HLA–DRB1*1001 (DR1001) is a shared epitope allele associated with rheumatoid arthritis (RA). The present study was undertaken to assess the capacity of DR1001 to accommodate citrulline in its binding pockets and to identify citrullinated T cell epitopes derived from joint-associated proteins.
The binding of peptide derivatives containing citrulline, arginine, and other amino acid substitutions was measured. A prediction algorithm was developed to identify arginine-containing sequences from joint-associated proteins that preferentially bind to DR1001 upon citrullination. Unmodified and citrullinated versions of these sequences were synthesized and were utilized to stimulate CD4+ T cells from healthy subjects and RA patients. Responses were measured by class II major histocompatibility complex tetramer staining and confirmed by isolating CD4+ T cell clones.
DR1001 accepted citrulline, but not arginine, in 3 of its anchoring pockets. The prediction algorithm identified sequences that preferentially bound to DR1001 with arginine replaced by citrulline. Three of these sequences elicited CD4+ T cell responses. T cell clones specific for these sequences proliferated only in response to citrullinated peptides.
Conversion of arginine to citrulline generates “altered-self” peptides that can be bound and presented by DR1001. Responses to these peptides implicate the corresponding proteins (fibrinogen α, fibrinogen β, and cartilage intermediate-layer protein) as relevant antigens. The finding of preferential responses to citrullinated sequences suggests that altered peptide binding affinity due to this posttranslational modification may be an important factor in the initiation or progression of RA. As such, measuring responsiveness to these peptides may be useful for immunologic monitoring.
Rheumatoid arthritis (RA) is a chronic disease characterized by inflammation and autoimmune-mediated destruction of joints and surrounding tissue (1). RA is differentiated from other forms of arthritis by important immunologic hallmarks, including rheumatoid factor and anticitrulline antibodies (2). The appearance of these autoantibodies implies a breakdown of both T and B cell tolerance. The risk of developing RA (and its immune markers) is linked to a subset of class II major histocompatibility complex (MHC) haplotypes containing the shared epitope (residues 70–74) within their third hypervariable region (3). It is established that these residues dictate the peptide binding preferences for pocket 4 of the class II MHC peptide-binding groove, and perhaps some aspects of T cell receptor (TCR) recognition (4). Several mechanisms for the contribution of the shared epitope to the disease process have been proposed, including direct triggering by the 5–amino acid shared epitope sequence leading to nitric oxide production (5), biased selection of autoreactive TCR (6, 7), ability to bind to heat-shock proteins (8), and ability to present citrullinated peptides (9). However, the precise effects of the shared epitope remain unresolved.
The process of citrullination is a deimination of arginine catalyzed by peptidyl arginine deiminases (PADs), which convert the side chain from basic to polar. Notably, PAD-2 and PAD-4 are expressed at increased levels within joint tissue during inflammation (10). The latter of these PAD isoforms has been associated with RA susceptibility (11). Due to the activity of these enzymes, joint-associated proteins such as filaggrin typically contain citrulline, thereby increasing their antigenicity (12). In addition, PAD expression has been shown to increase due to tissue inflammation or environmental insults such as smoking (13). As a result, additional joint-associated proteins such as fibrin, fibrinogen, and vimentin can be citrullinated during inflammation and cell death. There are very few anchor positions (besides pocket 7) where arginine may be accommodated, and even then this occurs only in a few of the many different human class II MHC with characterized motifs (14). In particular, it has been demonstrated that arginine is poorly tolerated in position 4 of the class II MHC proteins that comprise the shared epitope allele (15). These differences in pocket 4 binding preference correlate with susceptibility to autoimmune disease (16). Furthermore, it has been demonstrated that a joint-associated epitope (vimentin 66–77) binds to shared epitope alleles (DRB1*0101 and DRB1*0401) with appreciable affinity only when residue 70 is changed to citrulline (9). Therefore, it is plausible that the citrullination generates “altered-self” epitopes that can be presented only when key arginine residues are converted by PAD enzymes.
Among the shared epitope alleles, HLA–DRB1*1001 (DR1001) is strongly associated with RA in Spanish and Hungarian populations (16, 17) and has been reported to be one of the alleles most strongly associated with anticitrulline antibodies (17). However, DR1001 is among the least studied shared epitope alleles. For example, relatively few DR1001-restricted epitopes are known (18). In one recent study in which the sequences of eluted peptide were aligned, a binding motif for DR1001 was suggested (19), but there has been no reported investigation of citrulline binding to DR1001. In the current study, we hypothesized that DR1001 accepts citrulline at some of its class II MHC anchor positions. Accordingly, conversion of arginine to citrulline by PAD would increase the binding affinity of “altered-self” peptides. T cells that recognize these peptides would be expected to escape selection, creating a latent pool of autoreactive cells.
MATERIALS AND METHODS
Peptides and class II MHC protein.
Panels of 20-mer peptides with overlapping sequences spanning the influenza A/Puerto Rico/8/34 nucleoprotein, influenza A/Puerto Rico/8/34 matrix protein (MP), influenza B/Hong Kong/330/2001 hemagglutinin (HA), influenza A/Panama/2007/99 HA (HA Pan), influenza A/New Caledonia/20/99 HA (HA NC), tetanus toxin (TT) heavy chain, and anthrax-protective antigen proteins were synthesized on polyethylene pins with 9-fluorenylmethoxycarbonyl (FMOC) chemistry (Mimotopes). The biotinylated reference tetanus toxoid peptide (TT560–571) was synthesized using an Applied Biosystems 433A Peptide Synthesizer. For flexibility, 2 FMOC–6-aminohexanoic acid spacers were added between the N-terminal biotin label and the remainder of the peptide sequence. Panels of 12-mer peptides, 37 with sequences based on the TT560–571 sequence and 20 with sequences based on the HA217–236 sequence (modified for increased solubility) were synthesized on polyethylene pins with FMOC chemistry. Each peptide was dissolved in DMSO at 20 mg/ml and subsequently diluted as needed.
Recombinant DR1001 protein was produced as previously described (20). Briefly, soluble DR1001 was purified from insect cell culture supernatants by affinity chromatography and dialyzed against phosphate storage buffer (100 mM; pH 6.0).
DR1001 tetramer reagents.
For the preparation of class II MHC tetramers, DR1001 protein was biotinylated at a sequence-specific site using biotin ligase (Avidity) prior to dialysis into phosphate storage buffer. The biotinylated monomer was loaded with 0.2 mg/ml of peptide by incubating at 37°C for 72 hours in the presence of 2.5 mg/ml n-octyl-β-D-glucopyranoside and 1 mM Pefabloc SC (Sigma-Aldrich). Peptide-loaded monomers were subsequently conjugated as tetramers using R-phycoerythrin (PE)–streptavidin (Invitrogen) at a molar ratio of 8:1.
Samples for study were obtained from healthy subjects with no personal or family history of RA or autoimmunity and from individuals with RA who are participants in the Benaroya Research Institute's Immune Mediated Disease Registry. The protocol was approved by the Institutional Review Board at Benaroya Research Institute. Subjects were defined as having RA based on fulfillment of the American College of Rheumatology (formerly, the American Rheumatism Association) classification criteria (21), as judged by their rheumatologist. Anti–cyclic citrullinated peptide (anti-CCP) antibody status was determined based on results obtained from a clinical laboratory. HLA typing was performed at the Benaroya Research Institute Translational Core, and all subjects were confirmed to have HLA–DRB1*1001 haplotypes.
Tetramer-based T cell assays.
The tetramer-guided epitope mapping procedure was conducted as previously described (22) for each protein. Peripheral blood mononuclear cells (PBMCs) were isolated from the blood of vaccinated healthy DR1001+ subjects by Ficoll underlay, and CD4+ T cells were isolated using the Miltenyi CD4+ T cell isolation kit. Cells from the CD4− fraction were incubated in 48-well plates (3 × 106 cells/well) for 1 hour and then washed, leaving adherent cells as antigen-presenting cells. After addition of 2 million CD4+ T cells/well, each well was stimulated with a pool of 5 consecutive peptides (20 amino acids long with a 12-residue overlap). After 14 days, resuspended cells (100 μl) were stained with pooled-peptide PE-conjugated tetramers for 60 minutes at 37°C. Subsequently, cells were stained with peridinin chlorophyll A protein (PerCP)–conjugated CD4 monoclonal antibody (mAb) (BD Biosciences), fluorescein isothiocyanate (FITC)–conjugated CD3 mAb (eBioscience), and allophycocyanin (APC)–conjugated CD25 mAb (eBioscience) and analyzed by flow cytometry. Cells from pools that gave positive staining were analyzed again using the corresponding individual peptide tetramers.
T cell responses to single peptides were assessed in a similar manner. PBMCs were isolated from the blood of healthy subjects with DR1001 haplotypes and RA patients with DR1001 haplotypes. Two million CD4+ T cells were isolated and cultured in 48-well plates in the presence of adherent cells from the CD4− fraction. Each well was stimulated with a single peptide derived from a joint-associated protein. After 14 days, resuspended cells (100 μl) were stained with peptide-loaded tetramers for 60 minutes at 37°C. Subsequently, cells were stained with APC-conjugated CD4 mAb, PerCP-conjugated CD3 mAb, and FITC-conjugated CD25 mAb and analyzed by flow cytometry.
T cell cloning and proliferation assays.
CD4+ tetramer-positive cells were single-cell sorted into 96-well plates, using a FACSVantage (Becton Dickinson) containing T cell medium expanded by adding 2 μg/ml phytohemagglutinin and 200,000 irradiated PBMCs plus interleukin-2. Expanded cells were stained with tetramers and analyzed on a FACSCalibur (Becton Dickinson). To assess proliferation, T cells (104/well) were plated (in triplicate) in T cell medium with 105 irradiated PBMCs from a DRB1*1001+ donor, with or without 10 μg/ml peptide, incubated at 37°C for 48 hours, pulsed with 3H-thymidine (1 μCi/well), and harvested 18 hours later, and 3H-thymidine was measured with a scintillation counter. For blocking experiments, anti-DR (L243) or anti-DQ (SPVL3) antibody was added at 20 μg/ml.
Peptide binding competition.
Each test peptide was incubated, in various concentrations, in competition with 0.01 mM biotinylated TT560–571 peptide in wells coated with HLA–DR1001 protein as previously described (23). After washing, residual biotin–tetanus peptide was labeled using europium-conjugated streptavidin (PerkinElmer) and quantified using a Victor2 D time-resolved fluorometer (PerkinElmer). Peptide binding curves were fitted by nonlinear regression with a sigmoidal dose-response curve model using Prism software, version 4.03 (GraphPad Software). Fifty percent inhibition concentration (IC50) binding values (the peptide concentration [in μM] needed to reduce binding of the biotinylated reference peptide by 50%) and their corresponding error bounds were calculated from the resulting curves using Prism software. Relative binding affinity (RBA) was calculated as the IC50 of the substituted peptide divided by the IC50 of the nonsubstituted peptide; the ratio of the two IC50 values indicates the fold difference in peptide binding affinity.
Models of DR1001 with the modified HA217–236 sequence and several citrullinated variants were prepared on a Silicon Graphics Fuel work station using the program Insight II, version 2005 (Accelrys), essentially as previously described (24). Energy minimization was performed at pH 5.4, the experimental pH used for binding studies. The crystal structure of HLA–DRB1*0401 in complex with the type II collagen peptide (25) was used as the base molecule for all simulation studies. Figures were drawn with the aid of WebLabViewer, version 3.5 and DSViewer Pro, version 6.0 (Accelrys), using previously published formatting and color conventions (26). Information on the pdb coordinates is available from the authors upon request
To predict epitopes, we adapted the approach from our previously published work on DRB1*0901 (27). An array of binding coefficients (Cp) was developed for each pocket, based on the observed binding of single (at pocket 1, 4, 6, or 9) amino acid–substituted versions of the TT560–571 and modified HA217–236 peptide sequence. These Cp values are summarized in Supplementary Table 1 (available in the online version of this article at http://www3.interscience.wiley.com/journal/76509746/home). Because all possible amino acids were not measured for any of the pockets, missing values in the data set were estimated based on the observed values for chemically similar amino acids. Peptide binding affinities were calculated based on the formula RBA = Cp1 × Cp4 × Cp6 × Cp9. In this formula, each Cp refers to the observed or estimated binding coefficient. To predict RBA values for peptides, Cp values were taken from the table using lookup procedure, by scanning across every possible binding register and taking the highest observed RBA value for the sequence. To predict RBA values for entire proteins, Cp values were tabulated for every possible binding register.
Tetramer-guided epitope mapping of DR1001-restricted epitopes.
Because relatively few DR1001-restricted epitopes are known, we used tetramer-guided epitope mapping to identify DR1001-restricted epitopes within a variety of antigenic proteins, as described in Materials and Methods. CD4+ T cells from multiple DR1001+ subjects were stimulated with pooled peptides and analyzed by 2 rounds of staining using pooled peptide tetramers and, for wells with tetramer-positive populations, the corresponding individual peptide tetramers (representative results are available from the corresponding author upon request). A total of 16 peptides that contained DR1001-restricted epitopes were identified. These results are summarized in Table 1. Among these, 2 sequences, TT560–571 and a modified version of the HA217–236, were chosen as reference peptides to determine the binding preferences of DR1001.
Table 1. Motif analysis for novel and published DR1001 epitopes*
Predicted binding registers are in boldface; secondary registers are underlined. RBA = relative binding affinity; NP = influenza A/Puerto Rico/8/34 nucleoprotein (novel epitopes); MP = influenza A/Puerto Rico/8/34 matrix protein M1 (novel epitopes); HA HK = influenza B/Hong Kong/330/2001 hemagglutinin (novel epitopes); HA Pan = influenza A/Panama/2007/99 hemagglutinin (novel epitopes); HA NC = influenza A/New Caledonia/20/99 hemagglutinin (novel epitopes); TT = tetanus toxin heavy chain (novel epitopes); PA = anthrax-protective antigen (novel epitopes).
Peptide sequence has been published previously. MP1 = matrix protein (ref.29); HA1 = hemagglutinin (ref.30); HDV = hepatitis delta virus (ref.31); PTPRK = melanoma antigen (ref.32).
Binding of arginine and citrulline to DR1001 at class II MHC anchor positions.
The presence of arginine at class II MHC anchor positions has been previously shown to disrupt peptide binding, in particular for pocket 4 of shared epitope alleles (9, 15). We confirmed this by measuring the binding of arginine-substituted versions of the TT560–571 peptide to DR1001 protein (details available from the corresponding author upon request). Substitutions at residues 561, 564, 566, 567, 569, and 571 blocked peptide binding. These results suggest that arginine is not accepted within the binding pockets of DR1001 and implicate 561Y as the P1 anchor, 564L as the P4 anchor, 566A as the P6 anchor, 567Q as the P7 anchor, and 569S as the P9 anchor. Based on previously published observations on DR0401 (9), the conversion of arginine to citrulline at class II MHC anchor positions in pocket 4 can facilitate peptide binding to multiple shared epitope alleles. To determine whether citrulline is accepted within the binding pockets of DR1001, peptides with single citrulline or arginine substitutions were designed based on the HA217–236 sequence and bound to recombinant DR1001 protein. Arginine was not accepted within the binding pockets of DR1001. However, citrulline was accepted at pockets 4 and 9 (Figure 1). Citrulline substitution at position 7 also significantly enhanced peptide binding. Therefore, conversion of arginine to citrulline at these 3 positions would be expected to facilitate peptide binding to DR1001.
Modeling analysis of peptides bound to DR1001.
To visualize the binding pockets of DR1001, models of the HA NC 217–236 peptide (RFTKLIAKRSKV) in complex with DR1001 were created, as described in Materials and Methods. Modeling results for the unmodified peptide (available from the corresponding author upon request) suggested high-affinity binding with 218F as the P1 anchor. Based on the model, pocket 4 would be expected to favor medium-sized aliphatic or polar amino acids. As seen in Figure 2A, pocket 4 was shown to accept citrulline due to the formation of 3 hydrogen bonds and favorable hydrophobic interactions of the anchor's methylene groups with β13Phe and β26Leu. To allow these interactions, the citrulline side chain bends within the pocket. Pocket 6 accepts leucine (despite the presence of α11Glu and α66Asp [depiction available from the corresponding author upon request]) but probably not larger residues. Thus, it is not surprising that citrulline cannot anchor within this pocket.
Position 7, previously described as a solvent-accessible shelf that accommodates a wide variety of side chains (28), accepts charged residues such as lysine and arginine. However, as depicted in Figure 2B, a variety of interactions (numerous hydrogen bonds and favorable interaction of its methylene groups with β67Leu and β61Trp) strongly favor the binding of citrulline. Pocket 9 accepts serine (depiction available from the corresponding author upon request) and probably favors small polar and aliphatic residues. As shown in Figure 2C, citrulline is a difficult fit within pocket 9 because of β37Tyr, but favorable interactions with α76Arg and β9Glu promote its binding. Taken together, the modeling results further support the notion that conversion of arginine to citrulline at positions 4, 7, and 9 would facilitate peptide binding to DR1001.
Predicting the binding of citrullinated peptides to DR1001.
It would be convenient to be able to predict sequences that preferentially bind to DR1001 upon citrullination. To develop such an algorithm, 2 panels of peptides were designed for empirically measuring the binding of various amino acids to the pockets of DR1001. These peptides were bound, at various concentrations, to DR1001 protein, as described in Materials and Methods. The sequence of each peptide and the measured RBAs are summarized in Supplementary Table 2 (available in the online version of this article at http://www3.interscience.wiley.com/journal/76509746/home). The preferences for pocket 1, pocket 4, pocket 6, and pocket 9 (cumulative RBA values, calculated by averaging observed values for both peptide panels) are summarized in Figure 3. These observations were consistent with (but not identical to) the findings of a recent study that identified a peptide anchor motif for DR1001 by de novo sequencing of natural DR1001-associated peptide ligands (19).
Cumulative RBA values were used to develop an array of binding coefficients (Cp, summarized in Supplementary Table 1) to predict peptide binding to DR1001. The effectiveness of this algorithm was evaluated by testing its ability to predict epitopes within the peptides summarized in Table 1. For each of these peptides, RBAs for all possible binding registers were calculated as described in Materials and Methods. The predicted RBA of the best core epitope for each peptide is shown in the Table 1. For the majority of these peptides, single core epitopes consistent with the DR1001 binding motif were identified. A few peptides contained 2 distinct registers that could be expected to bind DR1001. Predicting epitopes within 2 of the peptides (MP 97–116 and HA Pan 313–332) was problematic because even the best registers for these peptides contained suboptimal residues. In a similar manner, predicted epitopes were identified for 4 previously published peptide sequences (29–32) (Table 1). In total, the prediction algorithm could predict epitopes within 18 of 20 peptides.
The same prediction algorithm was used to identify arginine-containing sequences from within several joint-associated proteins: vimentin, fibrinogen α (Fib A), fibrinogen β (Fib B), fibrinogen γ, α-enolase, filaggrin, and cartilage intermediate-layer protein (CILP). The complete results of this analysis are shown in Supplementary Table 3 (http://www3.interscience.wiley.com/journal/76509746/home). A total of 96 sequences containing sequences with arginine residues at position 4, 7, or 9 that created a predicted epitope when converted to citrulline were identified. These peptides would be expected to preferentially bind to DR1001 upon citrullination. Twelve of these sequences were selected for further study (with a preference for sequences with aromatic residues in position 1 and citrulline at position 4); unmodified and citrullinated versions of these peptides were synthesized, and binding to DR1001 was measured. The sequences and binding results for these peptides are summarized in Table 2. Five of the 12 citrullinated peptides bound to DR1001. The unmodified versions were either unable to bind or bound with similar (CILP 738–741) or lower (CILP 982–996) affinity in a different predicted register. For the remaining sequences, binding may have been influenced by intervening sequences; for example, Fib A 24–38 contains 3 consecutive glycine residues, which could destabilize binding.
Table 2. In vitro binding of citrullinated peptides from joint associated proteins*
Predicted binding registers are underlined; anchor residues are in boldface. X represents citrulline. IC50 = 50% inhibition concentration for binding; CILP = cartilage intermediate-layer protein.
Fibrinogen α 24−38
Fibrinogen α 383−397
Fibrinogen α 506−520
Fibrinogen α 737−751
Fibrinogen β 68−82
Fibrinogen γ 217−231
T cell responses to citrullinated peptides.
CD4+ T cells from 2 healthy subjects and 2 RA patients (1 anti-CCP positive and 1 anti-CCP negative) were stimulated with citrullinated peptides or the corresponding unmodified sequences (containing arginine) in separate wells. After 2 weeks in culture, these cells were analyzed using tetramers. Results in both RA patients are shown in Figure 4A. In RA patient 1 (anti-CCP negative), 2 citrullinated peptide sequences (Fib A737–751 and CILP982–996) were positive. In RA patient 2 (anti-CCP positive), 3 citrullinated peptide sequences (Fib A737–751, Fib B68–82, and CILP982–996) were positive. Representative staining results from a healthy control subject are also shown in Figure 4A. In that control subject, 1 positive response to CILP982–996 was observed, while all other staining was negative. All responses were negative in the second control subject (results not shown). Tetramer-positive T cell clones specific for these sequences were isolated for each of these specificities, and results from representative clones are shown in Figure 4B. As seen in Figure 4C, these T cell clones proliferated only in response to the citrullinated peptide sequences. Blocking experiments with anti-DR antibodies and HLA-matched antigen-presenting cells confirmed that the responses of these clones were restricted by DR1001 (details available from the corresponding author upon request).
The disease specificity and predictive value of anticitrulline antibodies (33, 34) and the association of these antibodies with severe disease (35) strongly suggest that the recognition of citrullinated epitopes by T and B cells is important in the initiation and progression of rheumatoid arthritis. While a few citrullinated epitopes have been validated, current knowledge is actually quite limited. In this study we demonstrated that citrulline is accepted in multiple pockets (positions 4, 7, and 9) of DR1001, a shared epitope allele that is strongly associated with RA and with anticitrulline antibodies (16, 17, 36). This accommodation of citrulline is consistent with molecular modeling results and with the DR1001 binding motif indicated by our peptide binding results. The acceptance of citrulline at position 4 mirrors the results of a previous study (9), which demonstrated that the conversion of arginine to citrulline at pocket 4 dramatically increases peptide affinity for DRB1*0401 and other shared epitope alleles. These current observations are the first to indicate that citrulline can be accepted at other positions. Among these 3 pockets, position 4 is likely to be of primary importance because its binding properties are dictated by the shared epitope residues (residues 70–74) of the class II β-chain. However, citrullination at positions 7 and 9 may also play a significant role in the creation of “altered-self” epitopes (for example, position 7 of the CILP 982–996 epitope was citrullinated).
We have also demonstrated an effective approach to predicting and validating citrullinated epitopes within RA-associated antigens. Our algorithm incorporated information from epitope discovery, peptide binding, and molecular modeling to allow the identification of sequences that bind with increased affinity after citrullination. Using this approach, we identified numerous sequences from joint-associated proteins that could contain citrullinated epitopes. For this initial study, only a subset of these peptides was included in binding and T cell studies, leading to the validation of 3 peptides that appear to contain citrullinated epitopes (although it has not yet been confirmed that these sequences are naturally processed and presented). Based on these findings, it seems likely that other epitopes are present among the peptides that were not studied. The approach applied here for DR1001 should be readily applicable to prediction of citrullinated epitopes for other RA-associated alleles once their binding characteristics have been measured. Citrullinated T cell epitopes identified using this approach will provide important tools, aiding our ability to monitor relevant T cell responses during RA progression and to appropriately target antigen-based therapies.
Although the number of subjects tested was modest, the T cell responses observed in this study have a few interesting implications. It is notable that while T cells specific for these RA-associated epitopes clearly recognized citrullinated sequences, the T cell repertoire appeared to be “blind” to the unmodified sequences (presumably because only the citrullinated sequences could be bound and presented by DR1001). This demonstrates that citrullinated T cell epitopes must be modified by PAD enzymes in order to be recognized, as has been suggested for DR0401-restricted epitopes (9). Previous studies in mice have demonstrated vimentin peptides as naturally processed T cell epitopes (37), induction of arthritis with citrullinated fibrinogen (38), and epitope spreading to multiple citrullinated antigens (39). Therefore, these T cell specificities likely play a role in the induction and/or progression of human RA.
Our current data are inadequate for comparing the T cell responses of RA patients and healthy controls. However, based on the findings of other recent studies it could be expected that RA patients have a higher frequency of memory T cells specific for citrullinated joint antigens. For example, one study demonstrated enhanced cytokine responses to an immunogenic vimentin peptide in RA patients compared with healthy control subjects (37). It might be expected that anticitrulline T cell responses would be closely correlated with anti-CCP status. However, our preliminary results do not suggest a close correlation. RA patient 1, who was anti-CCP negative, had T cell responses to CILP and Fib A. RA patient 2, who was anti-CCP positive, had T cell responses to CILP, Fib A, and Fib B. One healthy subject also had a T cell response to CILP. Of course, a lack of close correlation was not totally unexpected since anti-CCP status reflects only a subset of the anticitrulline antibody responses that are possible.
Recent findings implicate environmental factors such as smoking (40), apoptosis (41), and inflammation (10) in the up-regulation of PAD activity and consequent protein modifications. In inflammation, CD4+ T cells that recognize the resulting citrullinated antigens secrete interleukin-17 (42). Based on these observations, citrulline may provide a crucial link between genetic, immunologic, and environmental factors in rheumatoid arthritis. In this paradigm, “altered-self” epitopes are presented to T cells only when key arginine residues are converted by PAD enzymes. Although one PAD isoform may be expressed in the thymus (43), T cells that recognize these peptides appear to escape thymic selection, creating a latent pool of autoreactive cells. Increased PAD activity, due to one or more environmental factors, could then initiate a cascade of self-reactive T cell responses, followed by humoral responses to citrullinated self proteins and epitope spreading to secondary self antigens, including PAD enzymes themselves (44). Within this paradigm, identifying citrullinated T cell epitopes and monitoring responsiveness to these citrullinated antigens may be essential for evaluating the efficacy of therapeutic agents and for targeting antigen-based therapies.
All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be published. Dr. James had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study conception and design. James, Kwok.
Acquisition of data. James, Moustakas, Bui, Papadopoulos, Bondinas.
Analysis and interpretation of data. James, Moustakas, Bui, Papadopoulos, Buckner, Kwok.
We wish to acknowledge the staff of the Benaroya Research Institute Translational Research Program for subject recruitment and sample management.