Islet–immune interactions in type 1 diabetes: the nexus of beta cell destruction

Summary

Recent studies in Type 1 Diabetes (T1D) support an emerging model of disease pathogenesis that involves intrinsic β‐cell fragility combined with defects in both innate and adaptive immune cell regulation. This combination of defects induces systematic changes leading to organ‐level atrophy and dysfunction of both the endocrine and exocrine portions of the pancreas, ultimately culminating in insulin deficiency and β‐cell destruction. In this review, we discuss the animal model data and human tissue studies that have informed our current understanding of the cross‐talk that occurs between β‐cells, the resident stroma, and immune cells that potentiate T1D. Specifically, we will review the cellular and molecular signatures emerging from studies on tissues derived from organ procurement programs, focusing on in situ defects occurring within the T1D islet microenvironment, many of which are not yet detectable by standard peripheral blood biomarkers. In addition to improved access to organ donor tissues, various methodological advances, including immune receptor repertoire sequencing and single‐cell molecular profiling, are poised to improve our understanding of antigen‐specific autoimmunity during disease development. Collectively, the knowledge gains from these studies at the islet–immune interface are enhancing our understanding of T1D heterogeneity, likely to be an essential component for instructing future efforts to develop targeted interventions to restore immune tolerance and preserve β‐cell mass and function.

Introduction

Type 1 Diabetes (T1D) is classically thought to arise from dysregulated immune responses that culminate in the destruction of insulin producing β‐cells in the pancreatic islets 1. While there is general consensus for an organ‐specific autoimmune process, observations from clinical trials and studies on human organ donor tissues include not only stark differences among patients in rate of progression, age of onset, insulitis composition and frequency, and C‐peptide production at disease presentation but in addition, a surprising level of heterogeneity related to β‐cell death and dysfunction in subjects with long‐standing disease 2, 3. Beyond this, emerging data suggest that multiple pathways and cell subsets may be subject to dysregulation at the level of intra‐islet/paracrine interactions as well as between islets, the surrounding acinar pancreas tissue, and immune infiltrating cells. There is an outstanding need within the field to better understand the complicated interplay between genetic risk factors and potential environmental influences that control localized immune cell activation as well as residual β‐cell function and mass during T1D pathogenesis 4. While animal models have helped elucidate key pathways involved in T1D, tissue biobanks containing samples from cross‐sectional and/or organ donor sources now offer the opportunity to interrogate cell interactions at the islet:immune interface and when coupled with novel experimental platforms, provide a comprehensive picture of the cellular and molecular mechanisms contributing to human T1D.

Interrogating the islet: immune interactions in mouse models of T1D

Our understanding of the molecular mechanisms underlying T1D pathogenesis has been advanced significantly by leveraging animal models. In particular, the non‐obese diabetic (NOD) mouse 5, as well as humanized 6 and transgenic 7, 8, 9 models, have informed on central autoantigens [i.e. preproinsulin, glutamic acid decarboxylase 65 (GAD65), islet antigen‐2 (IA‐2), islet specific glucose‐6‐phosphatase catalytic subunit related protein (IGRP), zinc transporter 8 (ZnT8), and chromogranin A] targeted by autoreactive T cells 10, 11, 12, 13, 14, 15, 16 (including posttranslationally modified autoantigens) 12, 17. They have also provided insights into potential mechanisms behind the loss of tolerance 17, 18, and allowed for in vivo assessment of phenotype and function of human cells 19, 20. Recent studies have illuminated interspecies differences in islet cell morphology and function that may contribute to the lack of success in translating therapeutics from mouse models to human patients 21, 22, 23, 24. Indeed, therapies targeting effector T cells for depletion 25 and those inhibiting T cell co‐stimulation 26 successfully prevented immune cell infiltration of the pancreatic islets and symptomatic diabetes in NOD mice hundreds 27 of times and reversed in a handful of studies 28, 29, 30. In contrast, clinical trials of anti‐CD3 31, 32, anti‐thymocyte globulin (ATG) 33, 34, 35, abatacept (CTLA4‐Ig) 36, and alefacept (LFA‐3/IgG1) 37 have, at best, provided only temporary preservation of baseline C‐peptide production in subgroups of T1D patients while anti‐CD3 was recently reported to delay T1D onset in at‐risk individuals 38. Though an in‐depth analysis of the contributions of animal models is beyond the scope of this review, Table 1 summarizes a selection of key findings relevant to human disease made possible by in vivo models.

Table 1.

A selection of NOD mouse models facilitating studies on islet–immune interactions in T1D pathogenesis.

In vivo T1D models	Critical findings	Advantages	Shortcomings	References
NOD mouse	CD4+ and CD8+ T cells, as well as B cells, are integral to disease development	Parallels the polygenic nature of T1D and importance of MHC	Differences in disease kinetics, inflammatory infiltrate composition, islet cell architecture, pancreas morphology, and number of PLN	5, 6, 10, 11, 12, 14, 15, 16, 17, 22, 75, 120
	Islet antigen specific T cells recognize Ins B:9–23, Ins1 B5–14 and Ins1/2 A2–10
	ChgA and IAPP are autoantigens and function to initiate disease and promote Th1 responses	Serves as a valuable pre‐clinical model for therapeutics	Differences in endocrine cell distribution, β‐cell regenerative capacity, and immune cell receptor expression and signaling
	Antigen specific T cells recognize post‐translationally modified epitopes which may alter binding to MHC molecules	Capacity for transgenics, adoptive transfers and lineage tracing, and intervention testing in a spontaneous model system
NOD‐scid Il2rγ −/− (NSG) mouse	Adoptively transferred CD8+ T cells from T1D donors stimulated with pooled islet antigen peptides [IGRP, IAPP, Ins, and IA‐2] traffic to the islets and produce IFN‐γ	Lack endogenous T, B and NK cells	Increased β‐cell proliferative capacity as compared to humans	6, 19
		Can be engrafted with human PBMCs	Alterations in homing, chemokine and cytokine use, and secondary lymphatics in xenogeneic system
NOD‐SCID BLT HLA‐DQ8 transgenic mouse	Demonstrated the in vivo pathogenicity of human HLA‐DQ8 restricted InsB:9–23 specific CD4+ T cells in exacerbating insulitis and β‐cell death	Possess a complete human lymphoid and myeloid immune cell repertoire	GVHD and wasting syndrome	6, 20
		T cells are educated autologously and are HLA restricted
HLA‐A2.1 transgenic NOD mouse	Accelerated disease compared to nontransgenic NOD mouse	Possession of human HLA molecules allow for testing a variety of agents, including adoptive cell therapy, and ASI on human cells in vivo	Often reduced disease incidence as compared to NOD	7, 8, 9, 13
	Islet infiltrating T cells directly lyse HLA‐A2.1+ β‐cells
NOD.β2mnull.HHD mouse	CD8+ islet infiltrating T cells from HLA‐A2.1 transgenic mice target an IGRP epitope cross‐reactive to human IGRP (IGRP228–236)
NOD.mβ2mnull.hβ2m.HLA‐A11 transgenic mouse	HLA‐A11 restricted CD8+ islet infiltrating T cells in HLA‐A11 transgenic mice recognize IGRP and Ins C‐peptide and are present prior to disease onset
Foxp3‐GFP‐Cre × R26‐YFPNOD transgenic mouse model	GFP–YFP+Foxp3– ex‐Treg which lost Foxp3 were identifiable and shown to have a pro‐inflammatory phenotype	Facilitates genetic lineage tracing	Potential for off‐target Cre recombination	18
		Can identify plasticity in cell lineages and sort out these plastic populations to conduct functional studies
		Trafficking and localization can be visualized in situ

^*ASI = Antigen specific immunotherapy; Ins = Insulin; ChgA = Chromogranin A; IAPP = Islet Amyloid Polypeptide; IGRP = Islet‐specific glucose‐6‐phosphatase catalytic subunit‐related protein; IA‐2 = Islet antigen‐2; BLT = Bone marrow, Liver, Thymus; NK = Natural Killer; PBMCs = Peripheral blood mononuclear cells; GVHD = Graft Versus Host Disease; T_regs = regulatory T cells.

Lessons from human T1D pathology

Insulitis has long been considered the histopathological hallmark of T1D 39, yet differences in pancreatic mass and volume have recently been observed in T1D subjects as well as autoantibody negative (AAb^–) first‐degree relatives and autoantibody positive (AAb⁺) subjects 40, 41. These findings support the possibility that T1D may involve early atrophy or growth defects affecting the entire pancreas prior to clinical diagnosis, yet the disease symptoms almost exclusively reflect defects in β‐cell function and/or mass. However, there still remains a paucity of data surrounding starting pancreas mass and volume for these subjects. Hence, this section focuses primarily on immune‐islet interactions in T1D pathogenesis but also highlights recently reported alterations within the acinar pancreas from studies of primary human tissues obtained from living and organ donor cohorts 42, 43, 44, 45 (Table 2).

Table 2.

Tissue procurement programs for the study of T1D pathogenesis in human pancreata 121.

Tissue Procurement Programs and Biobanks	Cohort information	Initiatives	Reference
Network for Pancreatic Organ Donors (nPOD)	Transplant quality pancreas and lymphoid tissues collected from deceased organ donors at T1D onset to established disease, along with AAb+ donors and non‐diabetic corresponding controls. Samples are processed freshly at the University of Florida, banked, and distributed to hundreds of approved investigators around the world.	Investigate pancreas architecture and extracellular matrix in health and T1D pathogenesis	42, 47
		Define autoreactive T and B cell repertoire and antigen specificities with an interest in therapeutic intervention
		Investigate the role of viruses in T1D
		Attain comprehensive ‘omics data
		Examine pancreata from organ donors who received a pancreas transplant
Exeter Archival Diabetes Biobank (EADB)	Pancreata collected at autopsy from predominantly young patients with recent‐onset T1D	Identification of age‐dependent differential insulitic profiles	43, 50, 71
		Investigate enteroviral infection as a possible trigger for T1D
Diabetes Virus Detection Study (DiVID)	Pancreatic biopsies from living patients with T1D	Investigate potential viral triggers for T1D	44
Human Pancreas Analysis Program (HPAP)	Transplant quality pancreas and lymphoid tissues collected from deceased organ donors at T1D onset to established disease, along with AAb+ donors and non‐diabetic corresponding controls. Samples are processed and subjected to comprehensive analyses at Vanderbilt University and University of Pennsylvania. Metadata are made available to investigators via a publicly accessible database.	Utilize novel technologies to profile immune and endocrine cells over the natural history of disease.	45
Human Atlas of the Neonatal Development and Early Life‐Pancreas (HANDEL‐P)	Transplant quality pancreas collected from control organ donors without diabetes ranging from prenatal to 10 years of age	Understand the early changes, whether structural, immunological, β‐cell‐centric or otherwise, that occur in the normal human pancreas, unaffected by diabetes	122

^*AAb⁺ = Autoantibody positive; T1D = type 1 diabetes.

Immunological determinants of human T1D

Within the pancreatic islets of T1D organ donors, CD8⁺ T cells comprise a majority of the infiltrating immune cells, with the remainder consisting primarily of B cells, CD4⁺ T cells, and macrophages 46. Yet, the severity of CD3⁺ infiltrate and residual β‐cell mass varies appreciably across T1D organ donors according to disease duration (Fig. 1a‐d) 47, 48. B cell infiltrate has also been shown to differ according to donor age at T1D onset with younger‐onset donors (<13 years of age) 49 exhibiting a “hyper‐immune” CD20^Hi phenotype and fewer residual insulin containing islets (ICI), while older‐onset donors displayed fewer intra‐islet CD45⁺ immune cells and a CD20^Lo profile within ICI (Fig. 1e‐f) 50. β‐cells expressing both insulin and the replication marker, Ki67, have been observed within insulitic islets of adult non‐diabetic donors with multiple AAb, potentially revealing simultaneous T cell mediated β‐cell destruction and attempts to restore endogenous β‐cell mass prior to T1D onset (Fig. 1g‐h) 51, 52. Stratifying patients by islet immune signatures may indicate different modes of pathogenesis or potentially, disease endotypes 53 that could be targeted with precision therapies.

Figure 1.

Heterogeneous islet morphology and immune cell infiltration across disease duration and according to age of T1D onset. Representative islets were imaged from serial paraffin sections stained for Ki67 plus insulin (INS) and CD3 plus glucagon (GCG) for a 13‐year‐old donor at T1D onset (nPOD 6228; a & c) and a 6 year old with 3 years T1D duration (nPOD 69; b & d) 47, 48. CD3⁺ infiltrate is present in both donors (c, d), though insulin containing islets are only observed in the first donor (a, b). Scale bars: a and c, 50μm; b and d, 100μm 47, 48. Pancreas samples from donors with recent‐onset T1D stained for CD20 (green) and glucagon (red), and nuclei (DAPI) exhibit differences in infiltrate composition, which can separate subjects based on hyper‐immune CD20^Hi (nPOD 6052; e) and pauci‐immune CD20^Lo profiles (nPOD 6070; f) 50. Histology of a 46 year old donor with ≥3 islet AAb shows both Ins⁺Ki67^– β‐cells and Ins⁺Ki67⁺ cells replicating β‐cells (g, arrows) within islets that contain CD3⁺ T cell infiltrate (h) 51. Figures have been reprinted with permission from the American Diabetes Association 47, 48, 50, 51.

A second reproducible histological feature of T1D involves β‐cell hyperexpression of HLA Class I, which is observed most commonly within residual ICI and accompanied by elevated expression of the transcription factor STAT1 54. Whether this phenotype is the consequence or driver of lymphocyte infiltration and IFN‐γ production 55 within the islet is a subject of debate, but in either case, it is likely that HLA hyperexpression may facilitate surveillance by innate immune cells and β‐cell destruction by antigen‐specific CD8⁺ T cells. In a seminal report by Coppetiers et al., in situ HLA‐tetramer staining revealed CD8⁺ T cells specific for islet antigens – insulin, IGRP and IA‐2 – within insulitic lesions, though the persistence of β‐cell mass and number of islet antigen‐reactive T cell specificities varied across donors in accordance with disease duration 56. Similarly, CD4⁺ T cells isolated from the islets of organ donors with recent‐onset T1D exhibited reactivity to multiple GAD65 epitopes, as well as proinsulin_76–90 and IA‐2_545–562, measured by antigen‐stimulated IFNγ secretion 57. Moreover, islet‐infiltrating CD4⁺ T cell clones, when reconstructed to express T cell receptors (TCRs) as transductants, have been identified to respond to proinsulin, C‐peptide amino acids 19–35 (C:19–35), and insulin B:9–23 48. These data support a critical role for T cells in mediating islet antigen specific pathology.

In addition to examining autoantigen specificities, extensive adaptive immune cell repertoire analyses from peripheral blood and organ donor tissues of subjects with T1D have revealed disease‐related repertoire changes. We previously performed TCRβ chain and B cell immunoglobulin heavy chain (IgH) immunosequencing on lymphocytes isolated from the pancreatic draining lymph node (pLN), peripheral blood, spleen, and in one case, islet infiltrate from T1D and control nPOD donors. Overall, we observed limited receptor sharing in sorted CD4⁺ T cell subsets across tissues from a given donor, while CD8⁺ T cells demonstrated increased clonality, with one donor possessing shared complementarity determining region 3‐β (CDR3β) sequences across the islets, pLN, and peripheral blood mononuclear cells (PBMCs) 58. TCR sequencing of single sorted islet‐resident T cells has corroborated this oligoclonality of CD8⁺ T cells 48. TCR sequencing of islet‐infiltrating CD4⁺ T cells from a single donor revealed a bias in TRBV gene usage, with 30% of clones expressing TRBV5–1*01, and three clones expressing identical TCRs using TRBV5–1*01 recognized overlapping C‐peptide epitopes 59. Reactivity to these same epitopes was also found in PBMCs from living T1D patients 59. Identification of overlapping TCR sequences and reactivities within peripheral blood and the target organ suggests profiling of circulating autoreactive T cells could have disease predictive value or serve as a tool to assess efficacy of therapeutics aimed at reducing the autoreactive T cell pool.

Intrinsic markers of β‐cell stress and dysfunction in T1D

Due to the significant influence of genetics on T1D pathogenesis, studies investigating the expression of candidate genes in the islets and their functional implications are of great interest. Furthermore, the finding that disease‐associated T1D loci often map to noncoding regions, specifically regulatory elements 60, suggests a role for these loci in regulating gene expression. There is evidence to suggest T1D candidate genes not only impact immune cell repertoire and activity but also, may function at the level of the islet to regulate β‐cell apoptosis and immune interactions 61 (Fig. 2), though there is a currently a paucity of mechanistic data. Recent studies combining transcriptomic, epigenomic, and proteomic data to assess the influence of T1D risk loci on β‐cell dysfunction have shown isolated human islets treated with IFN‐γ and IL‐1β in culture to exhibit differential transcriptomic and epigenetic remodeling. This was mediated by inflammatory response transcription factor recruitment, DNA looping and chromatin acetylation, cumulatively leading to upregulation of genes and proteins involved in the inflammatory response and apoptosis 62, implicating these as mechanisms likely underpinning β‐cell dysfunction. In particular, knockdown of T1D candidate gene GLIS3 in human islets has been shown to sensitize β‐cells to IFN‐γ and IL‐1β induced death 63, found to be mediated by a reduction in alternative splicing factor SRp55 which normally negatively regulates apoptosis and endoplasmic reticulum (ER) stress 64. Thus, crosstalk between T1D candidate genes and splicing regulators may result in increased β‐cell susceptibility to immune‐mediated as well as endogenous stress related dysfunction.

Figure 2.

T1D candidate genes are highly expressed in endothelial, islet, and immune tissues. T1D risk loci were collected from ImmunoBase (http://www.immunobase.org), tissue expression was identified per tissue (genevisible.com/search), and a venn diagram was created based on relative abundance of expression in immune (blue), endothelial (purple), and pancreatic islet tissue (green) 61. Figure has been reprinted with permission from Frontiers in Endocrinology 61.

Recent attention has been directed toward the role of β‐cell stress in T1D pathology, due to findings of increased levels of ER stress markers such as C/EBP homologous protein (CHOP) glucose‐regulated protein 78 (GRP78, also known as IgH binding protein (BiP)) in the islets of T1D subjects 65. These function as part of the Unfolded Protein Response (UPR) to promote cell death and aid in protein folding, respectively 66. Aberrant protein processing, in the form of misfolded or alternatively spliced isoforms, may result in the generation and presentation of neoantigens 67. Indeed, T cells reactive to post‐translationally modified proteins such as a citrullinated form of GRP78_292–305 and islet amyloid polypeptide (IAPP)_65–84, as well as defective ribosomal insulin gene products (DRiPs) and peptides formed from the fusion of insulin C‐peptide fragments with chromogranin A or IAPP (termed hybrid insulin peptides, HIPs) have been isolated from the islets of T1D donors 57, 68. Thus, β‐cells may play a role in their own destruction through stress‐induced protein processing defects, which may serve to induce a critical break in tolerance or to exacerbate existing pathology by expanding the β‐cell antigenic repertoire.

The search for viral triggers of T1D

Extensive efforts to identify precise environmental triggers that might initiate or potentiate the autoimmune process have proven challenging thus far, but examination of donor pancreata have revealed viral response signatures which could offer clues into early T1D etiology. Biopsies of pancreas from living donors with recent‐onset T1D, aged 24–35 years, through DiViD contained some indications of viral capsid protein VP1 immunostaining, HLA Class I hyperexpression, and enterovirus RNA within the islets 69, possibly the result of a β‐cell tropism mediated by expression of a specific isoform of the Coxsackie and Adenovirus Receptor 70. Furthermore, islets infected with coxsackievirus B (CVB) in‐vitro demonstrated reduced insulin mRNA expression and insulin secretion 71, suggesting viral infection could impair β‐cell function. Additional studies have shown CVB infection to induce the production of type III interferons, the magnitude of this response being associated with the single nucleotide polymorphism (SNP) rs1990760 within the T1D candidate gene, IFIH1, suggesting a role for this T1D risk locus in influencing viral clearance 72. These results mirror those from The Environmental Determinants of Diabetes in the Young (TEDDY) study, where susceptibility to enteroviral infection was shown to correlate with HLA genotype, with HLA‐DQ2/DQ8 individuals, who have the highest risk of developing T1D, presenting with more enteroviral infections 73. Hence, in situ and clinical data together suggest a model in which T1D susceptibility loci may predispose to viral infection that could, in turn, promote immune dysregulation. However, it is also possible that the anti‐viral immune signature could be impacted by a viral infection that does not immediately localize to the islet, or alternatively, host viral sensing machinery is detecting a build‐up of endogenous mRNA and triggering a form of “sterile” inflammation and viral sensing pathways 74. Thus, caution must be used when interpreting studies of an anti‐viral signature in the islet microenvironment.

Immune dysfunction within the pLN, migration, and trafficking

The critical role of pLN in initiating antigen‐specific T cell responses, as demonstrated by disease protection upon early (3 weeks) excision in the NOD 75, suggests defective signaling or activation within the pLN could contribute to islet‐directed immune dysfunction in human T1D. A recent study observed the pLN to be disorganized, containing fewer secondary follicles and follicular dendritic cell (fDC) networks in donors with recent‐onset T1D (≤1.5 years duration) compared to non‐diabetic controls and long‐duration (4–19 years) T1D donors 76. Both B and T_FH cells have been implicated in T1D, with increased islet infiltrating CD20⁺ B cells being associated with rapid progression to T1D 49 and with T_FH frequency and IL‐21 production being increased in the peripheral blood of T1D subjects 77, collectively highlighting the need to determine the source(s) of pLN germinal center dysfunction in T1D.

In order for diabetogenic immune cells to infiltrate the pancreas and exert their effector functions, they must bypass inhibitory immune checkpoints (e.g. PD‐L1:PD‐1) and migrate down chemokine gradients. Thus, an area of great therapeutic interest involves the development of agents to modulate these processes. The PD1:PD‐L1 interaction has been therapeutically targeted in cancer to enhance CD8⁺ T cell‐mediated tumor destruction, though the use of these immune checkpoint inhibitors sometimes results in the manifestation of immune‐related adverse events, including T1D 78. Increased PD‐L1 expression was observed in isolated islets and human β‐cell lines exposed to IFNα and IFNγ treatment in culture via JAK‐STAT dependent signaling 54. Importantly, increased PD‐L1 expression was also observed in the ICI of T1D organ donors suggesting that PD‐L1 upregulation might protect residual β‐cells in the context of the proinflammatory milieu 79. The interferon inducible chemokine CXCL10 was also expressed in ICI of recent‐onset T1D subjects, along with its receptor CXCR3 on infiltrating lymphocytes 80, 81, cumulatively providing a potential mechanism wherein local interferon production might drive lymphocyte infiltration via chemotactic cues, resulting in the selective destruction of β‐cells that fail to upregulate PD‐L1.

The contributions of pancreas architecture to T1D pathology

As noted above, T1D is clinically identified following β‐cell dysfunction/destruction sufficient to induce hyperglycemia, but the entire pancreas appears to be compromised in donors with recent‐onset and pre‐T1D. Deficits in exocrine pancreas mass and function have been identified in subjects with and at‐risk for T1D. Indeed, reduced secretion of pancreatic enzymes, such as trypsinogen 82, amylase, and lipase 83, as well as a smaller pancreas organ as measured by weight or volume 40, 41, are potentially reflective of exocrine damage accompanying T1D pathology. Increased complement deposition was also observed on the vascular endothelium and extracellular matrix (ECM) surrounding vessels and ducts within the exocrine pancreas tissue in T1D versus control donors 84, indicating localized inflammation. Moreover, studies examining immune infiltration of the exocrine pancreas have found CD8⁺ T cells, CD4⁺ T cells and CD11c⁺ dendritic cells (DCs) to be present at higher numbers in T1D versus control donors, with CD11c⁺ cells being increased in both AAb⁺ donors (prior to disease onset) and short‐duration T1D donors 85. These findings raise important questions surrounding mechanisms underlying loss of exocrine pancreas mass and function as well as the potential for interactions between islet and exocrine tissues via the insulo‐acinar portal system wherein exocrine pancreas defects may contribute to endocrine cell death (or vice versa).

Immune cell infiltration around and within islets is thought to be, in part, facilitated by defects in ECM, namely in basement membrane integrity, which permit leukocyte penetration 86. The ECM component hyaluronan (HA) has been shown in vitro to promote lymphocyte adhesion and migration 87, proliferation 88, and antigen presentation 89, suggesting low molecular weight HA could drive immune activation and infiltration in T1D. Indeed, accumulation of HA has been observed in islets of young recent‐onset (0–8 weeks duration) T1D donors and was associated with CD45⁺ infiltrate 90. Inhibiting HA synthesis impairs antigen presentation in vitro, and in vivo treatment promotes tolerance in a mouse model of autoimmune encephalitis 91, suggesting that targeting components of ECM may be beneficial in T1D.

Islets require a high degree of vascularity for optimal β‐ and α‐cell function in sensing and maintaining glucose homeostasis 92, a function that is directed in part by branches of the sympathetic nervous system⁶³. However, high vascularity may also contribute toward immune infiltration in T1D. Canzano et al. showed reduced islet vessel diameter in T1D subjects as compared to controls, but T1D subjects with residual ICI more closely resembled control subjects, making it difficult to discern whether changes in microvasculature precede or follow loss of functional β‐cell mass 93. At the same time, T1D islets exhibit α‐cell dysfunction, which clinically results in hyperglycemia complicated by hyperglucagonemia or hypoglycemia with failed counterregulation. Though the exact mechanisms remain unknown, it has been speculated that α‐cell failure may reflect a loss of islet cell paracrine signaling 94 or a response to the local inflammatory milieu. Indeed, RNA‐sequencing of human T1D islet α‐cells has revealed decreased expression of genes involved in calcium signaling and electrical activity, with partial resolution when transplanted into a non‐autoimmune environment 95. Thus, loss of islet vasculature may contribute toward α‐ and β‐cell dysfunction by impeding communication between and across islets, serving to exacerbate inflammation‐induced dysfunction.

Intra‐islet vascular defects could potentially point to underlying sympathetic nervous system dysfunction as sympathetic neurons are thought to control vascular tone and thus, determine responsiveness to both glucose and neurotransmitters important for β‐cell function 96. Reduced sympathetic nerve density observed in the islets of recent‐onset and long‐duration T1D versus control donors supports this notion 97. Moreover, β‐cells have been shown to express the inhibitory neurotransmitter gamma‐aminobutyric acid (GABA) produced by GAD, of which the 65kD isoform is a potent autoantigen in T1D 98. Interestingly, positive allosteric modulators of GABA promote β‐cell proliferation in vitro 99, indicating a potential therapeutic role for this molecule in replenishing lost β‐cell mass. GABA receptors are also expressed on immune cells 100, and GABA was recently demonstrated to function in an immunoregulatory capacity, suppressing T cell proliferation in vitro as well as T_H1 and T_H2 cytokine production by PBMCs isolated from patients with T1D 101. GABA has also been suggested to influence α‐ to β‐cell conversion 102, though this area remains controversial and requires additional study 103. Thus, GABA could potentially serve in a regenerative context to promote β‐cell expansion or to bolster the efficacy of islet cell transplantation. The aforementioned findings illuminate the complex T1D pathology involving dysfunction throughout the pancreas organ and across multiple physiological systems, emphasizing the need for more comprehensive approaches to study and treat the underlying mechanisms of T1D pathogenesis.

Multiplexed analyses of human pancreas tissue

High‐throughput single cell transcriptomic profiling of immune and islet cells 104 provides a means to assess the contributions of candidate genes/gene expression toward T1D‐associated phenotypic and functional defects at greater depth and with less starting material. Thus, information gleaned from valuable donor tissue is maximized, and it is possible to identify rare cell subsets that might be masked with bulk sequencing efforts. Using this technology to interrogate the β‐cell transcriptome has revealed population heterogeneity in the form of differential expression of genes involved in β‐cell function (i.e. UCN3) and ER stress inducible genes (e.g. HERPUD1, DDIT3, and HSP5, the latter of which encodes GRP78/BiP) 105. This suggests the existence of β‐cell populations that are predisposed to stress and might preferentially be destroyed in an autoimmune environment. Additionally, the Assay for Transposase Accessible Chromatin with sequencing (ATAC‐seq, Table 3), previously used to examine cell‐type specific regulatory elements in endocrine cells 106, has recently been scaled down to single cell resolution and optimized for use in frozen tissue 107. Hence, studies investigating complex DNA regulatory networks from banked tissue samples are expected to uncover defects in epigenetic regulation which function to promote T1D at the level of the islet–immune interface.

Table 3.

Emerging technologies for studies of T1D pathology.

Emerging Technologies/Platforms	Applications	Reference
Single cell transcriptomics/ proteomics	Assess expression of candidate genes and their protein products for paired cell genotype/phenotype data, as well as adaptive immune cell repertoire analysis	104
Single cell ATAC‐sequencing	Investigate the contribution of dysregulated gene networks, particularly in candidate loci, to immune or β‐cell function	106, 107
CyTOF	Following labeling with metal tagged antibodies, deep phenotyping of single cell suspensions can be performed	110
IMC	By applying metal tagged antibodies to fixed tissue sections, deep phenotyping of cells can be performed in situ	111, 112
Laser capture microdissection	Identify differentially expressed genes and proteins to develop disease‐predictive biomarkers or targeted therapeutics	108
nanoPOTS	Identify novel post‐translational modifications within a single islet and the proteomic basis for islet heterogeneity	109
CODEX	Examine disease‐related tissue and cell subset reorganization, as well as perform multiplexed deep phenotyping	113
Tissue clearing (e.g. X‐CLARITY, PARS)	Visualization of intact morphology, vasculature, innervation, and extracellular matrix	114
RNA single‐molecule FISH	Identify the dynamics of candidate gene and checkpoint molecule expression in all subsets present in the tissue microenvironment, examine how they influence cell phenotype and function	115
Microphysiological Systems	Introduce targeted therapeutics or innate and adaptive immune cells to assess their contribution to disease development/treatment	116
	Investigate the underlying cause of the islet anti‐viral immune signature
	Examine the role of hybrid insulin peptides (HIPs), defective ribosomal products (DRiPs) and neoantigens in β‐cell stress or destruction
Tissue Slice	Profile live immune and endocrine cells across the pancreas in the native tissue environment	24
	Assess the role of chemokines and adhesion molecules
	Determine which cells are directly pathogenic vs bystander or tissue resident cells

^*nanoPOTS = Nanodroplet processing in one pot for trace samples; PARS = Perfusion‐assisted agent release in situ; ATAC = Assay for Transposase Accessible Chromatin; CyTOF = Cytometry time of flight; IMC = Imaging mass cytometry.

Single cell assays such as mass cytometry (CyTOF), along with other new methods designed to profile the proteome at high resolution and with minimal cell input 108, 109, can offer insights into cellular heterogeneity but cannot discern cell‐cell interactions or orientation within the native tissue environment (Table 3). In contrast, Imaging Mass Cytometry (IMC), which facilitates visualization of tissue sections labeled with antibodies conjugated to rare metal isotopes using high‐resolution laser ablation and time‐of‐flight mass spectrometry, allows for high‐parameter in situ data acquisition without the compensation issues plaguing traditional immunofluorescence analyses 110, 111 (Table 3). Simultaneous detection of 36 parameters from a single tissue section by IMC coupled with analysis of pseudotime dynamics indicated that β‐cells lose identifying markers such as insulin, proinsulin, IAPP, and protein tyrosine phosphatase receptor type N (PTPRN) prior to their destruction 111, potentially indicating a direct role for β‐cells in inciting their own destruction by autoreactive T cells. Additionally, intra‐ and peri‐islet T cell numbers were negatively correlated with disease duration and residual β‐cell mass, with new‐onset T1D donors possessing the highest degree of infiltration, regardless of the presence of β‐cells (defined as islet cells expressing both Pancreatic And Duodenal Homeobox 1 (PDX1) and NKX6‐1) 111. Similarly, Wang et al. observed increased Granzyme B⁺ macrophages and CD8⁺ T cells in pancreas tissues from T1D donors, with β‐cell containing islets (defined by expression of insulin, NKX6.1 and PDX1) enriched in CD8⁺ T cells and CD20⁺ B cells 112, likely identifying islets that are actively being targeted by autoreactive immune cells. Defects in peri‐islet collagen and decreased intra‐islet vascularization were also observed in human donors with T1D as compared to controls 112. Cumulatively, these studies suggest that morphological, genetic, and proteomic dysfunction work in concert to influence aberrant immune responses, β‐cell dysfunction or loss of β‐cell identity, and β‐cell destruction in T1D (Fig. 3).

Figure 3.

Islet–immune interactions and their impact on β‐cell function in health and T1D. An islet in a normal microenvironment is surrounded by intact extracellular matrix and exocrine tissue, while provided sufficient vascularization and innervation to promote glucose homeostasis and immunoregulation through insulin and glucagon secretion and release of GABA (left). In T1D (a) reduced vessel diameter and innervation impair islet‐cell function, while morphological dysfunction in the form of (b) loss of basement membrane (BM) and extracellular matrix (ECM) integrity as well as hyaluronan (HA) accumulation permit (c) the infiltration and activation of lymphocytes in both the exocrine and intra‐islet tissue. These immune cells make use of chemokine gradients and promote a diabetogenic milieu through the release of pro‐inflammatory mediators. Cumulatively these defects contribute toward β‐cell dysfunction in the form of (d) MHC class I hyperexpression, loss of insulin and GABA expression. They also may serve to magnify endogenous β‐cell stress presented as protein processing defects, which in turn function as neoantigens to exacerbate immune activation, all of which culminate in β‐cell death. In addition to β‐cell defects, α‐cell dysfunction (e) contributes to impaired glucose homeostasis in T1D through hyperglucagonemia or failed counterregulatory responses. Figure created with Biorender.

A novel method developed by Nolan and colleagues, co‐detection by indexing (CODEX), enables multiplexed in situ deep phenotyping through the use of polymerase‐driven iterative antibody visualization, with up to 66 antigens able to be codetected on a standard 3–4 color microscope by iterative hybridization and staining 113 (Table 3). A comprehensive image is then constructed from the combination of images, allowing associations to be drawn between cell phenotype and spatial arrangement in the tissue microenvironment. Our lab and others are in the process of applying this technique to banked donor tissues spanning the natural history of disease. We expect this approach to further aid in deciphering the timeline of changes in morphology, immune and endocrine cell phenotypes, the nature of cell‐cell interactions within the islets and throughout the pancreas, and the profile of β‐cells that are more susceptible to autoimmune attack. Additionally, tissue clearing methods such as CLARITY, which allow for whole organ imaging without morphological or cellular perturbations 114 (Table 3), have enabled visualization of age and disease related changes in pancreas architecture, vascularization, and innervation across the pre‐ and post‐natal periods as well as in pediatric T1D tissues 23. Cleared tissues offer compatibility with new methods of single mRNA transcript visualization 115, allowing measurement of localization of transcripts within the whole organ. Collectively, the ongoing work leveraging these aforementioned advancements will provide a more comprehensive view of T1D pathology at the islet:immune interface related phenotypic, transcriptomic, and morphological changes as well as the molecular and cellular events underpinning disease development.

Ex vivo platforms for studying islet–immune interactions in human T1D

Novel platforms for ex vivo studies of live human islets have been developed to mimic the human islet microenvironment and model islet–immune cell interactions (Table 3). One such technology is the recently developed islet‐on‐a‐chip microphysiological system (MPS), which allows laminar flow of immunotherapeutic agents or specific immune cells over human pancreatic islets with immunofluorescent imaging in real time, providing a way to monitor β‐cell function and phenotype in response to any number of putatively diabetogenic or protective stimuli 116. Indeed, in a recent study, Lenguito et al. were able to maintain viable islets and reliably detect insulin secretion in response to glucose and KCl stimulation 116, illustrating the capacity to further leverage this MPS to interrogate the etiological role of host‐pathogen interactions; specific antigen targets, lymphocyte activation state, as well as function of autoreactive T and B cells at the islet–immune interface within an isogenic system; and the potential for regulatory T cells (T_regs) to inhibit β‐cell destruction. Importantly, we expect that such information might facilitate the development and ex vivo functional validation of immune and β‐cell directed therapeutics.

Islet isolation will introduce confounding effects, such as induced stress or bias for healthy islets, and cannot recapitulate the islet‐acinar tissue interactions that occur in vivo. Thus, a promising tissue slice platform was developed by the Speier lab 24 facilitating studies that link endocrine and exocrine secretory function with morphological features of intact pancreatic tissues maintained under physiological conditions using a perfusion system. Responses to well characterized stimuli for the secretion of hormones [e.g. insulin (glucose, KCl) and glucagon (KCl, arginine)] and enzymes [amylase, lipase and trypsinogen (CCK‐8, carbachol)] 117 can be assessed in real time under steady state conditions, and the experimental system can likely be modulated with the addition of inflammatory cytokines or other soluble factors to mimic or mollify the T1D microenvironment. The potential drawbacks of this platform include the confounding influence of pancreatic enzymes, as well as lack of innervation and blood flow limiting tissue thickness to limit hypoxia‐induced stress. Comparison of human and mouse pancreas slices illustrated differences in endocrine and epithelial cell contacts, with human slices showing increased β‐cell‐α‐cell contacts 21, 118, illustrating the importance of paracrine signaling in optimal human pancreas function. Furthermore, reduced β‐cell connectivity in human slices as compared to mouse slices illustrates interspecies differences in islet cell‐cell communication 21, a factor that potentially contributes to poor translation of T1D therapies from mouse to humans. Multifluorescent 3‐D imaging of human pancreas slices has also provided in‐depth structural analysis of the individual islet vasculature, the surrounding duct cells and ECM 119. These high‐resolution analyses may serve to identify subtle changes occurring within the microenvironment in AAb⁺ pre‐T1D donors prior to diagnosis. Co‐registration of endocrine and exocrine functional profiles with precise anatomical location and visualization of immune cell infiltration will expand our understanding of mechanistic relationships between islet, acinar and immune defects in T1D as well as our ability to test novel therapeutics directed at one or more of these components.

Implications for natural history studies and interventions

The aforementioned knowledge gains surrounding the islet:immune interface have collectively advanced our understanding of T1D pathogenesis in humans. Animal model studies continue to inform on mechanisms underlying β‐cell destruction, namely migration and activation of autoantigen‐specific T cells, which are essential to T1D pathology. However, numerous effective immunomodulatory therapies in mice have failed to meet their primary clinical endpoints in human trials, suggesting a need for additional and complementary models to recapitulate the human disease. With the development of ex vivo experimental platforms (e.g. islet‐on‐a‐chip MPS and pancreas slices), we are poised to investigate the complex interplay between the various pancreas cell types at play (e.g. islet, immune, neural, vascular, and exocrine) from fresh human donor tissues. Indeed, studies of human pancreata have shown T1D pathogenesis to extend far beyond the β‐cell with defects affecting multiple cell types across the entire pancreas, though we have yet to identify the precise disease initiating event(s). Hence, multiparameter analyses coupled with advanced bioinformatics and statistical methods will be essential to linking complex datasets to determine the underlying mechanisms of β‐cell destruction, to identify disease predictive biomarkers of pathogenic events occurring within the endocrine or exocrine pancreas, and to develop targeted approaches to alleviate autoimmunity and restore β‐cell mass. Evidence is building for multifactorial defects within the β‐cells, islet niche, acinar pancreas, and immune compartment, and a combinatorial strategy targeting multiple arms of T1D pathogenesis will likely be necessary to effectively treat the disease.

Author contributions

LP wrote the manuscript, AP reviewed/edited the manuscript and contributed to discussion, TMB conceived of the article and wrote the manuscript.

Disclosures

The authors declare that no conflicts of interest exist pertaining to this manuscript.