DNA Methylation-Based Assessment of Cell Composition in Human Pancreas and Islets.

Assessment of pancreas cell type composition is crucial to the understanding of the genesis of diabetes. Current approaches use immunodetection of protein markers, for example, insulin as a marker of ß-cells. A major limitation of these methods is that protein content varies in physiological and pathological conditions, complicating the extrapolation to actual cell number. Here, we demonstrate the use of cell type-specific DNA methylation markers for determining the fraction of specific cell types in human islet and pancreas specimens. We identified genomic loci that are uniquely demethylated in specific pancreatic cell types and applied targeted PCR to assess the methylation status of these loci in tissue samples, enabling inference of cell type composition. In islet preparations, normalization of insulin secretion to ß-cell DNA revealed similar ß-cell function in pre-type 1 diabetes (T1D), T1D, and type 2 diabetes (T2D), which was significantly lower than in donors without diabetes. In histological pancreas specimens from recent-onset T1D, this assay showed ß-cell fraction within the normal range, suggesting a significant contribution of ß-cell dysfunction. In T2D pancreata, we observed increased α-cell fraction and normal ß-cell fraction. Methylation-based analysis provides an accurate molecular alternative to immune detection of cell types in the human pancreas, with utility in the interpretation of insulin secretion assays and the assessment of pancreas cell composition in health and disease.

5-Year simulation of diabetes-related complications in people treated with tirzepatide or semaglutide versus insulin glargine.

AIM: This study compared the 5-year incidence rate of macrovascular and microvascular complications for tirzepatide, semaglutide and insulin glargine in individuals with type 2 diabetes, using the Building, Relating, Assessing, and Validating Outcomes (BRAVO) diabetes simulation model. RESEARCH DESIGN AND METHODS: This study was a 5-year SURPASS-2 trial extrapolation, with an insulin glargine arm added as an additional comparator. The 1-year treatment effects of tirzepatide (5, 10 or 15 mg), semaglutide (1 mg) and insulin glargine on glycated haemoglobin, systolic blood pressure, low-density lipoprotein and body weights were obtained from the SUSTAIN-4 and SURPASS-2 trials. We used the BRAVO model to predict 5-year complications for each study arm under two scenarios: the 1-year treatment effects persisted (optimistic) or diminished to none in 5 years (conservative). RESULTS: When compared with insulin glargine, we projected a 5-year risk reduction in cardiovascular adverse events [rate ratio (RR) 0.64, 95% confidence interval (CI) 0.61-0.67] and microvascular composite (RR 0.67, 95% CI 0.64-0.70) with 15 mg tirzepatide, and 5-year risk reduction in cardiovascular adverse events (RR 0.75, 95% CI 0.72-0.79) and microvascular composite (RR 0.79, 95% CI 0.76-0.82) with semaglutide (1 mg) under an optimistic scenario. Lower doses of tirzepatide also had similar, albeit smaller benefits. Treatment effects for tirzepatide and semaglutide were smaller but still significantly higher than insulin glargine under a conservative scenario. The 5-year risk reduction in diabetes-related complication events and mortality for the 15 mg tirzepatide compared with insulin glargine ranged from 49% to 10% under an optimistic scenario, which was reduced by 17%-33% when a conservative scenario was assumed. CONCLUSION: With the use of the BRAVO diabetes model, tirzepatide and semaglutide exhibited potential to reduce the risk of macrovascular and microvascular complications among individuals with type 2 diabetes, compared with insulin glargine in a 5-year window. Based on the current modelling assumptions, tirzepatide (15 mg) may potentially outperform semaglutide (1 mg). While the BRAVO model offered insights, the long-term cardiovascular benefit of tirzepatide should be further validated in a prospective clinical trial.

Low-Dose Antithymocyte Globulin: A Pragmatic Approach to Treating Stage 2 Type 1 Diabetes.

OBJECTIVE: Low-dose antithymocyte globulin (ATG) (2.5 mg/kg) preserves C-peptide and reduces HbA1c in new-onset stage 3 type 1 diabetes, yet efficacy in delaying progression from stage 2 to stage 3 has not been evaluated. RESEARCH DESIGN AND METHODS: Children (n = 6) aged 5-14 years with stage 2 type 1 diabetes received off-label, low-dose ATG. HbA1c, C-peptide, continuous glucose monitoring, insulin requirements, and side effects were followed for 18-48 months. RESULTS: Three subjects (50%) remained diabetes free after 1.5, 3, and 4 years of follow-up, while three developed stage 3 within 1-2 months after therapy. Eighteen months posttreatment, even disease progressors demonstrated near-normal HbA1c (5.1% [32 mmol/mol], 5.6% [38 mmol/mol], and 5.3% [34 mmol/mol]), time in range (93%, 88%, and 98%), low insulin requirements (0.17, 0.18, and 0.34 units/kg/day), and robust C-peptide 90 min after mixed meal (1.3 ng/dL, 2.3 ng/dL, and 1.4 ng/dL). CONCLUSIONS: These observations support additional prospective studies evaluating ATG in stage 2 type 1 diabetes.

The role of health system penetration rate in estimating the prevalence of type 1 diabetes in children and adolescents using electronic health records.

OBJECTIVE: Having sufficient population coverage from the electronic health records (EHRs)-connected health system is essential for building a comprehensive EHR-based diabetes surveillance system. This study aimed to establish an EHR-based type 1 diabetes (T1D) surveillance system for children and adolescents across racial and ethnic groups by identifying the minimum population coverage from EHR-connected health systems to accurately estimate T1D prevalence. MATERIALS AND METHODS: We conducted a retrospective, cross-sectional analysis involving children and adolescents <20 years old identified from the OneFlorida+ Clinical Research Network (2018-2020). T1D cases were identified using a previously validated computable phenotyping algorithm. The T1D prevalence for each ZIP Code Tabulation Area (ZCTA, 5 digits), defined as the number of T1D cases divided by the total number of residents in the corresponding ZCTA, was calculated. Population coverage for each ZCTA was measured using observed health system penetration rates (HSPR), which was calculated as the ratio of residents in the corresponding ZTCA and captured by OneFlorida+ to the overall population in the same ZCTA reported by the Census. We used a recursive partitioning algorithm to identify the minimum required observed HSPR to estimate T1D prevalence and compare our estimate with the reported T1D prevalence from the SEARCH study. RESULTS: Observed HSPRs of 55%, 55%, and 60% were identified as the minimum thresholds for the non-Hispanic White, non-Hispanic Black, and Hispanic populations. The estimated T1D prevalence for non-Hispanic White and non-Hispanic Black were 2.87 and 2.29 per 1000 youth, which are comparable to the reference study's estimation. The estimated prevalence of T1D for Hispanics (2.76 per 1000 youth) was higher than the reference study's estimation (1.48-1.64 per 1000 youth). The standardized T1D prevalence in the overall Florida population was 2.81 per 1000 youth in 2019. CONCLUSION: Our study provides a method to estimate T1D prevalence in children and adolescents using EHRs and reports the estimated HSPRs and prevalence of T1D for different race and ethnicity groups to facilitate EHR-based diabetes surveillance.

Human immune phenotyping reveals accelerated aging in type 1 diabetes.

The proportions and phenotypes of immune cell subsets in peripheral blood undergo continual and dramatic remodeling throughout the human life span, which complicates efforts to identify disease-associated immune signatures in type 1 diabetes (T1D). We conducted cross-sectional flow cytometric immune profiling on peripheral blood from 826 individuals (stage 3 T1D, their first-degree relatives, those with ≥2 islet autoantibodies, and autoantibody-negative unaffected controls). We constructed an immune age predictive model in unaffected participants and observed accelerated immune aging in T1D. We used generalized additive models for location, shape, and scale to obtain age-corrected data for flow cytometry and complete blood count readouts, which can be visualized in our interactive portal (ImmScape); 46 parameters were significantly associated with age only, 25 with T1D only, and 23 with both age and T1D. Phenotypes associated with accelerated immunological aging in T1D included increased CXCR3+ and programmed cell death 1-positive (PD-1+) frequencies in naive and memory T cell subsets, despite reduced PD-1 expression levels on memory T cells. Phenotypes associated with T1D after age correction were predictive of T1D status. Our findings demonstrate advanced immune aging in T1D and highlight disease-associated phenotypes for biomarker monitoring and therapeutic interventions.

Responders to low-dose ATG induce CD4+ T cell exhaustion in type 1 diabetes.

BACKGROUNDLow-dose anti-thymocyte globulin (ATG) transiently preserves C-peptide and lowers HbA1c in individuals with recent-onset type 1 diabetes (T1D); however, the mechanisms of action and features of the response remain unclear. Here, we characterized the post hoc immunological outcomes of ATG administration and their potential use as biomarkers of metabolic response to therapy (i.e., improved preservation of endogenous insulin production).METHODSWe assessed gene and protein expression, targeted gene methylation, and cytokine concentrations in peripheral blood following treatment with ATG (n = 29), ATG plus granulocyte colony-stimulating factor (ATG/G-CSF, n = 28), or placebo (n = 31).RESULTSTreatment with low-dose ATG preserved regulatory T cells (Tregs), as measured by stable methylation of FOXP3 Treg-specific demethylation region (TSDR) and increased proportions of CD4+FOXP3+ Tregs (P < 0.001) identified by flow cytometry. While treatment effects were consistent across participants, not all maintained C-peptide. Responders exhibited a transient rise in IL-6, IP-10, and TNF-α (P < 0.05 for all) 2 weeks after treatment and a durable CD4+ exhaustion phenotype (increased PD-1+KLRG1+CD57- on CD4+ T cells [P = 0.011] and PD1+CD4+ Temra MFI [P < 0.001] at 12 weeks, following ATG and ATG/G-CSF, respectively). ATG nonresponders displayed higher proportions of senescent T cells (at baseline and after treatment) and increased methylation of EOMES (i.e., less expression of this exhaustion marker).CONCLUSIONAltogether in these exploratory analyses, Th1 inflammation-associated serum and CD4+ exhaustion transcript and cellular phenotyping profiles may be useful for identifying signatures of clinical response to ATG in T1D.TRIAL REGISTRATIONClinicalTrials.gov NCT02215200.FUNDINGThe Leona M. and Harry B. Helmsley Charitable Trust (2019PG-T1D011), the NIH (R01 DK106191 Supplement, K08 DK128628), NIH TrialNet (U01 DK085461), and the NIH NIAID (P01 AI042288).

Ethnic Variations in Cardiovascular and Renal Outcomes From Newer Glucose-Lowering Drugs: A Meta-Analysis of Randomized Outcome Trials.

Background Hispanic populations are more likely to develop diabetes and its related diseases than non-Hispanic White populations. Little evidence exists to support whether the cardiovascular and renal benefits of sodium-glucose cotransporter 2 inhibitors and glucagon-like peptide-1 receptor agonists are generalizable to the Hispanic populations. Methods and Results We included the cardiovascular and renal outcome trials (up to March 2021) that reported the major adverse cardiovascular events (MACEs), cardiovascular death/hospitalization for heart failure, and composite renal outcomes by ethnicity in individuals with type 2 diabetes (T2D), calculated pooled hazard ratios (HRs) with 95% CIs using fixed-effects models, and tested the differences between Hispanic and non-Hispanic populations (P for interaction [Pinteraction]). In 3 sodium-glucose cotransporter 2 inhibitor trials, there was a statistically significant difference between Hispanic (HR, 0.70 [95% CI, 0.54-0.91]) and non-Hispanic (HR, 0.96 [95% CI, 0.86-1.07]) groups in treatment effects on MACE risk (Pinteraction=0.03), except for risks of cardiovascular death/hospitalization for heart failure (Pinteraction=0.46) and composite renal outcome (Pinteraction=0.31). In 5 glucagon-like peptide-1 receptor agonist trials, there was no statistically significant difference in treatment effect on MACE risk between Hispanic (HR, 0.82 [95% CI, 0.70-0.96]) and non-Hispanic (HR, 0.92 [95% CI, 0.84-1.00]) populations (Pinteraction=0.22). In 3 dipeptidyl peptidase-4 inhibitor trials, the HR for MACE risk appeared greater in Hispanic (HR, 1.15 [95% CI, 0.98-1.35]) than non-Hispanic (HR, 0.96 [95% CI, 0.88-1.04]) populations (Pinteraction=0.045). Conclusions Compared with non-Hispanic individuals, Hispanic individuals with T2D appeared to obtain a greater benefit of lowered MACE risk with sodium-glucose cotransporter 2 inhibitors.

Modeling the progression of Type 2 diabetes with underlying obesity.

Environmentally induced or epigenetic-related beta-cell dysfunction and insulin resistance play a critical role in the progression to diabetes. We developed a mathematical modeling framework capable of studying the progression to diabetes incorporating various diabetogenic factors. Considering the heightened risk of beta-cell defects induced by obesity, we focused on the obesity-diabetes model to further investigate the influence of obesity on beta-cell function and glucose regulation. The model characterizes individualized glucose and insulin dynamics over the span of a lifetime. We then fit the model to the longitudinal data of the Pima Indian population, which captures both the fluctuations and long-term trends of glucose levels. As predicted, controlling or eradicating the obesity-related factor can alleviate, postpone, or even reverse diabetes. Furthermore, our results reveal that distinct abnormalities of beta-cell function and levels of insulin resistance among individuals contribute to different risks of diabetes. This study may encourage precise interventions to prevent diabetes and facilitate individualized patient treatment.

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.

Type 1 Diabetes: A Disorder of the Exocrine and Endocrine Pancreas.

Type 1 diabetes has historically been described as an endocrine (ß-cell) specific autoimmune disease. However, a substantial reduction (20-50%) in pancreas organ size and subclinical to symptomatic exocrine pancreatic insufficiency are present at diagnosis and may begin even prior to the development of islet autoimmunity. The mechanisms of exocrine loss in type 1 diabetes are not well understood, but leading hypotheses include developmental defects, ß-cell loss resulting in exocrine atrophy, or autoimmune or inflammatory destruction of exocrine cells. Inflammatory changes including acute and chronic pancreatitis, exocrine T cell infiltration and classical complement activation, and serum exocrine autoantibodies within type 1 diabetes individuals suggest that an autoimmune or inflammatory process may contribute to exocrine pancreatic dysfunction. Exocrine pancreas atrophy primarily occurs prior to the onset of clinical disease. Indeed, recent work implicates exocrine-specific alterations in gene and protein expression as key in type 1 diabetes development. Measures of exocrine size and function could be useful additions in the prediction of disease onset and in identifying potential therapeutic responders to disease therapies, however, this is an underdeveloped area of research. Additionally, exocrine pancreatic insufficiency is underdiagnosed in individuals with type 1 diabetes and individualized treatment protocols are lacking. Much work remains to be done in this area, but we can definitively say that type 1 diabetes is a disorder of both the exocrine and endocrine pancreas likely from the start.

Rising Hemoglobin A1c in the Nondiabetic Range Predicts Progression of Type 1 Diabetes As Well As Oral Glucose Tolerance Tests.

OBJECTIVE: Biomarkers predicting risk of type 1 diabetes (stage 3) among children with islet autoantibodies are greatly needed to prevent diabetic ketoacidosis and facilitate prevention therapies. RESEARCH DESIGN AND METHODS: Children in the prospective The Environmental Determinants of Diabetes in the Young (TEDDY) study (n = 707) with confirmed diabetes-associated autoantibodies (GAD antibody, IA-2A, and/or insulin autoantibody) and two or more HbA1c measurements were followed to diabetes or median age 11.1 years. Once confirmed autoantibody positive, HbA1c was measured quarterly. Cox models and receiver operative characteristic curve analyses revealed the prognostic utility for risk of stage 3 on a relative HbA1c increase from the baseline visit or an oral glucose tolerance test (OGTT) 2-h plasma glucose (2-hPG). This HbA1c approach was then validated in the Type 1 Diabetes TrialNet Pathway to Prevention Study (TrialNet) (n = 1,190). RESULTS: A 10% relative HbA1c increase from baseline best marked the increased risk of stage 3 in TEDDY (74% sensitive; 88% specific). Significant predictors of risk for HbA1c change were age and HbA1c at the baseline test, genetic sex, maximum number of autoantibodies, and maximum rate of HbA1c increase by time of change. The multivariable model featuring a HbA1c ≥10% increase and these additional factors revealed increased risk of stage 3 in TEDDY (hazard ratio [HR] 12.74, 95% CI 8.7-18.6, P < 0.0001) and TrialNet (HR 5.09, 95% CI 3.3-7.9, P < 0.0001). Furthermore, the composite model using HbA1c ≥10% increase performed similarly to an OGTT 2-hPG composite model (TEDDY area under the curve [AUC] 0.88 and 0.85, respectively) and to the HbA1c model in TrialNet (AUC 0.82). CONCLUSIONS: An increase of ≥10% in HbA1c from baseline is as informative as OGTT 2-hPG in predicting risk of stage 3 in youth with genetic risk and diabetes-associated autoantibodies.

Incidence Trends of New-Onset Diabetes in Children and Adolescents Before and During the COVID-19 Pandemic: Findings From Florida.

This study examined the incidence trends of new-onset type 1 and type 2 diabetes in children and adolescents in Florida before and during the coronavirus disease 2019 (COVID-19) pandemic. In this observational descriptive cohort study, we used a validated computable phenotype to identify incident diabetes cases among individuals <18 years of age in the OneFlorida+ network of the national Patient-Centered Clinical Research Network between January 2017 and June 2021. We conducted an interrupted time series analysis based on the autoregressive integrated moving average model to compare changes in age-adjusted incidence rates of type 1 and type 2 diabetes before and after March 2020, when COVID-19 was declared a national health emergency in the U.S. The age-adjusted incidence rates of both type 1 and type 2 diabetes increased post-COVID-19 for children and adolescents. These results highlight the need for longitudinal cohort studies to examine how the pandemic might influence subsequent diabetes onset in young individuals.

Index60 Is Superior to HbA1c for Identifying Individuals at High Risk for Type 1 Diabetes.

CONTEXT: HbA1c from ≥ 5.7% to < 6.5% (39-46 mmol/mol) indicates prediabetes according to American Diabetes Association guidelines, yet its identification of prediabetes specific for type 1 diabetes has not been assessed. A composite glucose and C-peptide measure, Index60, identifies individuals at high risk for type 1 diabetes. OBJECTIVE: We compared Index60 and HbA1c thresholds as markers for type 1 diabetes risk. METHODS: TrialNet Pathway to Prevention study participants with ≥ 2 autoantibodies (GADA, IAA, IA-2A, or ZnT8A) who had oral glucose tolerance tests and HbA1c measurements underwent 1) predictive time-dependent modeling of type 1 diabetes risk (n = 2776); and 2) baseline comparisons between high-risk mutually exclusive groups: Index60 ≥ 2.04 (n = 268) vs HbA1c ≥ 5.7% (n = 268). The Index60 ≥ 2.04 threshold was commensurate in ordinal ranking with the standard prediabetes threshold of HbA1c ≥ 5.7%. RESULTS: In mutually exclusive groups, individuals exceeding Index60 ≥ 2.04 had a higher cumulative incidence of type 1 diabetes than those exceeding HbA1c ≥ 5.7% (P < 0.0001). Appreciably more individuals with Index60 ≥ 2.04 were at stage 2, and among those at stage 2, the cumulative incidence was higher for those with Index60 ≥ 2.04 (P = 0.02). Those with Index60 ≥ 2.04 were younger, with lower BMI, greater autoantibody number, and lower C-peptide than those with HbA1c ≥ 5.7% (P < 0.0001 for all comparisons). CONCLUSION: Individuals with Index60 ≥ 2.04 are at greater risk for type 1 diabetes with features more characteristic of the disorder than those with HbA1c ≥ 5.7%. Index60 ≥ 2.04 is superior to the standard HbA1c ≥ 5.7% threshold for identifying prediabetes in autoantibody-positive individuals. These findings appear to justify using Index60 ≥ 2.04 as a prediabetes criterion in this population.

Cost-Effectiveness of Low-Dose Antithymocyte Globulin Versus Other Immunotherapies for Treatment of New-Onset Type 1 Diabetes.

Objective: Several immunotherapies have shown efficacy in slowing C-peptide decline in new-onset type 1 diabetes. Although most of these biologic drugs are expensive, they offer the opportunity to reduce downstream disease management costs and risk of complications. The objective of this study is to examine the cost-effectiveness of immunotherapies versus no treatment for patients with new-onset type 1 diabetes. Methods: Using Markov microsimulation modeling and efficacy data from immunotherapy trials, we examined the cost-effectiveness of six immunotherapies for new-onset type 1 diabetes, namely, low-dose (2.5 mg/kg) antithymocyte globulin (ATG), high-dose (6.5 mg/kg) ATG, abatacept, alefacept, rituximab, and teplizumab, versus no treatment. Effectiveness was measured by quality-adjusted life-years (QALYs). Costs were estimated from a health system perspective. Results: Low-dose ATG treatment saves US$10,270, on average, over a patient's lifetime and generates 0.09 additional QALYs compared with no treatment. These cost savings arise as low-dose ATG generates downstream savings in disease management costs that more than offset its cost. In contrast, treatment with other immunotherapies yields smaller QALY gains (0.02-0.05 additional QALYs) and increases lifetime costs by US$9500-US$168,380 relative to no treatment, with incremental cost-effectiveness ratios that exceed the willingness-to-pay threshold of US$100,000 per QALY. Conclusions: Low-dose ATG treatment is both less costly and more effective relative to other immunotherapies and no treatment for new-onset type 1 diabetes.

The progression of secondary diabetes: A review of modeling studies.

Mathematical modeling has provided quantitative information consistent with experimental data, greatly improving our understanding of the progression of type 1 and type 2 diabetes. However, diabetes is a complex metabolic disease and has been found to be involved in crosstalk interactions with diverse endocrine diseases. Mathematical models have also been developed to investigate the quantitative impact of various hormonal disorders on glucose imbalance, advancing the precision treatment for secondary diabetes. Here we review the models established for the study of dysglycemia induced by hormonal disorders, such as excessive glucocorticoids, epinephrine, and growth hormone. To investigate the influence of hyperthyroidism on the glucose regulatory system, we also propose a hyperthyroid-diabetes progression model. Model simulations indicate that timely thyroid treatment can halt the progression of hyperglycemia and prevent beta-cell failure. This highlights the diagnosis of hormonal disorders, together withblood sugar tests, as significant measures for the early diagnosis and treatment of diabetes. The work recapitulates updated biological research on the interactions between the glucose regulatory system and other endocrine axes. Further mathematical modeling of secondary diabetes is desired to promote the quantitative study of the disease and the development of individualized diabetic therapies.

Substance Use Affects Type 1 Diabetes Pancreas Pathology: Implications for Future Studies.

Access to human pancreas samples from organ donors has greatly advanced our understanding of type 1 diabetes pathogenesis; however, previous studies have shown that donors have a high rate of substance use, and its impact on pancreatic histopathology in this disease is not well described. One-hundred-thirty-one type 1 diabetes and 111 control organ donor pancreata from persons 12-89 years of age (mean 29.8 ± 15.5 years) within the Network for Pancreatic Organ donors with Diabetes (nPOD) were examined for insulin positivity, insulitis, amyloid staining, acute and chronic pancreatitis, and chronic exocrine changes (acinar atrophy, fibrosis, fatty infiltration, or periductal fibrosis); findings were compared by history of substance use. A secondary analysis compared exocrine pancreatic histopathologic findings in type 1 diabetes versus control organ donors regardless of substance use history. We observed a high but congruent rate of substance use in type 1 diabetes and control organ donors (66.4% and 64% respectively). Among donors with type 1 diabetes (but not controls), islet amyloid (OR 9.96 [1.22, 81.29]) and acute pancreatitis (OR 3.2 [1.06, 9.63]) were more common in alcohol users while chronic exocrine changes (OR 8.86 [1.13, 69.31]) were more common in cocaine users. Substance use impacted the pancreata of donors with type 1 diabetes more than controls. Overall, despite similar rates of substance use, acute pancreatitis (15.3% versus 4.5%, p=0.0061), chronic pancreatitis (29.8% versus 9.9%, p=0.0001), and chronic exocrine changes (73.3% versus 36.9%, p<0.0001) were more common in type 1 diabetes donors than controls. Alcohol and/or cocaine use in type 1 diabetes organ donors increases exocrine pancreas pathology and islet amyloid deposition but does not affect insulitis or insulin positivity. Exocrine pathology in type 1 diabetes donors is common, and further study of the pathophysiology of these changes is needed.