Network for Pancreatic Organ Donors with Diabetes (nPOD): developing a tissue biobank for type 1 diabetes

Bioengineering and omics approaches for Type 1 diabetes practical research: advancements and constraints

Insulin dependency arises from autoimmunity that targets the β cells of the pancreas, resulting in Type 1 diabetes (T1D). Despite the fact that T1D patients require insulin for survival, insulin does not provide a cure for this disease or prevent its complications. Despite extensive genetic, molecular, and cellular research on T1D over the years, the translation of this understanding into effective clinical therapies continues to pose a significant obstacle. It is therefore difficult to develop effective clinical treatment strategies without a thorough understanding of disease pathophysiology. Pancreatic tissue bioengineering models of human T1D offer a valuable approach to examining and controlling islet function while tackling various facets of the condition. And in recent years, due to advances in high-throughput omics analysis, the genotypic and molecular profiles of T1D have become finer tuned. The present article will examine recent progress in these areas, along with their utilization and constraints in the realm of T1D.

The extra-islet pancreas supports autoimmunity in human type 1 diabetes

In autoimmune type 1 diabetes (T1D), immune cells infiltrate and destroy the islets of Langerhans - islands of endocrine tissue dispersed throughout the pancreas. However, the contribution of cellular programs outside islets to insulitis is unclear. Here, using CO-Detection by indEXing (CODEX) tissue imaging and cadaveric pancreas samples, we simultaneously examine islet and extra-islet inflammation in human T1D. We identify four sub-states of inflamed islets characterized by the activation profiles of CD8+T cells enriched in islets relative to the surrounding tissue. We further find that the extra-islet space of lobules with extensive islet-infiltration differs from the extra-islet space of less infiltrated areas within the same tissue section. Finally, we identify lymphoid structures away from islets enriched in CD45RA+ T cells - a population also enriched in one of the inflamed islet sub-states. Together, these data help define the coordination between islets and the extra-islet pancreas in the pathogenesis of human T1D.

Leveraging artificial intelligence and machine learning to accelerate discovery of disease-modifying therapies in type 1 diabetes

Progress in developing therapies for the maintenance of endogenous insulin secretion in, or the prevention of, type 1 diabetes has been hindered by limited animal models, the length and cost of clinical trials, difficulties in identifying individuals who will progress faster to a clinical diagnosis of type 1 diabetes, and heterogeneous clinical responses in intervention trials. Classic placebo-controlled intervention trials often include monotherapies, broad participant populations and extended follow-up periods focused on clinical endpoints. While this approach remains the 'gold standard' of clinical research, efforts are underway to implement new approaches harnessing the power of artificial intelligence and machine learning to accelerate drug discovery and efficacy testing. Here, we review emerging approaches for repurposing agents used to treat diseases that share pathogenic pathways with type 1 diabetes and selecting synergistic combinations of drugs to maximise therapeutic efficacy. We discuss how emerging multi-omics technologies, including analysis of antigen processing and presentation to adaptive immune cells, may lead to the discovery of novel biomarkers and subsequent translation into antigen-specific immunotherapies. We also discuss the potential for using artificial intelligence to create 'digital twin' models that enable rapid in silico testing of personalised agents as well as dose determination. To conclude, we discuss some limitations of artificial intelligence and machine learning, including issues pertaining to model interpretability and bias, as well as the continued need for validation studies via confirmatory intervention trials.

Single-Cell Advances in Investigating and Understanding Chronic Kidney Disease and Diabetic Kidney Disease

Chronic kidney disease (CKD) and its subset diabetic kidney disease are progressive conditions that affect >850 million people worldwide. Diabetes, hypertension, and glomerulonephritis are the most common causes of CKD, which is associated with significant patient morbidity and an increased risk of cardiovascular events, such as heart failure, ultimately leading to premature death. Despite newly approved drugs, increasing evidence shows that patients respond to treatment differently given the complexity of disease heterogeneity and complicated pathophysiology. This review article presents an integrative approach to understanding and addressing CKD through the lens of precision medicine and therapeutics. Advancements in single-cell omics technologies and artificial intelligence can be leveraged to explore the intricate cellular mechanisms underlying CKD and diabetic kidney disease pathogenesis. Dissecting the cellular heterogeneity and identifying rare cell populations using single-cell approaches will facilitate uncovering novel therapeutic targets and biomarkers for personalized treatment strategies. Finally, we discuss the potential of artificial intelligence-driven analyses in predicting disease progression and treatment response, thereby paving the way for tailored interventions.

Network for Pancreatic Organ donors with Diabetes-Kidney: A Heterogenous Donor Cohort for the Investigation of Diabetic Kidney Disease Pathogenesis and Progression

Key Points

Lack of human kidney tissue availability and access has hindered molecular understanding of human diabetic kidney disease processes and disease heterogeneity. Preclinical validation of diabetic kidney disease targets using data from large, human kidney samples should reduce poor translatability to clinical trials. The Network for Pancreatic Organ donors with Diabetes-Kidney cohort is validated and available for use by the research community.

Background

The Network for Pancreatic Organ Donors with Diabetes-Kidney (nPOD-K) project was initiated to assess the feasibility of using kidneys from organ donors to enhance understanding of diabetic kidney disease (DKD) progression.

Methods

Traditional and digital pathology approaches were used to characterize the nPOD-K cohort. Periodic acid–Schiff- and hematoxylin and eosin-stained sections were used to manually examine and score each nPOD-K case. Brightfield and fluorescently labeled whole slide images of nPOD-K sections were used to train, validate, and test deep learning compartment segmentation and machine learning image analysis tools within Visiopharm software. These digital pathology tools were subsequently used to evaluate kidney cell-specific markers and pathological indicators.

Results

Digital quantitation of mesangial expansion, tubular atrophy, kidney injury molecule-1 expression, cellular infiltration, and fibrosis index aligned with histological DKD classification, as defined by pathologists' review. Histological quantification confirmed loss of podocyte, endothelial, and tubular markers, correlating with DKD progression. Altered expression patterns of prominin-1, protein-tyrosine phosphatase receptor type O, and coronin 2B were validated, in agreement with reported literature.

Conclusions

The nPOD-K cohort provides a unique open resource opportunity to not only validate putative drug targets, but also better understand DKD pathophysiology. A broad range of pathogenesis can be visualized in each case, providing a simulated timeline of DKD progression. We conclude that organ donor-derived tissues serve as high-quality samples, provide a comprehensive view of tissue pathology, and address the need for human kidney tissues available for research.

Leveraging pre-trained machine learning models for islet quantification in type 1 diabetes

Human islets display a high degree of heterogeneity in terms of size, number, architecture, and endocrine cell-type compositions. An ever-increasing number of immunohistochemistry-stained whole slide images (WSIs) are available through the online pathology database of the Network for Pancreatic Organ donors with Diabetes (nPOD) program at the University of Florida (UF). We aimed to develop an enhanced machine learning-assisted WSI analysis workflow to utilize the nPOD resource for analysis of endocrine cell heterogeneity in the natural history of type 1 diabetes (T1D) in comparison to donors without diabetes. To maximize usability, the user-friendly open-source software QuPath was selected for the main interface. The WSI data were analyzed with two pre-trained machine learning models (i.e., Segment Anything Model (SAM) and QuPath's pixel classifier), using the UF high-performance-computing cluster, HiPerGator. SAM was used to define precise endocrine cell and cell grouping boundaries (with an average quality score of 0.91 per slide), and the artificial neural network-based pixel classifier was applied to segment areas of insulin- or glucagon-stained cytoplasmic regions within each endocrine cell. An additional script was developed to automatically count CD3+ cells inside and within 20 μm of each islet perimeter to quantify the number of islets with inflammation (i.e., CD3+ T-cell infiltration). Proof-of-concept analysis was performed to test the developed workflow in 12 subjects using 24 slides. This open-source machine learning-assisted workflow enables rapid and high throughput determinations of endocrine cells, whether as single cells or within groups, across hundreds of slides. It is expected that the use of this workflow will accelerate our understanding of endocrine cell and islet heterogeneity in the context of T1D endotypes and pathogenesis.

The Extra-Islet Pancreas Supports Autoimmunity in Human Type 1 Diabetes

In autoimmune Type 1 diabetes (T1D), immune cells infiltrate and destroy the islets of Langerhans - islands of endocrine tissue dispersed throughout the pancreas. However, the contribution of cellular programs outside islets to insulitis is unclear. Here, using CO-Detection by indEXing (CODEX) tissue imaging and cadaveric pancreas samples, we simultaneously examine islet and extra-islet inflammation in human T1D. We identify four sub-states of inflamed islets characterized by the activation profiles of CD8 + T cells enriched in islets relative to the surrounding tissue. We further find that the extra-islet space of lobules with extensive islet-infiltration differs from the extra-islet space of less infiltrated areas within the same tissue section. Finally, we identify lymphoid structures away from islets enriched in CD45RA + T cells - a population also enriched in one of the inflamed islet sub-states. Together, these data help define the coordination between islets and the extra-islet pancreas in the pathogenesis of human T1D.

Dysfunctional β-cell longevity in diabetes relies on energy conservation and positive epistasis

Long-lived PFKFB3-expressing β-cells are dysfunctional partly because of prevailing glycolysis that compromises metabolic coupling of insulin secretion. Their accumulation in type 2 diabetes (T2D) appears to be related to the loss of apoptotic competency of cell fitness competition that maintains islet function by favoring constant selection of healthy "winner" cells. To investigate how PFKFB3 can disguise the competitive traits of dysfunctional "loser" β-cells, we analyzed the overlap between human β-cells with bona fide "loser signature" across diabetes pathologies using the HPAP scRNA-seq and spatial transcriptomics of PFKFB3-positive β-cells from nPOD T2D pancreata. The overlapping transcriptional profile of "loser" β-cells was represented by down-regulated ribosomal biosynthesis and genes encoding for mitochondrial respiration. PFKFB3-positive "loser" β-cells had the reduced expression of HLA class I and II genes. Gene-gene interaction analysis revealed that PFKFB3 rs1983890 can interact with the anti-apoptotic gene MAIP1 implicating positive epistasis as a mechanism for prolonged survival of "loser" β-cells in T2D. Inhibition of PFKFB3 resulted in the clearance of dysfunctional "loser" β-cells leading to restored glucose tolerance in the mouse model of T2D.

Quantitative analysis of islet prohormone convertase 1/3 expression in human pancreas donors with diabetes

AIMS/HYPOTHESIS

Islet prohormone-processing enzymes convert peptide hormone precursors to mature hormones. Defective beta cell prohormone processing and the release of incompletely processed peptide hormones are observed prior to the onset of diabetes, yet molecular mechanisms underlying impaired prohormone processing during the development of diabetes remains largely unknown. Previous studies have shown that prohormone convertase 1/3 (PC1/3) protein and mRNA expression levels are reduced in whole islets from donors with type 1 diabetes, although whether PC1/3-mediated prohormone processing in alpha and beta cells is disrupted in type 1 diabetes remained to be explored. Herein, we aimed to analyse the expression of PC1/3 in islets from non-diabetic donors, autoantibody-positive donors and donors diagnosed with type 1 diabetes or type 2 diabetes.

METHODS

Immunostaining and high-dimensional image analysis were performed on pancreatic sections from a cross-sectional cohort of 54 donors obtained from the Network for Pancreatic Organ Donors with Diabetes (nPOD) repository, to evaluate PC1/3 expression patterns in islet alpha, beta and delta cells at different stages of diabetes.

RESULTS

Alpha and beta cell morphology were altered in donors with type 1 diabetes, including decreased alpha and beta cell size. As expected, the insulin-positive and PC1/3-positive areas in the islets were both reduced, and this was accompanied by a reduced percentage of PC1/3-positive and insulin-positive/PC1/3-positive cells in islets. PC1/3 and insulin co-localisation was also reduced. The glucagon-positive area, as well as the percentage of glucagon-positive and glucagon-positive/PC1/3-positive cells in islets, was increased. PC1/3 and glucagon co-localisation was also increased in donors with type 1 diabetes. The somatostatin-positive cell area and somatostatin staining intensity were elevated in islets from donors with recent-onset type 1 diabetes.

CONCLUSIONS/INTERPRETATION

Our high-resolution histomorphological analysis of human pancreatic islets from donors with and without diabetes has uncovered details of the cellular origin of islet prohormone peptide processing defects. Reduced beta cell PC1/3 and increased alpha cell PC1/3 in islets from donors with type 1 diabetes pinpointed the functional deterioration of beta cells and the concomitant potential increase in PC1/3 usage for prohormone processing in alpha cells during the pathogenesis of type 1 diabetes. Our finding of PC1/3 loss in beta cells may inform the discovery of new prohormone biomarkers as indicators of beta cell dysfunction, and the finding of elevated PC1/3 expression in alpha cells may encourage the design of therapeutic targets via leveraging alpha cell adaptation in diabetes.

Genetic association and machine learning improves discovery and prediction of type 1 diabetes

Type 1 diabetes (T1D) has a large genetic component, and expanded genetic studies of T1D can lead to novel biological and therapeutic discovery and improved risk prediction. In this study, we performed genetic association and fine-mapping analyses in 817,718 European ancestry samples genome-wide and 29,746 samples at the MHC locus, which identified 165 independent risk signals for T1D of which 19 were novel. We used risk variants to train a machine learning model (named T1GRS) to predict T1D, which highly differentiated T1D from non-disease and type 2 diabetes (T2D) in Europeans as well as African Americans at or beyond the level of current standards. We identified extensive non-linear interactions between risk loci in T1GRS, for example between HLA-DQB1*57 and INS, coding and non-coding HLA alleles, and DEXI, INS and other beta cell loci, that provided mechanistic insight and improved risk prediction. T1D individuals formed distinct clusters based on genetic features from T1GRS which had significant differences in age of onset, HbA1c, and renal disease severity. Finally, we provided T1GRS in formats to enhance accessibility of risk prediction to any user and computing environment. Overall, the improved genetic discovery and prediction of T1D will have wide clinical, therapeutic, and research applications.

Cracking the type 1 diabetes code: Genes, microbes, immunity, and the early life environment

Type 1 diabetes (T1D) results from a complex interplay of genetic predisposition, immunological dysregulation, and environmental triggers, that culminate in the destruction of insulin-secreting pancreatic β cells. This review provides a comprehensive examination of the multiple factors underpinning T1D pathogenesis, to elucidate key mechanisms and potential therapeutic targets. Beginning with an exploration of genetic risk factors, we dissect the roles of human leukocyte antigen (HLA) haplotypes and non-HLA gene variants associated with T1D susceptibility. Mechanistic insights gleaned from the NOD mouse model provide valuable parallels to the human disease, particularly immunological intricacies underlying β cell-directed autoimmunity. Immunological drivers of T1D pathogenesis are examined, highlighting the pivotal contributions of both effector and regulatory T cells and the multiple functions of B cells and autoantibodies in β-cell destruction. Furthermore, the impact of environmental risk factors, notably modulation of host immune development by the intestinal microbiome, is examined. Lastly, the review probes human longitudinal studies, unveiling the dynamic interplay between mucosal immunity, systemic antimicrobial antibody responses, and the trajectories of T1D development. Insights garnered from these interconnected factors pave the way for targeted interventions and the identification of biomarkers to enhance T1D management and prevention strategies.

Impaired islet function and normal exocrine enzyme secretion occur with low inter-regional variation in type 1 diabetes

Histopathological heterogeneity in the human pancreas is well documented; however, functional evidence at the tissue level is scarce. Herein, we investigate in situ glucose-stimulated islet and carbachol-stimulated acinar cell secretion across the pancreas head (PH), body (PB), and tail (PT) regions in donors without diabetes (ND; n = 15), positive for one islet autoantibody (1AAb+; n = 7), and with type 1 diabetes (T1D; <14 months duration, n = 5). Insulin, glucagon, pancreatic amylase, lipase, and trypsinogen secretion along with 3D tissue morphometrical features are comparable across regions in ND. In T1D, insulin secretion and beta-cell volume are significantly reduced within all regions, while glucagon and enzymes are unaltered. Beta-cell volume is lower despite normal insulin secretion in 1AAb+, resulting in increased volume-adjusted insulin secretion versus ND. Islet and acinar cell secretion in 1AAb+ are consistent across the PH, PB, and PT. This study supports low inter-regional variation in pancreas slice function and, potentially, increased metabolic demand in 1AAb+.

HumanIslets: An integrated platform for human islet data access and analysis

Comprehensive molecular and cellular phenotyping of human islets can enable deep mechanistic insights for diabetes research. We established the Human Islet Data Analysis and Sharing (HI-DAS) consortium to advance goals in accessibility, usability, and integration of data from human islets isolated from donors with and without diabetes at the Alberta Diabetes Institute (ADI) IsletCore. Here we introduce HumanIslets.com, an open resource for the research community. This platform, which presently includes data on 547 human islet donors, allows users to access linked datasets describing molecular profiles, islet function and donor phenotypes, and to perform various statistical and functional analyses at the donor, islet and single-cell levels. As an example of the analytic capacity of this resource we show a dissociation between cell culture effects on transcript and protein expression, and an approach to correct for exocrine contamination found in hand-picked islets. Finally, we provide an example workflow and visualization that highlights links between type 2 diabetes status, SERCA3b Ca2+-ATPase levels at the transcript and protein level, insulin secretion and islet cell phenotypes. HumanIslets.com provides a growing and adaptable set of resources and tools to support the metabolism and diabetes research community.

Germline-like TCR-α chains shared between autoreactive T cells in blood and pancreas

Human type 1 diabetes (T1D) is caused by autoimmune attack on the insulin-producing pancreatic beta cells by islet antigen-reactive T cells. How human islet antigen-reactive (IAR) CD4+ memory T cells from peripheral blood affect T1D progression in the pancreas is poorly understood. Here, we aim to determine if IAR T cells in blood could be detected in pancreas. We identify paired αβ (TRA/TRB) T cell receptors (TCRs) in IAR T cells from the blood of healthy, at-risk, new-onset, and established T1D donors, and measured sequence overlap with TCRs in pancreata from healthy, at risk and T1D organ donors. We report extensive TRA junction sharing between IAR T cells and pancreas-infiltrating T cells (PIT), with perfect-match or single-mismatch TRA junction amino acid sequences comprising ~29% total unique IAR TRA junctions (942/3,264). PIT-matched TRA junctions were largely public and enriched for TRAV41 usage, showing significant nucleotide sequence convergence, increased use of germline-encoded versus non-templated residues in epitope engagement, and a potential for cross-reactivity. Our findings thus link T cells with distinctive germline-like TRA chains in the peripheral blood with T cells in the pancreas.

The immunology of type 1 diabetes

Following the seminal discovery of insulin a century ago, treatment of individuals with type 1 diabetes (T1D) has been largely restricted to efforts to monitor and treat metabolic glucose dysregulation. The recent regulatory approval of the first immunotherapy that targets T cells as a means to delay the autoimmune destruction of pancreatic β-cells highlights the critical role of the immune system in disease pathogenesis and tends to pave the way for other immune-targeted interventions for T1D. Improving the efficacy of such interventions across the natural history of the disease will probably require a more detailed understanding of the immunobiology of T1D, as well as technologies to monitor residual β-cell mass and function. Here we provide an overview of the immune mechanisms that underpin the pathogenesis of T1D, with a particular emphasis on T cells.

NKX2-2 based nuclei sorting on frozen human archival pancreas enables the enrichment of islet endocrine populations for single-nucleus RNA sequencing

BACKGROUND

Current approaches to profile the single-cell transcriptomics of human pancreatic endocrine cells almost exclusively rely on freshly isolated islets. However, human islets are limited in availability. Furthermore, the extensive processing steps during islet isolation and subsequent single cell dissolution might alter gene expressions. In this work, we report the development of a single-nucleus RNA sequencing (snRNA-seq) approach with targeted islet cell enrichment for endocrine-population focused transcriptomic profiling using frozen archival pancreatic tissues without islet isolation.

RESULTS

We cross-compared five nuclei isolation protocols and selected the citric acid method as the best strategy to isolate nuclei with high RNA integrity and low cytoplasmic contamination from frozen archival human pancreata. We innovated fluorescence-activated nuclei sorting based on the positive signal of NKX2-2 antibody to enrich nuclei of the endocrine population from the entire nuclei pool of the pancreas. Our sample preparation procedure generated high-quality single-nucleus gene-expression libraries while preserving the endocrine population diversity. In comparison with single-cell RNA sequencing (scRNA-seq) library generated with live cells from freshly isolated human islets, the snRNA-seq library displayed comparable endocrine cellular composition and cell type signature gene expression. However, between these two types of libraries, differential enrichments of transcripts belonging to different functional classes could be observed.

CONCLUSIONS

Our work fills a technological gap and helps to unleash frozen archival pancreatic tissues for molecular profiling targeting the endocrine population. This study opens doors to retrospective mappings of endocrine cell dynamics in pancreatic tissues of complex histopathology. We expect that our protocol is applicable to enrich nuclei for transcriptomics studies from various populations in different types of frozen archival tissues.

Factors Governing B Cell Recognition of Autoantigen and Function in Type 1 Diabetes

Islet autoantibodies predict type 1 diabetes (T1D) but can be transient in murine and human T1D and are not thought to be directly pathogenic. Rather, these autoantibodies signal B cell activity as antigen-presenting cells (APCs) that present islet autoantigen to diabetogenic T cells to promote T1D pathogenesis. Disrupting B cell APC function prevents T1D in mouse models and has shown promise in clinical trials. Autoantigen-specific B cells thus hold potential as sophisticated T1D biomarkers and therapeutic targets. B cell receptor (BCR) somatic hypermutation is a mechanism by which B cells increase affinity for islet autoantigen. High-affinity B and T cell responses are selected in protective immune responses, but immune tolerance mechanisms are known to censor highly autoreactive clones in autoimmunity, including T1D. Thus, different selection rules often apply to autoimmune disease settings (as opposed to protective host immunity), where different autoantigen affinity ceilings are tolerated based on variations in host genetics and environment. This review will explore what is currently known regarding B cell signaling, selection, and interaction with T cells to promote T1D pathogenesis.

Influence of sphingolipid enzymes on blood glucose levels, development of diabetes, and involvement of pericytes

AIMS

Sulfatide is a chaperone for insulin manufacturing in beta cells. Here we explore whether the blood glucose values normally could be associated with this sphingolipid and especially two of its building enzymes CERS2 and CERS6. Both T1D and T2D have low blood sulfatide levels, and insulin resistance on beta cells at clinical diagnosis. Furthermore, we examined islet pericytes for sulfatide, and beta-cell receptors for GLP-1, both of which are related to the insulin production.

MATERIALS AND METHODS

We examined mRNA levels in islets from the DiViD and nPOD studies, performed genetic association analyses, and histologically investigated pericytes in the islets for sulfatide.

RESULTS

Polymorphisms of the gene encoding the CERS6 enzyme responsible for synthesising dihydroceramide, a precursor to sulfatide, are associated with random blood glucose values in non-diabetic persons. This fits well with our finding of sulfatide in pericytes in the islets, which regulates the capillary blood flow in the islets of Langerhans, which is important for oxygen supply to insulin production. In the islets of newly diagnosed T1D patients, we observed low levels of GLP-1 receptors; this may explain the insulin resistance in their beta cells and their low insulin production. In T2D patients, we identified associated polymorphisms in both CERS2 and CERS6.

CONCLUSIONS

Here, we describe several polymorphisms in sulfatide enzymes related to blood glucose levels and HbA1c in non-diabetic individuals. Islet pericytes from such persons contain sulfatide. Furthermore, low insulin secretion in newly diagnosed T1D may be explained by beta-cell insulin resistance due to low levels of GLP-1 receptors.

Impaired islet function with normal exocrine enzyme secretion is consistent across the head, body, and tail pancreas regions in type 1 diabetes

Histopathological heterogeneity in human pancreas has been well documented; however, functional evidence at the tissue level is scarce. Herein we investigated in situ glucose-stimulated islet and carbachol-stimulated acinar cell secretion across the pancreas head (PH), body (PB), and tail (PT) regions in no diabetes (ND, n=15), single islet autoantibody-positive (1AAb+, n=7), and type 1 diabetes donors (T1D, <14 months duration, n=5). Insulin, glucagon, pancreatic amylase, lipase, and trypsinogen secretion along with 3D tissue morphometrical features were comparable across the regions in ND. In T1D, insulin secretion and beta-cell volume were significantly reduced within all regions, while glucagon and enzymes were unaltered. Beta-cell volume was lower despite normal insulin secretion in 1AAb+, resulting in increased volume-adjusted insulin secretion versus ND. Islet and acinar cell secretion in 1AAb+ were consistent across PH, PB and PT. This study supports low inter-regional variation in pancreas slice function and potentially, increased metabolic demand in 1AAb+.

Insulitis in human type 1 diabetes: lessons from an enigmatic lesion

Type 1 diabetes is caused by a deficiency of insulin secretion which has been considered traditionally as the outcome of a precipitous decline in the viability of β-cells in the islets of Langerhans, brought about by autoimmune-mediated attack. Consistent with this, various classes of lymphocyte, as well as cells of the innate immune system have been found in association with islets during disease progression. However, analysis of human pancreas from subjects with type 1 diabetes has revealed that insulitis is often less intense than in equivalent animal models of the disease and can affect many fewer islets than expected, at disease onset. This is especially true in subjects developing type 1 diabetes in, or beyond, their teenage years. Such studies imply that both the phenotype and the number of immune cells present within insulitic lesions can vary among individuals in an age-dependent manner. Additionally, the influent lymphocytes are often mainly arrayed peripherally around islets rather than gaining direct access to the endocrine cell core. Thus, insulitis remains an enigmatic phenomenon in human pancreas and this review seeks to explore the current understanding of its likely role in the progression of type 1 diabetes.

Bridging the Gap: Pancreas Tissue Slices From Organ and Tissue Donors for the Study of Diabetes Pathogenesis

Over the last two decades, increased availability of human pancreatic tissues has allowed for major expansions in our understanding of islet biology in health and disease. Indeed, studies of fixed and frozen pancreatic tissues, as well as efforts using viable isolated islets obtained from organ donors, have provided significant insights toward our understanding of diabetes. However, the procedures associated with islet isolation result in distressed cells that have been removed from any surrounding influence. The pancreas tissue slice technology was developed as an in situ approach to overcome certain limitations associated with studies on isolated islets or fixed tissue. In this Perspective, we discuss the value of this novel platform and review how pancreas tissue slices, within a short time, have been integrated in numerous studies of rodent and human islet research. We show that pancreas tissue slices allow for investigations in a less perturbed organ tissue environment, ranging from cellular processes, over peri-islet modulations, to tissue interactions. Finally, we discuss the considerations and limitations of this technology in its future applications. We believe the pancreas tissue slices will help bridge the gap between studies on isolated islets and cells to the systemic conditions by providing new insight into physiological and pathophysiological processes at the organ level.

ARTICLE HIGHLIGHTS

Human pancreas tissue slices represent a novel platform to study human islet biology in close to physiological conditions. Complementary to established technologies, such as isolated islets, single cells, and histological sections, pancreas tissue slices help bridge our understanding of islet physiology and pathophysiology from single cell to intact organ. Diverse sources of viable human pancreas tissue, each with distinct characteristics to be considered, are available to use in tissue slices for the study of diabetes pathogenesis.

Type 1 diabetes in the pancreas: A histological perspective

AIMS

This review aims to introduce research in the pancreas to a broader audience. The pancreas is a heterocrine gland residing deep within our abdominal cavity. It is the home to our islets, which play a pivotal role in regulating metabolic homeostasis. Due to its structure and location, it is an impossible organ to study, in molecular detail, in living humans, and yet, understanding the pancreas is critical if we aim to characterise the immunopathology of type 1 diabetes (T1D) and one day prevent the triggering of the autoimmune attack associated with ß-cell demise.

METHODS

Over a 100 years ago, we began studying pancreatic histology using cadaveric samples and clever adaptations to microscopes. As histologists, some may say nothing much has changed. Nevertheless, our microscopes can now interrogate multiple proteins at molecular resolution. Images of pancreas sections are no longer constrained to a single field of view and can capture a thousands and thousands of cells. AI-image-analysis packages can analyse these massive data sets offering breakthrough findings.

CONCLUSION

This narrative review will provide an overview of pancreatic anatomy, and the importance of research focused on the pancreas in T1D. It will range from histological breakthroughs to briefly discussing the challenges associated with characterising the organ. I shall briefly introduce a selection of the available global biobanks and touch on the distinct pancreatic endotypes that differ immunologically and in ß-cell behaviour. Finally, I will introduce the idea of developing a collaborative tool aimed at developing a cohesive framework for characterising heterogeneity and stratifying endotypes in T1D more readily.

Imaging in Type 1 Diabetes, Current Perspectives and Directions

Type 1 diabetes (T1D) is characterized by the autoimmune-mediated attack of insulin-producing beta cells in the pancreas, leading to reliance on exogenous insulin to control a patient's blood glucose levels. As progress is being made in understanding the pathophysiology of the disease and how to better develop therapies to treat it, there is an increasing need for monitoring technologies to quantify beta cell mass and function throughout T1D progression and beta cell replacement therapy. Molecular imaging techniques offer a possible solution through both radiologic and non-radiologic means including positron emission tomography, magnetic resonance imaging, electron paramagnetic resonance imaging, and spatial omics. This commentary piece outlines the role of molecular imaging in T1D research and highlights the need for further applications of such methodologies in T1D.

Self-reactive germline-like TCR alpha chains shared between blood and pancreas

Human islet antigen reactive CD4 + memory T cells (IAR T cells) from peripheral blood have been studied extensively for their role in the pathogenesis of autoimmune type 1 diabetes (T1D). However, IAR T cells are rare, and it remains poorly understood how they affect T1D progression in the pancreas. Using single cell RNA-sequencing coupled with a multiplexed activation induced marker (AIM) enrichment assay, we identified paired TCR alpha/beta (TRA/TRB) T cell receptors (TCRs) in IAR T cells from the blood of healthy, at-risk, new onset, and established T1D donors. Using TCR sequences as barcodes, we measured infiltration of IAR T cells from blood into pancreas of organ donors with and without T1D. We detected extensive TCR sharing between IAR T cells from peripheral blood and pancreatic infiltrating T cells (PIT), with perfectly matched or single mismatched TRA junctions and J gene regions, comprising ~ 34% of unique IAR TCRs. PIT-matching IAR T cells had public TRA chains that showed increased use of germline-encoded residues in epitope engagement and a propensity for cross-reactivity. The link with T cells in the pancreas implicates autoreactive IAR T cells with shared TRA junctions and increased levels in blood with the prediabetic and new onset phases of T1D progression.

The role of the interferon/JAK-STAT axis in driving islet HLA-I hyperexpression in type 1 diabetes

The hyperexpression of human leukocyte antigen class I (HLA-I) molecules on pancreatic beta-cells is widely accepted as a hallmark feature of type 1 diabetes pathogenesis. This response is important clinically since it may increase the visibility of beta-cells to autoreactive CD8+ T-cells, thereby accelerating disease progression. In this review, key factors which drive HLA-I hyperexpression will be explored, and their clinical significance examined. It is established that the presence of residual beta-cells is essential for HLA-I hyperexpression by islet cells at all stages of the disease. We suggest that the most likely drivers of this process are interferons released from beta-cells (type I or III interferon; possibly in response to viral infection) or those elaborated from influent, autoreactive immune cells (type II interferon). In both cases, Janus Kinase/Signal Transducer and Activator of Transcription (JAK/STAT) pathways will be activated to induce the downstream expression of interferon stimulated genes. A variety of models have highlighted that HLA-I expression is enhanced in beta-cells in response to interferons, and that STAT1, STAT2 and interferon regulatory factor 9 (IRF9) play key roles in mediating these effects (depending on the species of interferon involved). Importantly, STAT1 expression is elevated in the beta-cells of donors with recent-onset type I diabetes, and this correlates with HLA-I hyperexpression on an islet-by-islet basis. These responses can be replicated in vitro, and we consider that chronically elevated STAT1 may have a role in maintaining HLA-I hyperexpression. However, other data have highlighted that STAT2-IRF9 may also be critical to this process. Thus, a better understanding of how these factors regulate HLA-I under chronically stimulated conditions needs to be gathered. Finally, JAK inhibitors can target interferon signaling pathways to diminish HLA-I expression in mouse models. It seems probable that these agents may also be effective in patients; diminishing HLA-I hyperexpression on islets, reducing the visibility of beta-cells to the immune system and ultimately slowing disease progression. The first clinical trials of selective JAK inhibitors are underway, and the outcomes should have important implications for type 1 diabetes clinical management.

Heterogeneity and endotypes in type 1 diabetes mellitus

Despite major advances over the past decade, prevention and treatment of type 1 diabetes mellitus (T1DM) remain suboptimal, with large and unexplained variations in individual responses to interventions. The current classification schema for diabetes mellitus does not capture the complexity of this disease or guide clinical management effectively. One of the approaches to achieve the goal of applying precision medicine in diabetes mellitus is to identify endotypes (that is, well-defined subtypes) of the disease each of which has a distinct aetiopathogenesis that might be amenable to specific interventions. Here, we describe epidemiological, clinical, genetic, immunological, histological and metabolic differences within T1DM that, together, suggest heterogeneity in its aetiology and pathogenesis. We then present the emerging endotypes and their impact on T1DM prediction, prevention and treatment.

Alpha cell receptor for advanced glycation end products associate with glucagon expression in type 1 diabetes

Hypoglycemia in type 1 diabetes associates with changes in the pancreatic islet α cells, where the receptor for advanced glycation end products (RAGE) is highly expressed. This study compared islet RAGE expression in donors without diabetes, those at risk of, and those with type 1 diabetes. Laser-dissected islets were subject to RNA bioinformatics and adjacent pancreatic tissue were assessed by confocal microscopy. We found that islets from type 1 diabetes donors had differential expression of the RAGE gene (AGER) and its correlated genes, based on glucagon expression. Random forest machine learning revealed that AGER was the most important predictor for islet glucagon levels. Conversely, a generalized linear model identified that glucagon expression could be predicted by expression of RAGE signaling molecules, its ligands and enzymes that create or clear RAGE ligands. Confocal imaging co-localized RAGE, its ligands and signaling molecules to the α cells. Half of the type 1 diabetes cohort comprised of adolescents and a patient with history of hypoglycemia-all showed an inverse relationship between glucagon and RAGE. These data confirm an association between glucagon and islet RAGE, its ligands and signaling pathways in type 1 diabetes, which warrants functional investigation into a role for RAGE in hypoglycemia.

The extent and magnitude of islet T cell infiltration as powerful tools to define the progression to type 1 diabetes

AIMS/HYPOTHESIS

Insulitis is not present in all islets, and it is elusive in humans. Although earlier studies focused on islets that fulfilled certain criteria (e.g. ≥15 CD45+ cells or ≥6 CD3+ cells), there is a fundamental lack of understanding of the infiltration dynamics in terms of its magnitude (i.e. how much) and extent (i.e. where). Here, we aimed to perform an in-depth characterisation of T cell infiltration by investigating islets with moderate (1-5 CD3+ cells) and high (≥6 CD3+ cells) infiltration in individuals with and without type 1 diabetes.

METHODS

Pancreatic tissue sections from 15 non-diabetic, eight double autoantibody-positive and ten type 1 diabetic (0-2 years of disease duration) organ donors were obtained from the Network for Pancreatic Organ Donors with Diabetes, and stained for insulin, glucagon, CD3 and CD8 by immunofluorescence. T cell infiltration was quantified in a total of 8661 islets using the software QuPath. The percentage of infiltrated islets and islet T cell density were calculated. To help standardise the analysis of T cell infiltration, we used cell density data to develop a new T cell density threshold capable of differentiating non-diabetic and type 1 diabetic donors.

RESULTS

Our analysis revealed that 17.1% of islets in non-diabetic donors, 33% of islets in autoantibody-positive and 32.5% of islets in type 1 diabetic donors were infiltrated by 1 to 5 CD3+ cells. Islets infiltrated by ≥6 CD3+ cells were rare in non-diabetic donors (0.4%) but could be found in autoantibody-positive (4.5%) and type 1 diabetic donors (8.2%). CD8+ and CD8- populations followed similar patterns. Likewise, T cell density was significantly higher in the islets of autoantibody-positive donors (55.4 CD3+ cells/mm2) and type 1 diabetic donors (74.8 CD3+ cells/mm2) compared with non-diabetic individuals (17.3 CD3+ cells/mm2), which was accompanied by higher exocrine T cell density in type 1 diabetic individuals. Furthermore, we showed that the analysis of a minimum of 30 islets and the use of a reference mean value for T cell density of 30 CD3+ cells/mm2 (the 30-30 rule) can differentiate between non-diabetic and type 1 diabetic donors with high specificity and sensitivity. In addition, it can classify autoantibody-positive individuals as non-diabetic or type 1 diabetic-like.

CONCLUSIONS/INTERPRETATION

Our data indicates that the proportion of infiltrated islets and T cell density change dramatically during the course of type 1 diabetes, and these changes can be already observed in double autoantibody-positive individuals. This suggests that, as disease progresses, T cell infiltration extends throughout the pancreas, reaching the islets and exocrine compartment. While it predominantly targets insulin-containing islets, large accumulations of cells are rare. Our study fulfils the need to further understand T cell infiltration, not only after diagnosis but also in individuals with diabetes-related autoantibodies. Furthermore, the development and application of new analytical tools based on T cell infiltration, like the 30-30 rule, will allow us to correlate islet infiltration with demographic and clinical variables with the aim of identifying individuals at the very early stages of the disease.

A genomic data archive from the Network for Pancreatic Organ donors with Diabetes

The Network for Pancreatic Organ donors with Diabetes (nPOD) is the largest biorepository of human pancreata and associated immune organs from donors with type 1 diabetes (T1D), maturity-onset diabetes of the young (MODY), cystic fibrosis-related diabetes (CFRD), type 2 diabetes (T2D), gestational diabetes, islet autoantibody positivity (AAb+), and without diabetes. nPOD recovers, processes, analyzes, and distributes high-quality biospecimens, collected using optimized standard operating procedures, and associated de-identified data/metadata to researchers around the world. Herein describes the release of high-parameter genotyping data from this collection. 372 donors were genotyped using a custom precision medicine single nucleotide polymorphism (SNP) microarray. Data were technically validated using published algorithms to evaluate donor relatedness, ancestry, imputed HLA, and T1D genetic risk score. Additionally, 207 donors were assessed for rare known and novel coding region variants via whole exome sequencing (WES). These data are publicly-available to enable genotype-specific sample requests and the study of novel genotype:phenotype associations, aiding in the mission of nPOD to enhance understanding of diabetes pathogenesis to promote the development of novel therapies.

Milder loss of insulin-containing islets in individuals with type 1 diabetes and type 2 diabetes-associated TCF7L2 genetic variants

AIMS/HYPOTHESIS

TCF7L2 variants are the strongest genetic risk factor for type 2 diabetes. In individuals with type 1 diabetes, these variants are associated with a higher C-peptide AUC, a lower glucose AUC during an OGTT, single autoantibody positivity near diagnosis, particularly in individuals older than 12 years of age, and a lower frequency of type 1 diabetes-associated HLA genotypes. Based on initial observations from clinical cohorts, we tested the hypothesis that type 2 diabetes-predisposing TCF7L2 genetic variants are associated with a higher percentage of residual insulin-containing cells (ICI%) in pancreases of donors with type 1 diabetes, by examining genomic data and pancreatic tissue samples from the Network for Pancreatic Organ donors with Diabetes (nPOD) programme.

METHODS

We analysed nPOD donors with type 1 diabetes (n=110; mean±SD age at type 1 diabetes onset 12.2±7.9 years, mean±SD diabetes duration 15.3±13.7 years, 53% male, 80% non-Hispanic White, 12.7% African American, 7.3% Hispanic) using data pertaining to residual beta cell number; quantified islets containing insulin-positive beta cells in pancreatic tissue sections; and expressed these values as a percentage of the total number of islets from each donor (mean ± SD ICI% 9.8±21.5, range 0-92.2).

RESULTS

Donors with a high ICI% (≥5) (n=30; 27%) vs a low ICI% (<5) (n=80; 73%) were older at onset (15.3±6.9 vs 11.1±8 years, p=0.013), had a shorter diabetes duration at donor tissue procurement (7.0±7.4 vs 18.5±14.3 years, p<0.001), a higher African ancestry score (0.2±0.3 vs 0.1±0.2, p=0.043) and a lower European ancestry score (0.7±0.3 vs 0.9±0.3, p=0.023). After adjustment for age of onset (p=0.105), diabetes duration (p<0.001), BMI z score (p=0.145), sex (p=0.351) and African American race (p=0.053), donors with the TCF7L2 rs7903146 T allele (TC or TT, 45.5%) were 2.93 times (95% CI 1.02, 8.47) more likely to have a high ICI% than those without it (CC) (p=0.047).

CONCLUSIONS/INTERPRETATION

Overall, these data support the presence of a type 1 diabetes endotype associated with a genetic factor that predisposes to type 2 diabetes, with donors in this category exhibiting less severe beta cell loss. It is possible that in these individuals the disease pathogenesis may include mechanisms associated with type 2 diabetes and thus this may provide an explanation for the poor response to immunotherapies to prevent type 1 diabetes or its progression in a subset of individuals. If so, strategies that target both type 1 diabetes and type 2 diabetes-associated factors when they are present may increase the success of prevention and treatment in these individuals.

Advanced Glycation End Products and Inflammation in Type 1 Diabetes Development

Type 1 diabetes (T1D) is an autoimmune disease in which the β-cells of the pancreas are attacked by the host's immune system, ultimately resulting in hyperglycemia. It is a complex multifactorial disease postulated to result from a combination of genetic and environmental factors. In parallel with increasing prevalence of T1D in genetically stable populations, highlighting an environmental component, consumption of advanced glycation end products (AGEs) commonly found in in Western diets has increased significantly over the past decades. AGEs can bind to cell surface receptors including the receptor for advanced glycation end products (RAGE). RAGE has proinflammatory roles including in host-pathogen defense, thereby influencing immune cell behavior and can activate and cause proliferation of immune cells such as islet infiltrating CD8+ and CD4+ T cells and suppress the activity of T regulatory cells, contributing to β-cell injury and hyperglycemia. Insights from studies of individuals at risk of T1D have demonstrated that progression to symptomatic onset and diagnosis can vary, ranging from months to years, providing a window of opportunity for prevention strategies. Interaction between AGEs and RAGE is believed to be a major environmental risk factor for T1D and targeting the AGE-RAGE axis may act as a potential therapeutic strategy for T1D prevention.

Non-coding variants disrupting a tissue-specific regulatory element in HK1 cause congenital hyperinsulinism

Gene expression is tightly regulated, with many genes exhibiting cell-specific silencing when their protein product would disrupt normal cellular function1. This silencing is largely controlled by non-coding elements, and their disruption might cause human disease2. We performed gene-agnostic screening of the non-coding regions to discover new molecular causes of congenital hyperinsulinism. This identified 14 non-coding de novo variants affecting a 42-bp conserved region encompassed by a regulatory element in intron 2 of the hexokinase 1 gene (HK1). HK1 is widely expressed across all tissues except in the liver and pancreatic beta cells and is thus termed a 'disallowed gene' in these specific tissues. We demonstrated that the variants result in a loss of repression of HK1 in pancreatic beta cells, thereby causing insulin secretion and congenital hyperinsulinism. Using epigenomic data accessed from public repositories, we demonstrated that these variants reside within a regulatory region that we determine to be critical for cell-specific silencing. Importantly, this has revealed a disease mechanism for non-coding variants that cause inappropriate expression of a disallowed gene.

PDE12 in type 1 diabetes

Type 1 diabetes (T1D) incidence is increased after COVID-19 infection in children under 18 years of age. Interferon-α-activated oligoadenylate synthetase and downstream RNAseL activation degrade pathogen RNA, but can also damage host RNA when RNAseL activity is poorly regulated. One such regulator is PDE12 which degrades 2'-5' oligoadenylate units, thereby decreasing RNAseL activity. We analyzed PDE12 expression in islets from non-diabetic donors, individuals with newly (median disease duration 35 days) and recently (5 years) diagnosed T1D, and individuals with type 2 diabetes (T2D). We also analyzed PDE12 single-nucleotide polymorphisms (SNPs) relative to T1D incidence. PDE12 expression was decreased in individuals with recently diagnosed T1D, in three of five individuals with newly diagnosed T1D, but not in individuals with T2D. Two rare PDE12 SNPs were found to have odds ratios of 1.80 and 1.74 for T1D development. We discuss whether decreased PDE12 expression after COVID-19 infection might be part of the up to 2.5-fold increase in T1D incidence.

Exocrine and Endocrine Inflammation Increases Cellular Replication in the Pancreatic Duct Compartment in Type 1 Diabetes

Context

We recently demonstrated increased cellular proliferation in the pancreatic ductal gland (PDG) compartment of organ donors with type 1 diabetes, suggesting that PDGs may harbor progenitor cells capable of pancreatic regeneration.

Objective

We evaluated the impact of diabetes and pancreatic inflammation on PDG and interlobular duct (ILD) cellular proliferation and profiles.

Methods

Endocrine hormone expression (insulin, glucagon, somatostatin, pancreatic polypeptide) and proliferating Ki67+ cells were localized within the PDG and ILD compartments by multicolor immunohistochemistry in cross-sections from the head, body, and tail regions of pancreata from those with (n = 31) or without type 1 diabetes (n = 43). Whole-slide scanned images were analyzed using digital pathology.

Results

Type 1 diabetes donors with insulitis or histologically identified pancreatitis had increased cellular replication in the ILD and PDG compartments. Interestingly, while cellular proliferation within the pancreatic ductal tree was significantly increased in type 1 diabetes (PDG mean = 3.36%, SEM = 1.06; ILD mean = 2.78%, SEM = 0.97) vs nondiabetes(ND) subjects without pancreatic inflammation (PDG mean = 1.18%, SEM = 0.42; ILD mean = 0.74%, SEM = 0.15, P < 0.05), robust replication was also observed in ND donors with pancreatitis (PDG mean = 3.52%, SEM = 1.33; ILD mean = 2.18%, SEM = 0.54, P < 0.05). Few polyhormonal cells were present in the ILD (type 1 diabetes = 0.04 ± 0.02%; ND = 0.08 ± 0.03%, P = 0.40) or PDG compartment (type 1 diabetes = 0.02 ± 0.01%; ND = 0.08 ± 0.13%, P = 0.63).

Conclusion

These data suggest that increased pancreatic ductal cell replication is associated with sustained pancreatic inflammation; however, as replicating cells were hormone-negative, PDGs do not appear to represent a compelling endogenous source of hormone-positive endocrine cells.

3D chromatin maps of the human pancreas reveal lineage-specific regulatory architecture of T2D risk

Three-dimensional (3D) chromatin organization maps help dissect cell-type-specific gene regulatory programs. Furthermore, 3D chromatin maps contribute to elucidating the pathogenesis of complex genetic diseases by connecting distal regulatory regions and genetic risk variants to their respective target genes. To understand the cell-type-specific regulatory architecture of diabetes risk, we generated transcriptomic and 3D epigenomic profiles of human pancreatic acinar, alpha, and beta cells using single-cell RNA-seq, single-cell ATAC-seq, and high-resolution Hi-C of sorted cells. Comparisons of these profiles revealed differential A/B (open/closed) chromatin compartmentalization, chromatin looping, and transcriptional factor-mediated control of cell-type-specific gene regulatory programs. We identified a total of 4,750 putative causal-variant-to-target-gene pairs at 194 type 2 diabetes GWAS signals using pancreatic 3D chromatin maps. We found that the connections between candidate causal variants and their putative target effector genes are cell-type stratified and emphasize previously underappreciated roles for alpha and acinar cells in diabetes pathogenesis.

Detection of Antiviral Tissue Responses and Increased Cell Stress in the Pancreatic Islets of Newly Diagnosed Type 1 Diabetes Patients: Results From the DiViD Study

Aims/hypothesis

The Diabetes Virus Detection (DiViD) study has suggested the presence of low-grade enteroviral infection in pancreatic tissue collected from six of six live adult patients newly diagnosed with type 1 diabetes. The present study aimed to compare the gene and protein expression of selected virally induced pathogen recognition receptors and interferon stimulated genes in islets from these newly diagnosed type 1 diabetes (DiViD) subjects vs age-matched non-diabetic (ND) controls.

Methods

RNA was extracted from laser-captured islets and Affymetrix Human Gene 2.0 ST arrays used to obtain gene expression profiles. Lists of differentially expressed genes were subjected to a data-mining pipeline searching for enrichment of canonical pathways, KEGG pathways, Gene Ontologies, transcription factor binding sites and other upstream regulators. In addition, the presence and localisation of specific viral response proteins (PKR, MxA and MDA5) were examined by combined immunofluorescent labelling in sections of pancreatic tissue.

Results

The data analysis and data mining process revealed a significant enrichment of gene ontologies covering viral reproduction and infectious cycles; peptide translation, elongation and initiation, as well as oxidoreductase activity. Enrichment was identified in the KEGG pathways for oxidative phosphorylation; ribosomal and metabolic activity; antigen processing and presentation and in canonical pathways for mitochondrial dysfunction, oxidative phosphorylation and EIF2 signaling. Protein Kinase R (PKR) expression did not differ between newly diagnosed type 1 diabetes and ND islets at the level of total RNA, but a small subset of β-cells displayed markedly increased PKR protein levels. These PKR+ β-cells correspond to those previously shown to contain the viral protein, VP1. RNA encoding MDA5 was increased significantly in newly diagnosed type 1 diabetes islets, and immunostaining of MDA5 protein was seen in α- and certain β-cells in both newly diagnosed type 1 diabetes and ND islets, but the expression was increased in β-cells in type 1 diabetes. In addition, an uncharacterised subset of synaptophysin positive, but islet hormone negative, cells expressed intense MDA5 staining and these were more prevalent in DiViD cases. MxA RNA was upregulated in newly diagnosed type 1 diabetes vs ND islets and MxA protein was detected exclusively in newly diagnosed type 1 diabetes β-cells.

Conclusion/interpretation

The gene expression signatures reveal that pathways associated with cellular stress and increased immunological activity are enhanced in islets from newly diagnosed type 1 diabetes patients compared to controls. The increases in viral response proteins seen in β-cells in newly diagnosed type 1 diabetes provide clear evidence for the activation of IFN signalling pathways. As such, these data strengthen the hypothesis that an enteroviral infection of islet β-cells contributes to the pathogenesis of type 1 diabetes.

Circulating C-Peptide Levels in Living Children and Young People and Pancreatic β-Cell Loss in Pancreas Donors Across Type 1 Diabetes Disease Duration

C-peptide declines in type 1 diabetes, although many long-duration patients retain low, but detectable levels. Histological analyses confirm that β-cells can remain following type 1 diabetes onset. We explored the trends observed in C-peptide decline in the UK Genetic Resource Investigating Diabetes (UK GRID) cohort (N = 4,079), with β-cell loss in pancreas donors from the network for Pancreatic Organ donors with Diabetes (nPOD) biobank and the Exeter Archival Diabetes Biobank (EADB) (combined N = 235), stratified by recently reported age at diagnosis endotypes (<7, 7-12, ≥13 years) across increasing diabetes durations. The proportion of individuals with detectable C-peptide declined beyond the first year after diagnosis, but this was most marked in the youngest age group (<1-year duration: age <7 years: 18 of 20 [90%], 7-12 years: 107 of 110 [97%], ≥13 years: 58 of 61 [95%] vs. 1-5 years postdiagnosis: <7 years: 172 of 522 [33%], 7-12 years: 604 of 995 [61%], ≥13 years: 225 of 289 [78%]). A similar profile was observed in β-cell loss, with those diagnosed at younger ages experiencing more rapid loss of islets containing insulin-positive (insulin+) β-cells <1 year postdiagnosis: age <7 years: 23 of 26 (88%), 7-12 years: 32 of 33 (97%), ≥13 years: 22 of 25 (88%) vs. 1-5 years postdiagnosis: <7 years: 1 of 12 (8.3%), 7-12 years: 7 of 13 (54%), ≥13 years: 7 of 8 (88%). These data should be considered in the planning and interpretation of intervention trials designed to promote β-cell retention and function.

Self-Antigens Targeted by Regulatory T Cells in Type 1 Diabetes

While progress has been made toward understanding mechanisms that lead to the development of autoimmunity, there is less knowledge regarding protective mechanisms from developing such diseases. For example, in type 1 diabetes (T1D), the immune-mediated form of diabetes, the role of pathogenic T cells in the destruction of pancreatic islets is well characterized, but immune-mediated mechanisms that contribute to T1D protection have not been fully elucidated. One potential protective mechanism includes the suppression of immune responses by regulatory CD4 T cells (Tregs) that recognize self-peptides from islets presented by human leukocyte antigen (HLA) class II molecules. In this review, we summarize what is known about the antigenic self-peptides recognized by Tregs in the context of T1D.

Evidence of islet CADM1-mediated immune cell interactions during human type 1 diabetes

BACKGROUND

Pathophysiology of type 1 diabetes (T1D) is illustrated by pancreatic islet infiltration of inflammatory lymphocytes, including CD8⁺ T cells; however, the molecular factors mediating their recruitment remain unknown. We hypothesized that single-cell RNA-sequencing (scRNA-Seq) analysis of immune cell populations isolated from islets of NOD mice captured gene expression dynamics providing critical insight into autoimmune diabetes pathogenesis.

METHODS

Pancreatic sections from human donors were investigated, including individuals with T1D, autoantibody-positive (aAb⁺) individuals, and individuals without diabetes who served as controls. IHC was performed to assess islet hormones and both novel and canonical immune cell markers that were identified from unbiased, state-of-the-art workflows after reanalyzing murine scRNA-Seq data sets.

RESULTS

Computational workflows identified cell adhesion molecule 1–mediated (Cadm1-mediated) homotypic binding among the most important intercellular interactions among all cell clusters, as well as Cadm1 enrichment in macrophages and DCs from pancreata of NOD mice. Immunostaining of human pancreata revealed an increased number of CADM1⁺glucagon⁺ cells adjacent to CD8⁺ T cells in sections from T1D and aAb⁺ donors compared with individuals without diabetes. Numbers of CADM1⁺CD68⁺ peri-islet myeloid cells adjacent to CD8⁺ T cells were also increased in pancreatic sections from both T1D and aAb⁺ donors compared with individuals without diabetes.

CONCLUSION

Increased detection of CADM1⁺ cells adjacent to CD8⁺ T cells in pancreatic sections of individuals with T1D and those who were aAb⁺ validated workflows and indicated CADM1-mediated intercellular contact may facilitate islet infiltration of cytotoxic T lymphocytes and serve as a potential therapeutic target for preventing T1D pathogenesis.

FUNDING

The Johns Hopkins All Children’s Foundation Institutional Research Grant Program, the National Natural Science Foundation of China (grant 82071326), and the Deutsche Forschungsgemeinschaft (grants 431549029–SFB1451, EXC2030–390661388, and 411422114-GRK2550).

Modeling human T1D-associated autoimmune processes

BACKGROUND

Type 1 diabetes (T1D) is an autoimmune disease characterized by impaired immune tolerance to β-cell antigens and progressive destruction of insulin-producing β-cells. Animal models have provided valuable insights for understanding the etiology and pathogenesis of this disease, but they fall short of reflecting the extensive heterogeneity of the disease in humans, which is contributed by various combinations of risk gene alleles and unique environmental factors. Collectively, these factors have been used to define subgroups of patients, termed endotypes, with distinct predominating disease characteristics.

SCOPE OF REVIEW

Here, we review the gaps filled by these models in understanding the intricate involvement and regulation of the immune system in human T1D pathogenesis. We describe the various models developed so far and the scientific questions that have been addressed using them. Finally, we discuss the limitations of these models, primarily ascribed to hosting a human immune system (HIS) in a xenogeneic recipient, and what remains to be done to improve their physiological relevance.

MAJOR CONCLUSIONS

To understand the role of genetic and environmental factors or evaluate immune-modifying therapies in humans, it is critical to develop and apply models in which human cells can be manipulated and their functions studied under conditions that recapitulate as closely as possible the physiological conditions of the human body. While microphysiological systems and living tissue slices provide some of these conditions, HIS mice enable more extensive analyses using in vivo systems.

Single-cell multi-omics analysis of human pancreatic islets reveals novel cellular states in type 1 diabetes

Type 1 diabetes (T1D) is an autoimmune disease in which immune cells destroy insulin-producing beta cells. The aetiology of this complex disease is dependent on the interplay of multiple heterogeneous cell types in the pancreatic environment. Here, we provide a single-cell atlas of pancreatic islets of 24 T1D, autoantibody-positive and nondiabetic organ donors across multiple quantitative modalities including ~80,000 cells using single-cell transcriptomics, ~7,000,000 cells using cytometry by time of flight and ~1,000,000 cells using in situ imaging mass cytometry. We develop an advanced integrative analytical strategy to assess pancreatic islets and identify canonical cell types. We show that a subset of exocrine ductal cells acquires a signature of tolerogenic dendritic cells in an apparent attempt at immune suppression in T1D donors. Our multimodal analyses delineate cell types and processes that may contribute to T1D immunopathogenesis and provide an integrative procedure for exploration and discovery of human pancreatic function.

Detection of Glycosaminoglycans in Pancreatic Islets and Lymphoid Tissues

In this chapter, we describe the detection of the glycosaminoglycans hyaluronan and heparan sulfate in pancreatic islets and lymphoid tissues. The identification of hyaluronan in tissues is achieved by utilizing a highly specific hyaluronan binding protein (HABP) probe that interacts with hyaluronan in tissue sections. The HABP probe is prepared by enzymatic digestion of the chondroitin sulfate proteoglycan aggrecan which is present in bovine nasal cartilage and is then biotinylated in the presence of bound hyaluronan and the link protein. Hyaluronan is then removed by gel filtration chromatography. The biotinylated HABP-link protein complex is applied to tissue sections, and binding of the complex to tissue hyaluronan is visualized by enzymatic precipitation of chromogenic substrates.To determine hyaluronan content in tissues, tissues are first proteolytically digested to release hyaluronan from the macromolecular complexes that this molecule forms with other extracellular matrix constituents. Digested tissue is then incubated with HABP . The hyaluronan-HABP complexes are extracted, and the hyaluronan concentration in the tissue is determined using an ELISA-like assay.Historically, heparan sulfate was identified in tissue sections using the cationic dye Alcian blue and histochemistry based on the critical electrolyte concentration principle of differential staining of glycosaminoglycans using salt solutions. For both human and mouse pancreas sections, the current optimal method for detecting heparan sulfate is by indirect immunohistochemistry using a specific anti-heparan sulfate monoclonal antibody. A peroxidase-conjugated secondary antibody is then applied, and its binding to the anti-heparan sulfate antibody is visualized by oxidation and precipitation of a chromogenic substrate.

Development of Type 1 Diabetes may occur through a Type 2 Diabetes mechanism

BACKGROUND

At diagnosis of Type 1 Diabetes (T1D), 30% of the beta cells are dormant, i.e. alive, but inactive. This could reduce beta cell destruction, as cellular stress contributes to beta cell damage. However, the beta cells, that are still active, must produce more insulin and are therefore more vulnerable. The inactive beta cells represent a potential for restoring the insulin secretion.

METHODS

We analyzed the expression of selected genes in islets from live, newly diagnosed T1D patients from the DiViD study and organ doners with longer duration of T1D, type 2 diabetes (T2D), or no diabetes from the nPOD study. Additionally, analysis of polymorphisms was performed on all the investigated genes.

FINDINGS

Various possibilities were considered for the inactivity of the beta cells: secretion defect, fetal state, hibernation, and insulin resistance. We analyzed genes related to the ceramide and sphingomyelin synthesis and degradation, secretion, circadian rhythm and insulin action, and found changes in T1D islets that resemble fetal dedifferentiation and asynchrony. Furthermore, we found low levels of insulin receptor mRNA in the islets. No polymorphisms were found.

INTERPRETATION

Our findings suggest a secretion defect, but also fetal dedifferentiation and desynchronization in the inactive beta cells. Together with previous evidence, that predisposing factors for T2D are also present for T1D development, we raise the idea to treat individuals with ongoing T1D development prophylactically with T2D medicine like GLP-1 receptor agonists, metformin, or others, combined with anti-inflammatory compounds, in order to reactivate the dormant beta cells, and to prevent autoimmune destruction. T2D mechanisms during T1D development should be investigated further.

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.

Using the T Cell Receptor as a Biomarker in Type 1 Diabetes

T cell receptors (TCRs) are unique markers that define antigen specificity for a given T cell. With the evolution of sequencing and computational analysis technologies, TCRs are now prime candidates for the development of next-generation non-cell based T cell biomarkers, which provide a surrogate measure to assess the presence of antigen-specific T cells. Type 1 diabetes (T1D), the immune-mediated form of diabetes, is a prototypical organ specific autoimmune disease in which T cells play a pivotal role in targeting pancreatic insulin-producing beta cells. While the disease is now predictable by measuring autoantibodies in the peripheral blood directed to beta cell proteins, there is an urgent need to develop T cell markers that recapitulate T cell activity in the pancreas and can be a measure of disease activity. This review focuses on the potential and challenges of developing TCR biomarkers for T1D. We summarize current knowledge about TCR repertoires and clonotypes specific for T1D and discuss challenges that are unique for autoimmune diabetes. Ultimately, the integration of large TCR datasets produced from individuals with and without T1D along with computational 'big data' analysis will facilitate the development of TCRs as potentially powerful biomarkers in the development of T1D.

Single-cell analysis of the human pancreas in type 2 diabetes using multi-spectral imaging mass cytometry

Type 2 diabetes mellitus (T2D) is a chronic age-related disorder characterized by hyperglycemia due to the failure of pancreatic beta cells to compensate for increased insulin demand. Despite decades of research, the pathogenic mechanisms underlying T2D remain poorly defined. Here, we use imaging mass cytometry (IMC) with a panel of 34 antibodies to simultaneously quantify markers of pancreatic exocrine, islet, and immune cells and stromal components. We analyze over 2 million cells from 16 pancreata obtained from donors with T2D and 13 pancreata from age-similar non-diabetic controls. In the T2D pancreata, we observe significant alterations in islet architecture, endocrine cell composition, and immune cell constituents. Thus, both HLA-DR-positive CD8 T cells and macrophages are enriched intra-islet in the T2D pancreas. These efforts demonstrate the utility of IMC for investigating complex events at the cellular level in order to provide insights into the pathophysiology of T2D.

Chronic marijuana usage by human pancreas donors is associated with impaired islet function

We investigated the effect of chronic marijuana use, defined as 4 times weekly for more than 3 years, on human pancreatic islets. Pancreata from deceased donors who chronically used marijuana were compared to those from age, sex and ethnicity matched non-users. The islets from marijuana-users displayed reduced insulin secretion as compared to islets from non-users upon stimulation with high glucose (AUC, 3.41 ± 0.62 versus 5.14 ±0.47, p<0.05) and high glucose plus KCl (AUC, 4.48 ± 0.41 versus 7.69 ± 0.58, p<0.001). When human islets from chronic marijuana-users were transplanted into diabetic mice, the mean reversal rate of diabetes was 35% versus 77% in animals receiving islets from non-users (p<0.01). Immunofluorescent staining for cannabinoid receptor type 1 (CB1R) was shown to be colocalized with insulin and enhanced significantly in beta cells from marijuana-users vs. non-users (CB1R intensity/islet area, 14.95 ± 2.71 vs. 3.23 ± 0.87, p<0.001). In contrast, CB1R expression was not co-localized with glucagon or somatostatin. Furthermore, isolated islets from chronic marijuana-users appeared hypertrophic. In conclusion, excessive marijuana use affects islet endocrine phenotype and function in vitro and in vivo. Given the increasing use of marijuana, our results underline the importance of including lifestyle when evaluating human islets for transplantation or research.