (T1D). Herein, we have identified the citrullination of glucokinase (GK) as a result of inflammation, triggering autoimmunity and affecting its biological functions. Glucokinase is predominantly expressed in hepatocytes to regulate glycogen synthesis, and in pancreatic beta cells, where it acts as a glucose sensor to initiate glycolysis and insulin signaling. Herein, we demonstrate that glucokinase is citrullinated in inflamed non-obese diabetic (NOD) islets as well as in human GK. Autoantibodies against both native and citrullinated GK arise in both spontaneous human T1D and murine models. Likewise, autoreactive CD4+ T cells to both native and citrullinated glucokinase epitopes are present in the circulation of T1D patients. Finally, citrullination alters GK biologic activity and suppresses glucose-stimulated insulin secretion. Our studies define glucokinase as a T1D biomarker, providing new insights into altering glucose metabolism, creating neoautoantigens, and better define the broad impact of PTMs on the tissue pathology of T1D.

SUMMARYMany host RNA sensors are positioned in the cytosol to detect viral RNA during infection. However, most positive-strand RNA viruses replicate within a modified organelle co-opted from intracellular membranes of the endomembrane system, which shields viral products from host cell innate immune sensors. Targeting innate RNA sensors to the endomembrane system may enhance their ability to sense viral RNA generated by viruses that use these compartments for replication. Here, we reveal that an isoform of oligoadenylate synthetase 1, OAS1 p46, is prenylated and targeted to the endomembrane system. Membrane localization of OAS1 p46 confers enhanced access to viral replication sites and results in increased antiviral activity against a subset of RNA viruses including flavivirus, picornavirus, and SARS-CoV-2. Finally, our human genetic analysis shows that the OAS1 splice-site SNP responsible for production of the OAS1 p46 isoform strongly associates with COVID-19 severity. This study highlights the importance of endomembrane targeting for the antiviral specificity of OAS1 and suggests early control of SARS-CoV-2 replication through OAS1-p46 is an important determinant of COVID-19 severity.

Comprehensive data on early prognostic indicators in patients with mild COVID-19 remains sparse. In this single center case series, we characterized the initial clinical presentation in 180 patients with mild COVID-19 and defined the earliest predictors of subsequent deterioration and need for hospitalization. Three broad patient phenotypes and four symptom clusters were characterized, differentiated by varying risk for adverse outcomes. Among 14 symptoms assessed, subjective shortness of breath (SOB) most strongly associated with adverse outcomes (odds ratio (OR) 21.3, 95% confidence interval (CI): 2.7–166.4, p &lt, 0.0001). In combination, SOB and number of comorbidities were highly predictive of subsequent hospitalization (area under the curve (AUC) 92%). Additionally, initial lymphopenia (OR 21.0, 95% CI: 2.1–210.1, p = 0.002) and male sex (OR 3.5, 95% CI: 0.9–13.0, p = 0.05) were associated with increased risk of poor outcomes. Patients with known comorbidities, especially multiple, and those presenting with subjective SOB or lymphopenia should receive close monitoring and consideration for preemptive treatment, even when presenting with mild symptoms.

BACKGROUND: Despite a rapidly growing body of literature on coronavirus disease 2019 (COVID-19), our understanding of the immune correlates of disease severity, course, and outcome remains poor. METHODS: Using mass cytometry, we assessed the immune landscape in longitudinal whole-blood specimens from 59 patients presenting with acute COVID-19 and classified based on maximal disease severity. Hospitalized patients negative for SARS-CoV-2 were used as controls. RESULTS: We found that the immune landscape in COVID-19 formed 3 dominant clusters, which correlated with disease severity. Longitudinal analysis identified a pattern of productive innate and adaptive immune responses in individuals who had a moderate disease course, whereas those with severe disease had features suggestive of a protracted and dysregulated immune response. Further, we identified coordinate immune alterations accompanying clinical improvement and decline that were also seen in patients who received IL-6 pathway blockade. CONCLUSION: The hospitalized COVID-19 negative cohort allowed us to identify immune alterations that were shared between severe COVID-19 and other critically ill patients. Collectively, our findings indicate that selection of immune interventions should be based in part on disease presentation and early disease trajectory due to the profound differences in the immune response in those with mild to moderate disease and those with the most severe disease. FUNDING: Benaroya Family Foundation, the Leonard and Norma Klorfine Foundation, Glenn and Mary Lynn Mounger, and the National Institutes of Health.

Islet autoantibodies are key markers for the diagnosis of type 1 diabetes. Since their discovery, they have also been recognized for their potential to identify at-risk individuals prior to symptoms. To date, risk prediction using autoantibodies has been based on autoantibody number; it has been robustly shown that nearly all multiple-autoantibody-positive individuals will progress to clinical disease. However, longitudinal studies have demonstrated that the rate of progression among multiple-autoantibody-positive individuals is highly heterogenous. Accurate prediction of the most rapidly progressing individuals is crucial for efficient and informative clinical trials and for identification of candidates most likely to benefit from disease modification. This is increasingly relevant with the recent success in delaying clinical disease in presymptomatic subjects using immunotherapy, and as the field moves toward population-based screening. There have been many studies investigating islet autoantibody characteristics for their predictive potential, beyond a simple categorical count. Predictive features that have emerged include molecular specifics, such as epitope targets and affinity; longitudinal patterns, such as changes in titer and autoantibody reversion; and sequence-dependent risk profiles specific to the autoantibody and the subject’s age. These insights are the outworking of decades of prospective cohort studies and international assay standardization efforts and will contribute to the granularity needed for more sensitive and specific preclinical staging. The aim of this review is to identify the dynamic and nuanced manifestations of autoantibodies in type 1 diabetes, and to highlight how these autoantibody features have the potential to improve study design of trials aiming to predict and prevent disease.

We would like to thank Alhamar et al. (1) for their perspective on our article, which included questions regarding the utility of standard autoantibody measures in characterizing preclinical type 1 diabetes and recruitment of prevention trials. To summarize our findings, we reported that 96% of individuals with multiple autoantibodies sustain these autoantibodies over time (2). Further, we found that the 4% of individuals who did not sustain multiple-autoantibody status over time still retained a greater risk of progression to type 1 diabetes than those who never developed multiple autoantibodies. Indeed, decades of research in many population groups and different countries have repeatedly demonstrated that almost all individuals with multiple autoantibodies will eventually develop clinical disease. Additionally, among children at increased genetic risk for type 1 diabetes, those who reverted from a single autoantibody retained an increased risk for …

Islet autoantibodies are predominantly measured by radioassay to facilitate risk assessment and diagnosis of type 1 diabetes. However, the reliance on radioactive components, large sample volumes and limited throughput renders radioassay testing costly and challenging. We developed a multiplex analysis platform based on antibody detection by agglutination-PCR (ADAP) for the sample-sparing measurement of GAD, IA-2 and insulin autoantibodies/antibodies in 1 μL serum. The assay was developed and validated in 7 distinct cohorts (n = 858) with the majority of the cohorts blinded prior to analysis. Measurements from the ADAP assay were compared to radioassay to determine correlation, concordance, agreement, clinical sensitivity and specificity. The average overall agreement between ADAP and radioassay was above 91%. The average clinical sensitivity and specificity were 96% and 97%. In the IASP 2018 workshop, ADAP achieved the highest sensitivity of all assays tested at 95% specificity (AS95) rating for GAD and IA-2 autoantibodies and top-tier performance for insulin autoantibodies. Furthermore, ADAP correctly identified 95% high-risk individuals with two or more autoantibodies by radioassay amongst 39 relatives of T1D patients tested. In conclusion, the new ADAP assay can reliably detect the three cardinal islet autoantibodies/antibodies in 1μL serum with high sensitivity. This novel assay may improve pediatric testing compliance and facilitate easier community-wide screening for islet autoantibodies.

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.

T cells isolated from the pancreatic infiltrates of non-obese diabetic mice have been shown to recognize epitopes formed by the covalent cross-linking of proinsulin and secretory granule peptides. Formation of such hybrid insulin peptides (HIPs) was confirmed through mass spectrometry and responses to HIPs were observed among the islet-infiltrating T cells of pancreatic organ donors and in the peripheral blood of individuals with type 1 diabetes (T1D). However, questions remain about the prevalence of HIP-specific T cells in humans, the sequences they recognize, and their role in disease. We identified six novel HIPs that are recognized in the context of DRB1*04:01, discovered by utilizing a library of theoretical HIP sequences derived from insulin fragments covalently linked to one another or to fragments of secretory granule proteins or other islet-derived proteins. We demonstrate that T cells that recognize these HIPs are detectable in the peripheral blood of subjects with T1D and exhibit an effector memory phenotype. HIP-reactive T cell clones produced Th1-associated cytokines and proliferated in response to human islet preparations. These results support the relevance of HIPs in human disease, further establishing a novel post-translational modification that may contribute to the loss of peripheral tolerance in T1D.

OBJECTIVE Most individuals with two or more islet autoantibodies progress to clinical type 1 diabetes. However, in some individuals, autoantibodies are subsequently lost. Here, our objectives were to determine the frequency of autoantibody loss (reversion) in multiple-autoantibody–positive individuals and to determine the association between reversion and progression to clinical disease. RESEARCH DESIGN AND METHODS We analyzed multiple-autoantibody–positive individuals participating in TrialNet’s Pathway to Prevention Study for reversion and determined the effect of reversion on progression to clinical disease using a Cox regression analysis. RESULTS Of 3,284 multiple-autoantibody–positive subjects, reversion occurred in 134 (4.1%) and was associated with reduced incidence of clinical disease. Reversion occurred more frequently with older age, lower autoantibody titers, and fewer positive autoantibodies. CONCLUSIONS Although reversion of multiple-autoantibody positivity is rare, when it occurs, the risk of progressing to clinical disease is reduced. This suggests unknown mechanisms promoting immune remission in some individuals.

OBJECTIVE Abnormally elevated proinsulin secretion has been reported in type 2 and early type 1 diabetes when significant C-peptide is present. We questioned whether individuals with long-standing type 1 diabetes and low or absent C-peptide secretory capacity retained the ability to make proinsulin. RESEARCH DESIGN AND METHODS C-peptide and proinsulin were measured in fasting and stimulated sera from 319 subjects with long-standing type 1 diabetes (≥3 years) and 12 control subjects without diabetes. We considered three categories of stimulated C-peptide: 1) C-peptide positive, with high stimulated values ≥0.2 nmol/L; 2) C-peptide positive, with low stimulated values ≥0.017 but RESULTS Of individuals with long-standing type 1 diabetes, 95.9% had detectable serum proinsulin (>3.1 pmol/L), while 89.9% of participants with stimulated C-peptide values below the limit of detection ( CONCLUSIONS In individuals with long-duration type 1 diabetes, the ability to secrete proinsulin persists, even in those with undetectable serum C-peptide.