Type 1 diabetes (T1D) is an autoimmune disease that is caused, in part, by T cell–mediated destruction of insulin-producing β-cells. High risk for disease, in those with genetic susceptibility, is predicted by the presence of two or more autoantibodies against insulin, the 65-kDa form of glutamic acid decarboxylase (GAD65), insulinoma-associated protein 2 (IA-2), and zinc transporter 8 (ZnT8). Despite this knowledge, we still do not know what leads to the breakdown of tolerance to these autoantigens, and we have an incomplete understanding of T1D etiology and pathophysiology. Several new autoantibodies have recently been discovered using innovative technologies, but neither their potential utility in monitoring disease development and treatment nor their role in the pathophysiology and etiology of T1D has been explored. Moreover, neoantigen generation (through posttranslational modification, the formation of hybrid peptides containing two distinct regions of an antigen or antigens, alternative open reading frame usage, and translation of RNA splicing variants) has been reported, and autoreactive T cells that target these neoantigens have been identified. Collectively, these new studies provide a conceptual framework to understand the breakdown of self-tolerance, if such modifications occur in a tissue- or disease-specific context. A recent workshop sponsored by the National Institute of Diabetes and Digestive and Kidney Diseases brought together investigators who are using new methods and technologies to identify autoantigens and characterize immune responses toward these proteins. Researchers with diverse expertise shared ideas and identified resources to accelerate antigen discovery and the detection of autoimmune responses in T1D. The application of this knowledge will direct strategies for the identification of improved biomarkers for disease progression and treatment response monitoring and, ultimately, will form the foundation for novel antigen-specific therapeutics. This Perspective highlights the key issues that were addressed at the workshop and identifies areas for future investigation.

The Centers for Disease Control and Prevention reports that about 9.4% of the U.S. population has diabetes and about 5% of the people with diabetes have type 1 diabetes (T1D) (1). Although T1D has a significant genetic component, most diagnosed people do not have a known family history of the disease. The causes that lead to T1D are not fully established, but in individuals with genetic susceptibility (determined in large part by the expression of certain class II MHC molecules [2]), the development of the disease can usually be predicted by the presence of two or more autoantibodies with different specificities (3,4). Autoantibodies against insulin, the 65-kDa form of glutamic acid decarboxylase (GAD65), insulinoma-associated protein 2 (IA-2), and zinc transporter 8 (ZnT8) are commonly known as the major specificities in T1D, but their role in the pathophysiology of the disease is not clear. Recently, several new antigens and epitopes and their corresponding humoral and/or T cell–mediated responses have been reported. However, their potential utility in monitoring disease development, progression, and treatment and their role in the pathophysiology and etiology of T1D have been explored only in a very limited manner. What leads to the loss of tolerance and autoimmunity in T1D is certainly one of the key questions to be answered for understanding the pathogenesis of the disease. Although imperfect (5), central tolerance leads to the deletion of some proportion of self-reactive lymphocytes. However, lymphocytes specific for epitopes generated only in a tissue- and/or disease-specific context will not be subject to central tolerance mechanisms (6). Thus, the idea that a neoantigen or a modified self-antigen (e.g., arising from a tissue-specific posttranslational modification) can lead to the breakdown of tolerance is a compelling hypothesis (7) that warrants investigation.

For assessing the state of the art in elucidating the potential role of neoepitopes and neoantigens in the pathophysiology of T1D, the National Institute of Diabetes and Digestive and Kidney Diseases convened a group of scientists with different expertise at the Autoantigens Discovery and Characterization in Type 1 Diabetes workshop in Bethesda, MD, 31 October–1 November 2017 (www.niddk.nih.gov/news/meetings-workshops/2017/autoantigens2017). In particular, experts from other autoimmune diseases, cancer immunotherapy, and cutting-edge technologies for T-cell and antigen characterization and discovery were brought together. The workshop was organized around three main themes: characterization of the autoimmune response in T1D and other disease contexts, identification of new autoantigens and epitopes in T1D, and novel technologies in T-cell response and autoantigen identification and characterization. This report highlights the main points that were discussed at the workshop and reflects on possible future developments that might be needed for moving toward a better understanding of the autoimmune response in T1D.

In the 35 years since the discovery of insulin as the first autoantigen in human T1D, over 30 additional ones have been reported (8), though a substantial fraction of these putative autoantigens have only been sparsely studied and/or have not withstood the test of time. In contrast, insulin, GAD65, IA-2, and ZnT8 are well accepted by the field as major autoantigens (Table 1), due primarily to the utility of their corresponding autoantibodies in T1D risk assessment and diagnosis (3,4). Several additional antigens have also established their place in human T1D (Table 2). Examples include islet-specific glucose-6-phosphatase catalytic subunit-related protein (IGRP) (9,10), chromogranin A (ChgA) (11,12), and islet amyloid polypeptide (IAPP) (1315). Still others (Table 3), e.g., peripherin (16), tetraspanin-7 (17), prolyl-4-hydroxylase β (P4Hb) (18), glucose-regulated protein 78 (GRP78) (19), urocortin-3 (20), and insulin gene enhancer protein isl-1 (20), have only more recently been discovered and warrant further exploration.

Table 1

Major autoantigens used in human T1D diagnosis and risk assessment

AutoantigenExpressionSubcellular locationHuman T1D
AntibodiesCD4+ T cellsCD8+ T cells
Insulin β-cell Secretory granule 
GAD65 Neuroendocrine Synaptic-like microvesicles 
IA-2 Neuroendocrine Secretory granule 
ZnT8 β-cell Secretory granule 
AutoantigenExpressionSubcellular locationHuman T1D
AntibodiesCD4+ T cellsCD8+ T cells
Insulin β-cell Secretory granule 
GAD65 Neuroendocrine Synaptic-like microvesicles 
IA-2 Neuroendocrine Secretory granule 
ZnT8 β-cell Secretory granule 
Table 2

Select additional established autoantigens in human T1D

AutoantigenExpressionSubcellular locationHuman T1D
AntibodiesCD4+ T cellsCD8+ T cells
IGRP β-cell Endoplasmic reticulum  
ChgA Neuroendocrine Secretory granule  
IAPP β-cell Secretory granule 
AutoantigenExpressionSubcellular locationHuman T1D
AntibodiesCD4+ T cellsCD8+ T cells
IGRP β-cell Endoplasmic reticulum  
ChgA Neuroendocrine Secretory granule  
IAPP β-cell Secretory granule 
Table 3

Examples of recently identified autoantigens in human T1D

AutoantigenExpressionSubcellular locationHuman T1D
AntibodiesCD4+ T cellsCD8+ T cells
Peripherin Neuroendocrine Filaments   
Tetraspanin-7 Neuroendocrine Plasma membrane   
P4Hb Not restricted Endoplasmic reticulum   
GRP78 Not restricted Endoplasmic reticulum  
Urocortin-3 β-cell, α-cell Secretory granule   
Insulin gene enhancer protein isl-1 Not restricted Nucleus   
AutoantigenExpressionSubcellular locationHuman T1D
AntibodiesCD4+ T cellsCD8+ T cells
Peripherin Neuroendocrine Filaments   
Tetraspanin-7 Neuroendocrine Plasma membrane   
P4Hb Not restricted Endoplasmic reticulum   
GRP78 Not restricted Endoplasmic reticulum  
Urocortin-3 β-cell, α-cell Secretory granule   
Insulin gene enhancer protein isl-1 Not restricted Nucleus   

Islet-Infiltrating Cells

Until recently, nearly all of the knowledge concerning T-cell reactivity to islet antigens in humans was obtained using T cells from peripheral blood rather than from islets themselves. Some of the earliest evidence for the presence of islet-reactive T cells in the blood of T1D patients and at-risk individuals was reported in the early 1990s (21). Since then, more than 100 epitopes, derived from over 10 antigens, have been identified using peripheral blood as the T-cell source (22,23). It should be noted, however, that the majority of these epitopes have not yet been rigorously proven to be naturally processed and presented by relevant antigen-presenting cells. Hopes of similarly examining the antigenic reactivities of T cells isolated from islets were dampened by the problem of tissue accessibility, coupled with the notion that β-cells and, thus, β-cell–specific T cells, were unlikely to be present in the pancreata of long-standing T1D patients. However, the Joslin Medalist Study, which examined pancreata from T1D donors who had lived with the disease for 50 years or more, revealed that β-cells were indeed still present in such individuals, as were islet-infiltrating T cells (24). This finding led to the realization that there was much to be learned about human T1D, and it was surely one of the stimuli for continued investigator-initiated studies of the human T1D pancreas as well as the growth of the Network for Pancreatic Organ Donors with Diabetes (nPOD), an initiative which procures and distributes T1D pancreata to the research community (25). These efforts have recently made possible the first investigations of the antigenic specificities (2629) and T-cell receptor repertoire (30) of human islet-infiltrating T cells in T1D. Some of the specificities previously identified using peripheral blood have now been validated using islet T cells, supporting the continued and complementary use of peripheral blood T cells for antigen identification efforts, and new specificities have also been uncovered. Whether some specificities will be found only in the islets, and not also in peripheral blood, remains to be determined. However, it now appears that T cells specific for islet antigens are enriched in the pancreas, but not in the blood or pancreatic lymph nodes, of donors having T1D compared with donors without diabetes (20,31). Another important open question relevant to both antigen identification and T-cell receptor repertoire analyses is what proportion of the human islet-infiltrating T cells are truly specific for islet antigens. Findings from several mouse studies support the idea that islet-infiltrating T cells may be largely β-cell–specific (32,33), but this remains controversial (34,35) and ideally would be addressed using human samples. These open questions notwithstanding, the discovery of previously unknown specificities using islet T cells has breathed new life into the antigen identification efforts of the T1D community and has encouraged collaboration and consultation with those studying other related disease entities.

Modified Epitopes

Celiac disease is an enteropathy mediated by a T-cell response to gluten peptides in which tissue transglutaminase 2 has converted at least one glutamine to glutamic acid (36). The deamidation of glutamine residues in gliadin and other wheat proteins generates high-affinity peptide ligands for the disease-associated HLA-DQ alleles (36). This reflects the preference of HLA-DQ2 and HLA-DQ8 for peptides with acidic residues, and the resultant conversion of glutamine to glutamic acid facilitates the binding of these peptides to the disease-associated alleles. Unlike in T1D, in celiac disease an immune response with a defined onset can be experimentally induced in humans with an oral gluten challenge, thus greatly facilitating the antigen identification efforts that led to these discoveries. Despite this important difference, T1D investigators continue to draw inspiration from their celiac disease colleagues, especially since the two diseases share a genetic association with the same HLA-DQ alleles. Deamidated peptides of several classical T1D antigens, i.e., insulin (37,38), GAD65 (37,39), and IA-2 (26,40), have recently been shown to be recognized by peripheral blood and/or islet T cells from T1D patients.

The association of citrullination of arginine residues of joint autoantigens with rheumatoid arthritis was first suggested by a genetic association with a single nucleotide polymorphism that affects stability of the PADI4 transcript, encoding protein-arginine deiminase type-4 (41). Subsequent studies have indeed shown citrullinated joint autoantigens to be the target of both autoantibodies (42,43) and also CD4+ T cells restricted by the rheumatoid arthritis–associated alleles HLA-DR4 and -DR1 (44,45). Citrullination, at least in part, appears to dictate the binding of autoantigen-derived peptides to disease-associated HLA-DR molecules as well as affecting T-cell recognition by some patient-derived T-cell clones. As in rheumatoid arthritis, autoantibodies (19,46) and T cells from patients with T1D, including islet-infiltrating ones, have also been shown to respond to citrullinated autoantigens including GRP78 (19,26), GAD65 (39), and IAPP (26).

Another recent advance has been the identification of so-called hybrid insulin peptides, which comprise peptide fragments derived from both insulin and other insulin secretory granule proteins that are fused together to form the hybrid peptide. Though first identified as the cognate antigens for pathogenic CD4+ T-cell clones derived from NOD mice, their potential importance in human T1D was suggested by the finding that they are also recognized by islet-infiltrating T cells obtained from patients (26,27).

These discoveries support the contention that antigen identification efforts in T1D must continue, as novel and important insights are still arising from such work. They also suggest the cautionary note that antigen identification efforts should consider posttranslationally modified peptides and other forms of neoepitopes (e.g., ones generated by translation of RNA splicing variants [20] or alternative open reading frame usage [47]) whenever feasible. For example, recently it was reported that a defective ribosomal product, or DRiP (48), can be translated from the human insulin mRNA when an out-of-frame downstream AUG serves as a translation initiation site. This leads to usage of an alternative reading frame that includes the 3′ untranslated region and the synthesis of a product having 43 amino acids (47). A nonapeptide derived from this was predicted to bind well to the human class I MHC molecule HLA-A*02:01 and was found to be recognized by CD8+ T cells from HLA-A*02:01–positive T1D patients (47).

The burgeoning area of neoepitopes in T1D is ushering in the idea of the β-cell contributing to its own demise (49), in the sense that neoepitope formation, including alternative open reading frame usage, can be enhanced under conditions of endoplasmic reticulum stress and inflammation (47,50,51), with the resulting neoepitopes potentially contributing to the breakdown of immunological self-tolerance. Furthermore, β-cells have recently been shown to release peptides derived from insulin catabolism into the circulation, and these peptides can subsequently activate pathogenic insulin-specific T cells (52).

Disease Heterogeneity

It is now becoming appreciated that, whether designing antigen identification strategies or clinical trials, T1D should not simply be viewed as a single disease but rather as a heterogeneous entity. Some aspects of heterogeneity, e.g., age at onset, have long been known and appreciated, while others, such as the pattern of autoantibody appearance (53,54) and pancreatic immune cell presence (both among individuals and among islets in a single individual) (25,55,56), have only been ushered in relatively recently. From studies of insulitic lesions, among other approaches, investigators are now working to identify T1D endotypes, or subsets of the disease likely sharing a common pathogenic mechanism (57). Characterization of the spectrum of antigens and epitopes recognized in each case will likely help in these efforts. This is important work, as disease heterogeneity has been blamed, at least in part, for the failure of the field to identify a robust preventive or reversal strategy for T1D, despite years of earnest and exhausting efforts (58).

With multiple established autoantigens well accepted by the field (Tables 1 and 2), the quest to identify new autoantigens may seem redundant on first inspection. However, additional autoantigens may not only prove to be powerful targets of immunomodulatory therapies but also shed light on the pathogenesis of T1D. Moreover, given the noted heterogeneity of the disease, a more personalized approach to immune profiling will be facilitated through the validation of a broader spectrum of disease-relevant autoantigens. Additional autoantigens may also help to further stratify treatment modalities and provide diagnostic or prognostic tests that go beyond current clinical management of individuals with T1D. Perhaps more importantly, there is still an immediate requirement to identify the HLA class I– and class II–restricted epitopes recognized by autoreactive T cells in T1D, as the vast majority of identified and validated T-cell epitopes are restricted to a mere handful of HLA alleles (22,23). Given the independent associations of HLA class I and class II alleles with disease (2), understanding the T-cell reactivity on a personalized basis will herald in a new era of T1D treatments and diagnostics.

In addition to a requirement to identify additional autoantigens of relevance to different stages of the disease, understanding the role of posttranslational modifications of both new and established autoantigens is critical for the launching of new therapies and for providing a molecular basis of the disease. Posttranslational modification of antigens can impact the liberation of immunogenic epitopes during antigen processing (59), altering the spectrum of presented peptides. Modification of peptide antigens can also affect their binding to different HLA alleles, with some modifications enhancing binding to disease-associated allomorphs (37,49,59,60) and others providing novel targets for T-cell recognition (6170).

Besides modification of antigens by processes such as deamidation and citrullination, a more novel class of neoepitopes has also been implicated in T1D. This class is potentially generated through transpeptidation, a reverse proteolysis reaction, that can generate spliced or hybrid peptide antigens such as the hybrid insulin peptides recognized by CD4+ T cells discussed above (27). Likewise, recent studies have also emphasized the contribution of proteasomal or other posttranslational splicing reactions to the class I MHC antigen processing pathway (7175), estimated in multiple studies (71,72), though not in all (73), to contribute an astonishing 30% of peptides to the peptide repertoire of antigen-presenting cells. While their role in T1D is not yet apparent, such peptides may be targets of the autoimmune response in T1D. Consistent with this notion is the recent finding that a peptide derived from noncontiguous parts of IAPP is recognized by islet-infiltrating CD8+ T cells from T1D patients (20).

T1D has seen a recent uptake of new and novel technologies for the characterization of T-cell responses and the identification of autoantigens. Prominent among these has been recent progress in the development of autoimmune-prone mice “humanized” to express HLA molecules for use in epitope mapping and pathogenicity studies (7678). Similarly, the generation of tissue repositories has facilitated the production of islet-derived T-cell clone libraries and related resources for the validation and discovery of novel T-cell targets (25,26,29,30,79). Such resources can be interrogated with synthetic peptides, antigen preparations from islets and other sources, or with relevant peptide-MHC multimers. Though not limited to T1D-related antigens, the Immune Epitope Database (iedb.org) is a critical resource for the selection of candidates for such screening efforts (80). In each case, appropriate posttranslational modifications can be introduced, as is particularly evident by recent studies with HLA class II tetramers in T1D (19,40) and other autoimmune diseases (45,81,82). Multiplexing these assays, particularly tetramers with either coded fluorophores (83,84), mass cytometry tags (85), or DNA bar codes (86,87), significantly extends the use of this screening technology and interfaces with single-cell genomic studies to study gene expression in autoreactive T-cell clones (86,87). Indeed, advances in single-cell analysis have led to extrapolation of T-cell and B-cell reactivity profiles and the identification of additional modifiers of disease. At least for class I MHC–restricted T-cell epitopes, coupling peptide/MHC multimer technology with other analyses may be of particular importance, given the recent finding that the frequency of tetramer-binding islet-reactive CD8+ T cells in peripheral blood does not differ between T1D patients and healthy control subjects (31).

Finally, continued development of unbiased approaches for antigen and epitope identification is also urgently needed. In one such strategy, small molecules are used as “epitope surrogates” to enrich for T1D-specific autoantibodies from patient sera (16). The enriched antibodies are then used to identify the target protein(s), the approach that yielded the identification of phosphorylated peripherin as an autoantigen in T1D (Table 3) (16). Likewise, serum screening of a nucleic acid–programmable, cell-free protein array, designed in an unbiased manner (i.e., without regard to pancreas expression level), recently revealed close to 20 previously unidentified targets of the autoantibody response in T1D (88). These targets await further study. It should be noted that each autoantigen discovery approach has its own characteristic strengths and weaknesses (89). Thus, the different strategies are best viewed as complementary rather than competing or redundant.

In the quest for unbiased approaches for antigen and epitope identification, mass spectrometry has certainly risen to the fore. Improvements in sensitivity and speed of this instrumentation now make peptidome profiling of HLA-bound peptides relatively routine and have opened up the possibility to work with limited patient-derived material (90,91). Such analysis also allows for unambiguous definition of posttranslational modifications of epitopes (9295) or from proteome extracts (19,9698) of patient-derived material. To date, characterization of the HLA class I–bound peptides from human β-cells has been limited, primarily due to difficulties in obtaining sufficient material (20). Islets harvested from cadaveric donors with T1D have very few β-cells remaining, and those from donors without diabetes have naturally low levels of cell surface HLA expression in the absence of inflammation, making direct detection of presented peptides challenging. To circumvent these issues, various approaches have been used to discover epitopes of relevance to T1D including the direct biochemical isolation and characterization of naturally presented autoantigen-derived peptides from murine β-cell lines (99), stably transfected human non–β-cell lines expressing autoantigen(s) and cell surface HLA allotypes of interest (100,101), or human β-cell lines generated by targeted oncogenesis (20). These latter approaches take advantage of the cellular antigen processing machinery and can directly identify the antigenic peptides sampled for cell surface presentation by disease-associated MHC molecules, although questions remain as to whether such approaches faithfully represent natural presentation on primary human β-cells. Peptidomics was recently combined with transcriptomics to identify peptides derived from two new autoantigens, insulin gene enhancer protein isl-1 and urocortin-3 (Table 3), for which the cognate T cells are enriched in the pancreata of T1D donors compared with those without diabetes (20).

A more complete knowledge of the specificities of T and B cells in T1D will assist in the development of targeted immune tolerance as well as in diagnosis, patient characterization, and pre- and posttherapy immune monitoring. Exhilarating recent discoveries, such as T-cell recognition of hybrid and other posttranslationally modified peptides, have demonstrated that much remains to be discovered. Targeted immune system tolerance remains a highly sought-after yet elusive goal for the prevention and treatment of T1D. The need is urgent, given that the incidence of the disease is on the rise, and T1D associated with immune checkpoint inhibitor therapy for cancer is an emerging entity also requiring our focused and immediate attention.

The opinions expressed in this article are the authors’ own and do not necessarily reflect the views of the National Institute of Diabetes and Digestive and Kidney Diseases.

Acknowledgments. The authors acknowledge all those who attended the Autoantigens Discovery and Characterization in Type 1 Diabetes workshop whose participation contributed to our views regarding the themes presented here. The authors especially thank Lisa M. Spain of the National Institute of Diabetes and Digestive and Kidney Diseases for discussions, suggestions, and encouragement throughout the workshop.

Funding. A.W.P. acknowledges fellowship support from the Australian National Health and Medical Research Council (1044215). Work in the laboratory of T.P.D. is supported by the National Institute of Diabetes and Digestive and Kidney Diseases (R01 DK120420, and P30 DK020541, which supports the Einstein-Mount Sinai Diabetes Research Center), the National Institute of Allergy and Infectious Diseases (R01 AI123730), and the American Diabetes Association (1-16-IBS-069). T.P.D. is the Diane Belfer, Cypres & Endelson Families Faculty Scholar in Diabetes Research.

Duality of Interest. No potential conflicts of interest relevant to this article were reported.

1.
Centers for Disease Control and Prevention
.
National Diabetes Statistics Report, 2017
.
Atlanta, GA
,
Centers for Disease Control and Prevention, U.S. Dept of Health and Human Services
,
2017
2.
Nejentsev
S
,
Howson
JM
,
Walker
NM
, et al.;
Wellcome Trust Case Control Consortium
.
Localization of type 1 diabetes susceptibility to the MHC class I genes HLA-B and HLA-A
.
Nature
2007
;
450
:
887
892
[PubMed]
3.
Achenbach
P
,
Lampasona
V
,
Landherr
U
, et al
.
Autoantibodies to zinc transporter 8 and SLC30A8 genotype stratify type 1 diabetes risk
.
Diabetologia
2009
;
52
:
1881
1888
[PubMed]
4.
Ziegler
AG
,
Rewers
M
,
Simell
O
, et al
.
Seroconversion to multiple islet autoantibodies and risk of progression to diabetes in children
.
JAMA
2013
;
309
:
2473
2479
[PubMed]
5.
Yu
W
,
Jiang
N
,
Ebert
PJ
, et al
.
Clonal deletion prunes but does not eliminate self-specific αβ CD8+ T lymphocytes
.
Immunity
2015
;
42
:
929
941
[PubMed]
6.
Raposo
B
,
Merky
P
,
Lundqvist
C
, et al
.
T cells specific for post-translational modifications escape intrathymic tolerance induction
.
Nat Commun
2018
;
9
:
353
[PubMed]
7.
Harbige
J
,
Eichmann
M
,
Peakman
M
.
New insights into non-conventional epitopes as T cell targets: the missing link for breaking immune tolerance in autoimmune disease?
J Autoimmun
2017
;
84
:
12
20
[PubMed]
8.
Chaparro
RJ
,
Dilorenzo
TP
.
An update on the use of NOD mice to study autoimmune (type 1) diabetes
.
Expert Rev Clin Immunol
2010
;
6
:
939
955
[PubMed]
9.
Mallone
R
,
Martinuzzi
E
,
Blancou
P
, et al
.
CD8+ T-cell responses identify β-cell autoimmunity in human type 1 diabetes
.
Diabetes
2007
;
56
:
613
621
[PubMed]
10.
Yang
J
,
Danke
NA
,
Berger
D
, et al
.
Islet-specific glucose-6-phosphatase catalytic subunit-related protein-reactive CD4+ T cells in human subjects
.
J Immunol
2006
;
176
:
2781
2789
[PubMed]
11.
Gottlieb
PA
,
Delong
T
,
Baker
RL
, et al
.
Chromogranin A is a T cell antigen in human type 1 diabetes
.
J Autoimmun
2014
;
50
:
38
41
[PubMed]
12.
Li
Y
,
Zhou
L
,
Li
Y
, et al
.
Identification of autoreactive CD8+ T cell responses targeting chromogranin A in humanized NOD mice and type 1 diabetes patients
.
Clin Immunol
2015
;
159
:
63
71
[PubMed]
13.
Denroche
HC
,
Verchere
CB
.
IAPP and type 1 diabetes: implications for immunity, metabolism and islet transplants
.
J Mol Endocrinol
2018
;
60
:
R57
R75
[PubMed]
14.
Panagiotopoulos
C
,
Qin
H
,
Tan
R
,
Verchere
CB
.
Identification of a β-cell-specific HLA class I restricted epitope in type 1 diabetes
.
Diabetes
2003
;
52
:
2647
2651
[PubMed]
15.
Standifer
NE
,
Ouyang
Q
,
Panagiotopoulos
C
, et al
.
Identification of Novel HLA-A*0201-restricted epitopes in recent-onset type 1 diabetic subjects and antibody-positive relatives
.
Diabetes
2006
;
55
:
3061
3067
[PubMed]
16.
Doran
TM
,
Morimoto
J
,
Simanski
S
, et al
.
Discovery of phosphorylated peripherin as a major humoral autoantigen in type 1 diabetes mellitus
.
Cell Chem Biol
2016
;
23
:
618
628
[PubMed]
17.
McLaughlin
KA
,
Richardson
CC
,
Ravishankar
A
, et al
.
Identification of tetraspanin-7 as a target of autoantibodies in type 1 diabetes
.
Diabetes
2016
;
65
:
1690
1698
[PubMed]
18.
Yang
ML
,
Wen
L
,
Herold
KC
,
Mamula
MJ
. Posttranslational modification of islet autoantigens in type 1 diabetes (Abstract). J Immunol
2016
;196 (Suppl. 1):Section 118, Abstract 009
19.
Buitinga
M
,
Callebaut
A
,
Marques Câmara Sodré
F
, et al
.
Inflammation-induced citrullinated glucose-regulated protein 78 elicits immune responses in human type 1 diabetes
.
Diabetes
2018
;
67
:
2337
2348
[PubMed]
20.
Gonzalez-Duque
S
,
Azoury
ME
,
Colli
ML
, et al
.
Conventional and neo-antigenic peptides presented by β cells are targeted by circulating naive CD8+ T cells in type 1 diabetic and healthy donors
.
Cell Metab
2018
;
28
:
946
960.e6
[PubMed]
21.
Harrison
LC
,
Chu
SX
,
DeAizpurua
HJ
,
Graham
M
,
Honeyman
MC
,
Colman
PG
.
Islet-reactive T cells are a marker of preclinical insulin-dependent diabetes
.
J Clin Invest
1992
;
89
:
1161
1165
[PubMed]
22.
Di Lorenzo
TP
,
Peakman
M
,
Roep
BO
.
Translational mini-review series on type 1 diabetes: systematic analysis of T cell epitopes in autoimmune diabetes
.
Clin Exp Immunol
2007
;
148
:
1
16
[PubMed]
23.
Mallone
R
,
Brezar
V
,
Boitard
C
.
T cell recognition of autoantigens in human type 1 diabetes: clinical perspectives
.
Clin Dev Immunol
2011
;
2011
:
513210
[PubMed]
24.
Keenan
HA
,
Sun
JK
,
Levine
J
, et al
.
Residual insulin production and pancreatic β-cell turnover after 50 years of diabetes: Joslin Medalist Study
.
Diabetes
2010
;
59
:
2846
2853
[PubMed]
25.
Kaddis
JS
,
Pugliese
A
,
Atkinson
MA
.
A run on the biobank: what have we learned about type 1 diabetes from the nPOD tissue repository?
Curr Opin Endocrinol Diabetes Obes
2015
;
22
:
290
295
[PubMed]
26.
Babon
JA
,
DeNicola
ME
,
Blodgett
DM
, et al
.
Analysis of self-antigen specificity of islet-infiltrating T cells from human donors with type 1 diabetes
.
Nat Med
2016
;
22
:
1482
1487
[PubMed]
27.
Delong
T
,
Wiles
TA
,
Baker
RL
, et al
.
Pathogenic CD4 T cells in type 1 diabetes recognize epitopes formed by peptide fusion
.
Science
2016
;
351
:
711
714
[PubMed]
28.
Michels
AW
,
Landry
LG
,
McDaniel
KA
, et al
.
Islet-derived CD4 T cells targeting proinsulin in human autoimmune diabetes
.
Diabetes
2017
;
66
:
722
734
[PubMed]
29.
Pathiraja
V
,
Kuehlich
JP
,
Campbell
PD
, et al
.
Proinsulin-specific, HLA-DQ8, and HLA-DQ8-transdimer-restricted CD4+ T cells infiltrate islets in type 1 diabetes
.
Diabetes
2015
;
64
:
172
182
[PubMed]
30.
Seay
HR
,
Yusko
E
,
Rothweiler
SJ
, et al
.
Tissue distribution and clonal diversity of the T and B cell repertoire in type 1 diabetes
.
JCI Insight
2016
;
1
:
e88242
[PubMed]
31.
Culina
S
,
Lalanne
AI
,
Afonso
G
, et al.; ImMaDiab Study Group. Islet-reactive CD8+ T cell frequencies in the pancreas, but not in blood, distinguish type 1 diabetic patients from healthy donors. Sci Immunol
2018
;3:eaao4013
32.
Lennon
GP
,
Bettini
M
,
Burton
AR
, et al
.
T cell islet accumulation in type 1 diabetes is a tightly regulated, cell-autonomous event
.
Immunity
2009
;
31
:
643
653
[PubMed]
33.
Wang
J
,
Tsai
S
,
Shameli
A
,
Yamanouchi
J
,
Alkemade
G
,
Santamaria
P
.
In situ recognition of autoantigen as an essential gatekeeper in autoimmune CD8+ T cell inflammation
.
Proc Natl Acad Sci U S A
2010
;
107
:
9317
9322
[PubMed]
34.
Christoffersson
G
,
Chodaczek
G
,
Ratliff
SS
,
Coppieters
K
,
von Herrath
MG
. Suppression of diabetes by accumulation of non-islet-specific CD8+ effector T cells in pancreatic islets. Sci Immunol
2018
;3:eaam6533
35.
Magnuson
AM
,
Thurber
GM
,
Kohler
RH
,
Weissleder
R
,
Mathis
D
,
Benoist
C
.
Population dynamics of islet-infiltrating cells in autoimmune diabetes
.
Proc Natl Acad Sci U S A
2015
;
112
:
1511
1516
[PubMed]
36.
Sollid
LM
.
The roles of MHC class II genes and post-translational modification in celiac disease
.
Immunogenetics
2017
;
69
:
605
616
[PubMed]
37.
van Lummel
M
,
Duinkerken
G
,
van Veelen
PA
, et al
.
Posttranslational modification of HLA-DQ binding islet autoantigens in type 1 diabetes
.
Diabetes
2014
;
63
:
237
247
[PubMed]
38.
van Lummel
M
,
van Veelen
PA
,
de Ru
AH
, et al
.
Discovery of a selective islet peptidome presented by the highest-risk HLA-DQ8trans molecule
.
Diabetes
2016
;
65
:
732
741
[PubMed]
39.
McGinty
JW
,
Chow
IT
,
Greenbaum
C
,
Odegard
J
,
Kwok
WW
,
James
EA
.
Recognition of posttranslationally modified GAD65 epitopes in subjects with type 1 diabetes
.
Diabetes
2014
;
63
:
3033
3040
[PubMed]
40.
Acevedo-Calado
M
,
James
EA
,
Morran
MP
, et al
.
Identification of unique antigenic determinants in the amino terminus of IA-2 (ICA512) in childhood and adult autoimmune diabetes: new biomarker development
.
Diabetes Care
2017
;
40
:
561
568
[PubMed]
41.
Suzuki
A
,
Yamada
R
,
Chang
X
, et al
.
Functional haplotypes of PADI4, encoding citrullinating enzyme peptidylarginine deiminase 4, are associated with rheumatoid arthritis
.
Nat Genet
2003
;
34
:
395
402
[PubMed]
42.
Darrah
E
,
Andrade
F
.
Rheumatoid arthritis and citrullination
.
Curr Opin Rheumatol
2018
;
30
:
72
78
[PubMed]
43.
Pruijn
GJ
.
Citrullination and carbamylation in the pathophysiology of rheumatoid arthritis
.
Front Immunol
2015
;
6
:
192
[PubMed]
44.
Lac
P
,
Saunders
S
,
Tutunea-Fatan
E
,
Barra
L
,
Bell
DA
,
Cairns
E
.
Immune responses to peptides containing homocitrulline or citrulline in the DR4-transgenic mouse model of rheumatoid arthritis
.
J Autoimmun
2018
;
89
:
75
81
[PubMed]
45.
James
EA
,
Rieck
M
,
Pieper
J
, et al
.
Citrulline-specific Th1 cells are increased in rheumatoid arthritis and their frequency is influenced by disease duration and therapy
.
Arthritis Rheumatol
2014
;
66
:
1712
1722
[PubMed]
46.
Nguyen
H
,
James
EA
.
Immune recognition of citrullinated epitopes
.
Immunology
2016
;
149
:
131
138
[PubMed]
47.
Kracht
MJ
,
van Lummel
M
,
Nikolic
T
, et al
.
Autoimmunity against a defective ribosomal insulin gene product in type 1 diabetes
.
Nat Med
2017
;
23
:
501
507
[PubMed]
48.
Yewdell
JW
.
DRiPs solidify: progress in understanding endogenous MHC class I antigen processing
.
Trends Immunol
2011
;
32
:
548
558
[PubMed]
49.
Roep
BO
,
Kracht
MJ
,
van Lummel
M
,
Zaldumbide
A
.
A roadmap of the generation of neoantigens as targets of the immune system in type 1 diabetes
.
Curr Opin Immunol
2016
;
43
:
67
73
[PubMed]
50.
Marre
ML
,
McGinty
JW
,
Chow
IT
, et al
.
Modifying enzymes are elicited by ER stress, generating epitopes that are selectively recognized by CD4+ T cells in patients with type 1 diabetes
.
Diabetes
2018
;
67
:
1356
1368
[PubMed]
51.
McLaughlin
RJ
,
de Haan
A
,
Zaldumbide
A
, et al
.
Human islets and dendritic cells generate post-translationally modified islet autoantigens
.
Clin Exp Immunol
2016
;
185
:
133
140
[PubMed]
52.
Wan
X
,
Zinselmeyer
BH
,
Zakharov
PN
, et al
.
Pancreatic islets communicate with lymphoid tissues via exocytosis of insulin peptides
.
Nature
2018
;
560
:
107
111
[PubMed]
53.
Endesfelder
D
,
Castell
WZ
,
Bonifacio
E
, et al.;
TEDDY Study Group
.
Time-resolved autoantibody profiling facilitates stratification of preclinical type 1 diabetes in children
.
Diabetes
2019
;
68
:
119
130
[PubMed]
54.
Ilonen
J
,
Lempainen
J
,
Hammais
A
, et al.;
Finnish Pediatric Diabetes Register
.
Primary islet autoantibody at initial seroconversion and autoantibodies at diagnosis of type 1 diabetes as markers of disease heterogeneity
.
Pediatr Diabetes
2018
;
19
:
284
292
[PubMed]
55.
Campbell-Thompson
M
,
Fu
A
,
Kaddis
JS
, et al
.
Insulitis and β-cell mass in the natural history of type 1 diabetes
.
Diabetes
2016
;
65
:
719
731
[PubMed]
56.
Rodriguez-Calvo
T
,
Suwandi
JS
,
Amirian
N
, et al
.
Heterogeneity and lobularity of pancreatic pathology in type 1 diabetes during the prediabetic phase
.
J Histochem Cytochem
2015
;
63
:
626
636
[PubMed]
57.
Arif
S
,
Leete
P
,
Nguyen
V
, et al
.
Blood and islet phenotypes indicate immunological heterogeneity in type 1 diabetes
.
Diabetes
2014
;
63
:
3835
3845
[PubMed]
58.
Michels
AW
,
Gottlieb
PA
.
Learning from past failures of oral insulin trials
.
Diabetes
2018
;
67
:
1211
1215
[PubMed]
59.
Scally
SW
,
Petersen
J
,
Law
SC
, et al
.
A molecular basis for the association of the HLA-DRB1 locus, citrullination, and rheumatoid arthritis
.
J Exp Med
2013
;
210
:
2569
2582
[PubMed]
60.
Sidney
J
,
Vela
JL
,
Friedrich
D
, et al
.
Low HLA binding of diabetes-associated CD8+ T-cell epitopes is increased by post translational modifications
.
BMC Immunol
2018
;
19
:
12
[PubMed]
61.
Ramarathinam
SH
,
Gras
S
,
Alcantara
S
, et al
.
Identification of native and posttranslationally modified HLA-B*57:01-restricted HIV envelope derived epitopes using immunoproteomics
.
Proteomics
2018
;
18
:
e1700253
[PubMed]
62.
Marino
F
,
Mommen
GPM
,
Jeko
A
, et al
.
Arginine (di)methylated human leukocyte antigen class I peptides are favorably presented by HLA-B*07
.
J Proteome Res
2017
;
16
:
34
44
[PubMed]
63.
Malaker
SA
,
Ferracane
MJ
,
Depontieu
FR
, et al
.
Identification and characterization of complex glycosylated peptides presented by the MHC class II processing pathway in melanoma
.
J Proteome Res
2017
;
16
:
228
237
[PubMed]
64.
Alpízar
A
,
Marino
F
,
Ramos-Fernández
A
, et al
.
A molecular basis for the presentation of phosphorylated peptides by HLA-B antigens
.
Mol Cell Proteomics
2017
;
16
:
181
193
[PubMed]
65.
Marino
F
,
Bern
M
,
Mommen
GPM
, et al
.
Extended O-GlcNAc on HLA class-I-bound peptides
.
J Am Chem Soc
2015
;
137
:
10922
10925
[PubMed]
66.
Marcilla
M
,
Alpízar
A
,
Lombardía
M
,
Ramos-Fernandez
A
,
Ramos
M
,
Albar
JP
.
Increased diversity of the HLA-B40 ligandome by the presentation of peptides phosphorylated at their main anchor residue
.
Mol Cell Proteomics
2014
;
13
:
462
474
[PubMed]
67.
Cobbold
M
,
De La Peña
H
,
Norris
A
, et al
.
MHC class I-associated phosphopeptides are the targets of memory-like immunity in leukemia
.
Sci Transl Med
2013
;
5
:
203ra125
[PubMed]
68.
Petersen
J
,
Wurzbacher
SJ
,
Williamson
NA
, et al
.
Phosphorylated self-peptides alter human leukocyte antigen class I-restricted antigen presentation and generate tumor-specific epitopes
.
Proc Natl Acad Sci U S A
2009
;
106
:
2776
2781
[PubMed]
69.
Mohammed
F
,
Cobbold
M
,
Zarling
AL
, et al
.
Phosphorylation-dependent interaction between antigenic peptides and MHC class I: a molecular basis for the presentation of transformed self
.
Nat Immunol
2008
;
9
:
1236
1243
[PubMed]
70.
Zarling
AL
,
Polefrone
JM
,
Evans
AM
, et al
.
Identification of class I MHC-associated phosphopeptides as targets for cancer immunotherapy
.
Proc Natl Acad Sci U S A
2006
;
103
:
14889
14894
[PubMed]
71.
Faridi
P
,
Li
C
,
Ramarathinam
SH
, et al. A subset of HLA-I peptides are not genomically templated: evidence for cis- and trans-spliced peptide ligands. Sci Immunol 2018;3:eaar3947
72.
Liepe
J
,
Marino
F
,
Sidney
J
, et al
.
A large fraction of HLA class I ligands are proteasome-generated spliced peptides
.
Science
2016
;
354
:
354
358
[PubMed]
73.
Mylonas
R
,
Beer
I
,
Iseli
C
, et al
.
Estimating the contribution of proteasomal spliced peptides to the HLA-I ligandome
.
Mol Cell Proteomics
2018
;
17
:
2347
2357
[PubMed]
74.
Platteel
AC
,
Mishto
M
,
Textoris-Taube
K
, et al
.
CD8+ T cells of Listeria monocytogenes-infected mice recognize both linear and spliced proteasome products
.
Eur J Immunol
2016
;
46
:
1109
1118
[PubMed]
75.
Platteel
ACM
,
Liepe
J
,
Textoris-Taube
K
, et al
.
Multi-level strategy for identifying proteasome-catalyzed spliced epitopes targeted by CD8+ T cells during bacterial infection
.
Cell Reports
2017
;
20
:
1242
1253
[PubMed]
76.
Racine
JJ
,
Stewart
I
,
Ratiu
J
, et al
.
Improved murine MHC-deficient HLA transgenic NOD mouse models for type 1 diabetes therapy development
.
Diabetes
2018
;
67
:
923
935
[PubMed]
77.
Schloss
J
,
Ali
R
,
Racine
JJ
,
Chapman
HD
,
Serreze
DV
,
DiLorenzo
TP
.
HLA-B*39:06 efficiently mediates type 1 diabetes in a mouse model incorporating reduced thymic insulin expression
.
J Immunol
2018
;
200
:
3353
3363
[PubMed]
78.
Serreze
DV
,
Niens
M
,
Kulik
J
,
DiLorenzo
TP
.
Bridging mice to men: using HLA transgenic mice to enhance the future prediction and prevention of autoimmune type 1 diabetes in humans
.
Methods Mol Biol
2016
;
1438
:
137
151
[PubMed]
79.
Pugliese
A
,
Vendrame
F
,
Reijonen
H
,
Atkinson
MA
,
Campbell-Thompson
M
,
Burke
GW
.
New insight on human type 1 diabetes biology: nPOD and nPOD-transplantation
.
Curr Diab Rep
2014
;
14
:
530
[PubMed]
80.
Vita
R
,
Mahajan
S
,
Overton
JA
, et al
.
The Immune Epitope Database (IEDB): 2018 update
.
Nucleic Acids Res
2019
;
47
:
D339
D343
[PubMed]
81.
Pieper
J
,
Dubnovitsky
A
,
Gerstner
C
, et al
.
Memory T cells specific to citrullinated α-enolase are enriched in the rheumatic joint
.
J Autoimmun
2018
;
92
:
47
56
[PubMed]
82.
Rims
C
,
Uchtenhagen
H
,
Kaplan
MJ
, et al
.
Citrullinated aggrecan epitopes as targets of auto-reactive CD4+ T cells in patients with rheumatoid arthritis
.
Arthritis Rheumatol
2019
;
71
:
518
528
83.
Dolton
G
,
Zervoudi
E
,
Rius
C
, et al
.
Optimized peptide-MHC multimer protocols for detection and isolation of autoimmune T-cells
.
Front Immunol
2018
;
9
:
1378
[PubMed]
84.
Uchtenhagen
H
,
Rims
C
,
Blahnik
G
, et al
.
Efficient ex vivo analysis of CD4+ T-cell responses using combinatorial HLA class II tetramer staining
.
Nat Commun
2016
;
7
:
12614
[PubMed]
85.
Newell
EW
,
Sigal
N
,
Nair
N
,
Kidd
BA
,
Greenberg
HB
,
Davis
MM
.
Combinatorial tetramer staining and mass cytometry analysis facilitate T-cell epitope mapping and characterization
.
Nat Biotechnol
2013
;
31
:
623
629
[PubMed]
86.
Bentzen
AK
,
Hadrup
SR
.
Evolution of MHC-based technologies used for detection of antigen-responsive T cells
.
Cancer Immunol Immunother
2017
;
66
:
657
666
[PubMed]
87.
Bentzen
AK
,
Marquard
AM
,
Lyngaa
R
, et al
.
Large-scale detection of antigen-specific T cells using peptide-MHC-I multimers labeled with DNA barcodes
.
Nat Biotechnol
2016
;
34
:
1037
1045
[PubMed]
88.
Bian
X
,
Wasserfall
C
,
Wallstrom
G
, et al
.
Tracking the antibody immunome in type 1 diabetes using protein arrays
.
J Proteome Res
2017
;
16
:
195
203
[PubMed]
89.
Ganesan
V
,
Ascherman
DP
,
Minden
JS
.
Immunoproteomics technologies in the discovery of autoantigens in autoimmune diseases
.
Biomol Concepts
2016
;
7
:
133
143
[PubMed]
90.
Ramarathinam
SH
,
Croft
NP
,
Illing
PT
,
Faridi
P
,
Purcell
AW
.
Employing proteomics in the study of antigen presentation: an update
.
Expert Rev Proteomics
2018
;
15
:
637
645
[PubMed]
91.
Ternette
N
,
Purcell
AW
.
Immunopeptidomics special issue
.
Proteomics
2018
;
18
:
e1800145
[PubMed]
92.
Bilich
T
,
Nelde
A
,
Bichmann
L
, et al
.
The HLA ligandome landscape of chronic myeloid leukemia delineates novel T-cell epitopes for immunotherapy
.
Blood
2019
;
133
:
550
565
93.
Mohme
M
,
Hotz
C
,
Stevanovic
S
, et al
.
HLA-DR15-derived self-peptides are involved in increased autologous T cell proliferation in multiple sclerosis
.
Brain
2013
;
136
:
1783
1798
[PubMed]
94.
Shraibman
B
,
Barnea
E
,
Kadosh
DM
, et al
.
Identification of tumor antigens among the HLA peptidomes of glioblastoma tumors and plasma
.
Mol Cell Proteomics
2018
;
17
:
2132
2145
[PubMed]
95.
Ternette
N
,
Olde Nordkamp
MJM
,
Müller
J
, et al
.
Immunopeptidomic profiling of HLA-A2-positive triple negative breast cancer identifies potential immunotherapy target antigens
.
Proteomics
2018
;
18
:
e1700465
[PubMed]
96.
Kosteria
I
,
Kanaka-Gantenbein
C
,
Anagnostopoulos
AK
,
Chrousos
GP
,
Tsangaris
GT
.
Pediatric endocrine and metabolic diseases and proteomics
.
J Proteomics
2018
;
188
:
46
58
[PubMed]
97.
Lepper
MF
,
Ohmayer
U
,
von Toerne
C
,
Maison
N
,
Ziegler
AG
,
Hauck
SM
.
Proteomic landscape of patient-derived CD4+ T cells in recent-onset type 1 diabetes
.
J Proteome Res
2018
;
17
:
618
634
[PubMed]
98.
Zhang
L
,
Lanzoni
G
,
Battarra
M
,
Inverardi
L
,
Zhang
Q
.
Label-free LC-MS/MS strategy for comprehensive proteomic profiling of human islets collected using laser capture microdissection from frozen pancreata
.
Methods Mol Biol
2019
;
1871
:
253
264
[PubMed]
99.
Dudek
NL
,
Tan
CT
,
Gorasia
DG
,
Croft
NP
,
Illing
PT
,
Purcell
AW
.
Constitutive and inflammatory immunopeptidome of pancreatic β-cells
.
Diabetes
2012
;
61
:
3018
3025
[PubMed]
100.
Kronenberg
D
,
Knight
RR
,
Estorninho
M
, et al
.
Circulating preproinsulin signal peptide-specific CD8 T cells restricted by the susceptibility molecule HLA-A24 are expanded at onset of type 1 diabetes and kill β-cells
.
Diabetes
2012
;
61
:
1752
1759
[PubMed]
101.
Skowera
A
,
Ellis
RJ
,
Varela-Calviño
R
, et al
.
CTLs are targeted to kill β cells in patients with type 1 diabetes through recognition of a glucose-regulated preproinsulin epitope [published correction appears in J Clin Invest 2009;119:2844]
.
J Clin Invest
2008
;
118
:
3390
3402
[PubMed]
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