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Type 2 diabetes (T2D) is associated with loss of transcription factors (TFs) from a subset of failing β-cells. Among these TFs is Pdx1, which controls the expression of numerous genes involved in maintaining β-cell function and identity. Pdx1 activity is modulated by transcriptional coregulators and has recently been shown, through an unbiased screen, to interact with the Chd4 ATPase subunit of the nucleosome remodeling and deacetylase complex. Chd4 contributes to the maintenance of cellular identity and functional status of numerous different cell types. Here, we demonstrated that Pdx1 dynamically interacts with Chd4 under physiological and stimulatory conditions within islet β-cells and established a fundamental role for Chd4 in regulating insulin secretion and modulating numerous Pdx1-bound genes in vitro, including the MafA TF, where we discovered Chd4 is bound to the MafA region 3 enhancer. Furthermore, we found that Pdx1:Chd4 interactions are significantly compromised in islet β-cells under metabolically induced stress in vivo and in human donor tissues with T2D. Our findings establish a fundamental role for Chd4 in regulating insulin secretion and modulating Pdx1-bound genes in vitro, and disruption of Pdx1:Chd4 interactions coincides with β-cell dysfunction associated with T2D.

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.

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.

Objective Metabolic zones were developed to characterize heterogeneity of individuals with islet autoantibodies. Research Design and Methods Baseline 2-hour oral glucose tolerance test (OGTT) data from 6,620 TrialNet Pathway to Prevention Study (TNPTP) autoantibody-positive participants (relatives of individuals with type 1 diabetes) were used to form 25 zones from 5 AUC glucose (AUCGLU) rows and 5 AUC C-peptide (AUCPEP) columns. Zone phenotypes were developed from demographic, metabolic, autoantibody, HLA, and risk data. Results As AUCGLU increased, changes of glucose and C-peptide response curves (GCRCs; from mean glucose and mean C-peptide values at 30,60,90,120 minutes) were similar within the 5 AUCPEP columns. Among the zones, 5-year risk for type 1 diabetes was highly correlated with IA-2A prevalence (r=0.96, p Conclusions Phenotypes of 25 zones formed from AUCGLU and AUCPEP were used to gain insights into type 1 diabetes heterogeneity. Zones were utilized to examine GCRC changes with increasing AUCGLU, associations between risk and autoantibody prevalence, the dependence of glucose as a predictor of risk according to C-peptide, and glucose heterogeneity from contributions of insulin secretion and insulin resistance.

The transcriptional activity of Pdx1 is modulated by a diverse array of coregulatory factors that govern chromatin accessibility, histone modifications, and nucleosome distribution. We previously identified the Chd4 subunit of the nucleosome remodeling and deacetylase complex as a Pdx1-interacting factor. To identify how loss of Chd4 impacts glucose homeostasis and gene expression programs in β-cells in vivo, we generated an inducible β-cell–specific Chd4 knockout mouse model. Removal of Chd4 from mature islet β-cells rendered mutant animals glucose intolerant, in part due to defects in insulin secretion. We observed an increased ratio of immature-to-mature insulin granules in Chd4-deficient β-cells that correlated with elevated levels of proinsulin both within isolated islets and from plasma following glucose stimulation in vivo. RNA sequencing and assay for transposase-accessible chromatin with sequencing showed that lineage-labeled Chd4-deficient β-cells have alterations in chromatin accessibility and altered expression of genes critical for β-cell function, including MafA, Slc2a2, Chga, and Chgb. Knockdown of CHD4 from a human β-cell line revealed similar defects in insulin secretion and alterations in several β-cell–enriched gene targets. These results illustrate how critical Chd4 activities are in controlling genes essential for maintaining β-cell function. Article Highlights Pdx1–Chd4 interactions were previously shown to be compromised in β-cells from human donors with type 2 diabetes. β-Cell–specific removal of Chd4 impairs insulin secretion and leads to glucose intolerance in mice. Expression of key β-cell functional genes and chromatin accessibility are compromised in Chd4-deficient β-cells. Chromatin remodeling activities enacted by Chd4 are essential for β-cell function under normal physiological conditions.

Background/Objective: Individuals with a family history of type 1 diabetes mellitus (T1D) are at increased genetic risk for T1D. Previous studies identified the presence of β-cell dysfunction before clinical onset and diagnosis of T1D. However, it is unclear if β-cell dysfunction predates islet autoimmunity in individuals at high genetic risk. Our objective was to test β-cell function in islet antibody negative adults who have a first-degree relative with T1D. We hypothesized that individuals at genetic risk for T1D would exhibit β-cell dysfunction even without detectable islet autoimmunity.Methods: We used ordinary one-way and Brown-Forsythe ANOVA to compare the repeated mixed meal tolerance test (MMTT) and hyperglycemic clamp glucose-stimulated β-cell response and function measures between three groups of individuals: normoglycemic adults without T1D family history age, sex, and BMI-matched islet antibody negative first-degree relatives of individuals with T1D, and islet antibody positive first-degree relatives of individuals with T1D.Results: Neither the MMTT first-phase insulin secretion measures (c-peptide0-15 minutes, c-peptide0-30 minutes, insulin0-15 minutes, insulin0-30 minutes), nor second-phase measures (c-peptide0-120 minutes, insulin0-120 minutes, and glucose0-120 minutes) showed a statistically significant difference between groups. The clamp acute c-peptide response to glucose, insulin sensitivity, c-peptide steady state, first-phase β-cell function, and second-phase β-cell function were similar between subject groups in both visits. Fasting proinsulin:c-peptide ratios, a biomarker of β-cell stress, were also similar between participant groups.Conclusion and Impact: Our data suggest that genetically at-risk autoantibody negative adult relatives of individuals with T1D do not demonstrate β-cell dysfunction compared to controls. Studies show that β-cell ER dysfunction preceding T1D onset is more striking in younger children. Thus, our findings may reflect the use of an adult study population. Alternatively, β-cell dysfunction in T1D may require initial autoimmune activation. This study will contribute to the growing understanding of risk factors contributing to T1D development.This project was funded, in part, with support from the Research Training Program in Diabetes and Obesity funded, in part by grant 3T32DK064466 from the National Institutes of Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Funding also provided by JDRF grant 2-SRA-2017-498-M-B.

Context Participants with stage 1 or 2 type 1 diabetes (T1D) qualify for prevention trials, but factors involved in screening for such trials are largely unknown. Objective To identify factors associated with screening for T1D prevention trials. Methods This study included TrialNet Pathway to Prevention participants who were eligible for a prevention trial: oral insulin (TN-07, TN-20), teplizumab (TN-10), abatacept (TN-18), and oral hydroxychloroquine (TN-22). Univariate and multivariate logistic regression models were used to examine participant, site, and study factors at the time of prevention trial accrual. Results Screening rates for trials were: 50% for TN-07 (584 screened/1172 eligible), 9% for TN-10 (106/1249), 24% for TN-18 (313/1285), 17% for TN-20 (113/667), and 28% for TN-22 (371/1336). Younger age and male sex were associated with higher screening rates for prevention trials overall and for oral therapies. Participants with an offspring with T1D showed lower rates of screening for all trials and oral drug trials compared with participants with other first-degree relatives as probands. Site factors, including larger monitoring volume and US site vs international site, were associated with higher prevention trial screening rates. Conclusions Clear differences exist between participants who screen for prevention trials and those who do not screen and between the research sites involved in prevention trial screening. Participant age, sex, and relationship to proband are significantly associated with prevention trial screening in addition to key site factors. Identifying these factors can facilitate strategic recruitment planning to support rapid and successful enrollment into prevention trials.

OBJECTIVE We assessed whether Index60, a composite measure of fasting C-peptide, 60-min C-peptide, and 60-min glucose, could improve the metabolic staging of type 1 diabetes for progression to clinical disease (stage 3) among autoantibody-positive (Ab+) individuals with normal 2-h glucose values ( RESEARCH DESIGN AND METHODS We analyzed 3,058 Type 1 Diabetes TrialNet Pathway to Prevention participants with 2-h glucose RESULTS HI-IND60 and HI-BOTH were younger, with greater frequency of more than two Ab+, and lower C-peptide levels, than either HI-2HGLU or LO-BOTH (all P < 0.001). The cumulative incidence for stage 3 was greater for HI-IND60 and HI-BOTH than for either HI-2HGLU or LO-BOTH (all P < 0.001). Those with Index60 values above the median were younger and had higher frequency of two or more Ab+ (P < 0.001) and DR3-DQ2/DR4-DQ8 prevalence (P < 0.001) and lower area under the curve (AUC) C-peptide levels (P < 0.001) than those below. Those above the 2-h glucose median had higher AUC C-peptide levels (P < 0.001), but otherwise did not differ from those below. CONCLUSIONS Index60 identifies individuals with characteristics of type 1 diabetes at appreciable risk for progression who would otherwise be missed by 2-h glucose staging criteria.

Extracellular vesicles (EVs) play important roles in cell-to-cell communication and are potential biomarkers as they carry markers of their derived tissues and disease signatures. However, obtaining pure EV preparations from biofluids is challenging due to contaminants with similar physicochemical properties. Here, we performed a meta-analysis of plasma EV proteomics data deposited in public repositories to refine the protein composition of EVs and investigate potential roles in type 1 diabetes development. With the concept that each purification method yields different proportions of distinct contaminants, we grouped proteins into clusters based on their abundance profiles. This allowed us to separate clusters with classical EV markers, such as CD9, CD40, C63 and CD81, from clusters of well-known contaminants, such as serum albumin, apolipoproteins and components of the complement and coagulation pathways. Two clusters containing a total of 1720 proteins combined were enriched with EV markers and depleted in common contaminants; therefore, they were considered to contain bona fide EV components. As possible origins of plasma EVs, these clusters had markers of tissues such as spleen, liver, brain, lungs, pancreas, and blood/immune cells. These clusters were also enriched in cell surface markers CD antigens, and proteins from cell-to-cell communication and signaling pathways, such as chemokine signaling and antigen presentation. We also show that the EV component and type 1 diabetes biomarker, platelet basic protein (PPBP/CXCL7) regulates apoptosis in both beta and macrophage cell lines. Overall, our meta-analysis refined the composition of plasma EVs, reinforcing a primary function as messengers for cell-to-cell communication and signaling. Furthermore, this analysis identifies optimal avenues to target EVs for development of disease biomarkers.

OBJECTIVE We studied longitudinal differences between progressors and nonprogressors to type 1 diabetes with similar and substantial baseline risk. RESEARCH DESIGN AND METHODS Changes in 2-h oral glucose tolerance test indices were used to examine variability in diabetes progression in the Diabetes Prevention Trial–Type 1 (DPT-1) study (n = 246) and Type 1 Diabetes TrialNet Pathway to Prevention study (TNPTP) (n = 503) among autoantibody (Ab)+ children (aged RESULTS Longitudinal analyses revealed annualized area under the curve (AUC) of C-peptide increases in nonprogressors versus decreases in progressors (P ≤ 0.026 for DPT-1 and TNPTP). Vector indices for AUC glucose and AUC C-peptide changes (on a two-dimensional grid) also differed significantly (P < 0.001). Despite marked baseline metabolic impairment of nonprogressors, changes in AUC C-peptide, AUC glucose, AUC C-peptide–to–AUC glucose ratio (AUC ratio), and Index60 did not differ from Ab− relatives during follow-up. Divergence between nonprogressors and progressors occurred by 6 months from baseline in both cohorts (AUC glucose, P ≤ 0.007; AUC ratio, P ≤ 0.034; Index60, P < 0.001; vector indices of change, P < 0.001). Differences in 6-month change were positively associated with greater diabetes risk (respectively, P < 0.001, P ≤ 0.019, P < 0.001, and P < 0.001) in DPT-1 and TNPTP, except AUC ratio, which was inversely associated with risk (P < 0.001). CONCLUSIONS Novel findings show that even with similarly abnormal baseline risk, progressors had appreciably more metabolic impairment than nonprogressors within 6 months and that the measures showing impairment were predictive of type 1 diabetes. Longitudinal metabolic patterns did not differ between nonprogressors and Ab− relatives, suggesting persistent β-cell responsiveness in nonprogressors.

Data suggest that β cell exosomes, extracellular vesicles released by exocytosis of multivesicular endosomes (MVEs) , may act as paracrine effectors in islet health. However, mechanisms linking β cell stress to changes in exosomes and whether activation of these pathways can impact diabetes remain less explored. In other cells, the enzyme neutral spingomyelinase 2 (nSMase2) induces ceramide dependent MVE vesicle formation and release of ceramide-enriched exosomes. We hypothesized that β cell inflammatory stress engages ceramide-dependent exosomal formation pathways, and that ceramide-enriched exosomes could then impact surrounding β cells. To test this we treated INS-1 β cells with 24 hrs of 5 ng/mL of IL1β. nSMase 2 and ceramide expression were quantified with immunoblot and/or flow cytometry and exosomes were isolated using a tetraspanin bead-based pulldown. IL1β increased β cell nSMase2 expression and ceramide expression in concert. Direct nSMase2 activation with 24 hrs of 5-ng/mL Caffeic acid phenethyl ester (CAPE) also increased β cell ceramide staining. IL1β and CAPE treatments also yielded increased ceramide expression on β cell exosomes. Human islets exhibited similar increases in cellular nSMase2 and ceramide staining after 24-hr cytokine mix treatment (5ng/mL IL1β, 10ng/mL TNFα, and 100ng/mL IFNγ) . To test the potential for transfer of β cell exosomes to surrounding cells, we generated INS-1 cells with GFP tagged CD9 (exosome transmembrane protein) , which release GFP labeled exosomes. Flow cytometry staining in wild-type INS-1 cells after 24-hr transwell coculture with CD9-GFP cells showed that cocultured wild-type cells exhibited increased green fluorescence, suggesting transfer of CD9-GFP exosomes. Our findings suggest that nSMase2 activity may regulate β cell exosome subpopulations under conditions of inflammatory stress. Future work will interrogate impacts on exosome cargo and physiologic impacts of transfer on recipient cells. Disclosure J.Xu: None. E.K.Sims: Other Relationship; Medscape, Patent. Funding 5 R01DK121929

Even after stratification based on established risk factors, the progression to T1D is variable. Thus, we aimed to examine differences in metabolic patterns of change between NP and P to T1D, and identify non-metabolic factors contributing to the differences. Specifically, we analyzed OGTT and autoantibody (Aab) data from children In conclusion, when NP and P have a similar degree of metabolic abnormality, IA-2A titers are greater in P. Moreover, as AUC ratio declines in P and improves in NP, IA-2A titers increase more in P than in NP. These findings suggest that IA-2A is a sensitive indicator of active β-cell pathology. Disclosure E.K.Sims: Other Relationship; Medscape, Patent. D.D.Cuthbertson: None. L.M.Jacobsen: None. H.M.Ismail: n/a. B.M.Nathan: None. M.J.Redondo: Advisory Panel; Provention Bio, Inc. J.Sosenko: None.

C-peptide area under the curve (AUC) at ≥1 year, a standard endpoint of recent-onset T1D clinical trials, is derived from a 120-minute mixed meal tolerance test (MMTT) . We analyzed whether composite glucose and C-peptide endpoints, useful in post hoc analyses of prevention trials, could detect treatment effects as early as 3 months between the combined treated and placebo groups from 3 TrialNet recent-onset T1D trials that met their primary endpoint. Comparisons were made between treated and placebo groups after adjustments for age, sex, and BMI Z-score using AUC C-peptide (standard measure) , AUC C-peptide/AUC glucose (AUC ratio) , and a new measure, the centroid ratio. Centroids, geometric central points of shapes, were derived from MMTT shapes formed from mean glucose and C-peptide values at 30, 60, 90, and 120 minutes. The centroid ratio is the C-peptide coordinate/glucose coordinate of the centroid. A treatment effect at 3 months was evident for centroid and AUC ratios (p In conclusion, composite glucose and C-peptide endpoints appear to identify early treatment efficacy and should be considered in future new-onset pilot studies and trials. Disclosure L.M.Jacobsen: None. A.Pugliese: Advisory Panel; Provention Bio, Inc., Consultant; Quell Tx. P.Gottlieb: Advisory Panel; Janssen Research & Development, LLC, ViaCyte, Inc., Other Relationship; IM Therapeutics, Research Support; Caladrius Biosciences, Inc., Immune Tolerance Network, National Institute of Diabetes and Digestive and Kidney Diseases, Novo Nordisk, Precigen, Inc., Tolerion, Inc. J.Sosenko: None. D.D.Cuthbertson: None. M.J.Haller: Advisory Panel; SAB Biotherapeutics , Consultant; MannKind Corporation, Sanofi. H.M.Ismail: n/a. E.K.Sims: Other Relationship; Medscape, Patent. S.E.Gitelman: Advisory Panel; Abata Therapeutics, Avotres Inc., Biolojic Design, Ltd., Provention Bio, Inc., Rubius, SAB Biotherapeutics, Inc., Tolerion, Inc. D.K.Wherrett: n/a. A.Moran: Advisory Panel; Dompé, Other Relationship; Novo Nordisk, Research Support; Abbott Diabetes, Provention Bio, Inc. M.A.Atkinson: None.

The link between COVID-19 infection and diabetes has been explored in several studies since the start of the pandemic, with associations between comorbid diabetes and poorer prognosis in patients infected with the virus and reports of diabetic ketoacidosis occurring with COVID-19 infection. As such, significant interest has been generated surrounding mechanisms by which the virus may exert effects on the pancreatic β cells. In this review, we consider possible routes by which SARS-CoV-2 may impact β cells. Specifically, we outline data that either support or argue against the idea of direct infection and injury of β cells by SARS-CoV-2. We also discuss β cell damage due to a “bystander” effect in which infection with the virus leads to damage to surrounding tissues that are essential for β cell survival and function, such as the pancreatic microvasculature and exocrine tissue. Studies elucidating the provocation of a cytokine storm following COVID-19 infection and potential impacts of systemic inflammation and increases in insulin resistance on β cells are also reviewed. Finally, we summarize the existing clinical data surrounding diabetes incidence since the start of the COVID-19 pandemic.

Purpose of review Emerging data have suggested that β-cell dysfunction may exacerbate the development and progression of type 1 diabetes (T1D). In this review, we highlight clinical and preclinical studies suggesting a role for β-cell dysfunction during the evolution of T1D and suggest agents that may promote β-cell health in T1D. Recent findings Metabolic abnormalities exist years before development of hyperglycemia and exhibit a reproducible pattern reflecting progressive deterioration of β-cell function and increases in β-cell stress and death. Preclinical studies indicate that T1D may be prevented by modification of pathways impacting intrinsic β-cell stress and antigen presentation. Recent findings suggest that differences in metabolic phenotypes and β-cell stress may reflect differing endotypes of T1D. Multiple pathways representing potential drug targets have been identified, but most remain to be tested in human populations with preclinical disease. Summary This cumulative body of work shows clear evidence that β-cell stress, dysfunction, and death are harbingers of impending T1D and likely contribute to progression of disease and insulin deficiency. Treatment with agents targeting β-cell health could augment interventions with immunomodulatory therapies but will need to be tested in intervention studies with endpoints carefully designed to capture changes in β-cell function and health.

Most screening programs to identify individuals at risk for type 1 diabetes have targeted relatives of people living with the disease to improve yield and feasibility. However, ~90% of those who develop type 1 diabetes do not have a family history. Recent successes in disease modifying therapies to impact the course of early-stage disease have ignited the consideration of the need for and feasibility of population screening to identify those at increased risk. Existing population screening programs rely on genetic or autoantibody (AA) screening, and these have yielded significant information about disease progression and approaches for timing for screening in clinical practice. At the March 2021 Type 1 Diabetes TrialNet Steering Committee meeting, a session was held in which ongoing efforts for screening in the general population were discussed. This report reviews the background of these efforts and the details of those programs. Additionally, we present hurdles that need to be addressed for successful implementation of population screening and provide initial recommendations for individuals with positive screens so that standardized guidelines for monitoring and follow-up can be established.

Endpoints that provide an early identification of treatment effects are needed to implement type 1 diabetes prevention trials more efficiently. To this end, we assessed whether metabolic endpoints can be used to detect a teplizumab effect on rapid β-cell decline within 3 months after treatment in high-risk individuals in the TrialNet teplizumab trial. Glucose and C-peptide response curves (GCRCs) were constructed by plotting mean glucose and C-peptide values from 2-hour oral glucose tolerance tests on a 2-dimensional grid. Groups were compared visually for changes in GCRC shape and movement. GCRC changes reflected marked metabolic deterioration in the placebo group within 3 months of randomization. By 6 months, GCRCs resembled typical GCRCs at diagnosis. In contrast, GCRC changes in the teplizumab group suggested metabolic improvement. Quantitative comparisons, including two novel metabolic endpoints that indicate GCRC changes, the Within Quadrant Endpoint (WQE) and the Ordinal Directional Endpoint (ODE), were consistent with visual impressions of an appreciable treatment effect at 3 and 6-month timepoints. In conclusion, an analytic approach combining visual evidence with novel endpoints, demonstrated that Teplizumab delays rapid metabolic decline, and improves the metabolic state within 3 months after treatment; this effect extends for at least 6 months.

Background: The TrialNet Immune Effects of Oral Insulin (OI) in Relatives at Risk for Type 1 Diabetes Mellitus (TN20) study (2-arm, randomized, open-label clinical trial for Stages 1-2 T1D ) observed, in a subset of participants (pts), a decline in insulin autoantibody (Ab) titers associated with an increase in islet-specific CD4+ T cell frequencies in Arm A (OI 67.5 mg/d) but not Arm B (500 mg/2 wks). Here, we compared the 2 arms to assess whether metabolic effects also occur in the 67.5 mg/d treatment arm. Methods: High-risk Ab+ pts (mean age 6.4±3.1 yrs; range 3-16 yrs) were randomized, treated for 6 months, and assessed at 0, 6 and 12 months. We compared the 2 arms for changes of mean glucose and C-peptide response curves (GCRCs) during OGTTs in pts with Diabetes Prevention Trial Risk Score (DPTRS) ≥6.75 (a subset where a metabolic effect of OI has been shown). Results: GCRC shapes and centroids (central point of GCRC shape) in each arm are shown in the Figure. The C-peptide/glucose ratio of centroid coordinates changed little in Arm A but decreased in Arm B (1.03±8.71 vs. -4.39±7.01; p Conclusions: The better metabolic outcome of 67.5 mg/d of OI than 500 mg/2 wks is consistent with the prior finding that immunologic change is associated with 67.5 mg/d, suggesting a linkage of immune and metabolic effects. Disclosure M. J. Redondo: Advisory Panel; Self; Provention Bio, Inc. A. Lernmark: None. P. Gottlieb: Advisory Panel; Self; Janssen Research & Development, LLC, Tolerion, Inc., Viacyte, Inc., Other Relationship; Self; ImmunoMolecular Therapeutics, Inc., Research Support; Self; Caladrius Biosciences, Inc., Immune Tolerance Network, Mercia Pharma Inc., National Institute of Diabetes and Digestive and Kidney Diseases, Precigen, Inc., Tolerion, Inc. J. Sosenko: None. E. K. Sims: None. D. D. Cuthbertson: None. E. A. James: Consultant; Self; Provention Bio, Inc., Research Support; Self; Bristol-Myers Squibb Company, Janssen Pharmaceuticals, Inc., Novartis AG, Sanofi. S. Long: None. W. Kwok: None. L. Yu: None. A. W. Michels: Stock/Shareholder; Self; IM Therapeutics. Funding National Institute of Diabetes and Digestive and Kidney Diseases; National Institute of Allergy and Infectious Diseases; Eunice Kennedy Shriver National Institute of Child Health and Human Development; JDRF

The spectrum of nonalcoholic liver disease (NAFLD) ranges from simple steatosis to steatohepatitis with the latter having the potential to irreversibly progress to cirrhosis. Compared with the general population, NAFLD is more frequently seen in patients with type 2 diabetes (T2D), and conversely, NAFLD is associated with increased incidence of T2D. Existing rodent models of NAFLD focus narrowly on certain stages of liver damage and insufficiently encompass all metabolic changes, limiting their utility. The aims of this study were to develop a new model of NAFLD in young zebrafish and use it to probe the associations between liver inflammation and pancreatic islet function. We examined hepatopancreatic inflammation under three conditions: (1) in a zebrafish line (fabp10-CETI-PIC3) in which liver-specific expression of pro-inflammatory cytokines IL-1β, TNFα, and IFN-γ was induced by doxycycline treatment (M1); (2) in wild-type zebrafish fed a high-fat diet (M2); and (3) in a combination of these models (M3). All three conditions showed increased expression of inflammatory cytokines compared to Tg(fabp10:cre) control larvae, and when compared to controls, all three showed increased macrophage infiltration in the liver. Strikingly, staining with CellRox Deep Red to assess reactive oxygen species (ROS)-mediated stress in the liver revealed a 2-fold increase in the M3 combination model, but not in either M1 or M2. Further, although all models showed hyperglycemia, decreased insulin transcription without β cell death, and ROS accumulation in the pancreas, only the M3 condition demonstrated a significant increase in macrophage infiltration of the pancreatic islets as compared to controls. In sum, our novel zebrafish model of liver steatosis and steatohepatitis is a promising model in which to study the intricate associations between NAFLD and T2D, and may serve as an amenable platform for screening novel pharmaceutical interventions. Disclosure S. Ibrahim: None. I. Haider: None. A. Kulkarni: None. I. Doycheva: None. R. G. Mirmira: Advisory Panel; Self; Hibercell Inc., Sigilon Therapeutics, Inc., Veralox Therapeutics, Employee; Spouse/Partner; Beta Bionics, Inc. E. K. Sims: None. R. Anderson: None.

The TrialNet OI prevention trial (TN07) with T1D as an endpoint showed no effect. However, in a smaller trial run in parallel with TN07 (termed secondary stratum 1), in which all participants had low first-phase insulin release, a statistically significant delay in T1D onset was found. Since trials with T1D as an endpoint take years to complete, we aimed to determine if combination C-peptide and glucose markers could identify a therapeutic benefit after 12 months of OI in this high-risk population. All participants were at-risk relatives with multiple autoantibodies including mIAA and normal glucose tolerance (n=40 with full data). The Figure shows changes in glucose and C-peptide response curves and their centroids (central points). Glucose rose and C-peptide declined in the placebo group compared to a minimal glucose rise with an increase of C-peptide in the OI group. Change from baseline to 1 year in the centroid ratio (C-peptide/glucose) differed significantly between groups (p=0.037 after adjustments for age, BMI, and baseline C-peptide and glucose). The AUC C-peptide/AUC glucose ratio and Index60 did not differ (both p=0.108). In conclusion, the findings support a positive effect of OI on combined glucose and C-peptide endpoints in high-risk individuals. These measures appear to detect differences in a shorter time than the standard T1D endpoint. Disclosure L. M. Jacobsen: None. M. A. Atkinson: None. J. Krischer: None. D. Schatz: Advisory Panel; Self; Abbott, Medtronic. J. Sosenko: None. D. D. Cuthbertson: None. E. K. Sims: None. H. M. Ismail: None. L. Dimeglio: Advisory Panel; Self; MannKind Corporation. T. M. Triolo: None. M. J. Redondo: Advisory Panel; Self; Provention Bio, Inc. M. Lundgren: None. P. Gottlieb: Advisory Panel; Self; Janssen Research & Development, LLC, Tolerion, Inc., Viacyte, Inc., Other Relationship; Self; ImmunoMolecular Therapeutics, Inc., Research Support; Self; Caladrius Biosciences, Inc., Immune Tolerance Network, Mercia Pharma Inc., National Institute of Diabetes and Digestive and Kidney Diseases, Precigen, Inc., Tolerion, Inc.

T1D staging is used for eligibility criteria in T1D prevention trials, but recent findings suggest that using glucose alone, without measures of insulin secretion, to define T1D progression may group together highly heterogeneous individuals. Thus, utilizing the large TrialNet Pathway to Prevention cohort, we aimed to examine heterogeneity for T1D-related characteristics, including risk for T1D, among 1,325 Ab+ individuals who upon OGTT screening were in the highest AUC glucose quintile (≥151 mg/dL) within the nondiabetic range. Within that highest AUC glucose quintile, we compared T1D characteristics of participants in the highest (≥8.03 ng/mL, n=378) vs. the lowest ( In conclusion, despite similar AUC glucose values, C-peptide levels identified individuals with greatly different characteristics, including a near 3-fold difference in 5-yr T1D risk of those in lowest vs. highest C-peptide quintiles. Using glucose without C-peptide to define T1D stages results in pronounced heterogeneity, which can lower the ability to demonstrate efficacy in T1D prevention trials. Disclosure M. J. Redondo: Advisory Panel; Self; Provention Bio, Inc. J. Sosenko: None. D. D. Cuthbertson: None. B. M. Nathan: None. E. K. Sims: None. M. Tosur: Advisory Panel; Self; Provention Bio, Inc. I. Libman: Advisory Panel; Self; Novo Nordisk. J. S. Skyler: Advisory Panel; Self; Abvance Therapeutics, ADOCIA, Oramed Pharmaceuticals, Inc., Orgenesis Inc., Tolerion, Inc., Viacyte, Inc., Board Member; Self; Applied Therapeutics, Dexcom, Inc., Intarcia Therapeutics, Inc., Consultant; Self; AstraZeneca, Avotres Inc., Bayer AG, IM Therapeutics, Novo Nordisk, Precigen, Inc., Provention Bio, Inc., Sanofi, Stock/Shareholder; Self; Applied Therapeutics, Dexcom, Inc. C. Evans-molina: Advisory Panel; Self; Provention Bio, Inc., Consultant; Self; Dompe, Other Relationship; Self; Bristol-Myers Squibb Company, Nimbus Pharmaceuticals, Pfizer Inc. M. A. Atkinson: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases; National Institute of Allergy and Infectious Diseases; Eunice Kennedy Shriver National Institute of Child Health and Human Development; JDRF

The value of a pre-diagnostic surrogate endpoint for T1D prevention trials is based on detection of efficacy and association with T1D. Thus, among multiple antibody+, dysglycemic individuals with baseline and 6-month OGTTs, we assessed metabolic endpoints for: 1) detecting a delay in metabolic decline from baseline to 6 months between placebo and teplizumab groups in the TrialNet teplizumab T1D prevention trial (TN 10), and 2) predicting T1D by metabolic change from baseline to 6 months in the TrialNet Pathway to Prevention study (TN01). The Table shows that the 6-month change in C-peptide (Cpep) measures (AUC and 30-0 minute) differed significantly between placebo and teplizumab groups, but not the change in glucose AUC. However, prediction of T1D, indicated by receiver operating curve AUC (ROCAUC), tended to be more accurate for 6-month change of glucose AUC than for Cpep changes. Although detection of a teplizumab effect by Cpep measures was comparable to that of combined measures (Index60 and Cpep AUC/glucose AUC), the latter were more accurate predictors. In conclusion, among metabolic endpoints there was discordance between detection of a teplizumab effect and prediction accuracy of T1D. However, such discordance suggests that metabolic endpoints provide more insight into understanding effects of teplizumab and other preventive treatments than the T1D endpoint alone. Disclosure E. K. Sims: None. D. D. Cuthbertson: None. L. M. Jacobsen: None. K. C. Herold: Consultant; Self; Provention Bio, Inc., Viela Bio, Consultant; Spouse/Partner; Provention Bio, Inc. J. Sosenko: None.

OBJECTIVE To better understand potential facilitators of individual engagement in type 1 diabetes natural history and prevention studies through analysis of enrollment data in the TrialNet Pathway to Prevention (PTP) study. RESEARCH DESIGN AND METHODS We used multivariable logistic regression models to examine continued engagement of eligible participants at two time points: 1) the return visit after screening to confirm an initial autoantibody-positive (Ab+) test result and 2) the initial oral glucose tolerance test (OGTT) for enrollment into the monitoring protocol. RESULTS Of 5,387 subjects who screened positive for a single autoantibody (Ab), 4,204 (78%) returned for confirmatory Ab testing. Younger age was associated with increased odds of returning for Ab confirmation (age 18 years: odds ratio [OR] 2.12, P < 0.0001). Racial and ethnic minorities were less likely to return for confirmation, particularly nonwhite non-Hispanic (OR 0.50, P < 0.0001) and Hispanic (OR 0.69, P = 0.0001) relative to non-Hispanic white subjects. Of 8,234 subjects, 5,442 (66%) were identified as eligible to be enrolled in PTP OGTT monitoring. Here, younger age and identification as multiple Ab+ were associated with increased odds of returning for OGTT monitoring (age 18 years: OR 1.43, P < 0.0001; multiple Ab+: OR 1.36, P < 0.0001). Parents were less likely to enroll into monitoring than other relatives (OR 0.78, P = 0.004). Site-specific factors, including site volume and U.S. site versus international site, were also associated with differences in rates of return for Ab+ confirmation and enrollment into monitoring. CONCLUSIONS These data confirm clear differences between successfully enrolled populations and those lost to follow-up, which can serve to identify strategies to increase ongoing participation.

Histological analysis of donor pancreases coupled with measurement of serum C-peptide in clinical cohorts has challenged the idea that all beta cells are eventually destroyed in type 1 diabetes. These findings have raised a number of questions regarding how the remaining beta cells have escaped immune destruction, whether pools of 'sleeping' or dysfunctional beta cells could be rejuvenated and whether there is potential for new growth of beta cells. In this Review, we describe histological and in vivo evidence of persistent beta cells in type 1 diabetes and discuss the limitations of current methods to distinguish underlying beta cell mass in comparison with beta cell function. We highlight that evidence for new beta cell growth in humans many years from diagnosis is limited, and that this growth may be very minimal if at all present. We review recent contributions to the debate around beta cell abnormalities contributing to the pathogenesis of type 1 diabetes. We also discuss evidence for restoration of beta cell function, as opposed to mass, in recent-onset type 1 diabetes, but highlight the absence of data supporting functional recovery in the setting of long-duration diabetes. Finally, future areas of research are suggested to help resolve the source and phenotype of residual beta cells that persist in some, but not all, people with type 1 diabetes.

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.

We analyzed the effects of a single 14-day course of teplizumab treatment on metabolic function and immune cells among participants in a previously reported randomized controlled trial of nondiabetic relatives at high risk for type 1 diabetes (T1D). In an extended follow-up (923-day median) of a previous report of teplizumab treatment, we found that the median times to diagnosis were 59.6 and 27.1 months for teplizumab- and placebo-treated participants, respectively (HR = 0.457, P = 0.01). Fifty percent of teplizumab-treated but only 22% of the placebo-treated remained diabetes-free. Glucose tolerance, C-peptide area under the curve (AUC), and insulin secretory rates were calculated, and relationships to T cell subsets and function were analyzed. Teplizumab treatment improved beta cell function, reflected by average on-study C-peptide AUC (1.94 versus 1.72 pmol/ml; P = 0.006). Drug treatment reversed a decline in insulin secretion before enrollment, followed by stabilization of the declining C-peptide AUC seen with placebo treatment. Proinsulin:C-peptide ratios after drug treatment were similar between the treatment groups. The changes in C-peptide with teplizumab treatment were associated with increases in partially exhausted memory KLRG1+TIGIT+CD8+ T cells (r = 0.44, P = 0.014) that showed reduced secretion of IFNγ and TNFα. A single course of teplizumab had lasting effects on delay of T1D diagnosis and improved beta cell function in high-risk individuals. Changes in CD8+ T cell subsets indicated that partially exhausted effector cells were associated with clinical response. Thus, this trial showed improvement in metabolic responses and delay of diabetes with immune therapy.

Background/Objective: Diabetic ketoacidosis (DKA) is a life-threatening complication of type 1 diabetes (T1D) resulting from ketone body production and metabolic acidosis occurring due to insulin deficiency. We sought to define the occurrence of DKA amongst pediatric patients presenting with new-onset T1D in Indiana and to determine whether patterns of DKA were affected by the COVID-19 pandemic. Methods: This was a retrospective chart review for patients 0.05). Of the 94 patients, 49% met criteria for DKA; 79% of cases were classified as severe and 21% as mild. More males were diagnosed with DKA in both 2019 and 2020 (61% of DKA cases). Non-Hispanic whites comprised 75% of all new onset T1D patients and no differences in race or ethnicity were present amongst those presenting in DKA. Conclusion: DKA was present in nearly half of all new onset pediatric T1D cases in Indiana in 2019 and 2020. There was no observed impact of the COVID-19 pandemic on T1D or DKA. Impact and Implications: DKA is common amongst pediatric patients with new onset T1D in Indiana. Prompt recognition of symptoms is needed to prevent this life-threatening complication of T1D.

Analysis of data from clinical cohorts, and more recently from human pancreatic tissue, indicates that reduced prohormone processing is an early and persistent finding in type 1 diabetes. In this article, we review the current state of knowledge regarding alterations in islet prohormone expression and processing in type 1 diabetes and consider the clinical impact of these findings. Lingering questions, including pathologic etiologies and consequences of altered prohormone expression and secretion in type 1 diabetes, and the natural history of circulating prohormone production in health and disease, are considered. Finally, key next steps required to move forward in this area are outlined, including longitudinal testing of relevant clinical populations, studies that probe the genetics of altered prohormone processing, the need for combined functional and histologic testing of human pancreatic tissues, continued interrogation of the intersection between prohormone processing and autoimmunity, and optimal approaches for analysis. Successful resolution of these questions may offer the potential to use altered prohormone processing as a biomarker to inform therapeutic strategies aimed at personalized intervention during the natural history of type 1 diabetes and as a pathogenic anchor for identification of potential disease-specific endotypes.

We demonstrated that a 2-week course of teplizumab (an Fc receptor-nonbinding anti-CD3 monoclonal antibody) delayed T1D progression by a median of 24 months in high risk relatives of patients with T1D (76 multiple islet autoantibody positive dysglycemic relatives; 912 day median follow-up). Over the study 72% of the placebo-treated and 43% of the teplizumab-treated participants were diagnosed with T1D. We hypothesized that teplizumab treatment would also result in a secondary outcome of improved C-peptide responses to oral glucose tolerance tests (OGTT) compared to placebo. The C-peptide, 1 hr insulin secretory rate (early ISR), and glucose area under the curve (AUC) means were calculated for each study timepoint. Results were modeled using ANCOVA, regressing on treatment group, age and the baseline value of the dependent variable. Teplizumab treatment was associated with a greater on-study C-peptide AUC (teplizumab vs. placebo adjusted means: 1.94 vs. 1.73 nmol/L; p=0.009). For both groups, C-peptide AUC mean slopes over a mean of 7.9 months preceding study entry were similar and significantly less than zero (declining; p=0.03). In the placebo group, this decline continued over the 6 months after study entry. By contrast, the teplizumab-treated group showed an increased C-peptide AUC over this period (p=0.003 relative to study entry). Insulin secretion during the 1st hr of the OGTT also declined in participants treated with placebo, but increased in those treated with teplizumab at 6 months (p=0.007). Increases in C-peptide AUC were correlated with increases in partially exhausted KLRG1+TIGIT+ CD8+ T cells (r=0.403; p=0.018). Although rates of diabetes were reduced in teplizumab-treated participants, OGTTs showed persistent dysglycemia. In conclusion, we found declines in C-peptide responses to OGTTs in high risk individuals prior to study treatment that were abrogated in the 6 month period after immunomodulation with teplizumab. Disclosure E.K. Sims: None. B.N. Bundy: None. K.D. Stier: None. E. Serti: None. N. Lim: None. G.T. Nepom: None. C. Evans-Molina: Consultant; Self; Bristol-Myers Squibb. K.C. Herold: Consultant; Self; Provention Bio, Inc. Funding National Institutes of Health; National Institute of Diabetes and Digestive and Kidney Diseases; National Institute of Allergy and Infectious Diseases; Eunice Kennedy Shriver National Institute of Child Health and Human Development; JDRF

We sought to determine whether a measure combining changes in C-peptide and glucose could show efficacy 3 months after teplizumab treatment among multiple islet autoantibody+ dysglycemic individuals (n=44, age 19.2± 11.9 yrs on teplizumab and n=32, age 17.5± 11.1 yrs on placebo) in the recent TrialNet teplizumab prevention trial (teplizumab delayed T1D onset). In the 2D analysis assessing changes in glucose and C-peptide below (Figure), mean glucose and C-peptide from 30 to 120 minutes are plotted from baseline and 3-month OGTTs. For each OGTT, centroids (central point of OGTT shape) are connected by vectors, showing opposite directionality from baseline to 3 months between groups. Since AUC C-peptide/AUC glucose (AUC Ratio) correlates highly with centroid C-peptide/centroid glucose (r=0.99), to quantify the differences in directionality, we compared AUC Ratio (x1,000; adjusted for baseline) change from baseline to 3 months. The teplizumab group showed a positive change in AUC Ratio: 1.5±2.9 vs. a negative change in placebo: - 0.78±2.7; p=0.001). This difference was sustained after 6 months of treatment (p=0.004). In summary, a 2D analysis of glucose and C-peptide change provided visual and quantitative evidence of an early treatment effect. As a centroid correlate, the AUC Ratio can be a useful endpoint for performing shorter prevention trials. Disclosure E.K. Sims: None. M.V. Warnock: None. K.C. Herold: Consultant; Self; Provention Bio, Inc. J. Sosenko: None. Funding National Institutes of Health; National Institute of Diabetes and Digestive and Kidney Diseases; National Institute of Allergy and Infectious Diseases; Eunice Kennedy Shriver National Institute of Child Health and Human Development; JDRF

Individuals both at risk for and newly diagnosed with type 1 diabetes (T1D) have a reduced pancreas volume as assessed by MRI. Furthermore, multiparametric quantitative MRI techniques have detected focal alterations in the T1D pancreas. However, performing quantitative MRI techniques in multi-site trials is challenging due to differences in MRI hardware and software. To determine if quantitative MRI measurements in T1D can be performed at different institutions, 5 academic centers (see author affiliation) have established the Multicenter Assessment of the Pancreas in T1D (MAP-T1D) group to develop harmonized MRI acquisition and image processing protocols. We established and implemented an MRI protocol for pancreas imaging on both Siemens and Philips MRI platforms at 5 imaging centers, consisting of T1- and T2-weighted anatomical images, diffusion-weighted MRI, magnetization transfer MRI, and longitudinal relaxation (T1) mapping. Imaging phantoms assessing volume, diffusion, magnetization transfer ratio, and T1 were created and imaged at each institution to test the reproducibility of multiparametric MRI. Measurement of phantom volume yielded an average error of 1.5% from the true volume. The apparent diffusion coefficient, magnetization transfer ratio, and T1 phantoms had coefficients of variation of 6.0%, 10.0%, and 9.5%, respectively, between sites. To assess the reproducibility of human MRI scanning, we recruited 5 healthy subjects to travel to 4 sites for imaging using the standardized MRI protocol. Pancreas volume measured at multiple sites had an average coefficient of variation between scans of 8.3% with a maximum difference of 17% (n = 9 MRIs). This study demonstrates the feasibility of quantitative pancreas MRI across multiple sites. Standardization of pancreas MRI acquisition and processing will accelerate integration of pancreas volume and other quantitative MRI measurements in future multi-center clinical trials of T1D. Disclosure J. Virostko: None. J.M. Williams: None. M.A. Hilmes: None. L. Du: None. H. Kang: None. W.E. Russell: None. T.M. Triolo: None. L.H. Philipson: None. E.K. Sims: None. C. Evans-Molina: Consultant; Self; Bristol-Myers Squibb. H.E. Thomas: None. T. Kay: None. S.W. Greeley: None. A. Steck: None. A.C. Powers: None. D.J. Moore: None. Funding JDRF (3-SRA-2019-759-M-B, 3-SRA-2015-102-M-B)

We previously showed that β cell microRNA 21 (miR-21) is increased by islet inflammatory stress and diabetes, that miR-21 induces β cell dysfunction by targeting mRNAs maintaining β cell identity, and that β cell miR-21 induction in vivo leads to hyperglycemia. However, upstream regulators of β cell miR-21 are poorly defined. We hypothesized that increases in the transcriptional regulator Hypoxia Inducible Factor 1 Subunit Alpha (Hif1a) during diabetogenic islet stress activate β cell miR-21 transcription, thereby contributing to loss of β cell identity occurring under these conditions. To test this, we examined Hif1a and miR-21 levels in β cell lines and mouse islets. Hif1a was increased in islets from mice after multiple low dose streptozotocin (STZ) or 4 wks of 60% high fat diet (HFD). INS1 cells and flow-sorted β cells showed increases in both miR-21 and Hif1a mRNA after 24-hr IL1β treatment. Hif1a overexpression in INS1 cells increased miR-21 levels, insulin and glucagon co-expression, and aldehyde dehydrogenase 1a3 staining, all suggesting loss of β cell identity. By contrast, siRNA depletion of Hif1a abrogated cytokine-induced reductions in mRNAs regulating β cell identity. Chromatin immunoprecipitation studies verified increased HIF1a occupancy at the miR-21 promoter after IL1β treatment. To test if these HIF1a-mediated increases in β cell miR-21 exacerbate β cell dysfunction under diabetogenic conditions in vivo, transgenic mice harboring a β cell tamoxifen inducible miR-21 transgene (Tg(β-miR-21, Ins1(CreERT2)Thor) were treated with STZ or HFD. Compared to controls, STZ and HFD-induced hyperglycemia was exacerbated in Tg(β-miR-21) mice following tamoxifen administration. By contrast, after STZ, conditional β cell miR-21 knock out (Ins1(Cre)Thor) mice showed improved glycemia. In conclusion, these findings implicate Hif1a-miR-21 signaling as a contributor to β cell dysfunction under conditions of inflammation and diabetes. Disclosure S. Ibrahim: None. C. Stephens: None. R.E. Moore: None. R. Mirmira: Advisory Panel; Self; Hibercell, Sigilon Therapeutics, Veralox Therapeutics. Employee; Spouse/Partner; Eli Lilly and Company. E.K. Sims: None.

Emerging evidence suggests intrinsic β cell dysfunction contributes to T1D development. However, it is unclear whether defects in β cell response are evident in individuals at genetic risk for T1D without detectable islet autoimmunity. To explore this, we performed mixed meal tolerance tests (MMTTs) and hyperglycemic clamps to measure stimulated β cell response in 2 groups: Islet Ab negative 1st-degree adult relatives of persons with T1D (FDR-) and normoglycemic, age, sex, and BMI-matched controls without T1D family history. Median and IQR values for 1st phase responses, including C-peptide15min-0 (MMTT) and C-peptide incremental AUC (iAUC)0-10min (clamp), and 2nd phase responses, including C-peptide iAUC0-120min (MMTT) and average C-peptide (C-peptideavg) during the steady state (clamp), were compared using paired t-tests or Wilcoxon tests. MMTTs and clamps were performed in 15 euglycemic (A1c0.99, C-peptideavg steady state was 12 (10.8-18.9) vs. 11.5 (8.9-14.5), p=0.98. In this small cohort, no significant differences between stimulated 1st or 2nd phase responses were detected between FDR- and matched controls, suggesting that FDR- relatives may not have a defect in stimulated β cell response. Nondiabetic relatives are heterogeneous in their risk of autoimmunity; this could explain a lack of between-group differences. At-risk pediatric cohorts, which have increased risks of developing autoimmunity, could be more likely to show a difference in β cell response. Ongoing investigations will define β cell function in relatives with detectable Abs. Disclosure A. Neyman: None. K. Moors: None. C. Evans-Molina: Consultant; Self; Bristol-Myers Squibb. L. DiMeglio: None. R. Mirmira: Advisory Panel; Self; Hibercell, Sigilon Therapeutics, Veralox Therapeutics. Employee; Spouse/Partner; Eli Lilly and Company. K.J. Mather: Research Support; Self; Abbott, Merck & Co., Inc., Novo Nordisk Inc., Sanofi. T.S. Hannon: None. E.K. Sims: None. Funding JDRF (2-SRA-2017-498-M-B)

Few studies have described the metabolic phenotype of AbPos individuals who remain T1D free for an extended period of time. We aimed to compare C-peptide and glucose (Glu) data from oral glucose tolerance tests (OGTTs) performed longitudinally in 646 AbPos TrialNet Pathway to Prevention (PTP) participants who remained T1D free for ≥5.0 yrs (LTNPs; mean follow-up: 7.8±2.3 yrs) versus 405 Rapid Progressor (RP) PTP participants who progressed to T1D within Disclosure C. Evans-Molina: Consultant; Self; Bristol-Myers Squibb. Z.I. Saeed: None. J. Sosenko: None. M.A. Atkinson: None. K.C. Herold: Consultant; Self; Provention Bio, Inc. H.M. Ismail: None. H. Elding Larsson: None. M. Lundgren: None. A. Moran: Research Support; Self; Abbott, Intrexon, JDRF, Medtronic, National Institute of Diabetes and Digestive and Kidney Diseases, Provention Bio, Inc. Other Relationship; Self; Novo Nordisk Inc. D.J. Moore: None. B.M. Nathan: None. J.P. Palmer: None. E.K. Sims: None. A. Steck: None. D.K. Wherrett: None. M.J. Redondo: None. Funding National Institutes of Health (U01107014, U01DK106993)

The risk for T1D, a major criterion for entry into disease prevention trials, can be assessed in various ways, but usually includes autoantibody (Ab) and/or metabolic measures. Given inherent variations in these biomarkers, it is possible that informative characteristics differ between populations selected by different risk measures. Thus, we assessed whether indices of insulin secretion [C-pep; first phase insulin response (FPIR)] vary between groups defined by distinctive risk measures. We used data from Diabetes Prevention Trial-Type 1 (DPT-1) participants, all being ICA positive subjects with or without biochemical Ab (bAb) positivity (GADA, IA-2A, mIAA). C-pep and FPIR values from baseline oral and intravenous glucose tolerance tests were compared between those who had 2-3 bAbs (≥2bAb) and those who had 0-1 bAb plus Index60≥0.40 (≤1bAb+Ind60). Index60 is a composite C-pep and glucose measure. These groups were chosen so that T1D risk would be similar (50% 5-year risk for both, log rank p=0.95). Ages (mean±SD) for ≥2bAb (n=289) and ≤1bAb+Ind60 (n=175) were 12.8±8.2 and 13.3±9.6 yrs, respectively (p=0.53). BMI Z-score was greater for ≥2bAb (0.42±1.12 vs. 0.15±1.09, p=0.01). C-pep levels were consistently higher for ≥2bAb than ≤1bAb+Ind60 [30-0 minute C-pep: 2.73±1.58 vs. 2.04±1.12 ng/mL, p In conclusion, C-pep and FPIR values can differ appreciably according to the measure that defines risk. This should be considered in choosing risk measures for prevention trials. Disclosure L.M. Jacobsen: None. B.M. Nathan: None. H.M. Ismail: None. M.J. Redondo: None. D. Schatz: None. M.J. Haller: Advisory Panel; Self; SAB Biotherapeutics, Inc. E.K. Sims: None. J.S. Skyler: Advisory Panel; Self; Abvance Therapeutics, ADOCIA, Avotres, Boehringer Ingelheim Pharmaceuticals, Inc., Dance Biopharm Holdings, Inc., Immunomolecular Therapeutics, Intrexon, Oramed Pharmaceuticals, Orgenesis Inc., Sanofi, Tolerion, Inc., Viacyte, Inc. Board Member; Self; Applied Therapeutics, Dexcom, Inc., Intarcia Therapeutics. Consultant; Self; Novo Nordisk A/S. Research Support; Self; Tolerion, Inc. Stock/Shareholder; Self; Applied Therapeutics, Dexcom, Inc., Intarcia Therapeutics. J.P. Palmer: None. K.C. Herold: Consultant; Self; Provention Bio, Inc. J. Sosenko: None.

AIMS/HYPOTHESIS: We aimed to compare characteristics of individuals identified in the peri-diagnostic range by Index60 (composite glucose and C-peptide measure) ≥2.00, 2 h OGTT glucose ≥11.1 mmol/l, or both. METHODS: We studied autoantibody-positive participants in the Type 1 Diabetes TrialNet Pathway to Prevention study who, at their baseline OGTT, had 2 h blood glucose ≥11.1 mmol/l and/or Index60 ≥2.00 (n=354, median age=11.2 years, age range=1.7–46.6; 49% male, 83% non-Hispanic White). Type 1 diabetes-relevant characteristics (e.g., age, C-peptide, autoantibodies, BMI) were compared among three mutually exclusive groups: 2 h glucose ≥11.1 mmol/l and Index60

BACKGROUND: Identification of islet β cell death prior to the onset of type 1 diabetes (T1D) or type 2 diabetes (T2D) might allow for interventions to protect β cells and reduce diabetes risk. Circulating unmethylated DNA fragments arising from the human INS gene have been proposed as biomarkers of β cell death, but this gene alone may not be sufficiently specific to report β cell death. RESULTS: To identify new candidate genes whose CpG sites may show greater specificity for β cells, we performed unbiased DNA methylation analysis using the Infinium HumanMethylation 450 array on 64 human islet preparations and 27 non-islet human tissues. For verification of array results, bisulfite DNA sequencing of human β cells and 11 non-β cell tissues was performed on 5 of the top 10 CpG sites that were found to be differentially methylated. We identified the CHTOP gene as a candidate whose CpGs show a greater frequency of unmethylation in human islets. A digital PCR strategy was used to determine the methylation pattern of CHTOP and INS CpG sites in primary human tissues. Although both INS and CHTOP contained unmethylated CpG sites in non-islet tissues, they occurred in a non-overlapping pattern. Based on Naïve Bayes classifier analysis, the two genes together report 100% specificity for islet damage. Digital PCR was then performed on cell-free DNA from serum from human subjects. Compared to healthy controls (N = 10), differentially methylated CHTOP and INS levels were higher in youth with new onset T1D (N = 43) and, unexpectedly, in healthy autoantibody-negative youth who have first-degree relatives with T1D (N = 23). When tested in lean (N = 32) and obese (N = 118) youth, increased levels of unmethylated INS and CHTOP were observed in obese individuals. CONCLUSION: Our data suggest that concurrent measurement of circulating unmethylated INS and CHTOP has the potential to detect islet death in youth at risk for both T1D and T2D. Our data also support the use of multiple parameters to increase the confidence of detecting islet damage in individuals at risk for developing diabetes., SCOPUS: ar.j, info:eu-repo/semantics/published

Maladaptive signaling by pro-inflammatory cytokines (PICs), such as TNFα, IL1β and IFNɣ, can activate downstream signaling cascades that are implicated in the development and progression of multiple inflammatory diseases. Despite playing critical roles in pathogenesis, the availability of in vivo models in which to model tissue-specific induction of PICs is limited. To bridge this gap, we have developed a novel multi-gene expression system dubbed Cre-enabled and tetracycline-inducible transgenic system for conditional, tissue-specific expression of pro-inflammatory cytokines (CETI-PIC3). This binary transgenic system permits the stoichiometric co-expression of proteins Tumor necrosis factor a (Tnfa), Interleukin-1 beta (Il1b) and Interferon gamma (Ifng1), and H2B-GFP fluorescent reporter in a dose-dependent manner. Furthermore, cytokine misexpression is enabled only in tissue domains that can be defined by Cre recombinase expression. We have validated this system in zebrafish using an insulin:cre line. In doubly transgenic fish, quantitative real-time polymerase chain reaction demonstrated increased expression levels of tnfa, il1b and ifng1 mRNA. Moreover, specific expression in pancreatic β cells was demonstrated by both Tnfa immunofluorescence and GFP fluorescence. Cytokine-overexpressing islets elicited specific responses: β cells exhibited increased expression of genes associated with reactive oxidative species-mediated stress and endoplasmic reticulum stress, surveilling and infiltrating macrophages were increased, and β cell death was promoted. This powerful and versatile model system can be used for modeling, analysis and therapy development of diseases with an underlying inflammatory etiology. This article has an associated First Person interview with the first author of the paper., Summary: Here, we report a novel transgenic zebrafish system that permits tissue-specific, inducible and tunable expression of pro-inflammatory cytokines for modeling inflammatory diseases.