Type 1 diabetes (T1D) is a chronic disease resulting from the destruction of pancreatic beta cells, due to a poorly understood combination of genetic, environmental, and immune factors. The JDRF ...Network for Pancreatic Organ donors with Diabetes (nPOD) program recovers transplantation quality pancreas from organ donors throughout the USA. In addition to recovery of donors with T1D, non‐diabetic donors include those with islet autoantibodies. Donors with type 2 diabetes and other conditions are also recovered to aid investigations directed at the full spectrum of pathophysiological mechanisms affecting beta cells. One central processing laboratory conducts standardized procedures for sample processing, storage, and distribution, intended for current and future cutting edge investigations. Baseline histology characterizations are performed on the pancreatic samples, with images of the staining results provided though whole‐slide digital scans. Uniquely, these high‐grade biospecimens are provided without expense to investigators, working worldwide, seeking methods for disease prevention and reversal strategies. Collaborative working groups are highly encouraged, bringing together multiple investigators with different expertise to foster collaborations in several areas of critical need. This mini‐review will provide some key histopathological findings emanating from the nPOD collection, including the heterogeneity of beta cell loss and islet inflammation (insulitis), beta cell mass, insulin‐producing beta cells in chronic T1D, and pancreas weight reductions at disease onset. Analysis of variations in histopathology observed from these organ donors could provide for mechanistic differences related to etiological agents and serve an important function in terms of identifying the heterogeneity of T1D.
Controversy exists regarding the potential regenerative influences of incretin therapy on pancreatic β-cells versus possible adverse pancreatic proliferative effects. Examination of pancreata from ...age-matched organ donors with type 2 diabetes mellitus (DM) treated by incretin therapy (n = 8) or other therapy (n = 12) and nondiabetic control subjects (n = 14) reveals an ∼40% increased pancreatic mass in DM treated with incretin therapy, with both increased exocrine cell proliferation (P < 0.0001) and dysplasia (increased pancreatic intraepithelial neoplasia, P < 0.01). Pancreata in DM treated with incretin therapy were notable for α-cell hyperplasia and glucagon-expressing microadenomas (3 of 8) and a neuroendocrine tumor. β-Cell mass was reduced by ∼60% in those with DM, yet a sixfold increase was observed in incretin-treated subjects, although DM persisted. Endocrine cells costaining for insulin and glucagon were increased in DM compared with non-DM control subjects (P < 0.05) and markedly further increased by incretin therapy (P < 0.05). In conclusion, incretin therapy in humans resulted in a marked expansion of the exocrine and endocrine pancreatic compartments, the former being accompanied by increased proliferation and dysplasia and the latter by α-cell hyperplasia with the potential for evolution into neuroendocrine tumors.
Aims/hypothesis
Previous studies of pancreases obtained at autopsy or by radiography note reduced pancreas weight (PW) and size, respectively, in type 1 diabetes; this finding is widely considered to ...be the result of chronic insulinopenia. This literature is, however, limited with respect to the influence of age, sex, anthropometric factors and disease duration on these observations. Moreover, data are sparse for young children, a group of particular interest for type 1 diabetes. We hypothesised that the pancreas-to-body weight ratio would normalise confounding inter-subject factors, thereby permitting better characterisation of PW in type 1 diabetes.
Methods
Transplant-grade pancreases were recovered from 216 organ donors with type 1 diabetes (
n
= 90), type 2 diabetes (
n
= 40) and no diabetes (
n
= 86). Whole-organ and head, body and tail weights were determined. The relative PW (RPW; PW g / body weight kg) was calculated and tested for normalisation of potential differences due to age, sex and BMI.
Results
PW significantly correlated with body weight in control donors (
R
2
= 0.76,
p
< 0.001) while RPW (1.03 ± 0.36, mean ± SD) did not significantly differ across ages (0–58 years). Donors with type 1 diabetes (0.57 ± 0.18,
p
< 0.001), but not those with type 2 diabetes (0.93 ± 0.30), had significantly lower RPW. The relative weights of each pancreatic region from donors with type 1 diabetes were significantly smaller than those of regions from control donors and donors with type 2 diabetes (
p
< 0.001). Perhaps most interestingly, the RPW was not significantly associated with duration of type 1 diabetes or type 2 diabetes.
Conclusions/interpretation
RPW allows for comparisons across a wide range of donor ages by eliminating confounding variables. These data validate an interesting feature of the type 1 diabetes pancreas and underscore the need for additional studies to identify the mechanistic basis for this finding, including those beyond the chronic loss of endogenous insulin secretion.
Pancreas size is reduced in patients at type 1 diabetes onset and in autoantibody (AAB)-positive donors without diabetes. We sought to determine whether pancreas volume (PV) imaging could improve ...understanding of the loss of pancreas size in first-degree relatives (FDRs) of patients with type 1 diabetes. We also examined relationships among PV, AAB status, and endocrine and exocrine functions.
We conducted a cross-sectional study that included five groups: AAB
control subjects (no diabetes and no first- or second-degree relatives with type 1 diabetes) (
= 49), AAB
FDRs (
= 61), AAB
FDRs (
= 67 total:
= 31 with a single positive AAB AAB
single and
= 36 with multiple positive AABs AAB
multiple), and patients with recent-onset type 1 diabetes (<1 year) (
= 52). Fasting subjects underwent 1.5T pancreatic MRI, and PV and relative PV (RPV) (PV-to-BMI ratio) were analyzed between groups and for correlations with HbA
, C-peptide, glucose, and trypsinogen.
All FDR groups had significantly lower RPV adjusted for BMI (RPV
) than control subjects (all
< 0.05). Patients with type 1 diabetes had lower RPV
than AAB
FDR (
< 0.0001) and AAB
multiple (
≤ 0.013) subjects. Transformed data indicated that trypsinogen levels were lowest in patients with type 1 diabetes.
This study demonstrates, for the first time, all FDRs having significantly smaller RPV
compared with AAB
control subjects. Furthermore, RPV
was significantly lower in patients with recent-onset type 1 diabetes than in the AAB
FDR and AAB
multiple groups. As such, RPV
may be a novel noninvasive biomarker for predicting progression through stages of type 1 diabetes risk. This study highlights the potential paracrine relationships between the exocrine and endocrine pancreas in progression to type 1 diabetes in subjects at risk.
Nanoscale or single-cell technologies are critical for biomedical applications. However, current mass spectrometry (MS)-based proteomic approaches require samples comprising a minimum of thousands of ...cells to provide in-depth profiling. Here, we report the development of a nanoPOTS (nanodroplet processing in one pot for trace samples) platform for small cell population proteomics analysis. NanoPOTS enhances the efficiency and recovery of sample processing by downscaling processing volumes to <200 nL to minimize surface losses. When combined with ultrasensitive liquid chromatography-MS, nanoPOTS allows identification of ~1500 to ~3000 proteins from ~10 to ~140 cells, respectively. By incorporating the Match Between Runs algorithm of MaxQuant, >3000 proteins are consistently identified from as few as 10 cells. Furthermore, we demonstrate quantification of ~2400 proteins from single human pancreatic islet thin sections from type 1 diabetic and control donors, illustrating the application of nanoPOTS for spatially resolved proteome measurements from clinical tissues.
Type 1 diabetes (T1D) is considered a pancreatic beta cell-specific disease that results in absolute insulin deficiency. Nevertheless, clinical studies from 1940 onwards showed that patients with T1D ...had an abnormal exocrine pancreas due to the presence of subclinical exocrine insufficiency and acinar atrophy. Exocrine abnormalities are an important, and mostly neglected, characteristic associated with T1D. It is however still unclear whether the exocrine dysfunction in T1D is a primary damage caused by the same pathogenic event that led to beta cell destruction or secondary to beta cell loss. In this review, we collect evidence supporting the hypothesis that T1D is a combined endocrine-exocrine disease in which the loss of functional beta cell mass is most clinically apparent.
The pancreatic β cell, as the sole source of the vital hormone insulin, has been under intensive study for more than a century. Given the potential of newly created insulin-producing cells as a ...treatment or even cure of type 1 diabetes (T1D) and possibly in severe cases of type 2 diabetes (T2D), multiple academic and commercial laboratories are working to derive surrogate glucose-responsive, insulin-producing cells.
The recent development of advanced phenotyping technologies, including molecular, epigenomic, histological, or functional, have greatly improved our understanding of the critical properties of human β cells. Using this information, here we summarize the salient features of normal, fully functional adult human β cells, and propose minimal criteria for what should rightfully be termed ‘β cells’ as opposed to insulin-producing but not fully-functional surrogates that we propose should be referred to as ‘β-like’ cells or insulin-producing cells.
Clear criteria can be established to differentiate fully functional, mature β cells from ‘β-like’ surrogates. In addition, we outline important knowledge gaps that must be addressed to enable a greater understanding of the β cell.
Clinical trials seeking to delay or prevent the onset of type 1 diabetes (T1D) face a series of pragmatic challenges. Despite more than 100 years since the discovery of insulin, teplizumab remains ...the only FDA‐approved therapy to delay progression from Stage 2 to Stage 3 T1D. To increase the efficiency of clinical trials seeking this goal, our project sought to inform T1D clinical trial designs by developing a disease progression model‐based clinical trial simulation tool. Using individual‐level data collected from the TrialNet Pathway to Prevention and The Environmental Determinants of Diabetes in the Young natural history studies, we previously developed a quantitative joint model to predict the time to T1D onset. We then applied trial‐specific inclusion/exclusion criteria, sample sizes in treatment and placebo arms, trial duration, assessment interval, and dropout rate. We implemented a function for presumed drug effects. To increase the size of the population pool, we generated virtual populations using multivariate normal distribution and ctree machine learning algorithms. As an output, power was calculated, which summarizes the probability of success, showing a statistically significant difference in the time distribution until the T1D diagnosis between the two arms. Using this tool, power curves can also be generated through iterations. The web‐based tool is publicly available: https://app.cop.ufl.edu/t1d/. Herein, we briefly describe the tool and provide instructions for simulating a planned clinical trial with two case studies. This tool will allow for improved clinical trial designs and accelerate efforts seeking to prevent or delay the onset of T1D.
Clinical trials seeking type 1 diabetes prevention are challenging in terms of identifying patient populations likely to progress to type 1 diabetes within limited (i.e., short‐term) trial durations. ...Hence, we sought to improve such efforts by developing a quantitative disease progression model for type 1 diabetes. Individual‐level data obtained from the TrialNet Pathway to Prevention and The Environmental Determinants of Diabetes in the Young natural history studies were used to develop a joint model that links the longitudinal glycemic measure to the timing of type 1 diabetes diagnosis. Baseline covariates were assessed using a stepwise covariate modeling approach. Our study focused on individuals at risk of developing type 1 diabetes with the presence of two or more diabetes‐related autoantibodies (AAbs). The developed model successfully quantified how patient features measured at baseline, including HbA1c and the presence of different AAbs, alter the timing of type 1 diabetes diagnosis with reasonable accuracy and precision (<30% RSE). In addition, selected covariates were statistically significant (p < 0.0001 Wald test). The Weibull model best captured the timing to type 1 diabetes diagnosis. The 2‐h oral glucose tolerance values assessed at each visit were included as a time‐varying biomarker, which was best quantified using the sigmoid maximum effect function. This model provides a framework to quantitatively predict and simulate the time to type 1 diabetes diagnosis in individuals at risk of developing the disease and thus, aligns with the needs of pharmaceutical companies and scientists seeking to advance therapies aimed at interdicting the disease process.
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