Despite the understanding that type 1 diabetes pathogenesis is mediated by T-cells, detection of these rare lymphocytes remains largely elusive. Suitable T-cell assays are highly needed, since they could offer preclinical diagnoses and immune surrogate end points for clinical trials. Although CD4+ T-cell assays have met with limited success, CD8+ T-cells are increasingly recognized as key actors in the diabetes of the NOD mouse. CD8+ T-cells are likely to play a role also in humans and may provide new markers of β-cell autoimmunity. Taking advantage of a panel of HLA-A2–restricted β-cell epitopes derived from preproinsulin, GAD, and islet glucose-6-phosphatase catalytic subunit-related protein (IGRP), we have implemented an islet-specific CD8+ T-cell interferon-γ enzyme-linked immunospot (ISL8Spot) assay. The ISL8Spot assay is capable of detecting and quantifying β-cell–reactive CD8+ T-cells directly ex vivo, without any preliminary expansion, using either fresh or frozen samples. Positive ISL8Spot responses separate new-onset diabetic and healthy samples with high accuracy (86% sensitivity, 91% specificity), using as few as five immunodominant epitopes. Moreover, sensitivity reaches 100% when the ISL8Spot assay is complemented by antibody determinations. Combination of CD8+ T-cell measurements with immune intervention strategies may open new avenues toward type 1 diabetes prediction and prevention.

T-cells play the central pathogenic role in the diabetes of the NOD mouse. Despite this knowledge, the relevance of T-cell effectors in human type 1 diabetes has been difficult to assess because of their very low frequencies in peripheral blood. Indeed, current etiopathological diagnosis of new-onset diabetes as type 1 disease, as well as type 1 diabetes risk assessment, heavily relies on antibody (Ab) markers. However, Abs are not required for β-cell destruction (1,2), and their titers do not seem to correlate with T-cell responses (3–5). More importantly, the kinetics of their fluctuations make them unsuitable to predict the time to type 1 diabetes onset in at-risk individuals and to reflect tolerance induction during immune modulatory treatment (6). For these reasons, development of suitable T-cell assays remains a primary goal in type 1 diabetes research. First, it is important for deciphering the underlying disease process. Second, surrogate immune markers closely reflecting the pathogenic evolution could be highly valuable to optimally assess eligibility for immune interventions (i.e., which patients and when) and to monitor clinical response.

Given the strong association between type 1 diabetes and the HLA class II locus (7), most studies to date have focused on β-cell–specific autoimmune responses driven by CD4+ T-cells. However, recent work in the NOD mouse has established a prominent role for CD8+ T-cells (8–10). NOD mice devoid of CD8+ lymphocytes do not experience insulitis (11,12), and CD8+ clones from pre-diabetic and diabetic animals can provoke diabetes (13–15). More importantly, CD8+ T-cells specific for insulin B15–23 (13,16) and for islet-specific glucose-6-phosphatase catalytic subunit–related protein (IGRP)206–214 (17) are early pathogenic actors in the diabetes pathogenesis of NOD mice. Quantification of IGRP206–214–specific CD8+ T-cells in the peripheral blood of NOD mice has also been shown to predict subsequent diabetes development (18). Therefore, CD8+ T-cell monitoring holds promise for the “immune staging” of human type 1 diabetes but is hampered by technical difficulties in their measurement.

Development of suitable CD8+ T-cell assays depends on several factors. First, appropriate readouts and measurement techniques must be selected. Interferon (IFN)-γ secretion, as measured by enzyme-linked immunospot (ELISpot), is currently the preferred system in the viral and tumor immunology setting, because of its excellent sensitivity and simple format. Second, assays should incorporate the most relevant HLA class I restrictions. Although no strong association has been proposed between particular HLA class I alleles and type 1 diabetes, HLA-A2 (HLA-A*0201) is the most represented allele among Caucasians (∼45% of subjects), and it has been suggested to mediate an additional susceptibility to diabetes in NOD mice (19,20). Third, the relevant epitopes should be identified. We recently reported a systematic HLA-A2–restricted epitope exploration for preproinsulin (PPI), using a reverse immunology approach combining proteasome digestions with prediction algorithms and subsequent verification of natural processing and immunogenicity (21,22). This study led to the identification of seven novel PPI candidate epitopes, two of which were subsequently shown to be targeted by CD8+ T-cells from type 1 diabetic patients (23,24). Taking advantage of this epitope information, we here describe an islet-specific CD8+ T-cell interferon-γ enzyme-linked immunospot (ISL8Spot) assay that reliably separates type 1 diabetic subjects from healthy subjects.

Peptides.

The epitope peptides used (>80% pure; Schafer-N, Copenhagen, Denmark) are listed in Table 1. A viral peptide mix of Flu MP58–66, Epstein-Barr virus BMLF280–288, and cytomegalovirus pp65495–503 (10 μmol/l each) and phytohemagglutinin (1 μg/ml; Sigma, Lyon, France) were used as positive controls. HIV gag77–85 and DMSO diluent were used as negative controls.

Patients.

Caucasian new-onset adult (>16 years old) type 1 diabetic patients with acute onset of symptoms requiring permanent insulin treatment from the time of diagnosis (25) were recruited from the Diabetes Registry of the Province of Turin, Italy, and from the GOFEDI Network, France, as detailed in the appendix. All patients had metabolically controlled disease and were free of recent (<2 weeks) infectious or inflammatory conditions at the time of blood draw. Parallel recruitment of Caucasian healthy control subjects took place at the same institutions. Type 2 diabetic patients were defined as Ab− subjects with normal fasting C-peptide levels (normal values 0.36–1.17 nmol/l; DPC, Los Angeles, CA). All subjects gave informed consent, and the study was approved by the relevant ethics committees.

Blood processing.

All blood samples were shipped overnight at room temperature in blinded fashion (typically, each type 1 diabetes sample was paired with a healthy sample). Rapid HLA-A2 screening was performed with the BB7.2 mAb (26), followed by subtyping using the Olerup SSP HLA*02 kit (GenoVision/Qiagen, Vienna, Austria). Peripheral blood mononuclear cells (PBMCs) were isolated by density gradient centrifugation using lymphocyte separation medium (PAA, Les Mureaux, France) and immediately used or stored frozen (10% DMSO in pooled human male AB serum).

Islet Abs.

Serum Abs were measured by radio-binding assays, using 35S-labeled GAD65 and intracellular insulinoma-associated protein 2 (IA-2) and 125I-labeled insulin, following protocols previously evaluated within the Diabetes Antibody Standardization Program (lab number 137) (27). Sensitivities in the 2005 Diabetes Antibody Standardization Program were 84% for anti-GAD, 76% for anti–IA-2, and 28% for insulin autoantibodies, where the specificity was set at 95%. Islet cell Abs were assayed by indirect immunofluorescence on frozen sections of human blood group 0 pancreas.

ISL8Spot assay.

Ninety-six–well PVDF plates (Millipore, Saint-Quentin-en-Yvelines, France) were coated overnight with an anti–IFN-γ Ab (U-CyTech, Utrecht, the Netherlands). Plates were subsequently blocked with RPMI + 10% human serum (PAA), and peptides were added (10 μmol/l final concentration) in triplicate wells along with recombinant human IL-2 (0.5 units/ml; R&D Systems, Lille, France). PBMCs were seeded at 3 × 105 cells/well and cultured for 20–24 h. In selected experiments, PBMCs preincubated for 10 min at room temperature with 25 μg/ml anti-CD8 (OKT8) or with 50 μg/ml anti–HLA-A2 (BB7.2) mAb, or the CD8− fraction negatively selected by anti-CD8 microbeads (Miltenyi Biotech, Paris, France), were seeded in parallel. After PBMC removal, IFN-γ secretion was visualized with a biotin-conjugated anti–IFN-γ Ab (U-CyTech), alkaline phosphatase-conjugated ExtrAvidin, and Sigmafast 5-bromo-4-chloro-3-indolyl phosphate/nitro blue tetrazolium (BCIP/NBT) tablets (both from Sigma). Spots were counted using an AID reader (Strassberg, Germany), and means of triplicate wells were calculated. All ISL8Spot readouts are expressed as spot-forming cells (SFC)/106 PBMCs.

Statistical analysis.

Values are expressed as means ± SD or median (range), according to their distribution. All graphs are displayed as means ± SE. Comparisons between proportions were made with the χ2 test and Fisher’s exact test, when appropriate. Comparisons of means between two groups were carried out with the Student’s t test for normal distributed variables or with the Mann-Whitney U test for non-normal variables. Analysis of data was done using Stata 7.0 (Stata, College Station, TX). P < 0.05 was considered to be of statistical significance.

Selection of HLA-A2–restricted β-cell epitopes.

The peptides used in the ISL8Spot assay are listed in Table 1. Most of these epitopes are derived from PPI and were recently characterized by us and others as naturally processed and immunogenic (21,23,24). Two PPI2–10 and PPI6–14 leader sequence peptides rating the highest in the SYFPEITHI algorithm (28) were also included, as this region is associated exclusively with β-cells and may contain additional epitopes. This 24–amino acid region was not included in our previous PPI epitope search (21), since it was found to be resistant to proteasome digestion, presumably because of its hydrophobicity (P.v.E., unpublished data). The GAD114–123 epitope originally described 10 years ago by Panina-Bordignon et al. (29) and two IGRP epitopes recently proposed by Takaki et al. (20) were also considered to cover additional β-cell antigens.

ISL8Spot validation.

We aimed to implement an assay format amenable to standardization for routine clinical use, with minimal sample handling. For this reason, our IFN-γ ELISpot system was set up to work with unfractionated PBMCs, without preliminary expansions, and with both freshly prepared and frozen samples. This format was first validated by studying PBMC responses against mixed viral epitopes. Suboptimal epitope concentrations (30 nmol/l) were used in order to have responses of a magnitude similar to that found against β-cell epitopes (basal-subtracted median positive responses of 44.0 SFC/106 PBMCs, range 6.0–832.7; Fig. 3). Within this range of sensitivity, intra-assay variability, as measured in single wells from single experiments, was typically 12.2–16.1% (Fig. 1A). Despite variable basal reactivities against the gag77–85 control peptide and the DMSO diluent alone, the interassay analytical variability, as determined by multiple assays on different PBMC aliquots frozen on the same occasion, was 4.2% (Fig. 1B). Because interassay variability in the clinical setting can also be determined by changes at the pre-analytical level, we determined the coefficients of variation (CVs) for multiple assays performed on different blood draws from the same subjects, finding a value of 9.2% (Fig. 1C). Finally, we compared the difference in sensitivity between fresh and frozen samples by testing PBMCs from the same subject either fresh or upon cryopreservation and thawing (Fig. 1D). Despite a higher average background reactivity in frozen PBMCs, the basal-subtracted signal was equivalent in both types of samples (74.8 vs. 76.3 SFC/106 PBMCs for cryopreserved vs. fresh PBMCs). This validation also supports the use of basal-subtracted values to compare different experiments.

A receiver-operator characteristic analysis was performed to select the best cutoff for assigning positive responses (Fig. 2A). The mean + 3 SD of basal readouts (DMSO and gag77–85) was thus selected as the cutoff attaining the best sensitivity and specificity.

Representative examples of ISL8Spot readouts are shown in Fig. 2B. As expected based on the 9–to 10–amino acid length of the peptides used, the visualized reactivities originated from HLA-A2–restricted CD8+ T-cells, as the signal was abolished by blocking anti–HLA-A2 or anti-CD8 mAbs (91.4 and 95.0% inhibition, respectively; Fig. 2C) or by depletion of the CD8+ fraction (not shown).

Detection of β-cell–specific CD8+ T-cells by ISL8Spot.

Characteristics of the study subjects are summarized in Table 2. For the HLA-A2+ type 1 diabetic patients, 86.4% (19/22) were islet Ab+ (1 of 17 healthy control subjects, 5.9%; P < 0.0001), 84.2% (16 of 19) were HLA-DR3+ and/or -DR4+ (5 of 18 healthy control subjects, 27.8%; P = 0.0006), and the median type 1 diabetes duration was 12 days (range 3–180). The type 1 diabetic and healthy cohorts were age matched (29.2 ± 8.5 vs. 32.7 ± 10.9 years; P = 0.55).

Results are summarized in Fig. 3. All data were obtained with blood samples shipped overnight and freshly prepared PBMCs, except for patients P03, P04, P12, P15, and P22, for whom blood samples were shipped overnight, processed, frozen, and used upon thawing. Reactivities were ranked as low (>3 and <4 SD), intermediate (>4 and <5 SD), and high (>5 SD).

Of 22 HLA-A2+ type 1 diabetic patients, 19 were positive for at least one epitope (86.4% sensitivity); reactivity frequently targeted multiple epitopes (median 2.0, range 0–5). Epitope-specific CD8+ T-cells were detected also in most (80.0%; 4 of 5) frozen PBMC samples. Of the 22 age-matched HLA-A2+ healthy control subjects tested, 20 were negative for all epitopes (90.9% specificity; P < 0.0001 for the type 1 diabetes vs. healthy cohort comparison). Interestingly, subject C12 was positive for T-cell responses and also harbored risk factors for type 1 diabetes, being HLA-DR3+ and weakly positive for insulin autoantibodies. Testing of HLA-A2+ type 2 diabetic patients (n = 5) and of age-matched new-onset HLA-A2− type 1 diabetic patients (n = 4) did not reveal any reactivity (Fig. 3).

Five epitopes (PPI2–10, PIB18–27, PIA12–20, GAD114–123, and IGRP228–236) were recognized by >25% of type 1 diabetic patients. Importantly, when the analysis is restricted to these five immunodominant epitopes, the same type 1 diabetic patients are correctly identified without any loss in sensitivity and specificity.

There was no correlation between number or quality of epitopes recognized and type 1 diabetes duration, age of onset, or sex. Although unlikely, a modifying effect of DR3/DR4 haplotypes on CD8+ T-cell responses was excluded, since the frequency of positive responses remained significantly higher in type 1 diabetic patients than in control subjects when the analysis was restricted to DR3+ and/or DR4+ subgroups (87.5% [14 of 16] vs. 14.3% [1 of 7] for type 1 diabetic vs. healthy and type 2 diabetic donors, P = 0.0006; P = 0.003 for type 1 diabetic vs. healthy subjects alone). Similarly, no correlation emerged between Ab and T-cell responses, considering single antigens separately (e.g., insulin autoantibodies vs. PPI T-cell responses) or together (i.e., any Ab vs. any T-cell response). However, the three patients negative by ISL8Spot were all Ab+, whereas the three Ab− patients (P04, P18, and P22) tested positive by ISL8Spot. Thus, a combination of ISL8Spot and Ab testing achieved 100% sensitivity in identifying type 1 diabetic patients.

Several immune intervention strategies for type 1 diabetes are currently under scrutiny (6,30–33). These interventions could achieve better results if implemented at a preclinical stage, when a larger β-cell mass can still be rescued from autoimmune destruction (34). However, this requires both accurate prediction of type 1 diabetes development and the possibility to monitor clinical efficacy through immune surrogate markers reflecting restoration of tolerance. It has emerged that anti-islet Abs are not sufficient to fulfill this task (6), and great hopes have therefore been invested in markers of T-cell activation against β-cell epitopes (35).

Because the association between DR3/DR4 alleles and type 1 diabetes skewed the interest of researchers, a decade of studies investigated whether CD4+ T-cell responses could differentiate between type 1 diabetes and health. Most of these studies were unsuccessful, since β-cell–reactive CD4+ T-cells were difficult to visualize, usually requiring in vitro pre-expansion (36,37). When detected, β-cell–specific CD4+ T-cells were also identified in healthy individuals (38,39), although possibly characterized by different functional phenotypes (37,40). The emergence of CD8+ T-cells as crucial actors in the type 1 diabetes pathogenesis of the NOD mouse (8–10) has brought up the possibility to study this lymphocyte subpopulation to the same end. However, only anecdotal analyses, mostly oriented toward epitope identification, have been reported for human type 1 diabetes (23,24,29,41,42).

We here propose the first validation of CD8+ T-cell measurements to differentiate between type 1 diabetes and health, using a portfolio of well-defined islet epitopes applied to an IFN-γ ELISpot format (ISL8Spot). Several possibilities may explain the accuracy we achieved by CD8+ T-cell measures compared with previous attempts with CD4+ T-cells (37,39,43). The simplest speculation is that β-cell–reactive CD8+ T-cells may be more numerous in the bloodstream than their CD4+ counterparts, at least at type 1 diabetes onset. This could relate in part to a different recirculation of these two subsets from target tissues to peripheral blood. Alternatively, β-cell–reactive CD8+ T-cells may preferentially undergo avidity maturation (17) or may display a more homogeneous IFN-γ–producing phenotype. Either feature would facilitate their detection, as well as their power to discriminate between type 1 diabetes and health by a single cytokine measure. Besides the biological differences between CD4+ and CD8+ T-cells, some specifics of our study probably contributed to these results. These may include the recruitment of type 1 diabetic patients with disease of very recent onset, the preliminary selection of a robust candidate epitope panel based on both immunogenicity and natural processing, and addition of low-dose IL-2 to increase the epitope-specific signal (R.M., unpublished data). Moreover, the short median type 1 diabetes duration of our study cohort (12 days) and the lack of correlation between T-cell responses and type 1 diabetes duration minimize the possibility of a bias on PPI-specific responses introduced by the daily insulin injections. Selection of patients based on permanent insulin requirement from the time of diagnosis also limited the potential inclusion of latent autoimmune diabetes in adults (LADA) patients (44).

Importantly (35,45,46), detection of β-cell–specific CD8+ T-cells was accomplished on both fresh and frozen PBMCs and directly ex vivo. This rules out any bias introduced by in vitro manipulation, while encouraging the transfer to clinical application. Furthermore, these measurements could be performed with as little as 10 ml of blood, since a panel of five immunodominant epitopes is sufficient for optimal assay accuracy. T-cell testing could therefore be offered also to children. We hypothesize that higher T-cell responses may be found in type 1 diabetic children, as their faster decline in β-cell function could subtend a more aggressive autoimmunity (47,48).

A recent study conducted by the Immune Tolerance Network recapitulated the state-of-the-art for T-cell assays in type 1 diabetes (35). Different assays were compared for their ability to distinguish type 1 diabetes from healthy donors, using 23 frozen samples from new-onset patients. While HLA class II tetramer (36) and IFN-γ ELISpot assays (49) could not be evaluated because of poor performance on frozen samples (45,46), a cellular immunoblot assay reached 91% sensitivity and 83% specificity (50,51). A T-cell proliferation assay (52) showed a lower sensitivity (58%) but higher specificity (94%). Both of these assays rely on [3H]thymidine incorporation as the final readout after a 5- to 7-day culture, using eluted proteins from whole islet cell lysates or different self-antigens/epitopes as stimuli. Given the nature of these stimuli (whole proteins and/or 13- to 15-mer peptides), the responding cells are likely to be CD4+ T-cells. The higher sensitivity of cellular immunoblotting compared with ISL8Spot is of note and may be due to the coverage of all potential T-cell targets ensured by the islet cell lysates. However, besides achieving a higher specificity, the ISL8Spot assay offers some distinct advantages. First, the ISL8Spot T-cell targets are molecularly defined epitopes that can be chemically synthesized. This allows for better consistency and makes the technique easier to implement. Second, direct ex vivo testing avoids any potential bias brought in by in vitro expansions. Third, the ISL8Spot assay requires smaller blood volumes, making it more suitable for younger patients and for repeated testing at different time points.

The 86% sensitivity of our prototype ISL8Spot is in the same range of that of GAD Ab radioimmunoassays, which have reached 80–85% sensitivity and 95–98% specificity through several years of improvements (27). The lower specificity (91%) of our T-cell measurements versus the Ab determinations may reflect detection of autoreactive T-cells without pathological significance, or identification of subclinical β-cell autoimmunity. Indeed, the observation that one of the two healthy subjects positive for T-cell responses was also a carrier of type 1 diabetes risk factors is intriguing. Although the predictive power of T-cell measures for subsequent type 1 diabetes development remains to be established, combined T-cell and Ab measures (i.e., positivity to either one) were able to correctly identify all type 1 diabetic patients, thus reaching 100% sensitivity. Larger multicentric studies will further elucidate whether T-cell assays can complement islet Ab determinations for an etiology-based diagnosis of type 1 diabetes, as currently recommended (25). Moreover, the recent description of additional T-cell epitopes derived from IGRP, IA-2, glial fibrillary acidic protein (GFAP), and islet amyloid polypeptide (IAPP) extends the panel available for testing (41,42).

This proof-of-concept study demonstrates that IFN-γ CD8+ T-cell responses, as measured by ISL8Spot, can propose themselves as new autoimmune markers of type 1 diabetes. After epitope identification, this strategy can be expanded to other HLA class I restrictions to cover the majority of the population. Characterization of the CD8+ T-cells recognizing the identified epitopes may provide new insights into type 1 diabetes pathogenesis. Further validation of the ISL8Spot assay in (pre)-diabetic subjects and patients enrolled in immune prevention trials will clarify their potential for risk assessment, etiology-based diagnosis, and therapeutic monitoring of type 1 diabetes.

The following colleagues and institutions contributed to the study with patient recruitment: Piedmont Study Group for Diabetes Epidemiology, Italy (coordinators: G. Novelli, G. Bruno): S. Cianciosi, Avigliana; A. Perrino, Carmagnola; C. Giorda, E. Imperiale, Chieri; A. Chiambretti, R. Fornengo, Chivasso; V. Trinelli, D. Gallo, Ciriè-Lanzo; A. Caccavale, Collegno; F. Ottenga, Cuneo; R. Autino, P. Modina, Cuognè; L. Gurioli, L. Costa-Laia, Ivrea; C. Marengo, M. Comoglio, Moncalieri; T. Mahagna, Nichelino; M. Trovati, F. Cavalot, San Luigi Hospital, Orbassano; A. Ozzello, P. Gennari, Pinerolo-Pomaretto-Torre Pellice; S. Bologna, D. D’Avanzo, Rivoli; S. Davìı, M. Dore, Susa; S. Martelli, E. Megale, Giovanni Bosco Hospital, Turin; S. Gamba, A. Blatto, Maria Vittoria Hospital, Turin; P. Griseri, C. Matteoda, Martini Hospital, Turin; A. Grassi, A. Mormile, Mauriziano Hospital, Turin; E. Pisu, G. Grassi, V. Martina, V. Inglese, R. Quadri, Molinette Hospital, Turin; G. Petraroli, L. Corgiat-Mansin, Ophtalmologic Hospital, Turin; F. Cerutti, C. Sacchetti, Regina Margherita Pediatric Hospital, Turin; A. Clerico, L. Richiardi, Valdese Hospital, Turin; G. Bendinelli, A. Bogazzi, Venaria.

GOFEDI (Groupe Ouest-France pour l’Etude du Diabète Insulino-dépendant), France (coordinator: L. Chaillous): C. Briet, Amiens; P.H. Ducluzeau, V. Rohmer, Angers; V. Kerlan, E. Sonnet, Brest; M. Dolz, B. Charbonnel, Nantes; R. Marechaud, Poitiers; P. Lecomte, Tours.

FIG. 1.
FIG. 1. A: ISL8Spot intra-assay variability. PBMCs from two HLA-A2+ donors were assayed against gag77–85 control peptide and DMSO diluent alone (“basal,” □; mean ± SE of 10 wells is shown) or with 30 nmol/l viral peptide mix (; single well counts are shown). CVs are 16.1 and 12.2% for donor A and B, respectively. B: Interassay variability, analytical level. An HLA-A2+ donor was venesected on a single occasion, PBMCs were frozen down, and single aliquots were subsequently thawed and tested in four separate experiments as above. Basal and viral mix–specific readouts are shown (□ and , respectively) along with final basal-subtracted values (▪; CV 4.2%). C: Interassay variability, analytical and preanalytical level. Blood was drawn from the same donor on four different occasions and at the same time of the day. The following day, PBMCs were prepared and assayed as above; CV 9.2%. D: Interassay variability, frozen versus fresh samples. The graph shows means ± SE for SFC/106 values of fresh PBMCs prepared and tested on four separate occasions and of cryopreserved PBMCs frozen on the same occasion and tested in four separate experiments.
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A: ISL8Spot intra-assay variability. PBMCs from two HLA-A2+ donors were assayed against gag77–85 control peptide and DMSO diluent alone (“basal,” □; mean ± SE of 10 wells is shown) or with 30 nmol/l viral peptide mix (; single well counts are shown). CVs are 16.1 and 12.2% for donor A and B, respectively. B: Interassay variability, analytical level. An HLA-A2+ donor was venesected on a single occasion, PBMCs were frozen down, and single aliquots were subsequently thawed and tested in four separate experiments as above. Basal and viral mix–specific readouts are shown (□ and , respectively) along with final basal-subtracted values (▪; CV 4.2%). C: Interassay variability, analytical and preanalytical level. Blood was drawn from the same donor on four different occasions and at the same time of the day. The following day, PBMCs were prepared and assayed as above; CV 9.2%. D: Interassay variability, frozen versus fresh samples. The graph shows means ± SE for SFC/106 values of fresh PBMCs prepared and tested on four separate occasions and of cryopreserved PBMCs frozen on the same occasion and tested in four separate experiments.

FIG. 1.
FIG. 1. A: ISL8Spot intra-assay variability. PBMCs from two HLA-A2+ donors were assayed against gag77–85 control peptide and DMSO diluent alone (“basal,” □; mean ± SE of 10 wells is shown) or with 30 nmol/l viral peptide mix (; single well counts are shown). CVs are 16.1 and 12.2% for donor A and B, respectively. B: Interassay variability, analytical level. An HLA-A2+ donor was venesected on a single occasion, PBMCs were frozen down, and single aliquots were subsequently thawed and tested in four separate experiments as above. Basal and viral mix–specific readouts are shown (□ and , respectively) along with final basal-subtracted values (▪; CV 4.2%). C: Interassay variability, analytical and preanalytical level. Blood was drawn from the same donor on four different occasions and at the same time of the day. The following day, PBMCs were prepared and assayed as above; CV 9.2%. D: Interassay variability, frozen versus fresh samples. The graph shows means ± SE for SFC/106 values of fresh PBMCs prepared and tested on four separate occasions and of cryopreserved PBMCs frozen on the same occasion and tested in four separate experiments.
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A: ISL8Spot intra-assay variability. PBMCs from two HLA-A2+ donors were assayed against gag77–85 control peptide and DMSO diluent alone (“basal,” □; mean ± SE of 10 wells is shown) or with 30 nmol/l viral peptide mix (; single well counts are shown). CVs are 16.1 and 12.2% for donor A and B, respectively. B: Interassay variability, analytical level. An HLA-A2+ donor was venesected on a single occasion, PBMCs were frozen down, and single aliquots were subsequently thawed and tested in four separate experiments as above. Basal and viral mix–specific readouts are shown (□ and , respectively) along with final basal-subtracted values (▪; CV 4.2%). C: Interassay variability, analytical and preanalytical level. Blood was drawn from the same donor on four different occasions and at the same time of the day. The following day, PBMCs were prepared and assayed as above; CV 9.2%. D: Interassay variability, frozen versus fresh samples. The graph shows means ± SE for SFC/106 values of fresh PBMCs prepared and tested on four separate occasions and of cryopreserved PBMCs frozen on the same occasion and tested in four separate experiments.

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FIG. 2.
FIG. 2. A: Receiver-operator characteristic plot analysis was used to select the cutoff value attaining the best assay accuracy. Sensitivity (i.e., number of type 1 diabetic [T1D] patients testing positive to at least one of the 11 β-cell epitopes listed in Table 1; n = 22) and specificity (i.e., number of healthy control subjects testing negative to all β-cell epitopes; n = 22) are compared for each possible cutoff value, and the value providing the best sensitivity and specificity is selected. B: Representative ISL8Spot assays against selected β-cell epitopes for three HLA-A2+ type 1 diabetic patients and three healthy control subjects. Numbers in the top right corner display the SFC/106 PBMCs (without basal subtraction). Each peptide is assayed in triplicate, while basal wells (DMSO diluent alone or irrelevant peptide) are assayed in sextuplicate. The symbol in the bottom right corner refers to whether reactivity was scored as negative (−), weakly positive (+; between 3 and 4 SD), intermediate positive (++; between 4 and 5 SD), or strongly positive (+++; >5 SD). C: ISL8Spot reactivity is mediated by HLA-A2–restricted CD8+ T-cells. A representative analysis from a type 1 diabetic patient positive for the GAD114–123 epitope is shown. PBMCs preincubated with an irrelevant IgG, anti–HLA-A2, or anti-CD8 mAb were subjected to the ISL8Spot assay in parallel wells. Means ± SE of basal-subtracted values are shown, where the basal was 2.3 SFC/106.
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A: Receiver-operator characteristic plot analysis was used to select the cutoff value attaining the best assay accuracy. Sensitivity (i.e., number of type 1 diabetic [T1D] patients testing positive to at least one of the 11 β-cell epitopes listed in Table 1; n = 22) and specificity (i.e., number of healthy control subjects testing negative to all β-cell epitopes; n = 22) are compared for each possible cutoff value, and the value providing the best sensitivity and specificity is selected. B: Representative ISL8Spot assays against selected β-cell epitopes for three HLA-A2+ type 1 diabetic patients and three healthy control subjects. Numbers in the top right corner display the SFC/106 PBMCs (without basal subtraction). Each peptide is assayed in triplicate, while basal wells (DMSO diluent alone or irrelevant peptide) are assayed in sextuplicate. The symbol in the bottom right corner refers to whether reactivity was scored as negative (−), weakly positive (+; between 3 and 4 SD), intermediate positive (++; between 4 and 5 SD), or strongly positive (+++; >5 SD). C: ISL8Spot reactivity is mediated by HLA-A2–restricted CD8+ T-cells. A representative analysis from a type 1 diabetic patient positive for the GAD114–123 epitope is shown. PBMCs preincubated with an irrelevant IgG, anti–HLA-A2, or anti-CD8 mAb were subjected to the ISL8Spot assay in parallel wells. Means ± SE of basal-subtracted values are shown, where the basal was 2.3 SFC/106.

FIG. 2.
FIG. 2. A: Receiver-operator characteristic plot analysis was used to select the cutoff value attaining the best assay accuracy. Sensitivity (i.e., number of type 1 diabetic [T1D] patients testing positive to at least one of the 11 β-cell epitopes listed in Table 1; n = 22) and specificity (i.e., number of healthy control subjects testing negative to all β-cell epitopes; n = 22) are compared for each possible cutoff value, and the value providing the best sensitivity and specificity is selected. B: Representative ISL8Spot assays against selected β-cell epitopes for three HLA-A2+ type 1 diabetic patients and three healthy control subjects. Numbers in the top right corner display the SFC/106 PBMCs (without basal subtraction). Each peptide is assayed in triplicate, while basal wells (DMSO diluent alone or irrelevant peptide) are assayed in sextuplicate. The symbol in the bottom right corner refers to whether reactivity was scored as negative (−), weakly positive (+; between 3 and 4 SD), intermediate positive (++; between 4 and 5 SD), or strongly positive (+++; >5 SD). C: ISL8Spot reactivity is mediated by HLA-A2–restricted CD8+ T-cells. A representative analysis from a type 1 diabetic patient positive for the GAD114–123 epitope is shown. PBMCs preincubated with an irrelevant IgG, anti–HLA-A2, or anti-CD8 mAb were subjected to the ISL8Spot assay in parallel wells. Means ± SE of basal-subtracted values are shown, where the basal was 2.3 SFC/106.
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A: Receiver-operator characteristic plot analysis was used to select the cutoff value attaining the best assay accuracy. Sensitivity (i.e., number of type 1 diabetic [T1D] patients testing positive to at least one of the 11 β-cell epitopes listed in Table 1; n = 22) and specificity (i.e., number of healthy control subjects testing negative to all β-cell epitopes; n = 22) are compared for each possible cutoff value, and the value providing the best sensitivity and specificity is selected. B: Representative ISL8Spot assays against selected β-cell epitopes for three HLA-A2+ type 1 diabetic patients and three healthy control subjects. Numbers in the top right corner display the SFC/106 PBMCs (without basal subtraction). Each peptide is assayed in triplicate, while basal wells (DMSO diluent alone or irrelevant peptide) are assayed in sextuplicate. The symbol in the bottom right corner refers to whether reactivity was scored as negative (−), weakly positive (+; between 3 and 4 SD), intermediate positive (++; between 4 and 5 SD), or strongly positive (+++; >5 SD). C: ISL8Spot reactivity is mediated by HLA-A2–restricted CD8+ T-cells. A representative analysis from a type 1 diabetic patient positive for the GAD114–123 epitope is shown. PBMCs preincubated with an irrelevant IgG, anti–HLA-A2, or anti-CD8 mAb were subjected to the ISL8Spot assay in parallel wells. Means ± SE of basal-subtracted values are shown, where the basal was 2.3 SFC/106.

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FIG. 3.
FIG. 3. Summary of HLA-A2+ type 1 diabetic (T1D) patients (n = 22), HLA-A2+ healthy control subjects (n = 22), HLA-A2+ type 2 diabetic (T2D) patients (n = 5), and HLA-A2− type 1 diabetic patients (n = 4) assayed for β-cell reactivities. All values, including basal + n SD cutoffs, are expressed as SFC/106 PBMCs and are basal subtracted. Unsubtracted basal values (reactivities to DMSO and gag77–85) are shown in the penultimate row of each column. Subjects positive to at least one epitope are highlighted in green in the second row. Reactivities are ranked as low (between 3 and 4 SD, in yellow), intermediate (between 4 and 5 SD, in orange), and high (more than 5 SD, in red). The five epitopes testing positive in more than 25% of type 1 diabetic patients are highlighted in blue. The number of positive epitopes in each subject is indicated in the last row. ++++, off-scale ELISpot reading.
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Summary of HLA-A2+ type 1 diabetic (T1D) patients (n = 22), HLA-A2+ healthy control subjects (n = 22), HLA-A2+ type 2 diabetic (T2D) patients (n = 5), and HLA-A2− type 1 diabetic patients (n = 4) assayed for β-cell reactivities. All values, including basal + n SD cutoffs, are expressed as SFC/106 PBMCs and are basal subtracted. Unsubtracted basal values (reactivities to DMSO and gag77–85) are shown in the penultimate row of each column. Subjects positive to at least one epitope are highlighted in green in the second row. Reactivities are ranked as low (between 3 and 4 SD, in yellow), intermediate (between 4 and 5 SD, in orange), and high (more than 5 SD, in red). The five epitopes testing positive in more than 25% of type 1 diabetic patients are highlighted in blue. The number of positive epitopes in each subject is indicated in the last row. ++++, off-scale ELISpot reading.

FIG. 3.
FIG. 3. Summary of HLA-A2+ type 1 diabetic (T1D) patients (n = 22), HLA-A2+ healthy control subjects (n = 22), HLA-A2+ type 2 diabetic (T2D) patients (n = 5), and HLA-A2− type 1 diabetic patients (n = 4) assayed for β-cell reactivities. All values, including basal + n SD cutoffs, are expressed as SFC/106 PBMCs and are basal subtracted. Unsubtracted basal values (reactivities to DMSO and gag77–85) are shown in the penultimate row of each column. Subjects positive to at least one epitope are highlighted in green in the second row. Reactivities are ranked as low (between 3 and 4 SD, in yellow), intermediate (between 4 and 5 SD, in orange), and high (more than 5 SD, in red). The five epitopes testing positive in more than 25% of type 1 diabetic patients are highlighted in blue. The number of positive epitopes in each subject is indicated in the last row. ++++, off-scale ELISpot reading.
View largeDownload slide

Summary of HLA-A2+ type 1 diabetic (T1D) patients (n = 22), HLA-A2+ healthy control subjects (n = 22), HLA-A2+ type 2 diabetic (T2D) patients (n = 5), and HLA-A2− type 1 diabetic patients (n = 4) assayed for β-cell reactivities. All values, including basal + n SD cutoffs, are expressed as SFC/106 PBMCs and are basal subtracted. Unsubtracted basal values (reactivities to DMSO and gag77–85) are shown in the penultimate row of each column. Subjects positive to at least one epitope are highlighted in green in the second row. Reactivities are ranked as low (between 3 and 4 SD, in yellow), intermediate (between 4 and 5 SD, in orange), and high (more than 5 SD, in red). The five epitopes testing positive in more than 25% of type 1 diabetic patients are highlighted in blue. The number of positive epitopes in each subject is indicated in the last row. ++++, off-scale ELISpot reading.

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TABLE 1

The HLA-A2–restricted epitope panel used in the ISL8Spot assay

SequenceSYFPEITHI scoreReference
PPI2–10 ALWMRLLPL 28 Unpublished 
PPI6–14 RLLPLLALL 31 Unpublished 
PIB10–18 (PPI34–42) HLVEALYLV 27 Hassainya et al. (21); Toma et al. (23); Pinkse et al. (24) 
PIB18–27 (PPI42–51) VCGERGFFYT 7 Hassainya et al. (21); Toma et al. (23) 
PIC20–28 (PPI76–84) SLQPLALEG 18 Hassainya et al. (21) 
PIC29-A5 (PPI85–94) SLQKRGIVEQ 20 Hassainya et al. (21) 
PIA1-A10 (PPI90–99) GIVEQCCTSI 21 Hassainya et al. (21) 
PIA12–20 (PPI101–109) SLYQLENYC 15 Hassainya et al. (21) 
GAD65114–123 VMNILLQYVV 21 Panina-Bordignon et al. (29) 
IGRP228–236 LNIDLLWSV 22 Takaki et al. (20) 
IGRP265–273 VLFGLGFAI 24 Takaki et al. (20) 
Flu MP58–66 GILGFVFTL 30 Viral mix positive control 
EBV BMLF1280–288 GLCTLVAML 28 Viral mix positive control 
CMV pp65495–503 NLVPMVATV 30 Viral mix positive control 
HIV gag77–85 SLYNTVATL 31 Negative control 
SequenceSYFPEITHI scoreReference
PPI2–10 ALWMRLLPL 28 Unpublished 
PPI6–14 RLLPLLALL 31 Unpublished 
PIB10–18 (PPI34–42) HLVEALYLV 27 Hassainya et al. (21); Toma et al. (23); Pinkse et al. (24) 
PIB18–27 (PPI42–51) VCGERGFFYT 7 Hassainya et al. (21); Toma et al. (23) 
PIC20–28 (PPI76–84) SLQPLALEG 18 Hassainya et al. (21) 
PIC29-A5 (PPI85–94) SLQKRGIVEQ 20 Hassainya et al. (21) 
PIA1-A10 (PPI90–99) GIVEQCCTSI 21 Hassainya et al. (21) 
PIA12–20 (PPI101–109) SLYQLENYC 15 Hassainya et al. (21) 
GAD65114–123 VMNILLQYVV 21 Panina-Bordignon et al. (29) 
IGRP228–236 LNIDLLWSV 22 Takaki et al. (20) 
IGRP265–273 VLFGLGFAI 24 Takaki et al. (20) 
Flu MP58–66 GILGFVFTL 30 Viral mix positive control 
EBV BMLF1280–288 GLCTLVAML 28 Viral mix positive control 
CMV pp65495–503 NLVPMVATV 30 Viral mix positive control 
HIV gag77–85 SLYNTVATL 31 Negative control 

For PPI, amino acid (aa) numbering is given both with respect to the PI sequence alone (aa B1-A21) and to the complete PPI sequence (aa 1–110).

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TABLE 2

Characteristics of study subjects

Case numberAge (years)SexDiabetes duration (days)HLA DRB1GAD Ab* (arbitrary units)IA-2 Ab† (arbitrary units)Insulin autoantibodies (arbitrary units)‡Islet cell Abs (Juvenile Diabetes Foundation units)§
HLA-A2+ type 1 diabetic patients (n = 22)          
P01 17 M 122 — 1,939 1,529 3.77 Negative  
P02 38 M 180 04–16 2,817 13 2.54 640  
P03 37 M 60 07–08 2,898 29.9 0.24 —  
P04 43 M 5 11–15 60 11 0.30 Negative  
P05 36 F 6 03–08 3,848 19 1.04 —  
P06 21 F 24 03–16 2,894 598 0.40 —  
P07 33 M 8 01–03 95 13 0.27 20  
P08 23 M 16 04–13 58 18 0.31 5  
P09 32 M 29 — 2,792 13 0.28 Negative  
P10 33 M 19 — 2,114 505 0.44 —  
P11 16 F 6 01–01 1,441 578 0.29 20  
P12 19 M 20 03–03 283 15 0.34 Negative  
P13 25 M 3 01–03 2,970 — — —  
P14 28 M 4 03–04 3,125 2,439 0.86 —  
P15 18 M 13 03–15 883 11 0.35 —  
P16 29 M 26 03–04 2,548 1,570 0.35 20  
P17 27 M 70 03–13 3,292 30 0.77 Negative  
P18 36 M 5 04–13 58 15 0.35 Negative  
P19 46 F 11 01–03 3,192 133 0.27 —  
P20 24 F 4 03–13 1,602 2,876 0.33 —  
P21 36 F 4 04–04 126 2,039 1.00 —  
P22 26 M 3 03–10 28 21 0.30 Negative  
HLA-A2+ healthy subjects (n = 22)          
C01 25 F — 13–14 40 19 0.23 Negative  
C02 26 F — 09–11 37 11 0.20 Negative  
C03 30 F — 01–16 41 15 0.37 Negative  
C04 32 M — 11–16 60 10 0.22 Negative  
C05 55 M — 03–13 — — — —  
C06 26 F — 07–07 48 16 0.40 Negative  
C07 29 M — 09–13 63 5 0.21 —  
C08 33 F — 04–14 63 9 0.23 Negative  
C09 27 M — 07–15 25 16 0.26 Negative  
C10 26 F — 08–11 — — — —  
C11 25 F — 11–15 48 14 0.36 Negative  
C12 23 F — 03–11 41 26 0.76 Negative  
C13 58 F — 07–14 — — — —  
C14 29 F — 04–11 46 13 0.19 Negative  
C15 27 M — 01–11 66 28 0.20 Negative  
C16 56 F — — — — — —  
C17 26 F — 01–07 43 27 0.28 Negative  
C18 26 F — 13–15 70 14 0.15 —  
C19 25 M — — 76 20 0.28 Negative  
C20 48 F — 04–11 70 13 0.13 —  
C21 35 M — — — — — —  
C22 33 M — — 60 14 0.49 —  
HLA-A2+ type 2 diabetic patients (n = 5)         Therapy 
Q01 26 M 7 04–09 48 25 — — Insulin 
Q02 31 M 5 11–12 46 6 — Negative Insulin 
Q03 46 M 162 11–16 15 9 — Negative OHA 
Q04 56 M 192 04–16 17 12 — Negative OHA 
Q05 41 M 360 11–11 66 13 — Negative OHA 
HLA-A2− type 1 diabetic patients (n = 4)          
N01 42 F 29 — 3,784 2,688 0.30 —  
N02 41 M 18 — 1,113 1,405 0.22 —  
N03 15 F 6 04–04 594 19 0.42 —  
N04 19 F 16 03–04 1,175 295 3.66 80  
Case numberAge (years)SexDiabetes duration (days)HLA DRB1GAD Ab* (arbitrary units)IA-2 Ab† (arbitrary units)Insulin autoantibodies (arbitrary units)‡Islet cell Abs (Juvenile Diabetes Foundation units)§
HLA-A2+ type 1 diabetic patients (n = 22)          
P01 17 M 122 — 1,939 1,529 3.77 Negative  
P02 38 M 180 04–16 2,817 13 2.54 640  
P03 37 M 60 07–08 2,898 29.9 0.24 —  
P04 43 M 5 11–15 60 11 0.30 Negative  
P05 36 F 6 03–08 3,848 19 1.04 —  
P06 21 F 24 03–16 2,894 598 0.40 —  
P07 33 M 8 01–03 95 13 0.27 20  
P08 23 M 16 04–13 58 18 0.31 5  
P09 32 M 29 — 2,792 13 0.28 Negative  
P10 33 M 19 — 2,114 505 0.44 —  
P11 16 F 6 01–01 1,441 578 0.29 20  
P12 19 M 20 03–03 283 15 0.34 Negative  
P13 25 M 3 01–03 2,970 — — —  
P14 28 M 4 03–04 3,125 2,439 0.86 —  
P15 18 M 13 03–15 883 11 0.35 —  
P16 29 M 26 03–04 2,548 1,570 0.35 20  
P17 27 M 70 03–13 3,292 30 0.77 Negative  
P18 36 M 5 04–13 58 15 0.35 Negative  
P19 46 F 11 01–03 3,192 133 0.27 —  
P20 24 F 4 03–13 1,602 2,876 0.33 —  
P21 36 F 4 04–04 126 2,039 1.00 —  
P22 26 M 3 03–10 28 21 0.30 Negative  
HLA-A2+ healthy subjects (n = 22)          
C01 25 F — 13–14 40 19 0.23 Negative  
C02 26 F — 09–11 37 11 0.20 Negative  
C03 30 F — 01–16 41 15 0.37 Negative  
C04 32 M — 11–16 60 10 0.22 Negative  
C05 55 M — 03–13 — — — —  
C06 26 F — 07–07 48 16 0.40 Negative  
C07 29 M — 09–13 63 5 0.21 —  
C08 33 F — 04–14 63 9 0.23 Negative  
C09 27 M — 07–15 25 16 0.26 Negative  
C10 26 F — 08–11 — — — —  
C11 25 F — 11–15 48 14 0.36 Negative  
C12 23 F — 03–11 41 26 0.76 Negative  
C13 58 F — 07–14 — — — —  
C14 29 F — 04–11 46 13 0.19 Negative  
C15 27 M — 01–11 66 28 0.20 Negative  
C16 56 F — — — — — —  
C17 26 F — 01–07 43 27 0.28 Negative  
C18 26 F — 13–15 70 14 0.15 —  
C19 25 M — — 76 20 0.28 Negative  
C20 48 F — 04–11 70 13 0.13 —  
C21 35 M — — — — — —  
C22 33 M — — 60 14 0.49 —  
HLA-A2+ type 2 diabetic patients (n = 5)         Therapy 
Q01 26 M 7 04–09 48 25 — — Insulin 
Q02 31 M 5 11–12 46 6 — Negative Insulin 
Q03 46 M 162 11–16 15 9 — Negative OHA 
Q04 56 M 192 04–16 17 12 — Negative OHA 
Q05 41 M 360 11–11 66 13 — Negative OHA 
HLA-A2− type 1 diabetic patients (n = 4)          
N01 42 F 29 — 3,784 2,688 0.30 —  
N02 41 M 18 — 1,113 1,405 0.22 —  
N03 15 F 6 04–04 594 19 0.42 —  
N04 19 F 16 03–04 1,175 295 3.66 80  

The 97.5th percentile cutoff values for Ab titers are as follows:

*

GAD Abs: 180 arbitrary units.

†

IA-2 Abs: 80 arbitrary units.

‡

Insulin autoantibodies: 0.7 arbitrary units.

§

Islet cell Abs: 5 Juvenile Diabetes Foundation units. Positive Ab titers are displayed in bold. —, Not done; OHA, oral hypoglycemic agent.

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The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

This study was supported by the Juvenile Diabetes Research Foundation International Grant 1-2005-39.

We are grateful to patients and control subjects for blood donation and to Huguette Roussely for performing Ab assays.

1
Martin S, Wolf-Eichbaum D, Duinkerken G, Scherbaum WA, Kolb H, Noordzij JG, Roep BO: Development of type 1 diabetes despite severe hereditary B-lymphocyte deficiency.
N Engl J Med
 
345
:
1036
–1040,
2001
2
Wong FS, Wen L, Tang M, Ramanathan M, Visintin I, Daugherty J, Hannum LG, Janeway CA Jr, Shlomchik MJ: Investigation of the role of B-cells in type 1 diabetes in the NOD mouse.
Diabetes
 
53
:
2581
–2587,
2004
3
Harrison LC, Honeyman MC, DeAizpurua HJ, Schmidli RS, Colman PG, Tait BD, Cram DS: Inverse relation between humoral and cellular immunity to glutamic acid decarboxylase in subjects at risk of insulin-dependent diabetes.
Lancet
 
341
:
1365
–1369,
1993
4
Hummel M, Durinovic-Bello I, Ziegler AG: Relation between cellular and humoral immunity to islet cell antigens in type 1 diabetes.
J Autoimmun
 
9
:
427
–430,
1996
5
Schloot NC, Roep BO, Wegmann D, Yu L, Chase HP, Wang T, Eisenbarth GS: Altered immune response to insulin in newly diagnosed compared to insulin-treated diabetic patients and healthy control subjects.
Diabetologia
 
40
:
564
–572,
1997
6
Herold KC, Hagopian W, Auger JA, Poumian-Ruiz E, Taylor L, Donaldson D, Gitelman SE, Harlan DM, Xu D, Zivin RA, Bluestone JA: Anti-CD3 monoclonal antibody in new-onset type 1 diabetes mellitus.
N Engl J Med
 
346
:
1692
–1698,
2002
7
Nepom GT: Class II antigens and disease susceptibility.
Annu Rev Med
 
46
:
17
–25,
1995
8
Liblau RS, Wong FS, Mars LT, Santamaria P: Autoreactive CD8 T cells in organ-specific autoimmunity: emerging targets for therapeutic intervention.
Immunity
 
17
:
1
–6,
2002
9
Walter U, Santamaria P: CD8+ T cells in autoimmunity.
Curr Opin Immunol
 
17
:
624
–631,
2005
10
DiLorenzo TP, Serreze DV: The good turned ugly: immunopathogenic basis for diabetogenic CD8+ T cells in NOD mice.
Immunol Rev
 
204
:
250
–263,
2005
11
Wicker LS, Leiter EH, Todd JA, Renjilian RJ, Peterson E, Fischer PA, Podolin PL, Zijlstra M, Jaenisch R, Peterson LB: Beta 2-microglobulin-deficient NOD mice do not develop insulitis or diabetes.
Diabetes
 
43
:
500
–504,
1994
12
Serreze DV, Leiter EH, Christianson GJ, Greiner D, Roopenian DC: Major histocompatibility complex class I-deficient NOD-B2mnull mice are diabetes and insulitis resistant.
Diabetes
 
43
:
505
–509,
1994
13
Wong FS, Visintin I, Wen L, Flavell RA, Janeway CA Jr: CD8 T cell clones from young nonobese diabetic (NOD) islets can transfer rapid onset of diabetes in NOD mice in the absence of CD4 cells.
J Exp Med
 
183
:
67
–76,
1996
14
Graser RT, DiLorenzo TP, Wang F, Christianson GJ, Chapman HD, Roopenian DC, Nathenson SG, Serreze DV: Identification of a CD8 T cell that can independently mediate autoimmune diabetes development in the complete absence of CD4 T cell helper functions.
J Immunol
 
164
:
3913
–3918,
2000
15
Nagata M, Santamaria P, Kawamura T, Utsugi T, Yoon JW: Evidence for the role of CD8+ cytotoxic T cells in the destruction of pancreatic beta-cells in nonobese diabetic mice.
J Immunol
 
152
:
2042
–2050,
1994
16
Wong FS, Karttunen J, Dumont C, Wen L, Visintin I, Pilip IM, Shastri N, Pamer EG, Janeway CA Jr: Identification of an MHC class I-restricted autoantigen in type 1 diabetes by screening an organ-specific cDNA library.
Nat Med
 
5
:
1026
–1031,
1999
17
Amrani A, Verdaguer J, Serra P, Tafuro S, Tan R, Santamaria P: Progression of autoimmune diabetes driven by avidity maturation of a T-cell population.
Nature
 
406
:
739
–742,
2000
18
Trudeau JD, Kelly-Smith C, Verchere CB, Elliott JF, Dutz JP, Finegood DT, Santamaria P, Tan R: Prediction of spontaneous autoimmune diabetes in NOD mice by quantification of autoreactive T cells in peripheral blood.
J Clin Invest
 
111
:
217
–223,
2003
19
Marron MP, Graser RT, Chapman HD, Serreze DV: Functional evidence for the mediation of diabetogenic T cell responses by HLA-A2.1 MHC class I molecules through transgenic expression in NOD mice.
Proc Natl Acad Sci U S A
 
99
:
13753
–13758,
2002
20
Takaki T, Marron MP, Mathews CE, Guttmann ST, Bottino R, Trucco M, DiLorenzo TP, Serreze DV: HLA-A*0201-restricted T cells from humanized NOD mice recognize autoantigens of potential clinical relevance to type 1 diabetes.
J Immunol
 
176
:
3257
–3265,
2006
21
Hassainya Y, Garcia-Pons F, Kratzer R, Lindo V, Greer F, Lemonnier FA, Niedermann G, van Endert PM: Identification of naturally processed HLA-A2 restricted proinsulin epitopes by reverse immunology.
Diabetes
 
54
:
2053
–2059,
2005
22
van Endert P, Hassainya Y, Lindo V, Bach JM, Blancou P, Lemonnier F, Mallone R: HLA class I epitope discovery in type 1 diabetes.
Ann N Y Acad Sci
 
1079
:
190
–197,
2006
23
Toma A, Haddouk S, Briand JP, Camoin L, Gahery H, Connan F, Dubois-Laforgue D, Caillat-Zucman S, Guillet JG, Carel JC, Muller S, Choppin J, Boitard C: Recognition of a subregion of human proinsulin by class I-restricted T cells in type 1 diabetic patients.
Proc Natl Acad Sci U S A
 
102
:
10581
–10586,
2005
24
Pinkse GG, Tysma OH, Bergen CA, Kester MG, Ossendorp F, van Veelen PA, Keymeulen B, Pipeleers D, Drijfhout JW, Roep BO: Autoreactive CD8 T cells associated with beta cell destruction in type 1 diabetes.
Proc Natl Acad Sci U S A
 
102
:
18425
–18430,
2005
25
American Diabetes Association: Diagnosis and classification of diabetes mellitus.
Diabetes Care
 
27 (Suppl. 1)
:
S5
–S10,
2004
26
Parham P, Brodsky FM: Partial purification and some properties of BB7.2: a cytotoxic monoclonal antibody with specificity for HLA-A2 and a variant of HLA-A28.
Hum Immunol
 
3
:
277
–299,
1981
27
Bingley PJ, Bonifacio E, Mueller PW: Diabetes Antibody Standardization Program: first assay proficiency evaluation.
Diabetes
 
52
:
1128
–1136,
2003
28
Rammensee H, Bachmann J, Emmerich NP, Bachor OA, Stevanovic S: SYFPEITHI: database for MHC ligands and peptide motifs.
Immunogenetics
 
50
:
213
–219,
1999
29
Panina-Bordignon P, Lang R, van Endert PM, Benazzi E, Felix AM, Pastore RM, Spinas GA, Sinigaglia F: Cytotoxic T cells specific for glutamic acid decarboxylase in autoimmune diabetes.
J Exp Med
 
181
:
1923
–1927,
1995
30
Nepom GT: Therapy of autoimmune diseases: clinical trials and new biologics.
Curr Opin Immunol
 
14
:
812
–815,
2002
31
Feldmann M, Steinman L: Design of effective immunotherapy for human autoimmunity.
Nature
 
435
:
612
–619,
2005
32
Serreze DV, Chen YG: Of mice and men: use of animal models to identify possible interventions for the prevention of autoimmune type 1 diabetes in humans.
Trends Immunol
 
26
:
603
–607,
2005
33
Keymeulen B, Vandemeulebroucke E, Ziegler AG, Mathieu C, Kaufman L, Hale G, Gorus F, Goldman M, Walter M, Candon S, Schandene L, Crenier L, De BC, Seigneurin JM, De PP, Pierard D, Weets I, Rebello P, Bird P, Berrie E, Frewin M, Waldmann H, Bach JF, Pipeleers D, Chatenoud L: Insulin needs after CD3-antibody therapy in new-onset type 1 diabetes.
N Engl J Med
 
352
:
2598
–2608,
2005
34
Atkinson MA: ADA Outstanding Scientific Achievement Lecture 2004: Thirty years of investigating the autoimmune basis for type 1 diabetes: why can’t we prevent or reverse this disease?
Diabetes
 
54
:
1253
–1263,
2005
35
Seyfert-Margolis V, Gisler TD, Asare AL, Wang RS, Dosch HM, Brooks-Worrell B, Eisenbarth GS, Palmer JP, Greenbaum CJ, Gitelman SE, Nepom GT, Bluestone JA, Herold KC: Analysis of T-cell assays to measure autoimmune responses in subjects with type 1 diabetes: results of a blinded controlled study.
Diabetes
 
55
:
2588
–2594,
2006
36
Reijonen H, Novak EJ, Kochik S, Heninger A, Liu AW, Kwok WW, Nepom GT: Detection of GAD65-specific T-cells by major histocompatibility complex class II tetramers in type 1 diabetic patients and at-risk subjects.
Diabetes
 
51
:
1375
–1382,
2002
37
Arif S, Tree TI, Astill TP, Tremble JM, Bishop AJ, Dayan CM, Roep BO, Peakman M: Autoreactive T cell responses show proinflammatory polarization in diabetes but a regulatory phenotype in health.
J Clin Invest
 
113
:
451
–463,
2004
38
Danke NA, Koelle DM, Yee C, Beheray S, Kwok WW: Autoreactive T cells in healthy individuals.
J Immunol
 
172
:
5967
–5972,
2004
39
Yang J, Danke NA, Berger D, Reichstetter S, Reijonen H, Greenbaum C, Pihoker C, James EA, Kwok WW: Islet-specific glucose-6-phosphatase catalytic subunit-related protein-reactive CD4+ T cells in human subjects.
J Immunol
 
176
:
2781
–2789,
2006
40
Viglietta V, Kent SC, Orban T, Hafler DA: GAD65-reactive T cells are activated in patients with autoimmune type 1a diabetes.
J Clin Invest
 
109
:
895
–903,
2002
41
Ouyang Q, Standifer NE, Qin H, Gottlieb P, Verchere CB, Nepom GT, Tan R, Panagiotopoulos C: Recognition of HLA class I-restricted β-cell epitopes in type 1 diabetes.
Diabetes
 
55
:
3068
–3074,
2006
42
Standifer NE, Ouyang Q, Panagiotopoulos C, Verchere CB, Tan R, Greenbaum CJ, Pihoker C, Nepom GT: Identification of novel HLA-A*0201-restricted epitopes in recent-onset type 1 diabetic subjects and antibody-positive relatives.
Diabetes
 
55
:
3061
–3067,
2006
43
Alleva DG, Crowe PD, Jin L, Kwok WW, Ling N, Gottschalk M, Conlon PJ, Gottlieb PA, Putnam AL, Gaur A: A disease-associated cellular immune response in type 1 diabetics to an immunodominant epitope of insulin.
J Clin Invest
 
107
:
173
–180,
2001
44
Fourlanos S, Dotta F, Greenbaum CJ, Palmer JP, Rolandsson O, Colman PG, Harrison LC: Latent autoimmune diabetes in adults (LADA) should be less latent.
Diabetologia
 
48
:
2206
–2212,
2005
45
Tree TI, Roep BO, Peakman M: Enhancing the sensitivity of assays to detect T cell reactivity: the effect of cell separation and cryopreservation media.
Ann N Y Acad Sci
 
1037
:
26
–32,
2004
46
Roep BO, Atkinson MA, van Endert PM, Gottlieb PA, Wilson SB, Sachs JA: Autoreactive T cell responses in insulin-dependent (type 1) diabetes mellitus: report of the First International Workshop for Standardization of T Cell Assays.
J Autoimmun
 
13
:
267
–282,
1999
47
DCCT Research Group: Effects of age, duration and treatment of insulin-dependent diabetes mellitus on residual beta-cell function: observations during eligibility testing for the Diabetes Control and Complications Trial (DCCT): the DCCT Research Group.
J Clin Endocrinol Metab
 
65
:
30
–36,
1987
48
Leslie RD, Delli CM: Age-dependent influences on the origins of autoimmune diabetes: evidence and implications.
Diabetes
 
53
:
3033
–3040,
2004
49
Schloot NC, Meierhoff G, Karlsson FM, Ott P, Putnam A, Lehmann P, Gottlieb P, Roep BO, Peakman M, Tree T: Comparison of cytokine ELISpot assay formats for the detection of islet antigen autoreactive T cells: Report of the Third Immunology of Diabetes Society T-Cell Workshop.
J Autoimmun
 
21
:
365
–376,
2003
50
Brooks-Worrell BM, Starkebaum GA, Greenbaum C, Palmer JP: Peripheral blood mononuclear cells of insulin-dependent diabetic patients respond to multiple islet cell proteins.
J Immunol
 
157
:
5668
–5674,
1996
51
Brooks-Worrell B, Gersuk VH, Greenbaum C, Palmer JP: Intermolecular antigen spreading occurs during the preclinical period of human type 1 diabetes.
J Immunol
 
166
:
5265
–5270,
2001
52
Dosch H, Cheung RK, Karges W, Pietropaolo M, Becker DJ: Persistent T cell anergy in human type 1 diabetes.
J Immunol
 
163
:
6933
–6940,
1999
DIABETES
2007