OBJECTIVE

Both the early steps and the high recurrence of autoimmunity once the disease is established are unexplained in human type 1 diabetes. Because CD8+ T cells are central and insulin is a key autoantigen in the disease process, our objective was to characterize HLA class I–restricted autoreactive CD8+ T cells specific for preproinsulin (PPI) in recent-onset and long-standing type 1 diabetic patients and healthy control subjects.

RESEARCH DESIGN AND METHODS

We used HLA-A*02:01 tetramers complexed to PPI peptides to enumerate circulating PPI-specific CD8+ T cells in patients and characterize them using membrane markers and single-cell PCR.

RESULTS

Most autoreactive CD8+ T cells detected in recent-onset type 1 diabetic patients are specific for leader sequence peptides, notably PPI6–14, whereas CD8+ T cells in long-standing patients recognize the B-chain peptide PPI33–42 (B9–18). Both CD8+ T-cell specificities are predominantly naïve, central, and effector memory cells, and their gene expression profile differs from cytomegalovirus-specific CD8+ T cells. PPI6–14–specific CD8+ T cells detected in one healthy control displayed Il-10 mRNA expression, which was not observed in diabetic patients.

CONCLUSIONS

PPI-specific CD8+ T cells in type 1 diabetic patients include central memory and target different epitopes in new-onset versus long-standing disease. Our data support the hypothesis that insulin therapy may contribute to the expansion of autoreactive CD8+ T cells in the long term.

Type 1 diabetes is an autoimmune disease driven by the activation of lymphocytes against pancreatic β-cells. Although the successive steps that control the activation of autoreactive lymphocytes have been extensively studied in animal models, the disease process remains ill defined in human type 1 diabetes (1). In mice, type 1 diabetes is transferred into naïve recipients by T cells, is prevented by antibodies that target T-cell differentiation, and fails to develop when key genes in T-cell differentiation or activation are nonfunctional. In humans, T cells—especially CD8+ T cells—are predominant within insulitis in most observations (25). Occurrence of type 1 diabetes in a patient deprived of B lymphocytes further underscores the role of T cells (6). An unexpected feature is the high recurrence level of autoimmunity in long-standing type 1 diabetic patients. Rapid diabetes recurrence is seen in type 1 diabetic recipients of isograft from a nondiabetic twin, accompanied by an almost exclusive islet CD8+ T cell infiltration (7). β-Cell­–specific T cells thus seem to maintain immune memory for years after type 1 diabetes onset. However, the differentiation patterns of autoreactive T cells once diabetes is diagnosed remain largely unknown.

Insulin has been ascribed a key antigenic role in type 1 diabetes. Altered diabetes development in proinsulin 1−/− or 2−/− NOD mice makes a strong case for the primary role of insulin in the NOD mouse (810). In humans, insulin and proinsulin are common targets of autoantibodies and T cells in prediabetic and diabetic individuals. Insulin autoantibodies are the first to be detected in children at risk for type 1 diabetes and carry a high positive predictive value for diabetes in siblings of patients (11). A restricted region of proinsulin located in the B chain and adjacent C-peptide clusters has epitopes that are recognized by CD8+ T cells (1216). Other epitopes are located within the A chain, the C-peptide and C-peptide–B chain junction (14), and preproinsulin (PPI) leader sequence (13,17,18), including residues excised during insulin processing. PPI-reactive CD8+ T cells have mostly been observed in recent-onset type 1 diabetic patients (12,13). However, some peptides, in particular peptides located in the insulin B chain, allow the detection of interferon-γ (IFN-γ)–producing CD8+ T cells in long-standing patients who have been treated with insulin for decades (12).

Most studies have used IFN-γ enzyme-linked immunospot (ELISpot) assays to characterize autoreactive CD8+ T cells (1215). More recently, HLA class I tetramers (TMrs) have identified CD8+ T cells expressing a T-cell receptor specific for HLA class I–restricted peptides, independently of cytokine production (13,18,19). Developing T-cell assays is a major challenge in human type 1 diabetes. It is therefore expected to help in identifying epitopes recognized by T cells and to pave the way toward immunotherapy to restore tolerance to β-cells. New T-cell technologies are expected to allow defining autoreactive T-cell differentiation programs and characterizing autoimmune responses in comparison with physiologically appropriate immune responses.

Here, we used TMrs to detect insulin-reactive CD8+ T cells in type 1 diabetic patients and characterize their functional profile in comparison with cytomegalovirus (CMV)-specific CD8+ T cells. Remarkably, CD8+ T cells detected in recent-onset type 1 diabetic patients are specific for leader sequence peptides, especially PPI6–14. The detection of CD8+ T cells against an insulin B-chain peptide in patients with established disease raises the hypothesis that insulin therapy may also contribute to expansion of autoreactive CD8+ T cells.

Patients.

Type 1 diabetic patients (n = 49) were HLA-A*0201+ and positive for anti-GAD, anti-insulin, or anti-IA2 autoantibodies at diagnosis (Table 1). Recent-onset patients (14 males, 11 females; aged 38.1 ± 11.1 years) were studied within 3 months from diagnosis (median 3 days; range 2–70 days). Long-standing type 1 diabetic patients (13 males, 11 females; aged 41.4 ± 11.6 years) had a median type 1 diabetes duration of 4 years (range 2–40). Control subjects were healthy blood donors (12 males, 9 females; aged 35.6 ± 11.8 years), type 2 diabetic patients under oral treatment (3 males, 4 females; mean age 56.6 ± 9.0 years) or insulin treatment (3 males, 4 females; mean age 55.4 ± 7.7 years) selected as expressing HLA-A*0201. Informed consent was obtained and the study was approved by the local ethics committees. HLA class I alleles were determined by Ambisolv genotyping (Dynal/Invitrogen) on DNA with Gentra Puregene Blood kit A (Qiagen). C-peptide was measured by time-resolved fluoroimmunoassay using Wallac Delfia reagents (Perkin-Elmer SAS, Courtaboeuf, France). Lower detection limit was 3.3 pmol/L. The intra- and interassay coefficients of variation at the level 1.1 ng/mL (364 pmol/L) were 3.9 and 5.2%, respectively, and at the level 6 ng/mL (1986 pmol/L) 3.1 and 3.4%, respectively. Intact insulin did not cross-react with C-peptide in this assay.

TABLE 1

Characteristics of patients and control subjects

PatientSexAge (years)Diabetes durationPatientSexAge (years)Diabetes durationControl subjectSexAge (years)T2DSexAge (years)
R1 54 8 weeks L1 34 3 years H1 49 T2D1 78 
R2 66 72 h L2 52 18 years H2 26 T2D2 66 
R3 49 72 h L3 44 31 years H3 57 T2D3 54 
R4 42 72 h L4 48 39 years H4 29 T2D4 61 
R5 33 48 h L5 34 29 years H5 32 T2D5 51 
R6 39 2 weeks L6 48 4 years H6 29 T2D6 64 
R7 35 10 weeks L7 63 4 years H7 50 T2D7 57 
R8 35 9 weeks L8 47 3 years H8 28 T2D8 63 
R9 30 72 h L9 29 3.5 years H9 21 T2D9 53 
R10 28 72 h L10 42 4 years H10 32 T2D10 57 
R11 37 72 h L11 24 4 years H11 21 T2D11 47 
R12 34 72 h L12 58 3.5 years H12 32 T2D12 51 
R13 23 72 h L13 36 2 years H13 32 T2D13 68 
R14 28 72 h L14 49 4 years H14 28 T2D14 49 
R15 33 72 h L15 29 4 years H15 35    
R16 52 72 h L16 64 40 years H16 66    
R17 26 72 h L17 35 2 years H17 28    
R18 38 72 h L18 28 3 years H18 48    
R19 38 72 h L19 29 4 years H19 35    
R20 38 72 h L20 24 14 years H20 32    
R21 41 72 h L21 44 13 years H21 37    
R22 63 72 h L22 45 25 years       
R23 26 72 h L23 37 31 years       
R24 36 72 h L24 51 9 years       
R25 28 72 h           
PatientSexAge (years)Diabetes durationPatientSexAge (years)Diabetes durationControl subjectSexAge (years)T2DSexAge (years)
R1 54 8 weeks L1 34 3 years H1 49 T2D1 78 
R2 66 72 h L2 52 18 years H2 26 T2D2 66 
R3 49 72 h L3 44 31 years H3 57 T2D3 54 
R4 42 72 h L4 48 39 years H4 29 T2D4 61 
R5 33 48 h L5 34 29 years H5 32 T2D5 51 
R6 39 2 weeks L6 48 4 years H6 29 T2D6 64 
R7 35 10 weeks L7 63 4 years H7 50 T2D7 57 
R8 35 9 weeks L8 47 3 years H8 28 T2D8 63 
R9 30 72 h L9 29 3.5 years H9 21 T2D9 53 
R10 28 72 h L10 42 4 years H10 32 T2D10 57 
R11 37 72 h L11 24 4 years H11 21 T2D11 47 
R12 34 72 h L12 58 3.5 years H12 32 T2D12 51 
R13 23 72 h L13 36 2 years H13 32 T2D13 68 
R14 28 72 h L14 49 4 years H14 28 T2D14 49 
R15 33 72 h L15 29 4 years H15 35    
R16 52 72 h L16 64 40 years H16 66    
R17 26 72 h L17 35 2 years H17 28    
R18 38 72 h L18 28 3 years H18 48    
R19 38 72 h L19 29 4 years H19 35    
R20 38 72 h L20 24 14 years H20 32    
R21 41 72 h L21 44 13 years H21 37    
R22 63 72 h L22 45 25 years       
R23 26 72 h L23 37 31 years       
R24 36 72 h L24 51 9 years       
R25 28 72 h           

R, recent-onset type 1 diabetic patients; L, long-standing type 1 diabetic patients; H, healthy control subjects; T2D, type 2 diabetic control subjects.

TMrs.

PPI peptides were selected from PPI sequence, synthetized, and purified as previously described (20) (Table 2) and were controlled by MALDI-TOF (matrix-assisted laser desorption/ionization−top of flight) on a Bruker Protein TOF mass spectrometer (12). Peptide nomenclature refers to N and C termini along the PPI protein sequence. Peptide binding to HLA-A*0201 was determined by major histocompatibility complex stabilization assays using TAP2-deficient HLA-A*0201–transfected T2 cells (21,22). Percent mean fluorescence intensity (MFI) increase corresponds to (MFI with a given peptide – MFI without peptide)/(MFI without peptide). For TMr assembly, HLA-A*0201 α-chain and human β2-microglobulin were produced in E. coli. HLA-A*0201/peptide monomers were refolded in vitro using 12 mg of peptide, purified by gel filtration (Superdex 200HR 10/30, Pharmacia), and biotinylated using the biotin-protein ligase BirA (Avidity) (23). Purified biotinylated HLA-A*0201/peptide monomers were tretramerized with Extravidin-R-Phycoerythrin conjugate (Sigma) (21,24).

TABLE 2

HLA-A*0201/peptide TMrs

PPI peptidesSequenceSYFPEITHI scoreBIMAS scoreT2/A2*0201 MFITMr productionPositive cutoff (%)TMr frequencies
Ref
Recent-onset T1DLong-standing T1D
2–11 ALWMRLLPLL 28 400 0.575 + 0.023 7/25 4/24 12,13  
6–14 RLLPLLALL 31 180 0.9 + 0.051 8/25 9/24 12,13  
6–15 RLLPLLALLA 0.45 Unstable    na 
7–16 LLPLLALLAL 28 0.063 —    na 
14–23 LALWGPDPAA 14 <1 0.075 —    12,13  
15–24 ALWGPDPAAA 22 40 1.18 + 0.029 8/25 7/24 12,13  
30–39 (B6–15) LCGSHLVEAL 17 0.507 + 0.077 1/25 1/24 na 
33–42 (B9–18) SHLVEALYLV 19 0.79 + 0.046 7/25 12/24 18 
34–42 (B10–18) HLVEALYLV 27 22 1.16 + 0.041 5/25 5/24 12,14,18  
41–51 (B17–27) LVCGERGFFYT 0.105 —    na 
42–51 (B18–27) VCGERGFFYT 20 0.11 + 0.03 3/25 4/24 12  
60–68 (C3–11) DLQVGQVEL 25 >2 0.095 —    na 
76–84 (C20–28) SLQPLALEG 18 0.215 —    14  
81–89 (C25-KR1) ALEGSLQKR 19 0.19 —    na 
85–94 (C29-A5) SLQKRGIVEQ 20 0.135 —    14  
97–105 (A8–16) TSICSLYQL 17 0.22 —    na 
101–109 (A12–20) SLYQLENYC 15 87 0.54 + 0.026 2/25 4/24 14  
PDHase (208–216) TLLEIENAV 26 1,055 na + 0.0165   na 
CMV (pp65 495–503) NLVPMVATV 30 160 1.5 + 1.433   46 
PPI peptidesSequenceSYFPEITHI scoreBIMAS scoreT2/A2*0201 MFITMr productionPositive cutoff (%)TMr frequencies
Ref
Recent-onset T1DLong-standing T1D
2–11 ALWMRLLPLL 28 400 0.575 + 0.023 7/25 4/24 12,13  
6–14 RLLPLLALL 31 180 0.9 + 0.051 8/25 9/24 12,13  
6–15 RLLPLLALLA 0.45 Unstable    na 
7–16 LLPLLALLAL 28 0.063 —    na 
14–23 LALWGPDPAA 14 <1 0.075 —    12,13  
15–24 ALWGPDPAAA 22 40 1.18 + 0.029 8/25 7/24 12,13  
30–39 (B6–15) LCGSHLVEAL 17 0.507 + 0.077 1/25 1/24 na 
33–42 (B9–18) SHLVEALYLV 19 0.79 + 0.046 7/25 12/24 18 
34–42 (B10–18) HLVEALYLV 27 22 1.16 + 0.041 5/25 5/24 12,14,18  
41–51 (B17–27) LVCGERGFFYT 0.105 —    na 
42–51 (B18–27) VCGERGFFYT 20 0.11 + 0.03 3/25 4/24 12  
60–68 (C3–11) DLQVGQVEL 25 >2 0.095 —    na 
76–84 (C20–28) SLQPLALEG 18 0.215 —    14  
81–89 (C25-KR1) ALEGSLQKR 19 0.19 —    na 
85–94 (C29-A5) SLQKRGIVEQ 20 0.135 —    14  
97–105 (A8–16) TSICSLYQL 17 0.22 —    na 
101–109 (A12–20) SLYQLENYC 15 87 0.54 + 0.026 2/25 4/24 14  
PDHase (208–216) TLLEIENAV 26 1,055 na + 0.0165   na 
CMV (pp65 495–503) NLVPMVATV 30 160 1.5 + 1.433   46 

MFI, mean fluorescent intensities; na, not available; T1D, type 1 diabetes.

TMr assays.

Peripheral blood mononuclear cells (PBMCs) were prepared from fresh blood using Lymphoprep (Axis Shield) separation in Leucosep tubes. TMr staining was performed by incubating 106 PBMCs with 5–10 μg/mL phycoerythrin (PE)-labeled TMrs at 37°C for 30 min. Anti–CD45RA-FITC, anti–CCR7-PE-Cy7, anti–CD8-PerCP (SK1 clone), and anti–CD3-APC-Cy7 antibodies (BD Pharmingen, eBioscience) were then added for 15 min at 4°C. After washing, cells were acquired on a BD FACSAria and analyzed using FlowJo (Tree Star) (25,26). The minimal number of TMr+ events analyzed in phenotyping studies was 5.103.

Cell sorting.

CD8+ PBMCs were negatively selected (Dynal/Invitrogen) by depleting CD4-, CD14-, CD16-, CD19-, CD36-, CD56-, CDw123-, and CD235a-expressing cells. Staining was performed on 106 CD8-enriched cells by adding 10–20 μg/mL of nonpooled PE-labeled TMr at 37°C for 30 min. Anti–CD8-PerCP–labeled antibody was then added for 15 min at 4°C. Small lymphocytes were gated according to forward/side scatter profiles. CD8+/TMr+ T cells were sorted on a FACSAria at 1 cell/well into 96-well PCR plates containing 5 μl PBS treated with diethyl pyrocarbonate (Sigma) and immediately frozen at −80°C.

Single-cell reverse transcriptase PCR.

RNA was extracted from sorted cells by direct cellular lysis for 2 min at 65°C. Procedures and primers for coamplification of multiple genes in single cells were designed as described (27,28). Reverse transcription was carried out with murine leukemia virus reverse transcriptase (Applied Biosystems) for 60 min at 37°C. Seminested PCR was then performed with gene-specific primers (Eurogentec) and AmpliTAQ Gold Polymerase (Applied Biosystems) by touch-down PCR. PCR products were resolved on a 2.5% (w/v) agarose gel. Perforin (Prf1), granzyme A (Gzma), granzyme B (Gzmb), Fas ligand (Fasl), IFN-γ (Ifng), TGF-β1 (Tgfb1), TNF-α (Tnfa), IL-2 (Il2), IL-10 (Il10), IL-10Rα (Il10ra), IL-7R (Il7r), MIP-1α (Mip1a), MIP-1β (Mip1b), PD1 (Pd1), RANTES (Ccl5), KLRG1 (Klrg1), CCR7 (Ccr7), and CD3ε (Cd3e) mRNAs were analyzed.

Statistical methods.

Comparison of distribution scores between patients and control subjects and TMr assessment used the nonparametric Kruskal-Wallis test or Fisher exact test. To study assay reliability, we used the graphical Altman and Bland method, which focuses on means and variability of differences between repeated measurement pairs (29). C-peptide levels were compared using the Mann-Whitney U test.

Insulin-specific CD8+ T cells are detected in type 1 diabetic patients.

PPI peptides are recognized by CD8+ T cells from type 1 diabetic patients using IFN-γ ELISpot (1215), which, methodologically, restricts recognition to a functional subset of T cells, precluding characterization of their differentiation stage. To characterize PPI-specific CD8+ T cells independently of their function, we prepared HLA-A*0201 PE-labeled TMrs complexed with previously defined PPI peptides (A2/PPI) (Table 2) (1215). Stable TMrs were obtained with peptides that showed a percent MFI >0.5 in HLA-A2 stabilization assays (Table 2). HLA-A2 TMrs complexed with CMV peptide pp65495–503 (A2/CMV TMrs) and PDHase208–216 (A2/PDHase TMrs) were used as positive and negative controls, respectively. A2/PPI TMrs+ CD8+ T cells were detected (Fig. 1A–E) in 35/49 type 1 diabetic patients (71.43%). Detection thresholds for each individual TMr+ were set at the 95th percentile of values obtained in controls. Percentages of TMr+ CD8+ T cells above 95th percentile of controls were considered positive. (Table 2). No CD8+ T cells were stained with A2/PDHase TMrs (Fig. 1F) or in absence of TMrs (Fig. 1G). As expected, more cells were often stained with HLA-A2/CMV TMrs than with A2/PPI TMrs (Fig. 1H).

FIG. 1.

TMr detection of CD8+ T cells specific for A2.1-restricted PPI peptides. A: Lymphocytes were gated according to forward/side scatter profiles. B: CD3+CD8+ T cells were gated to evaluate percent of TMr+ cells. C–E: CD8+ T cells stained with A2/PPI peptide TMr complexed with PPI6–14 (C), PPI15–24 (D), and PPI33–42 (E) peptides were detected in L24, R2, and L11 type 1 diabetic patients, respectively. F and G: For each staining, compensation settings were verified with the HLA-A2/PDHase208–216 negative control TMrs (F) and with a staining without TMr (G), here shown on the R2 patient. H: HLA-A2/CMV pp65495–503 TMrs were used as the virus-specific positive control (R2 patient). (A high-quality color representation of this figure is available in the online issue.)

FIG. 1.

TMr detection of CD8+ T cells specific for A2.1-restricted PPI peptides. A: Lymphocytes were gated according to forward/side scatter profiles. B: CD3+CD8+ T cells were gated to evaluate percent of TMr+ cells. C–E: CD8+ T cells stained with A2/PPI peptide TMr complexed with PPI6–14 (C), PPI15–24 (D), and PPI33–42 (E) peptides were detected in L24, R2, and L11 type 1 diabetic patients, respectively. F and G: For each staining, compensation settings were verified with the HLA-A2/PDHase208–216 negative control TMrs (F) and with a staining without TMr (G), here shown on the R2 patient. H: HLA-A2/CMV pp65495–503 TMrs were used as the virus-specific positive control (R2 patient). (A high-quality color representation of this figure is available in the online issue.)

Significant differences were observed among recent-onset, long-standing type 1 diabetic patients, and control subjects in the frequencies of TMr+ CD8+ T cells specific for PPI leader sequence peptides PPI6–14, PPI15–24, and B-chain peptide PPI33–42 (B9–18;Fig. 2A). Percentages of CD8+ T cells specific for leader sequence peptide PPI2–11, B chain peptides PPI30–39, PPI34–42, and PPI42–51, and A chain peptide PPI101–109 did not differ significantly among groups, but few individual responses were seen against these peptides (Fig. 2A and Supplementary Table 1). There was no significant difference in PPI-specific CD8+ T cells between healthy controls and type 2 diabetic patients, including with insulin-treated Type 2 diabetic patients (data not shown), and in CMV-specific CD8+ T cells between type 1 diabetic patients and control subjects (Fig. 2A). The number of individuals whose TMr+ frequencies were ≥95th percentile of control subjects was different between recent-onset patients and control subjects for PPI6–14 TMr+ cells (8/25, 32.0%; P < 0.03) and PPI15–24 (8/25, 32.0%; P < 0.03) but not for PPI33–42 (7/25, 28.0%; P = 0.06) and between long-standing type 1 diabetic patients and control subjects for PPI33–42 (12/24, 50.0%; P < 0.002) but not for PPI6–14 (9/24, 37.5%; P = 0.35) and PPI15–24 (7/24, 29.2%; P = 0.055). In a healthy control subject, a high (0.14%) frequency of PPI6–14–specific CD8+ T cells was observed (Fig. 2A).

FIG. 2.

Distribution of CD8+ T cells specific for A2.1-restricted PPI peptides in type 1 diabetic patients and control subjects. A: Each symbol represents the percentage of CD8+ T cells specific for A2.1-restricted PPI and control peptides detected in individual recent-onset type 1 diabetic (●), long-standing type 1 diabetic (■), and healthy and type 2 diabetic control (▲) subjects. A significantly higher percentage of CD8+ T cells specific for PPI6–14 (P = 0.0123), PPI15–24 (P = 0.0369), and PPI33–42 (P = 0.001) was observed in recent and long-standing type 1 diabetic patients compared with control subjects (Kruskal-Wallis test). Differences in detection of A2/PPI TMr+ were significant for leader sequence PPI6–14 (recent-onset: median 0.085% [range 0.009–0.6]; long-standing: 0.042% [0.003–0.1]; control: 0.014% [0.007–0.14]; P = 0.0123), PPI15–24 (recent-onset: 0.042% [0.002–0.2]; long-standing: 0.034% [0.004–0.18]; control: 0.012% [0.002–0.035]; P = 0.0369), and B chain PPI33–42 (recent-onset: 0.031% [0.001–0.14]; long-standing: 0.115% [0.007–0.79]; control: 0.018% [0.001–0.07]; P = 0.001). B: Plots for pairs of measurement scores of HLA-A2/peptide TMrs. Differences of ±0.000–0.005 were observed for PPI6–14, PPI15–24, and PPI33–42 TMrs (mean difference ± SD: 0.000 ± 0.019, 0.001 ± 0.021, and 0.005 ± 0.028, respectively) and 0.000–0.008 for CMV pp65495–503 TMrs (0.008 ± 0.09). The scatter plot of the difference between the measurements against their mean allows detecting no lack of individual reliability, which may be hidden by the use of global reliability statistics for PPI6–14, PPI15–24, PPI33–42, and CMV pp65495–503 TMr levels (24).

FIG. 2.

Distribution of CD8+ T cells specific for A2.1-restricted PPI peptides in type 1 diabetic patients and control subjects. A: Each symbol represents the percentage of CD8+ T cells specific for A2.1-restricted PPI and control peptides detected in individual recent-onset type 1 diabetic (●), long-standing type 1 diabetic (■), and healthy and type 2 diabetic control (▲) subjects. A significantly higher percentage of CD8+ T cells specific for PPI6–14 (P = 0.0123), PPI15–24 (P = 0.0369), and PPI33–42 (P = 0.001) was observed in recent and long-standing type 1 diabetic patients compared with control subjects (Kruskal-Wallis test). Differences in detection of A2/PPI TMr+ were significant for leader sequence PPI6–14 (recent-onset: median 0.085% [range 0.009–0.6]; long-standing: 0.042% [0.003–0.1]; control: 0.014% [0.007–0.14]; P = 0.0123), PPI15–24 (recent-onset: 0.042% [0.002–0.2]; long-standing: 0.034% [0.004–0.18]; control: 0.012% [0.002–0.035]; P = 0.0369), and B chain PPI33–42 (recent-onset: 0.031% [0.001–0.14]; long-standing: 0.115% [0.007–0.79]; control: 0.018% [0.001–0.07]; P = 0.001). B: Plots for pairs of measurement scores of HLA-A2/peptide TMrs. Differences of ±0.000–0.005 were observed for PPI6–14, PPI15–24, and PPI33–42 TMrs (mean difference ± SD: 0.000 ± 0.019, 0.001 ± 0.021, and 0.005 ± 0.028, respectively) and 0.000–0.008 for CMV pp65495–503 TMrs (0.008 ± 0.09). The scatter plot of the difference between the measurements against their mean allows detecting no lack of individual reliability, which may be hidden by the use of global reliability statistics for PPI6–14, PPI15–24, PPI33–42, and CMV pp65495–503 TMr levels (24).

Assay reliability was calculated from values obtained from two assays performed in two different samples collected at median intervals of 3 days following diagnosis (range 2–90 days) in the same individuals using PPI6–14, PPI15–24, PPI33–42, and CMV pp65495–503 TMrs. Differences of up to ±0.038, 0.042, 0.060, and 0.186% were observed for PPI6–14, PPI15–24, PPI33–42, and CMV pp65495–503 TMrs, respectively. Mean differences represent interassay mean errors and intervals acceptable errors. There is good interassay agreement for PPI6–14, PPI15–24, and PPI33–42 peptides, each value being included in the error interval, which is ≤0.05 (Fig. 2B). Overall, 68% of recent-onset and 83.3% of long-standing type 1 diabetic patients had detectable PPI-specific CD8+ T cells above the 95th centile of control subjects. Responses were observed against at least two peptides in 44.9% of patients (22/49), including 32.6% (16/49) who showed a response to either PPI6–14, PPI15–24, PPI33–42.

In long-standing patients who stained positive for A2/PPI TMrs, mean diabetes duration was 6.5 years (range: 3–25) for PPI6–14 peptide, 14.4 years (3–39) for PPI15–24 peptide, and 10.7 (3–39) for PPI33–42 peptide. Basal C-peptide values were available in 11/19 patients in whom increased A2/PPI33–42 TMr+ CD8+ T cells (TMr+ patients) were detected and 7/30 patients in whom A2/PPI33–42 TMr+ CD8+ T cells were in the basal range (TMr patients). Although differences between both groups were not significant, lower C-peptide values were observed in TMr+ patients (median 0.07 ± 0.09 nmol/L; range 0.01–0.27) than in TMr ones (median 0.22 ± 0.19 nmol/L; range 0.01–0.59; P = 0.07) (Fig. 3A). Moreover, an inverse correlation was observed between percentages of A2/PPI33–42 TMr+ CD8+ T cells detected and fasting C-peptide values (r = −0.63; P = 0.05) (Fig. 3B).

FIG. 3.

Correlation between C-peptide level and the presence of PPI33–42–specific CD8+ T cells in type 1 diabetic patients. A: Each symbol represents the fasting C-peptide level detected in type 1 diabetic patients depending on whether A2.1/PPI33–42 TMr+ CD8+ T cells were above (●) or below (■) detection threshold (TMr+ and TMr patients, respectively; threshold = 0.046%). P = 0.07 by Mann-Whitney U test. B: Each symbol represents the correlation between the percentage of PPI33–42–specific CD8+ T cells and basal C-peptide levels detected in type 1 diabetic patients in whom increased A2.1/PPI33–42 TMr+ CD8+ T cells were detected. A negative correlation (P ≤ 0.005, Spearman r = −0.63) was observed.

FIG. 3.

Correlation between C-peptide level and the presence of PPI33–42–specific CD8+ T cells in type 1 diabetic patients. A: Each symbol represents the fasting C-peptide level detected in type 1 diabetic patients depending on whether A2.1/PPI33–42 TMr+ CD8+ T cells were above (●) or below (■) detection threshold (TMr+ and TMr patients, respectively; threshold = 0.046%). P = 0.07 by Mann-Whitney U test. B: Each symbol represents the correlation between the percentage of PPI33–42–specific CD8+ T cells and basal C-peptide levels detected in type 1 diabetic patients in whom increased A2.1/PPI33–42 TMr+ CD8+ T cells were detected. A negative correlation (P ≤ 0.005, Spearman r = −0.63) was observed.

PPI-specific CD8+ T cells express central memory cell markers.

Upon antigen encounter, CD8+ T cells express differentiation programs that imprint their homing, survival, activation, and functions. Detection of circulating TMr+ CD8+ T cells allows characterizing membrane markers, especially homing and signaling markers that discriminate effector and memory cells from naïve cells. PPI-specific CD8+ T cells were gated to evaluate percent TMr+ cells and define (Fig. 4) (30) CD45RA+CCR7+ naïve T cells (TN), CD45RA CCR7+ central memory T cells (TCM), CCR7CD45RA effector memory T cells (TEM), and CCR7 CD45RA+ effector memory T cells (TEMRA) (Fig. 4A and B). Significant differences were seen in the distribution of CMV-specific and PPI-specific CD8+ naïve and memory T cells between type 1 diabetic patients and control subjects using the Kruskal-Wallis test, but not between recent-onset and long-standing type 1 diabetic patients (Fig. 4C). In recent-onset and long-standing type 1 diabetic patients, 31.5 and 32.0% TN PPI-specific CD8+ cells were detected, respectively, whereas these cells were almost undetectable among CMV-specific T cells. Similarly, PPI-specific TCMs represented 25.4 and 29.8% of CD8+ T cells in the two respective type 1 diabetic populations, whereas they represented only 15.6% of CMV-specific CD8+ T cells (P = 0.0071). In contrast, PPI-specific TEM and TEMRA were underrepresented in recent-onset (8.19%) and long-standing (12.1%) patients, as compared with CMV-specific TEM and TEMRA CD8+ T cells (50.47 and 29.97%, respectively). There was no difference in distributions of PPI6–14–, PPI15–24–, PPI33–42–specific CD8+ T cells. Altogether, these data show that PPI-specific CD8+ memory T cells are predominantly TN, TCM, and TEM cells, whereas the majority of CMV-specific CD8+ T cells are TEM and TEMRA cells. We observed no correlation between diabetes duration and percentage of PPI-specific CD8+ TN or TCM T cells on long-standing type 1 diabetic patients (data not shown).

FIG. 4.

Phenotype of PPI- and CMV-specific CD8+ T cells. Lymphocytes were gated according to forward/side scatter profiles and then on CD3+CD8+ T cells to evaluate percent of TMr+ cells on the R2 patient. A and B: Among CMV-specific (A) and PPI6–14–specific (B) CD3+CD8+ T cells, TN, TCM, TEM, and TEMRA were characterized. C: Distribution within each subset compartment of CMV-specific (black symbols) and PPI-specific CD3+CD8+ T cells in recent-onset (white symbols) and long-standing (gray symbols) type 1 diabetic patients. P values were calculated using the Kruskal-Wallis test. PPI-specific CD8+ TN cells represent 32.2% (range 3.3–75) and 33.6% (0–80.9), PPI-specific CD8+ TCM cells represent 25.4% (2.3–52) and 28.9% (0–6.2), and PPI-specific CD8+ TEM/TEMRA cells represent 18.5% (0–78.8) and 18.9% (0–80) in recent-onset and long-standing type 1 diabetic patients, respectively; CMV-specific TN cells 4.6% (0–18.7), TCM 13.1% (0.5–75), and TEM/TEMRA 40.2% (0.9–87.4). (A high-quality color representation of this figure is available in the online issue.)

FIG. 4.

Phenotype of PPI- and CMV-specific CD8+ T cells. Lymphocytes were gated according to forward/side scatter profiles and then on CD3+CD8+ T cells to evaluate percent of TMr+ cells on the R2 patient. A and B: Among CMV-specific (A) and PPI6–14–specific (B) CD3+CD8+ T cells, TN, TCM, TEM, and TEMRA were characterized. C: Distribution within each subset compartment of CMV-specific (black symbols) and PPI-specific CD3+CD8+ T cells in recent-onset (white symbols) and long-standing (gray symbols) type 1 diabetic patients. P values were calculated using the Kruskal-Wallis test. PPI-specific CD8+ TN cells represent 32.2% (range 3.3–75) and 33.6% (0–80.9), PPI-specific CD8+ TCM cells represent 25.4% (2.3–52) and 28.9% (0–6.2), and PPI-specific CD8+ TEM/TEMRA cells represent 18.5% (0–78.8) and 18.9% (0–80) in recent-onset and long-standing type 1 diabetic patients, respectively; CMV-specific TN cells 4.6% (0–18.7), TCM 13.1% (0.5–75), and TEM/TEMRA 40.2% (0.9–87.4). (A high-quality color representation of this figure is available in the online issue.)

PPI-specific CD8+ T cells show characteristic CD8+ T cells gene expression programs.

Cell surface phenotypes often fail to ascribe functional attributes to memory CD8+ T cells (25,31,32). To address how differentiation programs are established at clinical onset and in long-standing type 1 diabetes, we studied 18 genes coding for inflammatory chemokines, cytokines, cytotoxic molecules, and receptors involved in CD8+ T-cell responses. Gene expression was evaluated in TMr+ CD8+ T cells and nonpurified TMr+ CD8+-naïve and central memory cells. Cells were obtained by purifying CD8+ T cells, then sorting TMr+ cells from patients in whom a minimum of 0.05% TMr+ CD8+ T cells were detected. In these patients, the percentage of cells expressing the CD3e gene was 82.06 ± 14.35%, in contrast with patients who did not reach this threshold (16.50 ± 8.96%). Gene expression profiles were heterogeneous between single cells carrying the same peptide specificity, but a significant percentage of single cells coexpressed genes involved in the same functional program (Fig. 5). Gene expression in PPI-specific (Fig. 5A) and CMV-specific (Fig. 5B) CD8+ T cells was different. Figure 5A illustrates a representative subject (R18) displaying 0.19% A2/PPI6–14 TMr+ CD8+ T cells of which only 4.3% coexpressed Pfr and Gzma or Gzmb, none coexpressed Ccl5 (coding for RANTES) and Mip1b, but 40% expressed Ccr7. Opposite profiles were seen in A2/CMV-specific CD8+ T cells. In patient L9 (Fig. 5B), 2.0% A2/CMV TMr+ CD8+ T cells were detected of which 36% coexpressed Pfr and Gzma or Gzmb but only 4% expressed Ccr7, while 32% coexpressed Ccl5 and Mip1b.

FIG. 5.

Gene expression profiles and distribution of PPI- and CMV-specific CD8+ single T cells. AC: Examples of single-cell PCR of CD8+ T cells specific for PPI6–14 (A; patient R18), pp65495–503 CMV peptide (B; patient L9), and PPI6–14 (C; control subject H20). Genes tested are indicated in the upper row of each diagram. Each single cell tested is numbered in the first column on the left. Black squares indicate expression of the corresponding mRNA, and white squares indicate lack thereof. Gene expression is reported for cells expressing CD3ε mRNA. D: Each point represents, for a single individual, the mean percent of cells expressing the indicated gene out of the 35–40 single CD8+ T cells specific for PPI (○) or CMV pp65495–503 (△) CD8+ T cells studied. Results shown for PPI-specific CD8+ T cells correspond to pooled PPI6–14, PPI15–24, and PPI33–42 TMr+ cells in recent and long-standing type 1 diabetic patients. Only individuals in whom PPI or pp65495–503 CMV-specific CD8+ T cells were detected were further studied and are here represented. P values indicate statistically significant difference (Mann-Whitney U test) in the expression of Prf, Gzma, Gzmb, Ccl5, Mip1b, and Ccr7 between PPI- and CMV-specific CD8+ T cells. No significant difference was observed in the expression of the other genes tested.

FIG. 5.

Gene expression profiles and distribution of PPI- and CMV-specific CD8+ single T cells. AC: Examples of single-cell PCR of CD8+ T cells specific for PPI6–14 (A; patient R18), pp65495–503 CMV peptide (B; patient L9), and PPI6–14 (C; control subject H20). Genes tested are indicated in the upper row of each diagram. Each single cell tested is numbered in the first column on the left. Black squares indicate expression of the corresponding mRNA, and white squares indicate lack thereof. Gene expression is reported for cells expressing CD3ε mRNA. D: Each point represents, for a single individual, the mean percent of cells expressing the indicated gene out of the 35–40 single CD8+ T cells specific for PPI (○) or CMV pp65495–503 (△) CD8+ T cells studied. Results shown for PPI-specific CD8+ T cells correspond to pooled PPI6–14, PPI15–24, and PPI33–42 TMr+ cells in recent and long-standing type 1 diabetic patients. Only individuals in whom PPI or pp65495–503 CMV-specific CD8+ T cells were detected were further studied and are here represented. P values indicate statistically significant difference (Mann-Whitney U test) in the expression of Prf, Gzma, Gzmb, Ccl5, Mip1b, and Ccr7 between PPI- and CMV-specific CD8+ T cells. No significant difference was observed in the expression of the other genes tested.

Gene expressions were strikingly comparable in A2/PPI6–14, PPI15–24, and PPI33–42 TMr+ CD8+ T cells (data not shown). Considering the whole type 1 diabetic population, the mean percentage of PPI-specific CD8+ T cells that expressed Pfr and Gzma and Gzmb was 16.1, 11.0, and 6.9%, respectively, as compared with 51.5, 40.7, and 21.4% for CMV-specific CD8+ T cells (P = 0.0003, P = 0.0092, P = 0.0125, respectively; Fig. 5D). Differences in chemokine gene expression were also seen, such as Ccl5 and Mip1b, which drive immune cells to inflammatory sites. Indeed, a higher number of CMV-specific CD8+ T cells expressed Ccl5 compared with PPI-specific CD8+ T cells (81.9 vs. 27.8%; P=0.0026), and the same result was observed for Mip1b (20.6 vs. 6.0%; P = 0.01). By contrast, Ccr7, which controls recirculation through lymph nodes, was more expressed by PPI-specific CD8+ T cells (30.9%) than CMV-specific CD8+ cells (3.4%; P < 0.001). These data suggest that PPI-specific CD8+ T cells display gene expression programs that largely overlap TCM rather than TN phenotypes, based on expression of IFN-γ and Rantes genes (33), whereas CMV-specific CD8+ T cells are predominantly TEM cells. Expression of Fasl, Tnfa, Il2, Mip1a, and Il10 genes was remarkably rare. Expression of the Il7ra gene was above 70% in both A2/CMV and A2/PPI peptide TMr+ CD8+ T cells. In contrast with previous reports (34), the expression of Klrg1 by CMV-specific CD8+ T cells was heterogeneous, whereas it was low in most PPI-specific CD8+ T cells. A significant difference was further observed in expression of Pd1 between PPI- and CMV-specific CD8+ T cells (3.0 vs. 11.1%; P = 0.0117). There was no significant difference in gene expression levels by PPI-specific CD8+ T cells between recent-onset and long-standing type 1 diabetic patients (data not shown). In the only control individual who showed detectable PPI6–14–specific CD8+ T cells (Fig. 2A), a unique gene expression program was observed, with 34% CD8+ T cells expressing Il10, as compared with 2.2 ± 3.3% of PPI6–14–specific CD8+ T cells in type 1 diabetic patients.

HLA class I TMrs may prove instrumental in characterizing T cells in autoimmunity. Following previous identification of PPI-specific CD8+ T cells in type 1 diabetes using IFN-γ ELISpot (12), we here report the presence of circulating PPI-specific CD8+ T cells in type 1 diabetes. PPI-specific CD8+ T cells were detected against three major peptides, two within the PPI leader sequence (PPI6–14 and PPI15–24) and one within the insulin B chain (PPI33–42; also known as B9–18). CD8+ T cells that were specific for other PPI peptides were only seen in few patients. Overall, CD8+ T cells specific for at least one PPI peptide were detected in 68% of recent-onset and 83% of long-standing type 1 diabetic patients. These figures are likely underestimated, since stable TMrs were only obtained with peptides that showed sufficient binding affinity to HLA-A*0201 (Table 2). However, we cannot rule out that PPI-specific T cells not tested here are activated in type 1 diabetes and that different peptides are recognized at different stages of type 1 diabetes because we only tested individuals with clinical diabetes.

HLA-A*0201–restricted leader sequence peptides are commonly presented to CD8+ T cells, as previously reported for PPI6–14 and PPI15–24 (12,15). PPI6–14– and PPI15–24–specific CD8+ T cells have previously been shown to be cytotoxic against human islet T cells and HLA-A*0201–transfected P815 target cells, respectively (13,17). Recognition of PPI15–24 has been reported to increase when human islets were incubated in the presence of high glucose concentrations (17), adding further insight into its role in the natural history of human type 1 diabetes.

The differentiation of memory T cells in relation to antigen exposure has been extensively studied in immune responses to viruses but remains poorly understood in autoimmunity. Clinical diabetes occurs after a preclinical phase that spans over years in many patients. However, the β-cell mass in prediabetes and the level of autoantigen exposure once diabetes is diagnosed remain unknown (35,36). The persistence of CMV infection with time makes it a relevant control, since T cells are kept exposed to low levels of CMV antigens, as is the case for autoimmune T cells exposed to residual β-cells (36). We limited our study of membrane markers of PPI-specific CD8+ T cells to CCR7 and CD45RA, which discriminate central memory from effector memory CD8+ T cells. However, CD45RA does not fully correlate with effector memory functions. Markers such as CD27 and CD28 further discriminate at least three and four different CD8+ subsets within CCR7 CD45RA and CCR7CD45RA+ CMV-specific cells, respectively (25). These markers were, however, less relevant to study PPI-specific CD8+ T cells as these cells were mostly within the CD45RA CCR7+ central memory compartment. CD45RA+CD45RO+ double-positive T cells have been identified as possibly representing a transition population from naïve CD45RA+ to memory CD45RO+ T cells. This population has been shown to be increased in recent-onset type 1 diabetic patients but not in long-standing patients, possibly reflecting an imbalance between the two CD45 isoforms in autoimmunity (37). Because we did not exclude CD45RA+CD45RO+ T cells from the analysis of memory cells, we cannot exclude that we lost these transition cells that are likely to be included in naïve cells in our analysis. However, we saw the same increase in memory PPI-specific CD8+ T cells in long-standing type 1 diabetic patients in whom the double-positive CD45RA+CD45RO+ T cell is not increased. A recent work has reported the predominant detection of TN and TEMRA CD8+ T cells, but they were specific for different peptides, i.e., PPI2–10 and PPI34–42, with higher percentages of detection and in subjects who had possibly been treated with anti-CD3 antibody (38).

Analysis of postactivation CD8+ T cells actually illustrates much greater diversity in survival, recall potentials as well as tissue specificity than is defined by current phenotypic markers (32). We turned to single cell PCR to study gene expression programs in CD8+ T cells. In contrast to CMV-specific CD8+ T cells that showed effector/effector memory phenotypes, PPI-specific CD8+ T cells showed profiles that overlap with those of central memory cells. Gene expression profiles of PPI6–14– and PPI15–24–specific CD8+ T cells in recent-onset type 1 diabetic patients as well as PPI33–42– and PPI15–24–specific CD8+ T cells in long-standing type 1 diabetic patients were identical. Similarities in gene expression patterns of CD8+ T cells specific for PPI leader sequence peptides and B chain PPI33–42 are remarkable because exposition to B chain epitopes persists in insulin-treated, long-standing, type 1 diabetic patients independently of the persistence of residual β-cells. However, this may not be an exclusive mechanism, since PPI15–24–specific CD8+ T cells were detected in a subset of patients with long-standing diabetes, and thus independently of insulin therapy because insulin preparations are devoid of PPI leader sequence. No correlation was observed between detection of PPI15–24–specific CD8+ T cells and type 1 diabetes duration. Of further note, a significant fraction of PPI-specific T cells displayed a naïve status that was virtually absent in the CMV-specific repertoire, suggesting that there is still an unexpressed potential for further autoimmune activation in most patients. This unexpressed potential may explain the arousal of PPI33–42–specific CD8+ T cells upon insulin treatment in long-standing patients. Indeed, these cells were not detected in type 2 diabetic patients treated with insulin, suggesting that insulin treatment may effectively expand them only in the presence of preexisting autoimmunity. The detection of naïve PPI-specific CD8+ T cells may indicate their preexistence and maintenance in the repertoire of type 1 diabetic patients in relation with the slow chronic process that characterizes type 1 diabetes. Adding further value to the extensive functional characterization carried out by single-cell PCR, one single healthy subject harbored PPI6–14–specific CD8+ T cells expressing the regulatory cytokine Il10. Thus, the mere presence of autoreactive CD8+ T cells may not be considered pathogenic, as previously suggested for islet-reactive CD4+ T cells (39).

We observed a differentiated CMV-specific CD8+ T cell phenotype, as previously reported (25), with low expression of Ccr7 and high expression of cytolytic effector molecules and significant diversity among individuals. By contrast, PPI-specific CD8+ T cells expressed higher levels of Ccr7—presumably allowing them to repeatedly circulate to lymph nodes rather than directly homing to the islets—and lower levels of cytolytic effector molecules. An important factor in driving distinct memory T-cell phenotypes is the strength of T-cell activation in relationship with local factors in secondary lymphoid organs in which the initial T-cell activation takes place and at the inflammatory site (32,40). Expression of homing receptors for lymph nodes have usually been associated with situations in which low strength of activation or a low antigen load is seen (41). Although in most instances antigen persistence is not required for maintenance of memory T cells, recent data in type 1 diabetes suggest that long-standing type 1 diabetic patients may still harbor residual β-cells (42,43).

The detection of B chain–specific CD8+ T cells in a significant fraction of long-standing type 1 diabetic patients indicates that memory CD8+ T cells persist in the long-term range despite the likelihood that autoimmunity to β-cells is progressively downregulated, since residual β-cells disappear. This persistence of detectable central memory CD8+ T cells in the long term raises several nonexclusive hypotheses. They may persist in the absence of residual β-cells or in the presence of a minimal residual β-cell mass, either resisting autoimmune destruction or regenerating as destruction proceeds, as proposed in the NOD model (44). The persistent detection of PPI6–14– and, to a larger extent, PPI15–24–specific CD8+ T cells in few long-standing patients is compatible with either hypothesis. Alternatively, long-term treatment with exogenous insulin may contribute to activation of T cells against B-chain peptides. This is relevant in the light of the clinical observation that type 1 diabetes is a highly recurrent disease in patients who have been treated with exogenous insulin for years. The negative correlation observed between the percentage of A2/PPI33–42 TMr+ CD8+ T cells detected in type 1 diabetic patients and residual basal C-peptide values is compatible with this hypothesis.

In conclusion, a majority of type 1 diabetic patients harbor PPI-specific CD8+ central memory T cells. The absence of these cells in most control individuals makes a strong case for the role of PPI-specific CD8+ T cells in type 1 diabetes. Although type 1 diabetes is characterized by active autoimmunity many years after disease onset, our observation that exogenous insulin may contribute to expansion of autoreactive CD8+ T cells in the long term brings a new light to the natural history of the disease.

This work was supported by Agence Nationale de la Recherche grants COD-2005 MELTD1 and PHRC AOR 05034/P051078 (C.B.), the Juvenile Diabetes Research Foundation (JDRF; grant 1-2008-106), the European Foundation for the Study of Diabetes (EFSD/JDRF/Novo Nordisk European Programme in Type 1 Diabetes Research 2007), the INSERM Avenir Program (R.M.), and the Ile de France CODDIM. S.L. was supported by an Applied Research and Development grant.

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

S.L. performed experiments and contributed to writing the manuscript. J.-P.B., S.M., N.L., and B.R. performed experiments and contributed to discussions. J.C. performed statistical evaluations and reviewed and edited the manuscript. E.L. was responsible for patient recruitment and follow-up. F.L. and R.M. were involved in discussion and manuscript editing. C.B. designed experiments, chaired discussions, and wrote the manuscript.

Sincere thanks are expressed to Unité de Recherche Clinique of Cochin for their support for this study.

1.
Faideau
B
,
Larger
E
,
Lepault
F
,
Carel
JC
,
Boitard
C
.
Role of beta-cells in type 1 diabetes pathogenesis
.
Diabetes
2005
;
54
(
Suppl. 2
):
S87
S96
[PubMed]
2.
Itoh
N
,
Hanafusa
T
,
Miyazaki
A
, et al
.
Mononuclear cell infiltration and its relation to the expression of major histocompatibility complex antigens and adhesion molecules in pancreas biopsy specimens from newly diagnosed insulin-dependent diabetes mellitus patients
.
J Clin Invest
1993
;
92
:
2313
2322
[PubMed]
3.
Somoza
N
,
Vargas
F
,
Roura-Mir
C
, et al
.
Pancreas in recent onset insulin-dependent diabetes mellitus. Changes in HLA, adhesion molecules and autoantigens, restricted T cell receptor V beta usage, and cytokine profile
.
J Immunol
1994
;
153
:
1360
1377
[PubMed]
4.
Willcox
A
,
Richardson
SJ
,
Bone
AJ
,
Foulis
AK
,
Morgan
NG
.
Analysis of islet inflammation in human type 1 diabetes
.
Clin Exp Immunol
2009
;
155
:
173
181
[PubMed]
5.
Conrad
B
,
Weidmann
E
,
Trucco
G
, et al
.
Evidence for superantigen involvement in insulin-dependent diabetes mellitus aetiology
.
Nature
1994
;
371
:
351
355
[PubMed]
6.
Martin
S
,
Wolf-Eichbaum
D
,
Duinkerken
G
, et al
.
Development of type 1 diabetes despite severe hereditary B-lymphocyte deficiency
.
N Engl J Med
2001
;
345
:
1036
1040
[PubMed]
7.
Sibley
RK
,
Sutherland
DE
,
Goetz
F
,
Michael
AF
.
Recurrent diabetes mellitus in the pancreas iso- and allograft. A light and electron microscopic and immunohistochemical analysis of four cases
.
Lab Invest
1985
;
53
:
132
144
[PubMed]
8.
Thébault-Baumont
K
,
Dubois-Laforgue
D
,
Krief
P
, et al
.
Acceleration of type 1 diabetes mellitus in proinsulin 2-deficient NOD mice
.
J Clin Invest
2003
;
111
:
851
857
[PubMed]
9.
Moriyama
H
,
Abiru
N
,
Paronen
J
, et al
.
Evidence for a primary islet autoantigen (preproinsulin 1) for insulitis and diabetes in the nonobese diabetic mouse
.
Proc Natl Acad Sci USA
2003
;
100
:
10376
10381
[PubMed]
10.
Nakayama
M
,
Abiru
N
,
Moriyama
H
, et al
.
Prime role for an insulin epitope in the development of type 1 diabetes in NOD mice
.
Nature
2005
;
435
:
220
223
[PubMed]
11.
Ziegler
AG
,
Hummel
M
,
Schenker
M
,
Bonifacio
E
.
Autoantibody appearance and risk for development of childhood diabetes in offspring of parents with type 1 diabetes: the 2-year analysis of the German BABYDIAB Study
.
Diabetes
1999
;
48
:
460
468
[PubMed]
12.
Toma
A
,
Haddouk
S
,
Briand
JP
, et al
.
Recognition of a subregion of human proinsulin by class I-restricted T cells in type 1 diabetic patients
.
Proc Natl Acad Sci USA
2005
;
102
:
10581
10586
[PubMed]
13.
Toma
A
,
Laïka
T
,
Haddouk
S
, et al
.
Recognition of human proinsulin leader sequence by class I-restricted T-cells in HLA-A*0201 transgenic mice and in human type 1 diabetes
.
Diabetes
2009
;
58
:
394
402
[PubMed]
14.
Mallone
R
,
Martinuzzi
E
,
Blancou
P
, et al
.
CD8+ T-cell responses identify beta-cell autoimmunity in human type 1 diabetes
.
Diabetes
2007
;
56
:
613
621
[PubMed]
15.
Martinuzzi
E
,
Novelli
G
,
Scotto
M
, et al
.
The frequency and immunodominance of islet-specific CD8+ T-cell responses change after type 1 diabetes diagnosis and treatment
.
Diabetes
2008
;
57
:
1312
1320
[PubMed]
16.
Blancou
P
,
Mallone
R
,
Martinuzzi
E
, et al
.
Immunization of HLA class I transgenic mice identifies autoantigenic epitopes eliciting dominant responses in type 1 diabetes patients
.
J Immunol
2007
;
178
:
7458
7466
[PubMed]
17.
Skowera
A
,
Ellis
RJ
,
Varela-Calviño
R
, et al
.
CTLs are targeted to kill beta cells in patients with type 1 diabetes through recognition of a glucose-regulated preproinsulin epitope
.
J Clin Invest
2008
;
118
:
3390
3402
[PubMed]
18.
Pinkse
GG
,
Tysma
OH
,
Bergen
CA
, et al
.
Autoreactive CD8 T cells associated with beta cell destruction in type 1 diabetes
.
Proc Natl Acad Sci USA
2005
;
102
:
18425
18430
[PubMed]
19.
Velthuis
JH
,
Unger
WW
,
Abreu
JR
, et al
.
Simultaneous detection of circulating autoreactive CD8+ T-cells specific for different islet cell-associated epitopes using combinatorial MHC multimers
.
Diabetes
2010
;
59
:
1721
1730
[PubMed]
20.
Kuzushima
K
,
Hayashi
N
,
Kimura
H
,
Tsurumi
T
.
Efficient identification of HLA-A*2402-restricted cytomegalovirus-specific CD8(+) T-cell epitopes by a computer algorithm and an enzyme-linked immunospot assay
.
Blood
2001
;
98
:
1872
1881
[PubMed]
21.
Gannagé
M
,
Abel
M
,
Michallet
AS
, et al
.
Ex vivo characterization of multiepitopic tumor-specific CD8 T cells in patients with chronic myeloid leukemia: implications for vaccine development and adoptive cellular immunotherapy
.
J Immunol
2005
;
174
:
8210
8218
[PubMed]
22.
Passoni
L
,
Scardino
A
,
Bertazzoli
C
, et al
.
ALK as a novel lymphoma-associated tumor antigen: identification of 2 HLA-A2.1-restricted CD8+ T-cell epitopes
.
Blood
2002
;
99
:
2100
2106
[PubMed]
23.
Garboczi
DN
,
Utz
U
,
Ghosh
P
, et al
.
Assembly, specific binding, and crystallization of a human TCR-alphabeta with an antigenic Tax peptide from human T lymphotropic virus type 1 and the class I MHC molecule HLA-A2
.
J Immunol
1996
;
157
:
5403
5410
[PubMed]
24.
Altman
JD
,
Moss
PA
,
Goulder
PJ
, et al
.
Phenotypic analysis of antigen-specific T lymphocytes
.
Science
1996
;
274
:
94
96
[PubMed]
25.
Romero
P
,
Zippelius
A
,
Kurth
I
, et al
.
Four functionally distinct populations of human effector-memory CD8+ T lymphocytes
.
J Immunol
2007
;
178
:
4112
4119
[PubMed]
26.
Monteiro
M
,
Evaristo
C
,
Legrand
A
,
Nicoletti
A
,
Rocha
B
.
Cartography of gene expression in CD8 single cells: novel CCR7- subsets suggest differentiation independent of CD45RA expression
.
Blood
2007
;
109
:
2863
2870
[PubMed]
27.
Peixoto
A
,
Monteiro
M
,
Rocha
B
,
Veiga-Fernandes
H
.
Quantification of multiple gene expression in individual cells
.
Genome Res
2004
;
14
:
1938
1947
[PubMed]
28.
Peixoto
A
,
Evaristo
C
,
Munitic
I
, et al
.
CD8 single-cell gene coexpression reveals three different effector types present at distinct phases of the immune response
.
J Exp Med
2007
;
204
:
1193
1205
[PubMed]
29.
Bland
JM
,
Altman
DG
.
Statistical methods for assessing agreement between two methods of clinical measurement
.
Lancet
1986
;
1
:
307
310
[PubMed]
30.
Sallusto
F
,
Lenig
D
,
Förster
R
,
Lipp
M
,
Lanzavecchia
A
.
Two subsets of memory T lymphocytes with distinct homing potentials and effector functions
.
Nature
1999
;
401
:
708
712
[PubMed]
31.
Appay
V
,
Dunbar
PR
,
Callan
M
, et al
.
Memory CD8+ T cells vary in differentiation phenotype in different persistent virus infections
.
Nat Med
2002
;
8
:
379
385
[PubMed]
32.
Jameson
SC
,
Masopust
D
.
Diversity in T cell memory: an embarrassment of riches
.
Immunity
2009
;
31
:
859
871
[PubMed]
33.
Weninger
W
,
Manjunath
N
,
von Andrian
UH
.
Migration and differentiation of CD8+ T cells
.
Immunol Rev
2002
;
186
:
221
233
[PubMed]
34.
Ibegbu
CC
,
Xu
YX
,
Harris
W
,
Maggio
D
,
Miller
JD
,
Kourtis
AP
.
Expression of killer cell lectin-like receptor G1 on antigen-specific human CD8+ T lymphocytes during active, latent, and resolved infection and its relation with CD57
.
J Immunol
2005
;
174
:
6088
6094
[PubMed]
35.
Rother
KI
,
Harlan
DM
.
Challenges facing islet transplantation for the treatment of type 1 diabetes mellitus
.
J Clin Invest
2004
;
114
:
877
883
[PubMed]
36.
Liu
EH
,
Digon
BJ
 3rd
,
Hirshberg
B
, et al
.
Pancreatic beta cell function persists in many patients with chronic type 1 diabetes, but is not dramatically improved by prolonged immunosuppression and euglycaemia from a beta cell allograft
.
Diabetologia
2009
;
52
:
1369
1380
[PubMed]
37.
Peakman
M
,
Mahalingam
M
,
Leslie
RD
,
Vergani
D
.
Co-expression of CD45RA (naive) and CD45R0 (memory) T-cell markers
.
Lancet
1994
;
343
:
424
[PubMed]
38.
Cernea
S
,
Herold
KC
.
Monitoring of antigen-specific CD8 T cells in patients with type 1 diabetes treated with antiCD3 monoclonal antibodies
.
Clin Immunol
2010
;
134
:
121
129
[PubMed]
39.
Arif
S
,
Tree
TI
,
Astill
TP
, et al
.
Autoreactive T cell responses show proinflammatory polarization in diabetes but a regulatory phenotype in health
.
J Clin Invest
2004
;
113
:
451
463
[PubMed]
40.
Cui
W
,
Kaech
SM
.
Generation of effector CD8+ T cells and their conversion to memory T cells
.
Immunol Rev
2010
;
236
:
151
166
[PubMed]
41.
Champagne
P
,
Dumont
AR
,
Sékaly
RP
.
Learning to remember: generation and maintenance of T-cell memory
.
DNA Cell Biol
2001
;
20
:
745
760
[PubMed]
42.
Gianani
R
,
Campbell-Thompson
M
,
Sarkar
SA
, et al
.
Dimorphic histopathology of long-standing childhood-onset diabetes
.
Diabetologia
2010
;
53
:
690
698
[PubMed]
43.
Keenan
HA
,
Sun
JK
,
Levine
J
, et al
.
Residual insulin production and pancreatic ß-cell turnover after 50 years of diabetes: Joslin Medalist Study
.
Diabetes
2010
;
59
:
2846
2853
[PubMed]
44.
Sherry
NA
,
Kushner
JA
,
Glandt
M
,
Kitamura
T
,
Brillantes
AM
,
Herold
KC
.
Effects of autoimmunity and immune therapy on beta-cell turnover in type 1 diabetes
.
Diabetes
2006
;
55
:
3238
3245
[PubMed]
45.
Gras
S
,
Saulquin
X
,
Reiser
JB
, et al
.
Structural bases for the affinity-driven selection of a public TCR against a dominant human cytomegalovirus epitope
.
J Immunol
2009
;
183
:
430
437
[PubMed]

Supplementary data