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.

RNA-seq preprocessing and sample size considerations for gene network inference

Background

Gene network inference (GNI) methods have the potential to reveal functional relationships between different genes and their products. Most GNI algorithms have been developed for microarray gene expression datasets and their application to RNA-seq data is relatively recent. As the characteristics of RNA-seq data are different from microarray data, it is an unanswered question what preprocessing methods for RNA-seq data should be applied prior to GNI to attain optimal performance, or what the required sample size for RNA-seq data is to obtain reliable GNI estimates.

Results

We ran 9144 analysis of 7 different RNA-seq datasets to evaluate 300 different preprocessing combinations that include data transformations, normalizations and association estimators. We found that there was no single best performing preprocessing combination but that there were several good ones. The performance varied widely over various datasets, which emphasized the importance of choosing an appropriate preprocessing configuration before GNI. Two preprocessing combinations appeared promising in general: First, Log-2 TPM (transcript per million) with Variance-stabilizing transformation (VST) and Pearson Correlation Coefficient (PCC) association estimator. Second, raw RNA-seq count data with PCC. Along with these two, we also identified 18 other good preprocessing combinations. Any of these algorithms might perform best in different datasets. Therefore, the GNI performances of these approaches should be measured on any new dataset to select the best performing one for it. In terms of the required biological sample size of RNA-seq data, we found that between 30 to 85 samples were required to generate reliable GNI estimates.

Conclusions

This study provides practical recommendations on default choices for data preprocessing prior to GNI analysis of RNA-seq data to obtain optimal performance results.

Progression likelihood score identifies substages of presymptomatic type 1 diabetes in childhood public health screening

AIMS/HYPOTHESIS

The aim of this study was to develop strategies that identify children from the general population who have late-stage presymptomatic type 1 diabetes and may, therefore, benefit from immune intervention.

METHODS

We tested children from Bavaria, Germany, aged 1.75-10 years, enrolled in the Fr1da public health screening programme for islet autoantibodies (n=154,462). OGTT and HbA_1c were assessed in children with multiple islet autoantibodies for diagnosis of presymptomatic stage 1 (normoglycaemia) or stage 2 (dysglycaemia) type 1 diabetes. Cox proportional hazards and penalised logistic regression of autoantibody, genetic, metabolic and demographic information were used to develop a progression likelihood score to identify children with stage 1 type 1 diabetes who progressed to stage 3 (clinical) type 1 diabetes within 2 years.

RESULTS

Of 447 children with multiple islet autoantibodies, 364 (81.4%) were staged. Undiagnosed stage 3 type 1 diabetes, presymptomatic stage 2, and stage 1 type 1 diabetes were detected in 41 (0.027% of screened children), 30 (0.019%) and 293 (0.19%) children, respectively. The 2 year risk for progression to stage 3 type 1 diabetes was 48% (95% CI 34, 58) in children with stage 2 type 1 diabetes (annualised risk, 28%). HbA_1c, islet antigen-2 autoantibody positivity and titre, and the 90 min OGTT value were predictors of progression in children with stage 1 type 1 diabetes. The derived progression likelihood score identified substages corresponding to ≤90th centile (stage 1a, n=258) and >90th centile (stage 1b, n=29; 0.019%) of stage 1 children with a 4.1% (95% CI 1.4, 6.7) and 46% (95% CI 21, 63) 2 year risk of progressing to stage 3 type 1 diabetes, respectively.

CONCLUSIONS/INTERPRETATION

Public health screening for islet autoantibodies found 0.027% of children to have undiagnosed clinical type 1 diabetes and 0.038% to have undiagnosed presymptomatic stage 2 or stage 1b type 1 diabetes, with 50% risk to develop clinical type 1 diabetes within 2 years.

The emotional well-being of parents with children at genetic risk for type 1 diabetes before and during participation in the POInT-study

INTRODUCTION

This study examined the emotional impact that parents experience when confronted with an increased genetic risk of type 1 diabetes (T1D) in their child. Population-based screening of neonates for genetic risk of chronic disease carries the risk of increased emotional burden for parents.

METHODS

Information was collected using a well-being questionnaire for parents of infants identified as having an increased risk for T1D in a multinational research study. Parents were asked to complete this questionnaire after they were told their child had an increased risk for T1D (Freder1k-study) and at several time points during an intervention study (POInT-study), where oral insulin was administered daily.

RESULTS

Data were collected from 2595 parents of 1371 children across five countries. Panic-related anxiety symptoms were reported by only 4.9% after hearing about their child having an increased risk. Symptoms of depression were limited to 19.4% of the parents at the result-communication visit and declined over time during the intervention study. When thinking about their child's risk for developing T1D (disease-specific anxiety), 47.2% worried, felt nervous and tense. Mothers and parents with a first-degree relative (FDR) with T1D reported more symptoms of depression and disease-specific anxiety (p < 0.001) than fathers and parents without a FDR.

CONCLUSION

Overall, symptoms of depression and panic-related anxiety are comparable with the German population. When asked about their child's risk for T1D during the intervention study, some parents reported disease-specific anxiety, which should be kept in mind when considering population-based screening. As certain subgroups are more prone, it will be important to continue psychological screening and, when necessary, to provide support by an experienced, multidisciplinary team.

SARS-CoV-2 Seroprevalence in Preschool and School-Age Children

BACKGROUND

The SARS-CoV-2 pandemic is ongoing in Germany. Children and adolescents are increasingly being infected, and many cases presumably remain undetected and unreported. Sero-epidemiological studies can help estimate the true number of infections.

METHODS

From January 2020 to June 2022, 59 786 persons aged 1-17 years were tested for SARS-CoV-2 antibodies as part of a screening program for presymptomatic type 1 diabetes in the German federal state of Bavaria (the Fr1da study).

RESULTS

In June 2022, the seroprevalence in the overall population was 73.5%. The seroprevalence was significantly higher in school-age children (from 5 to 10 years of age) than in preschool children (ages 1-4): 84.4% vs. 66.6%, p <0.001. In contrast, in November 2021, before the appearance of the omicron variant, the overall seroprevalence was 14.7% (16.2% of school-age children, 13.0% of preschool children, p = 0.06). In the overall collective, seroprevalence increased fivefold from the fall of 2021 to June 2022 (by a factor of 5.2 in school-age children and 5.1 in preschool children). Similar seroprevalences, with smaller case numbers, were observed in June 2022 in the corresponding Fr1da studies in Saxony and Northern Germany: 87.8% and 76.7%, respectively.

CONCLUSION

Monthly case counts reveal a substantial rise in SARS-CoV-2-infections among children and adolescents from late 2021 to mid-2022. The high percentage of preschool and school-age children who have been infected with SARS-CoV-2, in a population that has low vaccination coverage, should be taken into account in the development of health policies.

A classification and regression tree analysis identifies subgroups of childhood type 1 diabetes

Background

Diabetes in childhood and adolescence includes autoimmune and non-autoimmune forms with heterogeneity in clinical and biochemical presentations. An unresolved question is whether there are subtypes, endotypes, or theratypes within these forms of diabetes.

Methods

The multivariable classification and regression tree (CART) analysis method was used to identify subgroups of diabetes with differing residual C-peptide levels in patients with newly diagnosed diabetes before 20 years of age (n=1192). The robustness of the model was assessed in a confirmation and prognosis cohort (n=2722).

Findings

The analysis selected age, haemoglobin A1c (HbA1c), and body mass index (BMI) as split parameters that classified patients into seven islet autoantibody-positive and three autoantibody-negative groups. There were substantial differences in genetics, inflammatory markers, diabetes family history, lipids, 25-OH-Vitamin D3, insulin treatment, insulin sensitivity and insulin autoimmunity among the groups, and the method stratified patients with potentially different pathogeneses and prognoses. Interferon-ɣ and/or tumour necrosis factor inflammatory signatures were enriched in the youngest islet autoantibody-positive groups and in patients with the lowest C-peptide values, while higher BMI and type 2 diabetes characteristics were found in older patients. The prognostic relevance was demonstrated by persistent differences in HbA1c at 7 years median follow-up.

Interpretation

This multivariable analysis revealed subgroups of young patients with diabetes that have potential pathogenetic and therapeutic relevance.

Funding

The work was supported by funds from the German Federal Ministry of Education and Research (01KX1818; FKZ 01GI0805; DZD e.V.), the Innovative Medicine Initiative 2 Joint Undertaking INNODIA (grant agreement No. 115797), the German Robert Koch Institute, and the German Diabetes Association.

A Public Health Antibody Screening Indicates a 6-Fold Higher SARS-CoV-2 Exposure Rate than Reported Cases in Children

BACKGROUND

Antibody responses to virus reflect exposure and potential protection.

METHODS

We developed a highly specific and sensitive approach to measuring antibodies against SARS-CoV-2 for population-scale immune surveillance. Antibody positivity was defined as a dual-positive response against both the receptor-binding domain and nucleocapsid proteins of SARS-CoV-2. Antibodies were measured by immunoprecipitation assays in capillary blood from 15,771 children aged 1 to 18 years living in Bavaria, Germany, and participating in a public health type 1 diabetes screening program (ClinicalTrials.gov: NCT04039945), in 1,916 dried blood spots from neonates in a Bavarian screening study (ClinicalTrials.gov: NCT03316261), and in 75 SARS-CoV-2-positive individuals. Virus positive incidence was obtained from the Bavarian health authority data.

FINDINGS

Dual-antibody positivity was detected in none of the 3,887 children in 2019 (100% specificity) and 73 of 75 SARS-CoV-2-positive individuals (97.3% sensitivity). Antibody surveillance in children during 2020 resulted in frequencies of 0.08% in January to March, 0.61% in April, 0.74% in May, 1.13% in June, and 0.91% in July. Antibody prevalence from April 2020 was 6-fold higher than the incidence of authority-reported cases (156 per 100,000 children), showed marked variation between the seven Bavarian regions (p < 0.0001), and was not associated with age or sex. Transmission in children with virus-positive family members was 35%. 47% of positive children were asymptomatic. No association with type 1 diabetes autoimmunity was observed. Antibody frequency in newborns was 0.47%.

CONCLUSIONS

We demonstrate the value of population-based screening programs for pandemic monitoring.

FUNDING

The work was supported by funding from the BMBF (FKZ01KX1818).

Islet expression of type I interferon response sensors is associated with immune infiltration and viral infection in type 1 diabetes

Previous results indicate the presence of an interferon (IFN) signature in type 1 diabetes (T1D), capable of inducing chronic inflammation and compromising b cell function. Here, we determined the expression of the IFN response markers MxA, PKR, and HLA-I in the islets of autoantibody-positive and T1D donors. We found that these markers can be coexpressed in the same islet, are more abundant in insulin-containing islets, are highly expressed in islets with insulitis, and their expression levels are correlated with the presence of the enteroviral protein VP1. The expression of these markers was associated with down-regulation of multiple genes in the insulin secretion pathway. The coexistence of an IFN response and a microbial stress response is likely to prime islets for immune destruction. This study highlights the importance of therapeutic interventions aimed at eliminating potentially persistent infections and diminishing inflammation in individuals with T1D.

Human herpesvirus-6 is present at higher levels in the pancreatic tissues of donors with type 1 diabetes

Human herpesvirus-6 (HHV-6) is a ubiquitous pathogen associated with nervous and endocrine autoimmune disorders. The aim of this study was to investigate the presence of HHV-6 in pancreatic tissue sections from non-diabetic, auto-antibody positive (AAB+), and donors with type 1 diabetes (T1D) and explore whether there is any association between HHV-6 and MHC class I hyperexpression and CD8 T cell infiltration. HHV-6 DNA was detected by PCR and its protein was examined by indirect immunofluorescence assay followed by imaging using high-resolution confocal microscopy. Viral DNA (U67) was found in most pancreata of non-diabetic (3 out of 4), AAB+ (3 out of 5) and T1D donors (6 out of 7). Interestingly, HHV-6 glycoprotein B (gB) was more expressed in islets and exocrine pancreas of donors with T1D. However, gB expression was not directly associated with other pathologies. Out of 20 islets with high gB expression, only 3 islets (15%) showed MHC class I hyperexpression. Furthermore, no correlation was found between gB expression and CD8 T cell infiltration on a per-islet basis in any of the groups. Our observations indicate that HHV-6 DNA and protein are present in the pancreas of non-diabetic subjects but gB expression is higher in the pancreas of donors with T1D. The possible role of HHV-6 as a contributory factor for T1D should therefore be further investigated.

Database of Immune Cell EQTLs, Expression, Epigenomics

Database of Immune Cell EQTLs, Expression, Epigenomics (DICE, dice-database.org) is a freely accessible web resource for diving deep into RNA-seq data across 13 human immune cell type (subsets of T cells, B cells, monocytes and NK cells), in a cohort of 91 healthy, genotyped donors1. The site is composed of four main modules that allow users to view the integrated data by gene, limit the scope to individual cell types, compare expression across cell types, and explore the effect of SNPs on gene expression. The site is optimized to be accessible on both desktop and mobile devices. DICE is an evolving resource with data for additional cell types being deposited on a continuous basis, with 3 additional B cell subsets being next in line. In addition to the core database website, an associated tools website (tools.dice-database.org) is actively being developed and currently hosts tools that operate on lists of genes to perform interactive GO enrichment analysis (GOnet), identify cell types most likely responsible for expression of a set of genes (CellTypeScorer), and examine GeneNetworks deduced from gene co-expression analysis.

Impact of genetic polymorphisms on human immune cell gene expression

While many genetic variants have been associated with risk for human diseases, how these variants affect gene expression in various cell types remains largely unknown. To address this gap, the DICE (database of immune cell expression, expression quantitative trait loci (eQTLs), and epigenomics) project was established. Considering all human immune cell types and conditions studied, we identified cis-eQTLs for a total of 12,254 unique genes, which represent 61% of all protein-coding genes expressed in these cell types. Strikingly, a large fraction (41%) of these genes showed a strong cis-association with genotype only in a single cell type. We also found that biological sex is associated with major differences in immune cell gene expression in a highly cell-specific manner. These datasets will help reveal the effects of disease risk-associated genetic polymorphisms on specific immune cell types, providing mechanistic insights into how they might influence pathogenesis (https://dice-database.org).

Unique phenotypes and clonal expansions of human CD4 effector memory T cells re-expressing CD45RA

The expression of CD45RA is generally associated with naive T cells. However, a subset of effector memory T cells re-expresses CD45RA (termed TEMRA) after antigenic stimulation with unknown molecular characteristics and functions. CD4 TEMRA cells have been implicated in protective immunity against pathogens such as dengue virus (DENV). Here we show that not only the frequency but also the phenotype of CD4 TEMRA cells are heterogeneous between individuals. These cells can be subdivided into two major subsets based on the expression of the adhesion G protein-coupled receptor GPR56, and GPR56+ TEMRA cells display a transcriptional and proteomic program with cytotoxic features that is distinct from effector memory T cells. Moreover, GPR56+ TEMRA cells have higher levels of clonal expansion and contain the majority of virus-specific TEMRA cells. Overall, this study reveals the heterogeneity of CD4 TEMRA cells and provides insights into T-cell responses against DENV and other viral pathogens.

Increase in Pancreatic Proinsulin and Preservation of β-Cell Mass in Autoantibody-Positive Donors Prior to Type 1 Diabetes Onset

Type 1 diabetes is characterized by the loss of insulin production caused by β-cell dysfunction and/or destruction. The hypothesis that β-cell loss occurs early during the prediabetic phase has recently been challenged. Here we show, for the first time in situ, that in pancreas sections from autoantibody-positive (Ab+) donors, insulin area and β-cell mass are maintained before disease onset and that production of proinsulin increases. This suggests that β-cell destruction occurs more precipitously than previously assumed. Indeed, the pancreatic proinsulin-to-insulin area ratio was also increased in these donors with prediabetes. Using high-resolution confocal microscopy, we found a high accumulation of vesicles containing proinsulin in β-cells from Ab+ donors, suggesting a defect in proinsulin conversion or an accumulation of immature vesicles caused by an increase in insulin demand and/or a dysfunction in vesicular trafficking. In addition, islets from Ab+ donors were larger and contained a higher number of β-cells per islet. Our data indicate that β-cell mass (and function) is maintained until shortly before diagnosis and declines rapidly at the time of clinical onset of disease. This suggests that secondary prevention before onset, when β-cell mass is still intact, could be a successful therapeutic strategy.

Alpha cells, the main source of IL-1β in human pancreas

Interleukin-1β (IL-1β) is known to trigger beta cell dysfunction in vitro and could potentially play a role during the pathogenesis of type 1 diabetes and type 2 diabetes. However, several clinical trials attempting to block IL-1β function have had minimal success. We therefore re-investigated local expression of IL-1β in human diabetic and non-diabetic pancreata. We obtained pancreatic tissue sections from the Network for Pancreatic Organ Donors with Diabetes (nPOD) including non-diabetic (n = 9), non-diabetic auto-antibody positive (AAb+, n = 5), type 1 diabetes (n = 6), and type 2 diabetes (n = 6) donors. Islets were systematically investigated for the presence of IL-1β mRNA by in situ hybridization and IL-1β protein by indirect immunofluorescence. We found that intra-islet IL-1β was produced at comparable level in both non-diabetic and diabetic donors. Interestingly, the main source for IL-1β was alpha cells but not beta cells. Our findings call into question the role of IL-1β in the diabetic pancreas as it has been proposed in previous literature. Additionally, our results regarding the localization of IL-1β should lead to further investigation into the role of IL-1β in the physiology of pancreatic alpha cells.

An Integrated Workflow To Assess Technical and Biological Variability of Cell Population Frequencies in Human Peripheral Blood by Flow Cytometry

In the context of large-scale human system immunology studies, controlling for technical and biological variability is crucial to ensure that experimental data support research conclusions. In this study, we report on a universal workflow to evaluate both technical and biological variation in multiparameter flow cytometry, applied to the development of a 10-color panel to identify all major cell populations and T cell subsets in cryopreserved PBMC. Replicate runs from a control donation and comparison of different gating strategies assessed the technical variability associated with each cell population and permitted the calculation of a quality control score. Applying our panel to a large collection of PBMC samples, we found that most cell populations showed low intraindividual variability over time. In contrast, certain subpopulations such as CD56 T cells and Temra CD4 T cells were associated with high interindividual variability. Age but not gender had a significant effect on the frequency of several populations, with a drastic decrease in naive T cells observed in older donors. Ethnicity also influenced a significant proportion of immune cell population frequencies, emphasizing the need to account for these covariates in immune profiling studies. We also exemplify the usefulness of our workflow by identifying a novel cell-subset signature of latent tuberculosis infection. Thus, our study provides a universal workflow to establish and evaluate any flow cytometry panel in systems immunology studies.

Transcriptional Profiling of Th2 Cells Identifies Pathogenic Features Associated with Asthma

Allergic asthma and rhinitis are two common chronic allergic diseases that affect the lungs and nose, respectively. Both diseases share clinical and pathological features characteristic of excessive allergen-induced type 2 inflammation, orchestrated by memory CD4(+) T cells that produce type 2 cytokines (Th2 cells). However, a large majority of subjects with allergic rhinitis do not develop asthma, suggesting divergence in disease mechanisms. Because Th2 cells play a pathogenic role in both these diseases and are also present in healthy nonallergic subjects, we performed global transcriptional profiling to determine whether there are qualitative differences in Th2 cells from subjects with allergic asthma, rhinitis, and healthy controls. Th2 cells from asthmatic subjects expressed higher levels of several genes that promote their survival as well as alter their metabolic pathways to favor persistence at sites of allergic inflammation. In addition, genes that enhanced Th2 polarization and Th2 cytokine production were also upregulated in asthma. Several genes that oppose T cell activation were downregulated in asthma, suggesting enhanced activation potential of Th2 cells from asthmatic subjects. Many novel genes with poorly defined functions were also differentially expressed in asthma. Thus, our transcriptomic analysis of circulating Th2 cells has identified several molecules that are likely to confer pathogenic features to Th2 cells that are either unique or common to both asthma and rhinitis.

Heterogeneity and Lobularity of Pancreatic Pathology in Type 1 Diabetes during the Prediabetic Phase

Type 1 diabetes (T1D) is an autoimmune disease in which insulin-producing beta cells are destroyed in the islets of Langerhans. One of its main pathological manifestations is the hyper-expression of Major Histocompatibility Complex I (MHC-I) by beta cells, which was first described over 3 decades ago yet its cause remains unknown. It might not only be a sign of beta cell dysfunction but could also render the cells susceptible to autoimmune destruction; for example, by islet-infiltrating CD8 T cells. In this report, we studied pancreas tissue from a 22-year-old non-diabetic male cadaveric organ donor who had been at high risk of developing T1D, in which autoantibodies against GAD and IA-2 were detected. Pancreas sections were analyzed for signs of inflammation. Multiple insulin-containing islets were identified, which hyper-expressed MHC-I. However, islet density and MHC-I expression exhibited a highly lobular and heterogeneous pattern even within the same section. In addition, many islets with high expression of MHC-I presented higher levels of CD8 T cell infiltration than normal islets. These results demonstrate the heterogeneity of human pathology that occurs early during the pre-diabetic, autoantibody positive phase, and should contribute to the understanding of human T1D.

Increased immune cell infiltration of the exocrine pancreas: a possible contribution to the pathogenesis of type 1 diabetes

Type 1 diabetes (T1D) results from a complex interplay between genetic susceptibility and environmental factors that have been implicated in the pathogenesis of disease both as triggers and potentiators of β-cell destruction. CD8 T cells are the main cell type found in human islets, and they have been shown in vitro to be capable of killing β-cells overexpressing MHC class I. In this study, we report that CD8 T cells infiltrate the exocrine pancreas of diabetic subjects in high numbers and not only endocrine areas. T1D subjects present significantly higher CD8 T cell density in the exocrine tissue without the presence of prominent insulitis. Even T1D donors without remaining insulin-containing islets and long disease duration show elevated levels of CD8 T cells in the exocrine compartment. In addition, higher numbers of CD4(+) and CD11c(+) cells were found in the exocrine tissue. Preliminary data in type 2 diabetic (T2D) subjects indicate that overall, there might be a spontaneous inflammatory infiltration of the exocrine tissue, common to both T1D and T2D subjects. Our study provides the first information on the precise tissue distribution of CD8 T cells in pancreata from T1D, T2D, autoantibody-positive, and healthy control subjects.