Beyond Stages: Predicting Individual Time Dependent Risk for Type 1 Diabetes.

BACKGROUND: Essentially all individuals with multiple autoantibodies will develop clinical type 1 diabetes. Multiple AABs and normal glucose tolerance define Stage 1 diabetes; abnormal glucose tolerance defines Stage 2. However, the rate of progression within these stages is heterogeneous, necessitating personalized risk calculators to improve clinical implementation. METHODS: We developed 3 models using TrialNet's Pathway to Prevention data to accommodate the reality that not all risk variables are clinically available. The Small model included AAB status, fasting glucose, HbA1c and age, while the Medium and Large models added predictors of disease progression measured via oral glucose tolerance testing. FINDINGS: All models markedly improved granularity regarding personalized risk missing from current categories of stages of T1D. Model derived risk calculations are consistent with the expected reduction of risk with increasing age and increase in risk with higher glucose and lower insulin secretion, illustrating the suitability of the models. Adding glucose and insulin secretion data altered model predicted probabilities within Stages. In those with high 2-hour glucose, a high C-peptide markedly decreased predicted risk; lower C-peptide obviated the age-dependent risk of 2-hour glucose alone, providing a more nuanced estimate of rate of disease progression within Stage 2. CONCLUSIONS: While essentially all those with multiple AABs will develop type 1 diabetes, the rate of progression is heterogeneous and not explained by any individual single risk variable. The model-based probabilities developed here provide an adaptable personalized risk calculator to better inform decisions about how and when to monitor disease progression in clinical practice.

Evidence for C-Peptide as a Validated Surrogate to Predict Clinical Benefits in Trials of Disease-Modifying Therapies for Type 1 Diabetes.

Type 1 diabetes is a chronic autoimmune disease in which destruction of pancreatic ß-cells causes life-threatening metabolic dysregulation. Numerous approaches are envisioned for new therapies, but limitations of current clinical outcome measures are significant disincentives to development efforts. C-peptide, a direct byproduct of proinsulin processing, is a quantitative biomarker of ß-cell function that is not cleared by the liver and can be measured in the peripheral blood. Studies of quantitative measures of ß-cell function have established a predictive relationship between stimulated C-peptide as a measure of ß-cell function and clinical benefits. C-peptide levels at diagnosis are often high enough to afford glycemic control benefits associated with protection from end-organ complications of diabetes, and even lower levels offer protection from severe hypoglycemia in type 1 diabetes, as observed in large prospective cohort studies and interventional trials of islet transplantation. These observations support consideration of C-peptide not just as a biomarker of ß-cell function but also as a specific, sensitive, feasible, and clinically meaningful outcome defining ß-cell preservation or restoration for clinical trials of disease-modifying therapies. Regulatory acceptance of C-peptide as a validated surrogate for demonstration of efficacy would greatly facilitate development of disease-modifying therapies for type 1 diabetes.

Testing a new platform to screen disease-modifying therapy in type 1 diabetes.

Studies of new therapies to preserve insulin secretion in early type 1 diabetes require several years to recruit eligible subjects and to see a treatment effect; thus, there is interest in alternative study designs to speed this process. Most people with longstanding type 1 diabetes no longer secrete insulin. However, studies from pancreata of those with longstanding T1D show that beta cells staining for insulin can persist for decades after diagnosis, and this is paralleled in work showing proinsulin secretion in individuals with longstanding disease; collectively this suggests that there is a reserve of alive but "sleeping" beta cells. Here, we designed a novel clinical trial platform to test whether a short course of therapy with an agent known to have effects in type 1 diabetes with residual endogenous insulin could transiently induce insulin secretion in those who no longer produce insulin. A therapy that transiently "wakes up" sleeping beta cells might be tested next in a fully powered trial in those with endogenous insulin secretion. In this three-arm non-randomized pilot study, we tested three therapies known to impact disease: two beta-cell supportive agents, liraglutide and verapamil, and an immunomodulatory agent, golimumab. The golimumab treated arm was not fully enrolled due to uncertainties about immunotherapy during the COVID-19 pandemic. Participants had mixed-meal tolerance test (MMTT)-stimulated C-peptide below the quantitation limit (<0.02 ng/mL) at enrollment and received 8 to 12 weeks of therapy. At the completion of therapy, none of the individuals achieved the primary outcome of MMTT-stimulated C-peptide ≥ 0.02 ng/mL. An exploratory outcome of the verapamil arm was MRI-assessed pancreas size, diffusion, and longitudinal relaxation time, which showed repeatability of these measures but no treatment effect. The liraglutide and golimumab arms were registered on clinicaltrials.gov under accession number NCT03632759 and the verapamil arm under accession number NCT05847413. Trail registration: Protocols are registered in ClinicalTrials.gov under accession numbers NCT03632759 and NCT05847413.

A standardized metric to enhance clinical trial design and outcome interpretation in type 1 diabetes.

The use of a standardized outcome metric enhances clinical trial 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 this approach in type 1 diabetes (T1D) trials aiming to preserve endogenous insulin secretion measured by C-peptide. C-peptide is predictable 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 increases statistical power. As smaller studies are especially subject to random sampling variability, using QR as the outcome introduces alternative interpretations of previous clinical trial results. 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 measurements. Using data from more than 1300 participants, we demonstrate the value of QR in advancing disease-modifying therapy in T1D. QR applies to any disease where outcome is predictable by pre-specified baseline covariates, rendering it useful for defining responders to therapy, comparing therapeutic efficacy, and understanding causal pathways in disease.

Shifts in isoform usage underlie transcriptional differences in regulatory T cells in type 1 diabetes.

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. Here we assay gene expression between T1D cases and healthy controls in two autoimmunity-relevant lymphocyte cell types, memory CD4+/CD25+ regulatory T 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 are observed in memory CD4+/CD25- T-cells. In Tregs, 402 genes demonstrate 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 pathophysiology.

Islet-autoreactive CD4+ T cells are linked with response to alefacept in type 1 diabetes.

Variation in the preservation of ß cell function in clinical trials in type 1 diabetes (T1D) has emphasized the need to define biomarkers to predict treatment response. The T1DAL trial targeted T cells with alefacept (LFA-3-Ig) and demonstrated C-peptide preservation in approximately 30% of new-onset T1D individuals. We analyzed islet antigen-reactive (IAR) CD4+ T cells in PBMC samples collected prior to treatment from alefacept- and placebo-treated individuals using flow cytometry and single-cell RNA sequencing. IAR CD4+ T cells at baseline had heterogeneous phenotypes. Transcript profiles formed phenotypic clusters of cells along a trajectory based on increasing maturation and activation, and T cell receptor (TCR) chains showed clonal expansion. Notably, the frequency of IAR CD4+ T cells with a memory phenotype and a unique transcript profile (cluster 3) were inversely correlated with C-peptide preservation in alefacept-treated, but not placebo-treated, individuals. Cluster 3 cells had a proinflammatory phenotype characterized by expression of the transcription factor BHLHE40 and the cytokines GM-CSF and TNF-α, and shared TCR chains with effector memory-like clusters. Our results suggest IAR CD4+ T cells as a potential baseline biomarker of response to therapies targeting the CD2 pathway and warrant investigation for other T cell-related therapies.

OGTT Metrics Surpass Continuous Glucose Monitoring Data for T1D Prediction in Multiple-Autoantibody-Positive Individuals.

CONTEXT: The value of continuous glucose monitoring (CGM) for monitoring autoantibody (AAB)-positive individuals in clinical trials for progression of type 1 diabetes (T1D) is unknown. OBJECTIVE: Compare CGM with oral glucose tolerance test (OGTT)-based metrics in prediction of T1D. METHODS: At academic centers, OGTT and CGM data from multiple-AAB relatives were evaluated for associations with T1D diagnosis. Participants were multiple-AAB-positive individuals in a TrialNet Pathway to Prevention (TN01) CGM ancillary study (n = 93). The intervention was CGM for 1 week at baseline, 6 months, and 12 months. Receiver operating characteristic (ROC) curves of CGM and OGTT metrics for prediction of T1D were analyzed. RESULTS: Five of 7 OGTT metrics and 29/48 CGM metrics but not HbA1c differed between those who subsequently did or did not develop T1D. ROC area under the curve (AUC) of individual CGM values ranged from 50% to 69% and increased when adjusted for age and AABs. However, the highest-ranking metrics were derived from OGTT: 4/7 with AUC ∼80%. Compared with adjusted multivariable models using CGM data, OGTT-derived variables, Index60 and DPTRS (Diabetes Prevention Trial-Type 1 Risk Score), had higher discriminative ability (higher ROC AUC and positive predictive value with similar negative predictive value). CONCLUSION: Every 6-month CGM measures in multiple-AAB-positive individuals are predictive of subsequent T1D, but less so than OGTT-derived variables. CGM may have feasibility advantages and be useful in some settings. However, our data suggest there is insufficient evidence to replace OGTT measures with CGM in the context of clinical trials.

Abatacept for Delay of Type 1 Diabetes Progression in Stage 1 Relatives at Risk: A Randomized, Double-Masked, Controlled Trial.

OBJECTIVE: Previous studies showed that inhibiting lymphocyte costimulation reduces declining ß-cell function in individuals newly diagnosed with type 1 diabetes. We tested whether abatacept would delay or prevent progression of type 1 diabetes from normal glucose tolerance (NGT) to abnormal glucose tolerance (AGT) or to diabetes and the effects of treatment on immune and metabolic responses. RESEARCH DESIGN AND METHODS: We conducted a phase 2, randomized, placebo-controlled, double-masked trial of abatacept in antibody-positive participants with NGT who received monthly abatacept/placebo infusions for 12 months. The end point was AGT or diabetes, assessed by oral glucose tolerance tests. RESULTS: A total of 101 participants received abatacept and 111 placebo. Of these, 81 (35 abatacept and 46 placebo) met the end point of AGT or type 1 diabetes diagnosis (hazard ratio 0.702; 95% CI 0.452, 1.09; P = 0.11) The C-peptide responses to oral glucose tolerance tests were higher in the abatacept arm (P < 0.03). Abatacept reduced the frequency of inducible T-cell costimulatory (ICOS)+ PD1+ T-follicular helper (Tfh) cells during treatment (P < 0.0001), increased naive CD4+ T cells, and also reduced the frequency of CD4+ regulatory T cells (Tregs) from the baseline (P = 0.0067). Twelve months after treatment, the frequency of ICOS+ Tfh, naive CD4+ T cells, and Tregs returned to baseline. CONCLUSIONS: Although abatacept treatment for 1 year did not significantly delay progression to glucose intolerance in at-risk individuals, it impacted immune cell subsets and preserved insulin secretion, suggesting that costimulation blockade may modify progression of type 1 diabetes.

CGM Metrics Identify Dysglycemic States in Participants From the TrialNet Pathway to Prevention Study.

OBJECTIVE: Continuous glucose monitoring (CGM) parameters may identify individuals at risk for progression to overt type 1 diabetes. We aimed to determine whether CGM metrics provide additional insights into progression to clinical stage 3 type 1 diabetes. RESEARCH DESIGN AND METHODS: One hundred five relatives of individuals in type 1 diabetes probands (median age 16.8 years; 89% non-Hispanic White; 43.8% female) from the TrialNet Pathway to Prevention study underwent 7-day CGM assessments and oral glucose tolerance tests (OGTTs) at 6-month intervals. The baseline data are reported here. Three groups were evaluated: individuals with 1) stage 2 type 1 diabetes (n = 42) with two or more diabetes-related autoantibodies and abnormal OGTT; 2) stage 1 type 1 diabetes (n = 53) with two or more diabetes-related autoantibodies and normal OGTT; and 3) negative test for all diabetes-related autoantibodies and normal OGTT (n = 10). RESULTS: Multiple CGM metrics were associated with progression to stage 3 type 1 diabetes. Specifically, spending ≥5% time with glucose levels ≥140 mg/dL (P = 0.01), ≥8% time with glucose levels ≥140 mg/dL (P = 0.02), ≥5% time with glucose levels ≥160 mg/dL (P = 0.0001), and ≥8% time with glucose levels ≥160 mg/dL (P = 0.02) were all associated with progression to stage 3 disease. Stage 2 participants and those who progressed to stage 3 also exhibited higher mean daytime glucose values; spent more time with glucose values over 120, 140, and 160 mg/dL; and had greater variability. CONCLUSIONS: CGM could aid in the identification of individuals, including those with a normal OGTT, who are likely to rapidly progress to stage 3 type 1 diabetes.

Risk Modeling to Reduce Monitoring of an Autoantibody-Positive Population to Prevent DKA at Type 1 Diabetes Diagnosis.

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.

IL-6-targeted therapies to block the cytokine or its receptor drive distinct alterations in T cell function.

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.

Rationale and Design for the Diabetes RElated to Acute Pancreatitis and Its Mechanisms Study: A Prospective Cohort Study From the Type 1 Diabetes in Acute Pancreatitis Consortium.

ABSTRACT: 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 after AP and understanding the underlying mechanisms. The DREAM (Diabetes RElated to Acute Pancreatitis and its Mechanisms) 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 after AP. In the following article, we summarize literature regarding the epidemiology of DM after AP and provide the rationale and an overview of the DREAM study.

Assessing the Pathophysiology of Hyperglycemia in the Diabetes RElated to Acute Pancreatitis and Its Mechanisms Study: From the Type 1 Diabetes in Acute Pancreatitis Consortium.

OBJECTIVES: The metabolic abnormalities that lead to diabetes mellitus (DM) after an episode of acute pancreatitis (AP) have not been extensively studied. This article describes the objectives, hypotheses, and methods of mechanistic studies of glucose metabolism that comprise secondary outcomes of the DREAM (Diabetes RElated to Acute pancreatitis and its Mechanisms) Study. METHODS: Three months after an index episode of AP, participants without preexisting DM will undergo baseline testing with an oral glucose tolerance test. Participants will be followed longitudinally in three subcohorts 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 ß-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 ß-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.

Recruitment and Retention Strategies for the Diabetes RElated to Acute Pancreatitis and Its Mechanisms Study: From the Type 1 Diabetes in Acute Pancreatitis Consortium.

ABSTRACT: Recruitment and retention of patients with acute pancreatitis (AP) in clinical studies can be challenging. While some obstacles are similar to other clinical conditions, some are unique to AP. Identifying potential barriers early and developing targeted solutions can help optimize recruitment and retention in AP studies. Such pre-emptive and detailed planning can help prospective, longitudinal studies focus on exocrine and endocrine complications of AP in accurately measuring outcomes. This article highlights the challenges in recruitment and retention strategies in AP studies and reviews available resources to create opportunities to address them. We describe the multifaceted approach used by the Recruitment and Retention Committee of the Type 1 Diabetes in Acute Pancreatitis Consortium, which builds upon earlier experiences to develop a recruitment and retention plan for the DREAM (Diabetes RElated to Acute pancreatitis and its Mechanisms) study.

IL-6-Driven pSTAT1 Response Is Linked to T Cell Features Implicated in Early Immune Dysregulation.

Elevated levels and enhanced sensing of the pro-inflammatory cytokine interleukin-6 (IL-6) are key features of many autoimmune and inflammatory diseases. To better understand how IL-6 signaling may influence human T cell fate, we investigated the relationships between levels of components of the IL-6R complex, pSTAT responses, and transcriptomic and translational changes in CD4+ and CD8+ T cell subsets from healthy individuals after exposure to IL-6. Our findings highlight the striking heterogeneity in mbIL-6R and gp130 expression and IL-6-driven pSTAT1/3 responses across T cell subsets. Increased mbIL-6R expression correlated with enhanced signaling via pSTAT1 with less impact on pSTAT3, most strikingly in CD4+ naïve T cells. Additionally, IL-6 rapidly induced expression of transcription factors and surface receptors expressed by T follicular helper cells and altered expression of markers of apoptosis. Importantly, many of the features associated with the level of mbIL-6R expression on T cells were recapitulated both in the setting of tocilizumab therapy and when comparing donor CD4+ T cells harboring the genetic variant, IL6R Asp358Ala (rs2228145), known to alter mbIL-6R expression on T cells. Collectively, these findings should be taken into account as we consider the role of IL-6 in disease pathogenesis and translating IL-6 biology into effective therapies for T cell-mediated autoimmune disease.

Citrullination of glucokinase is linked to autoimmune diabetes.

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.

Deep immune phenotyping reveals similarities between aging, Down syndrome, and 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 life span, 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-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 syndrome­relevant biology, also showed advanced immune aging in individuals with type 1 diabetes. Orthologous RNA sequencing­derived 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 that may have implications in other autoimmune diseases.

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.

Characterizing T cell responses to enzymatically modified beta cell neo-epitopes.

Introduction: Previous 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. Methods: To 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). Results: Consistent 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. Discussion: These 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.