A common genetic variant in the gene encoding the protein tyrosine phosphatase nonreceptor type 22 (PTPN22 C1858T) has been linked to a wide range of autoimmune disorders. Although a B cell–intrinsic role in promoting disease has been reported, the mechanism(s) through which this variant functions to alter the preimmune B cell repertoire remains unknown. Using a series of polyclonal and transgenic self-reactive models harboring the analogous mutation in murine Ptpn22, we show evidence for enhanced BCR, B cell–activating factor receptor, and CD40 coreceptor programs, leading to broadly enhanced positive selection of B cells at two discrete checkpoints in the bone marrow and spleen. We further identified a bias for selection of B cells into the follicular mature versus marginal zone B cell compartment. Using a biomarker to track a self-reactive H chain in peripheral blood, we found evidence of similarly enhanced positive selection in human carriers of the PTPN22 C1858T variant. Our combined data support a model whereby the risk variant augments the BCR and coreceptor programs throughout B cell development, promoting enrichment of self-reactive specificities into the follicular mature compartment and thereby likely increasing the risk for seeding of autoimmune B cell responses.

The protein tyrosine phosphatase nonreceptor type 22 gene (PTPN22) encodes for the phosphatase LYP (or PEP in mice), which functions as a negative regulator of AgR signaling through its direct modulation of Src family kinases (1). A genetic variant in PTPN22 (C1858T; encoding LYP-R620W) is a major risk factor for a number of autoimmune disorders, including type 1 diabetes, systemic lupus erythematosus, rheumatoid arthritis, Graves’ disease, and others (26). To model this variant in vivo, we previously generated knock-in mice with the analogous risk allele on a mixed 129/Sv and C57BL/6J background. Expression of the Ptpn22 variant significantly altered lymphocyte function and led to the development of systemic autoimmunity (7).

Although the PTPN22 risk variant promotes disease via its impact on multiple cell lineages, B cells appear to be particularly important for this process (7, 8). Notably, the disorders associated with the PTPN22 risk variant are characterized by high titers of disease-specific pathogenic autoantibodies (9). Although autoantibodies may result from B and/or T cell–driven processes, our group found that B cell–intrinsic Ptpn22 variant expression was sufficient to promote autoimmunity (7). The conclusion that altered B cell tolerance may potentiate similar risks in human subjects arose from the observation that transitional B cells were increased in human and murine carriers of the risk variant (7, 10). Lending further support to this idea, increased proportions of self-reactive B cells were identified at two checkpoints during human B cell development based on analyses of cells isolated from the peripheral blood of healthy subjects with the risk allele (11).

Taken together, these data suggest that the PTPN22 variant plays an important role in shaping the preimmune B cell repertoire in at-risk individuals and in murine models; however, several key questions remain that warrant further study. First, one major unresolved issue is whether the variant confers a gain versus loss, or alternatively an altered, functional activity. Indeed, a range of contradictory findings with respect to the impact of the variant on AgR signals has been observed in human and murine studies (reviewed in Ref. 12). The studies to date have relied upon in vitro stimulated cells; thus, direct ex vivo analysis of AgR signaling is needed. Second, other than the BCR signaling pathway, it is unclear whether additional networks are impacted by the PTPN22 variant. Of particular relevance, are the B cell–activating factor receptor (BAFFR) and CD40 coreceptor pathways, given their importance in regulating B cell tolerance and known cross-talk with the BCR signaling program (1316). Finally, a more complete understanding of how the PTPN22 variant shapes the specificities selected into the mature naive B cell compartments might help to predict the risk for subsequent aberrant activation of such cells in autoimmune individuals.

In the current study, we use a series of murine models, in association with a rigorous assessment of the naive repertoire, to track the development and selection of B cells expressing the Ptpn22 risk variant. Murine studies included mice homozygous for the nonrisk allele (Ptpn22CC) and heterozygous (Ptpn22CT) or homozygous (Ptpn22TT) risk allele animals intercrossed with various selection models. To reduce potential impacts from additional genetic modifiers, we used Ptpn22 variant and controls backcrossed onto the nonautoimmune C57BL/6J background. In parallel, a flow-based assay tracking a self-reactive H chain (HC) was used to monitor peripheral B cell selection in human carriers with the variant. Our combined results suggest that the Ptpn22 variant augments the coordinate BCR, BAFFR, and CD40 programs throughout B cell development, leading to altered tolerance at discrete checkpoints in the bone marrow (BM) and periphery. These events promoted enhanced positive selection of transitional B cells, with an unexpected bias for self-reactive specificities into the follicular mature (FM) compartment. Healthy human subjects expressing the risk variant exhibited a reduced proportion of transitional B cells using a specific self-reactive HC family; these findings are most consistent with broadly enhanced positive selection for developing B cells with a range of self-reactive specificities. Our collective data add to the understanding of B cell–mediated autoimmunity, suggesting that allelic variants that enhance the BCR and/or key coreceptor pathways preferentially skew self-reactive B cells into the follicular B cell compartment, thereby increasing the probability of subsequent events that trigger autoimmune germinal center responses.

Ptpn22CC (Ly 5.1 and Ly 5.2 lines), Ptpn22TT, Nur77-GFP–transgenic (Tg), BAFFR−/−, CD40−/−, CD40L−/−, MD4-Tg, membrane-bound hen egg lysozyme (mHEL)-expressing, soluble hen egg lysozyme (sHEL)-expressing, IgM deficient (μMT), and 125-Tg (VH125 and VK125 lines) mice were maintained in the specific pathogen–free animal facility of Seattle Children’s Research Institute and were handled according to Institutional Animal Care and Use Committee–approved protocols. Ptpn22TT–knock-in mice were generated as previously described (7) and backcrossed to C57BL/6J mice for 10 generations before crossing to Nur77-GFP–Tg, MD4, 125-Tg (VH125), or 125-Tg (VK125) mice. The experimental mice contained one copy of Nur77-GFP, one copy of MD4, or one copy each of the VH125 and VK125 transgenes.

Murine FM and marginal zone (MZ) B cell populations were bulk sorted, and genomic DNA was extracted for survey-depth sequencing of the IgH locus (Adaptive Biotechnologies, Seattle, WA). Adaptive Biotechnologies’ immunoSEQ Illumina-based sequencing platform was used to identify productive templates for assignment of IgH V and J genes and to determine CDR3 boundaries (defined as including the first base of the codon for the conserved cysteine in the V gene through the last base of the codon for the conserved residue in the J gene). Average hydrophobicity scores (GRAVY) were calculated using http://www.gravy-calculator.de/. Diversity scores (reciprocal Simpson Index) were calculated as described (17). The total number of productive templates generated can be found in Supplemental Table I. Data are representative of two independent experiments.

Frozen PBMCs from age- and sex-matched healthy subjects screened for PTPN22 1858 were obtained from the Benaroya Research Institute Immune Mediated Disease Registry. Subjects included PTPN22 C/C (n = 35), C/T (n = 35), and T/T (n = 3). For flow cytometry, single-cell PBMC suspensions were incubated with fluorescently labeled Abs (see below) for 20 min at 4°C in staining buffer, and data were collected using an LSR II and analyzed using FlowJo software. Subject information can be found in Supplemental Table II. Data are representative of three independent experiments.

Anti-murine Abs used in these studies include B220 (RA3-6B2), CD24 (M1/69), CD21 (7E9), CD23 (B3B4), CD4 (RM4-4), and CD44 (IM7) from BioLegend; IgMa (DS-1) and CD40 (3/23) from BD; Ly 5.1 (A20), Ly 5.2 (104), Gr1 (RB6-8C5), CD11b (M1/70), CD3 (17A2), BAFFR (eBio7H22-E16), CD93 (AA4.1), CD62L (MEL-14), and CD40L (MR1) from eBioscience; IgM (1B4B1) and IgD (1126) from SouthernBiotech; recombinant human insulin conjugated to biotin from Fitzgerald Industries; and Streptavidin (S-868) from Life Technologies. Anti-human Abs used include CD19 (HIB19) and IgM (MHM-88) from BioLegend; CD27 (O323) from eBioscience; CD10 (HI10a), CD24 (ML5), CD38 (HIT2), IgD (IA6-2), and BAFFR (IIC1) from BD; and anti-human FITC-conjugated 9G4 Ab (18).

Murine single-cell BM and splenocyte suspensions were incubated with fluorescently labeled Abs for 30 min at 4°C in staining buffer, and data were collected using an LSR II and analyzed using FlowJo software. Cell sorting was performed using an Aria II (BD); sort purities were >90% in all experiments.

Murine single FM and MZ cells were FACS sorted into 96-well plates. BCRs were cloned from the cDNA of single cells and used to generate mAbs using methods previously described (16, 19). Data are representative of at least two independent experiments.

All mAb ELISAs were performed with each mAb first normalized to a standard dilution ranging from 10 ng/ml to 10 μg/ml. Individual FM and MZ mAbs were tested for reactivity with insulin (Fitzgerald Industries International), malondialdehyde-modified low-density lipoprotein (MDA-LDL; 20P-MD L-105; Academy Biomedical), dsDNA (Sigma-Aldrich), phosphorylcholine (PC)-12 (Sigma-Aldrich), and Smith and nuclear ribonucleoprotein (smRNP; ATR01-10; Arotec Diagnostics), as previously described (18). Abs were considered reactive if the observed OD at the highest mAb concentration (10 μg/ml) was greater than a threshold value set at 0.5 OD. Anti–hen egg lysozyme (HEL) Abs in MD4 chimeras were measured by incubating serum on plates precoated with HEL, followed by detection with anti-IgMa conjugated to biotin (DS-1) and streptavidin-HRP. Serum B cell–activating factor (BAFF) levels were measured using a BAFF/BlyS Quantikine ELISA Kit (R&D Systems). Data are representative of two independent experiments.

BM was harvested from donor Ptpn22CC (Ly 5.1), Ptpn22TT (Ly 5.2), and μMT (Ly 5.1/Ly 5.2) mice, and single-cell suspensions were mixed at a 10:10:80 ratio for retro-orbital injection of 5 × 106 cells into lethally irradiated (900 cGy) Ptpn22CC (Ly 5.1/Ly 5.2) recipients. Resulting BM chimeras were sacrificed 12–14 wk posttransplantation. Data are representative of five independent experiments.

BM was harvested from donor Ptpn22CC MD4 or Ptpn22TT MD4 mice and made into single-cell suspensions, and 5 × 106 cells were retro-orbitally injected into lethally irradiated (900 cGy) mHEL-expressing or sHEL-expressing recipients. Resulting BM chimeras were sacrificed 8–12 wk posttransplantation. Data are representative of two independent experiments.

RNA was isolated from sorted cells (purity > 90% for all samples) using the AllPrep DNA/RNA Micro Kit (QIAGEN) and converted into cDNA by reverse transcription (Maxima Reverse Transcriptase; Thermo Scientific). Real-time PCR was performed using a CFX96 Real-Time PCR Detection System with iTaq Universal SYBR Green Supermix (both from Bio-Rad). Ratios were calculated using the comparative CT method with β2-microglobulin (β2M) as an endogenous control. Primers used were as follows: β2M forward, 5′-CTTCAGTCGTCAGCATGGCTCG-3′; β2M reverse, 5′-GCAGTTCAGTATGTTCGGCTTCCC-3′; BAFFR forward, 5′-CTGAGGCTGCAGAGCTGTC-3′; BAFFR reverse, 5′-GGTGAGAAACTGCGTGTCCT-3′; CD40 forward, 5′-CTGCATGGTGTCTTTGCCT-3′; CD40 reverse, 5′-GCCATCGTGGAGGTACTGTT-3′; PIM2 forward, 5′-CTTTCGAGGCCGATAACCGA-3′; PIM2 reverse, 5′-GATGGCCACCTGACGTCTAT-3′; A1 forward, 5′-CCTGGCTGAGCACTACCTTCA-3′; A1 reverse, 5′-CTGCATGCTTGGCTTGGA-3′; Notch2 forward, 5′-TTCGTGTCCCCCAGGCACCC-3′; Notch2 reverse, 5′-AATCCGGTCCACGCACTGGC-3′; Deltex1 forward, 5′-CGGACATTTGAGACCCACTT-3′; Deltex1 reverse, 5′-CCACTTTCAAGGAGGGAGAA-3′; Hes1 forward, 5′-GAGAAGAGGCGAAGGGCAAGAAT-3′; and Hes1 reverse, 5′-GAGGTGACTTCACAGTCA-3′.

To allow for receptor internalization, total splenocytes were cultured in RPMI 1640 media alone or were stimulated with 0.1 μg/ml recombinant murine BAFF (R&D Systems) or 0.1 μg/ml mouse soluble CD40L (SouthernBiotech) at 37°C for 5–60 min in prewarmed media. To prevent receptor internalization and thus assess the potential impact of ligand-mediated competition with BAFFR or CD40 Ab staining, similar stimulations were performed on ice for a similar time course in prechilled media in the presence of sodium azide (0.2%). All cells were immediately washed poststimulation with ice-cold PBS in a prechilled centrifuge and incubated with fluorescently labeled B220, BAFFR, and CD40 Abs for 30 min on ice in staining buffer. After washing, cells were immediately fixed in 2% paraformaldehyde, and data were collected using an LSR II and analyzed using FlowJo software. Data are representative of two independent experiments.

The p values were calculated using the two-tailed Student t test or paired t test, where appropriate (GraphPad). Differences were considered significant when *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.

Previous in vitro stimulation studies revealed evidence for subtly enhanced BCR signaling in bulk splenic B cells isolated from Ptpn22 variant mice (7). However, this change in signaling was only evident in cells prestimulated with a TLR ligand and correlated with an upregulation in PEP expression. To assess the potential impact of BCR signaling within unmanipulated B cells in vivo, we used the Nur77-GFP–Tg reporter strain. In this model, endogenous BCR signals activate a wide spectrum of GFP expression under control of the Nur77 regulatory region, consistent with self-antigen–mediated in vivo BCR signaling (20). For these studies, we assessed Ptpn22 variant mice with a single copy of the variant crossed to the Nur77-GFP–Tg model (Ptpn22CT Nur77 Tg), because we were unable to generate pups with two transgene copies (likely as the result of coinheritance with the randomly inserted Nur77 transgene). Compared with control animals, B cells from Ptpn22CT Nur77-Tg mice exhibited a higher frequency of GFP+ cells, as well as a higher GFP mean fluorescent intensity (MFI) beginning at the immature stage in the BM and continuing in all transitional and naive B cell subsets in the periphery (Fig. 1A, Supplemental Fig. 1A). These findings suggest that the Ptpn22 variant promotes a greater proportion of self-reactive B cells to survive tolerance mechanisms and enter the periphery, consistent with an enhanced BCR signaling program mediating these events.

FIGURE 1.

Ptpn22 variant B cells exhibit enhanced Ag-mediated BCR, BAFFR, and CD40 programs. (A) The Nur77-GFP–Tg model was used to assess in vivo Ag-mediated BCR signaling. Frequency of GFP+ cells (left panel) and MFI of GFP (right panel) in specific B cell subsets in 12-wk-old Ptpn22CC Nur77 (n = 6) and Ptpn22CT Nur77 (n = 6) mice. See Supplemental Fig. 1A for representative GFP graphs and see Supplemental Fig. 2A and 2B for details of B cell subset gating. (B) Representative gating of GFPlo, GFPmid, and GFPhi (left panel) and MFI of BAFFR (middle panel) and CD40 (right panel) on combined early and late transitional cells (T1/T2) (gated B220+ CD24hi CD21lo-mid) across various GFP intensities in 15-wk Ptpn22CC Nur77 (n = 6) mice. (C) MFI of surface BAFFR (left panel) and surface CD40 (right panel) in BM CD23+ immature and splenic T2 B cells in 10–12-wk Ptpn22CC (n = 9) and Ptpn22TT (n = 9) mice. See Supplemental Fig. 2B and 2C for gating. (D) Serum BAFF levels (left panel) in 8–12 wk Ptpn22CC (n = 10) and Ptpn22TT (n = 11) mice. Surface CD40L MFI (right panel) of CD4+ naive (CD44 CD62L+) and activated (CD44+ CD62L) T cell subsets in 8–11-wk Ptpn22CC (n = 12) and Ptpn22TT (n = 12) mice. CD40L-knockout mice were used as a negative staining control. (E) Splenocytes from 10-wk-old Ptpn22CC (n = 6) mice were stimulated with soluble BAFF (0.1 μg/ml) or CD40L (0.1 μg/ml) for the indicated times at 37°C, and MFI of surface BAFFR (left panel) and surface CD40 (right panel) of B220+ cells was analyzed by FACS. Similar stimulations were performed at 4°C in the presence of sodium azide (0.2%) to prevent receptor internalization and to test for possible competition between ligand and staining Abs (Supplemental Fig. 1C). (F and G) Quantitative PCR of CD23+ immature and T2 cells sorted from 8–10-wk Ptpn22CC mice (n = 8 samples for BM, 11 samples for spleen [SPL]) and Ptpn22TT mice (n = 6 samples for BM, 11 samples for SPL). mRNA levels of BAFFR (F, left panel), CD40 (F, right panel), Pim2 (G, left panel), and A1 (G, right panel) relative to β2M. See Supplemental Fig. 2B and 2C for gating. All data are representative of at least two independent experiments. Error bars show SD. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001, Student t test. ns, not significant.

FIGURE 1.

Ptpn22 variant B cells exhibit enhanced Ag-mediated BCR, BAFFR, and CD40 programs. (A) The Nur77-GFP–Tg model was used to assess in vivo Ag-mediated BCR signaling. Frequency of GFP+ cells (left panel) and MFI of GFP (right panel) in specific B cell subsets in 12-wk-old Ptpn22CC Nur77 (n = 6) and Ptpn22CT Nur77 (n = 6) mice. See Supplemental Fig. 1A for representative GFP graphs and see Supplemental Fig. 2A and 2B for details of B cell subset gating. (B) Representative gating of GFPlo, GFPmid, and GFPhi (left panel) and MFI of BAFFR (middle panel) and CD40 (right panel) on combined early and late transitional cells (T1/T2) (gated B220+ CD24hi CD21lo-mid) across various GFP intensities in 15-wk Ptpn22CC Nur77 (n = 6) mice. (C) MFI of surface BAFFR (left panel) and surface CD40 (right panel) in BM CD23+ immature and splenic T2 B cells in 10–12-wk Ptpn22CC (n = 9) and Ptpn22TT (n = 9) mice. See Supplemental Fig. 2B and 2C for gating. (D) Serum BAFF levels (left panel) in 8–12 wk Ptpn22CC (n = 10) and Ptpn22TT (n = 11) mice. Surface CD40L MFI (right panel) of CD4+ naive (CD44 CD62L+) and activated (CD44+ CD62L) T cell subsets in 8–11-wk Ptpn22CC (n = 12) and Ptpn22TT (n = 12) mice. CD40L-knockout mice were used as a negative staining control. (E) Splenocytes from 10-wk-old Ptpn22CC (n = 6) mice were stimulated with soluble BAFF (0.1 μg/ml) or CD40L (0.1 μg/ml) for the indicated times at 37°C, and MFI of surface BAFFR (left panel) and surface CD40 (right panel) of B220+ cells was analyzed by FACS. Similar stimulations were performed at 4°C in the presence of sodium azide (0.2%) to prevent receptor internalization and to test for possible competition between ligand and staining Abs (Supplemental Fig. 1C). (F and G) Quantitative PCR of CD23+ immature and T2 cells sorted from 8–10-wk Ptpn22CC mice (n = 8 samples for BM, 11 samples for spleen [SPL]) and Ptpn22TT mice (n = 6 samples for BM, 11 samples for SPL). mRNA levels of BAFFR (F, left panel), CD40 (F, right panel), Pim2 (G, left panel), and A1 (G, right panel) relative to β2M. See Supplemental Fig. 2B and 2C for gating. All data are representative of at least two independent experiments. Error bars show SD. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001, Student t test. ns, not significant.

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Recent studies suggest that BCR signals coordinate with BAFF family receptors and CD40 to shape the mature, naive B cell repertoire (21). BCR signaling promotes the BAFFR program through modulation of receptor transcript levels (22), as well as providing p100 substrate for induction of the alternative NF-κB pathway (23). Therefore, we determined whether BCR signaling in vivo correlated with surface expression levels of BAFFR and CD40. Using the Nur77-GFP–Tg model, we found that higher GFP expression in transitional cells indeed correlates with higher expression of BAFFR and CD40 (Fig. 1B), suggesting a direct and/or indirect role for Ag-mediated BCR signaling in regulating sensitivity to these coreceptor signals.

We also compared BAFFR and CD40 surface levels across BM and splenic subsets in control Ptpn22CC mice to determine the developmental stages that are most likely to be impacted by coreceptor signals. Prior reports have identified increased levels of BAFFR on the CD23+ subset of immature BM B cells, a population making up ∼20% of all immature IgM+ cells (gated as B220+ IgM+ AA4.1+ CD23+) (21, 2326). Therefore, we adopted a similar gating strategy in the BM. As shown in Supplemental Fig. 1B, CD23+ immature BM and splenic late transitional (T2) B cells (gated as B220+ CD24hi CD21mid) expressed higher levels of BAFFR and CD40 relative to their earlier developmental counterparts. Thus, we focused our subsequent analysis of coreceptor studies on these specific subsets in control and risk variant mice.

Based on the increased BCR signal observed in Ptpn22CT Nur77-Tg mice (Fig. 1A) and correlation of BCR signal strength with coreceptor expression (Fig. 1B), we hypothesized that Ptpn22TT animals may exhibit enhanced BAFFR and/or CD40 signaling in CD23+ immature and T2 cells. Consistent with this prediction, T2 cells from Ptpn22TT mice had greater surface CD40 levels (Fig. 1C). In contrast, surface levels of BAFFR and CD40 were reduced in Ptpn22TT immature CD23+ B cells compared with controls (Fig. 1C). Because serum BAFF and surface CD40L levels on T cell subsets did not differ between control and Ptpn22TT animals (Fig. 1D), reduced receptor levels could not be explained by reduced ligand availability. Instead, a potential explanation for the paradoxical reduction in coreceptor surface levels on Ptpn22TT CD23+ immature B cells was enhanced receptor internalization. Consistent with this possibility, we demonstrated that stimulation of control splenic B cells with BAFF or soluble CD40L is sufficient to reduce surface expression levels of BAFFR or CD40, respectively (Fig. 1E, Supplemental Fig. 1C). Similar to our findings, BAFFR levels were reported to decline following ex vivo BAFF stimulation of human B cells (27). Therefore, to determine whether reduced levels of these coreceptors on risk variant BM CD23+ B cells reflected increased signaling, we assessed transcript levels using quantitative PCR in sort-purified CD23+ and T2 B cells isolated from 8–10 wk control and Ptpn22TT mice. Consistent with an enhanced coreceptor signaling program, Ptpn22TT immature and transitional cells exhibited greater levels of BAFFR and CD40 transcripts, respectively (Fig. 1F).

To more directly parse out the interconnected BCR and coreceptor signaling programs, we measured transcript levels of the alternative NF-κB pathway target Pim2, which is responsive to coreceptor signals, and the alternative and classical NF-κB pathway target A1, which is responsive to the BCR and coreceptor signals (26, 2830). Pim2 transcripts were substantially increased at both stages of development in Ptpn22TT mice (Fig. 1G), whereas A1 was significantly increased only in the periphery. Collectively, these results demonstrate that the Ptpn22 variant coordinately increases Ag-mediated BCR signaling and the BAFFR and CD40 coreceptor programs. Although enhanced BCR signals mediated by the risk variant likely impact both coreceptor programs (directly and/or indirectly) during this developmental window, our findings suggest that the variant may exert a greater role on BAFFR in the BM and on CD40 in the periphery.

The HEL and anti-HEL (MD4) BCR-Tg mouse models have been used extensively to study negative selection of self-reactive B cells (31, 32). In these studies, MD4 B cells express high-affinity BCRs specific to the neo–self-Ag HEL. Upon development in mHEL-expressing mice, MD4 B cells receive a strong BCR signal and are deleted or undergo receptor editing before entry into the periphery (33, 34). In contrast, exposure to sHEL elicits a weaker BCR signal in MD4 B cells that allows them to enter the periphery, where they exhibit features of functional anergy, including downregulation of surface IgM and an inability to secrete anti-HEL Abs (35).

To evaluate whether the Ptpn22 variant modulates deletion or anergy of self-reactive B cells, we created mixed BM chimeras using Ptpn22CC MD4-Tg or Ptpn22TT MD4-Tg mice as donors for transplantation into lethally irradiated mHEL-expressing (Fig. 2A) and sHEL-expressing (Fig. 2B) recipient mice. We found that Ptpn22TT MD4-Tg B cells developing in mHEL- or sHEL-expressing recipients exhibit comparable deletion (Fig. 2C–E, gating as in Supplemental Fig. 2D) and anergy (Fig. 2F–H) as their Ptpn22CC MD4-Tg counterparts.

FIGURE 2.

Intact negative selection of self-reactive Ptpn22 variant B cells in a high-affinity BCR-Tg model. Mixed BM chimeras using the donor MD4 (anti-HEL Ig-Tg) and (A) mHEL-expressing or (B) sHEL-expressing recipients were used to assess deletion and anergy, respectively. (CE) mHEL-expressing recipients reconstituted with Ptpn22CC MD4 BM (n = 6) or Ptpn22TT MD4 BM (n = 6) were analyzed 2–3 mo after transplant. Reconstitution of donor MD4 B cell subsets in the BM (C) and spleen (D) of mHEL-expressing recipients was analyzed by FACS. (E) HEL-specific serum Ab levels from mHEL-expressing recipients. (FH) sHEL-expressing recipients reconstituted with Ptpn22CC MD4 BM (n = 12) or Ptpn22TT MD4 BM (n = 12) were analyzed 2–3 mo after transplant. (F) Reconstitution of donor MD4 B cells in the spleen of sHEL-expressing recipients. (G) MFI of MD4 anti-HEL transgene (IgMa) in sHEL-expressing recipients, gated on B220+ splenic B cells. (H) HEL-specific serum Ab levels from sHEL-expressing recipients. See Supplemental Fig. 2D for gating. All data represent at least two independent experiments. Error bars show SD. Statistical analysis was performed using the Student t test. ns, not significant.

FIGURE 2.

Intact negative selection of self-reactive Ptpn22 variant B cells in a high-affinity BCR-Tg model. Mixed BM chimeras using the donor MD4 (anti-HEL Ig-Tg) and (A) mHEL-expressing or (B) sHEL-expressing recipients were used to assess deletion and anergy, respectively. (CE) mHEL-expressing recipients reconstituted with Ptpn22CC MD4 BM (n = 6) or Ptpn22TT MD4 BM (n = 6) were analyzed 2–3 mo after transplant. Reconstitution of donor MD4 B cell subsets in the BM (C) and spleen (D) of mHEL-expressing recipients was analyzed by FACS. (E) HEL-specific serum Ab levels from mHEL-expressing recipients. (FH) sHEL-expressing recipients reconstituted with Ptpn22CC MD4 BM (n = 12) or Ptpn22TT MD4 BM (n = 12) were analyzed 2–3 mo after transplant. (F) Reconstitution of donor MD4 B cells in the spleen of sHEL-expressing recipients. (G) MFI of MD4 anti-HEL transgene (IgMa) in sHEL-expressing recipients, gated on B220+ splenic B cells. (H) HEL-specific serum Ab levels from sHEL-expressing recipients. See Supplemental Fig. 2D for gating. All data represent at least two independent experiments. Error bars show SD. Statistical analysis was performed using the Student t test. ns, not significant.

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Although negative-selection mechanisms appeared intact in Ptpn22 variant animals, it remained possible that the subtly enhanced BCR signal in Ptpn22TT mice was masked by the high-affinity signal used in the HEL models (which express anti-HEL BCRs originally generated from post–germinal center cells). Therefore, we generated mixed BM chimeras to assess the development of Ptpn22CC and Ptpn22TT variant B cells within a competitive polyclonal setting. Congenically marked Ptpn22CC (Ly5.1), Ptpn22TT (Ly5.2), and B cell–deficient Ptpn22CC (μMT; Ly5.1/5.2) donors were mixed at a 10:10:80 ratio for transplantation into lethally irradiated Ptpn22CC (Ly5.1/5.2) recipients. The addition of μMT BM allowed us to assess the B-intrinsic effects of Ptpn22 variant expression on B cell selection, because the majority (∼90%) of all non–B cells would express wild-type Ptpn22CC, whereas B cells were mixed evenly between those expressing Ptpn22CC and Ptpn22TT (Fig. 3A).

FIGURE 3.

Competitive advantage of murine Ptpn22 variant B cells in mixed BM chimeras. (A) B cell–intrinsic Ptpn22CC and Ptpn22TT competitive BM chimeras, created by transfer of congenically marked 80% μMT BM (Ly 5.1/5.2) + 10% Ptpn22CC BM (Ly5.1) + 10% Ptpn22TT BM (Ly5.2) into lethally irradiated Ptpn22CC mice (Ly5.1/5.2). Chimeras were sacrificed 3 mo after transplant (n = 28). (B) Representative gating of B cell and splenic monocyte (B220 CD3 Gr1 CD11b+) subsets by FACS. (C) Frequency of Ptpn22CC, Ptpn22TT, and host + μMT cells in each subset. Data represent five independent experiments. See Supplemental Fig. 2A and 2B for gating. Error bars show SD. ***p < 0.001, ****p < 0.0001, Student t test. ns, not significant.

FIGURE 3.

Competitive advantage of murine Ptpn22 variant B cells in mixed BM chimeras. (A) B cell–intrinsic Ptpn22CC and Ptpn22TT competitive BM chimeras, created by transfer of congenically marked 80% μMT BM (Ly 5.1/5.2) + 10% Ptpn22CC BM (Ly5.1) + 10% Ptpn22TT BM (Ly5.2) into lethally irradiated Ptpn22CC mice (Ly5.1/5.2). Chimeras were sacrificed 3 mo after transplant (n = 28). (B) Representative gating of B cell and splenic monocyte (B220 CD3 Gr1 CD11b+) subsets by FACS. (C) Frequency of Ptpn22CC, Ptpn22TT, and host + μMT cells in each subset. Data represent five independent experiments. See Supplemental Fig. 2A and 2B for gating. Error bars show SD. ***p < 0.001, ****p < 0.0001, Student t test. ns, not significant.

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Chimeras were sacrificed at 3 mo posttransplant to evaluate the frequencies of Ptpn22CC (Ly5.1) and Ptpn22TT (Ly5.2) B cells at each stage of development. Equivalent levels of donor cell engraftment were observed in splenic monocytes based upon congenic marker expression (Fig. 3B, 3C). The Pre+Pro B cell fraction also exhibited equal contributions from each genotype, suggesting that variant expression does not alter early B cell development (Fig. 3B, 3C). In contrast, Ptpn22TT B cells exhibited a competitive advantage at the BM immature and peripheral early transitional and T2 stages (Fig. 3B, 3C). Notably, although this competitive advantage was maintained in mature FM B cells, it was lost in MZ B cells (Fig. 3B, 3C). The enhanced competition at the immature/transitional stage, followed by discrepant competition into FM versus MZ B cell compartments, is consistent with a model in which the Ptpn22 risk variant alters B cell tolerance at two discrete checkpoints in the BM and periphery.

To better understand the differential impact of Ptpn22 risk variant expression on mature B cell subsets, we decided to test whether FM or MZ cell fate was altered. Given the role that BCR signal strength has been proposed to play in determining cell fate (36), we predicted that the increased BCR signal in Ptpn22TT mice might promote a preferential bias into the FM compartment. Previous studies in Ptpn22TT mice at >12 wk of age (in a mixed 129/Sv and C57BL/6J background) revealed normal proportions of mature subsets (7), a finding that was reproduced in the current study in the C57BL/6J background (data not shown). Because the murine MZ B cell compartment is established during the initial ∼12 wk of life, we determined whether earlier assessment of splenic subsets in Ptpn22TT animals might reveal subtle differences in FM versus MZ fate. Indeed, comparing the proportions of splenic peripheral subsets at 8.5–11 wk of age, we observed a significant increase in FM cells and a concomitant decrease in the proportion of MZ precursor (MZp) cells and MZ B cells in Ptpn22TT mice compared with controls (Fig. 4A). Consistent with an alteration in Notch2-dependent signals required for MZ B cell development (37, 38), analysis of MZp cells sorted from Ptpn22TT mice at 8.5 wk of age revealed reduced Notch2 and Notch target gene transcript levels compared to controls. In addition, a reduction in Hes1 transcripts was observed in sorted T2 cells (Fig. 4B).

FIGURE 4.

Preferential selection of murine Ptpn22 variant B cells into FM cell compartment. (A) Ptpn22CC (n = 9) and Ptpn22TT (n = 10) mice (8.5–11 wk) were analyzed for splenic B cell subsets by FACS. (B) Quantitative PCR of B cell subsets sorted from 8.5-wk Ptpn22CC (n = 6) and Ptpn22TT (n = 6) mice; mRNA levels of Notch2 (left panel), Deltex1 (middle panel), and Hes1 (right panel) relative to β2M. (C) The 125-Tg (anti-insulin Ig-Tg) model was used to track insulin-specific B cells in the periphery. Ptpn22CC 125-Tg (n = 11) and Ptpn22TT 125-Tg (n = 11) mice (9–16 wk) were analyzed for total splenic B cell subsets by FACS. All data represent at least two independent experiments. See Supplemental Fig. 2B for gating. Error bars show SD. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001, Student t test. ns, not significant.

FIGURE 4.

Preferential selection of murine Ptpn22 variant B cells into FM cell compartment. (A) Ptpn22CC (n = 9) and Ptpn22TT (n = 10) mice (8.5–11 wk) were analyzed for splenic B cell subsets by FACS. (B) Quantitative PCR of B cell subsets sorted from 8.5-wk Ptpn22CC (n = 6) and Ptpn22TT (n = 6) mice; mRNA levels of Notch2 (left panel), Deltex1 (middle panel), and Hes1 (right panel) relative to β2M. (C) The 125-Tg (anti-insulin Ig-Tg) model was used to track insulin-specific B cells in the periphery. Ptpn22CC 125-Tg (n = 11) and Ptpn22TT 125-Tg (n = 11) mice (9–16 wk) were analyzed for total splenic B cell subsets by FACS. All data represent at least two independent experiments. See Supplemental Fig. 2B for gating. Error bars show SD. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001, Student t test. ns, not significant.

Close modal

Although these polyclonal studies suggested widespread selection bias, these data did not assess whether self-reactive B cells in particular were affected. To track the selection of B cells with self-reactivity relevant to an autoimmune disorder associated with the PTPN22 risk variant, we crossed Ptpn22TT mice to the 125-Tg model. In this model, ∼95% of peripheral B cells express a fixed H and L chain (identified as IgMa+ by FACS) and are insulin reactive (39). Using FACS analysis of splenic B cell subsets, we found that Ptpn22TT 125-Tg mice similarly exhibited a marked reduction in the proportion of insulin-reactive MZ B cells, as well as a subtle (although not statistically significant) increase in FM B cells, compared with controls (Fig. 4C). Taken together with data demonstrating skewed mature compartments in a polyclonal setting, these findings support the idea that variant protein expression promotes Ag-mediated selection of self-reactive peripheral B cells, biasing their entry into the FM over MZ compartment.

Given the enhanced positive selection and differential selection of transitional cells into the FM and MZ compartments in Ptpn22TT mice, we hypothesized that these findings might correlate with skewing of the naive repertoires. Therefore, we performed a detailed assessment of the naive repertoire of Ptpn22TT mice using combined approaches: high throughput sequencing (HTS) of the BCR HC and single-cell BCR cloning and assessment of BCR self-reactivity.

We first sought to validate IgH HTS as an appropriate platform for reading out distinct CDR3 profiles between FM and MZ subsets. Although useful in many respects, prior sequencing studies have been limited by their restriction to a single VH family, gating strategies that included transitional cells, and/or analysis restricted to the BALB/c background (4042). To expand on these findings, we bulk sorted FM and MZ B cells from wild-type Ptpn22CC mice on the C57BL/6 background for HTS of the IgH locus (obtaining a total of 120,805–142,910 productive sequences for each sample; Supplemental Table I). Our studies revealed broadly altered differences in CDR3 length and composition among mature, naive FM, and MZ subsets (Fig. 5). Consistent with published data, we found that MZ B cells had increased usage for JH2 family (Fig. 5A), shorter average CDR3s (Fig. 5B), a greater proportion of CDR3s lacking N nucleotides (Fig. 5C), and slightly reduced hydrophobicity (Fig. 5D) compared with FM cells. This high-throughput approach further revealed novel differences, including broadly altered VH family (Fig. 5E) and amino acid usage (Fig. 5F) between subsets, decreased N2 insertions (Fig. 5G), and reduced diversity (Fig. 5H) in MZ cells. Notably, we found no difference in charged amino acid usage between subsets (data not shown), in contrast to prior studies (40, 42).

FIGURE 5.

HTS reveals broadly altered CDR3 characteristics between murine FM and MZ subsets. FM and MZ cells were sorted from 11–14-wk Ptpn22CC mice (n = 4 per subset) for high-throughput BCR IgH chain sequencing. Nonproductive templates were excluded from analysis. (A) JH family usage. (B) CDR3 length. (C) Templates lacking N insertions (between both V-D and D-J junctions). (D) Hydrophobic amino acids (includes F, I, W, L, V, M, Y, C, A). (E) VH family usage. (F) Amino acid usage. (G) N2 insertions (between D-J junction). (H) Diversity index. See Supplemental Fig. 2B for gating. See Supplemental Table I for numbers of sequences analyzed. Data represent two independent experiments. Error bars show SD. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001, Student t test.

FIGURE 5.

HTS reveals broadly altered CDR3 characteristics between murine FM and MZ subsets. FM and MZ cells were sorted from 11–14-wk Ptpn22CC mice (n = 4 per subset) for high-throughput BCR IgH chain sequencing. Nonproductive templates were excluded from analysis. (A) JH family usage. (B) CDR3 length. (C) Templates lacking N insertions (between both V-D and D-J junctions). (D) Hydrophobic amino acids (includes F, I, W, L, V, M, Y, C, A). (E) VH family usage. (F) Amino acid usage. (G) N2 insertions (between D-J junction). (H) Diversity index. See Supplemental Fig. 2B for gating. See Supplemental Table I for numbers of sequences analyzed. Data represent two independent experiments. Error bars show SD. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001, Student t test.

Close modal

Armed with an ability to read out distinct CDR3 profiles between mature FM and MZ subsets using IgH HTS, we next expanded our sequencing studies to include FM and MZ subsets sorted from Ptpn22TT mice (obtaining a total of 119,459–142,910 productive sequences for each sample; Supplemental Table I). Surprisingly, we found that the CDR3 profiles in naive subsets derived from Ptpn22 variant mice did not differ markedly from controls. We identified only minor differences in VH usage and N1 insertions in Ptpn22CC versus Ptpn22TT MZ B cells (Fig. 6). Thus, although an HTS approach was suitable for identifying unique CDR3 characteristics between FM and MZ B cells, it was for the most part unable to detect any impact of the Ptpn22 variant on the BCR repertoire.

FIGURE 6.

Control and murine Ptpn22 variant FM and MZ B cells exhibit indistinguishable IgH CDR3 profiles. FM and MZ subsets were FACS sorted from 11–14-wk Ptpn22CC (n = 4) and Ptpn22TT (n = 4) mice for high-throughput BCR IgH chain sequencing. Nonproductive templates were excluded from analysis. FM VH (A) and FM JH (B) family usage. MZ VH (C) and MZ JH (D) family usage. (E) CDR3 length. (F) N1 insertions (between V-D junction). See Supplemental Fig. 2B for gating. See Supplemental Table I for numbers of sequences analyzed. Data represent two independent experiments. Error bars show SD. *p < 0.05, Student t test.

FIGURE 6.

Control and murine Ptpn22 variant FM and MZ B cells exhibit indistinguishable IgH CDR3 profiles. FM and MZ subsets were FACS sorted from 11–14-wk Ptpn22CC (n = 4) and Ptpn22TT (n = 4) mice for high-throughput BCR IgH chain sequencing. Nonproductive templates were excluded from analysis. FM VH (A) and FM JH (B) family usage. MZ VH (C) and MZ JH (D) family usage. (E) CDR3 length. (F) N1 insertions (between V-D junction). See Supplemental Fig. 2B for gating. See Supplemental Table I for numbers of sequences analyzed. Data represent two independent experiments. Error bars show SD. *p < 0.05, Student t test.

Close modal

One possible explanation, supported by our polyclonal studies (Figs. 3, 4), is that the Ptpn22 variant impacts a broad range of BCR specificities, leading to a setting in which individual CDR3 features might appear largely unchanged. Differences that may exist in a subpopulation, such as in self-reactive cells, could be lost in a high-throughput approach. Therefore, we next turned to single-cell BCR cloning for a more targeted assessment of the naive repertoire. Using established methods (16, 19), BCRs were cloned from single FM and MZ cells sorted from Ptpn22CC and Ptpn22TT mice, producing a total of 273 recombinant mAbs. We assessed Ag specificity using ELISAs for a range of self-antigens, including insulin, MDA-LDL, dsDNA, PC-12, and smRNP. Strikingly, for each self-antigen tested, the proportion of Ptpn22TT mAbs considered reactive (reaching an OD threshold >0.5) was approximately doubled in FM cells. In striking contrast, we observed the opposite impact in MZ B cells: the proportion of Ptpn22TT mAbs considered reactive was reduced nearly in half compared with control mAbs (Fig. 7; ELISA curves in Supplemental Fig. 1D, 1E). The proportions of polyreactive clones exhibited similar differential skewing, with higher and lower proportions found in the FM and MZ compartments, respectively, of variant mice (Fig. 7). As predicted by our tolerance studies, we conclude that Ptpn22 variant mice exhibit a subset-specific skewing of the naive repertoire, with a preferential bias for self-reactive BCRs within the FM compartment over the MZ compartment.

FIGURE 7.

Ptpn22 variant mice exhibit an increased proportion of self-reactive FM B cells but fewer self-reactive MZ B cells. FM and MZ cells were FACS sorted from 8–12-wk Ptpn22CC (n = 5) and Ptpn22TT (n = 5) mice for single-cell BCR cloning of mAbs (n = 70 Ptpn22CC FM, n = 71 Ptpn22TT FM, n = 67 Ptpn22CC MZ, n = 65 Ptpn22TT MZ mAbs). Proportions of FM (A) and MZ (B) mAbs reactive to self-antigens (insulin, MDA-LDL, dsDNA, PC-12, smRNP) or polyreactive (reactive to three or more of above self-antigens) by ELISA assay. See Supplemental Fig. 2B for gating and Supplemental Fig. 1D and 1E for ELISA curves. Data represent two independent experiments.

FIGURE 7.

Ptpn22 variant mice exhibit an increased proportion of self-reactive FM B cells but fewer self-reactive MZ B cells. FM and MZ cells were FACS sorted from 8–12-wk Ptpn22CC (n = 5) and Ptpn22TT (n = 5) mice for single-cell BCR cloning of mAbs (n = 70 Ptpn22CC FM, n = 71 Ptpn22TT FM, n = 67 Ptpn22CC MZ, n = 65 Ptpn22TT MZ mAbs). Proportions of FM (A) and MZ (B) mAbs reactive to self-antigens (insulin, MDA-LDL, dsDNA, PC-12, smRNP) or polyreactive (reactive to three or more of above self-antigens) by ELISA assay. See Supplemental Fig. 2B for gating and Supplemental Fig. 1D and 1E for ELISA curves. Data represent two independent experiments.

Close modal

The increased self-reactivity of the FM compartment in Ptpn22TT mice closely mirrors the increase in self-reactivity observed in circulating naive B cells of healthy human subjects with the PTPN22 risk variant (11). In an effort to better understand the signaling events that drive the selection of autoreactive B cells in PTPN22 variant carriers, we turned to a flow-based assay that uses tracking of a self-reactive HC. We chose the VH4–34 family as a candidate for study because of its well-documented polyreactivity toward a range of self-antigens, including B cells, RBCs, and dsDNA (4345), as well as its relatively high frequency within the transitional and naive mature B cell compartments in healthy subjects. In addition, previous work from our laboratory and that of other investigators has documented enrichment of VH4–34 family–expressing transitional and mature B cells in autoimmune settings, which is thought to be driven through modulations in dual BCR and TLR signals (18, 46). Based on these previous studies, we anticipated that healthy PTPN22 risk variant carriers might exhibit an increased proportion of VH4-34+ B cells (as detected by the anti-idiotypic mAb 9G4), as would be consistent with a naive repertoire skewed toward autoreactivity prior to disease development. Surprisingly, in contrast to this prediction, we found that healthy PTPN22 risk subjects had fewer 9G4+ B cells across all peripheral blood compartments compared with healthy nonrisk controls, including most notably within the transitional subset (Fig. 8A, 8B, cells gated as in Supplemental Fig. 2E).

FIGURE 8.

Healthy subjects with the PTPN22 risk variant exhibit broadly enhanced positive selection. (A and B) PBMCs from age- and sex-matched healthy subjects screened for PTPN22 1858 C/C (n = 34), C/T (n = 34), and T/T (n = 3) genotypes were analyzed by FACS for VH4–34 family (9G4+) B cells. (A) Representative graphs quantifying 9G4+ B cells. (B) Percentage of 9G4+ cells across peripheral B cell subsets. PBMCs from age- and sex-matched healthy subjects screened for PTPN22 1858 C/C (n = 18) and C/T (n = 18) genotypes were analyzed by FACS for surface BAFFR MFI of total B cells (C) and 9G4 and 9G4+ gated B cells (D). See Supplemental Fig. 2E for gating. See Supplemental Table II for subject information. All data represent at least two independent experiments. Error bars show SD. *p < 0.05, **p < 0.01, ***p < 0.001, Student t test (B), paired t test (C). ns, not significant.

FIGURE 8.

Healthy subjects with the PTPN22 risk variant exhibit broadly enhanced positive selection. (A and B) PBMCs from age- and sex-matched healthy subjects screened for PTPN22 1858 C/C (n = 34), C/T (n = 34), and T/T (n = 3) genotypes were analyzed by FACS for VH4–34 family (9G4+) B cells. (A) Representative graphs quantifying 9G4+ B cells. (B) Percentage of 9G4+ cells across peripheral B cell subsets. PBMCs from age- and sex-matched healthy subjects screened for PTPN22 1858 C/C (n = 18) and C/T (n = 18) genotypes were analyzed by FACS for surface BAFFR MFI of total B cells (C) and 9G4 and 9G4+ gated B cells (D). See Supplemental Fig. 2E for gating. See Supplemental Table II for subject information. All data represent at least two independent experiments. Error bars show SD. *p < 0.05, **p < 0.01, ***p < 0.001, Student t test (B), paired t test (C). ns, not significant.

Close modal

One possible explanation for the reduced frequency of 9G4+ B cells in PTPN22 risk variant subjects, supported by our murine studies, is that globally enhanced positive selection across multiple specificities might reduce the relative proportion of BCRs using this specific HC family. In partial support of this idea, CD40 levels and signaling activity were previously reported to be increased in PTPN22 risk variant subjects (11). To test whether BAFFR levels were similarly increased and might reflect events similar to our observations in the murine model, we next compared surface BAFFR levels in PTPN22 nonrisk and risk subjects. Strikingly, the MFI of BAFFR expression was increased in all peripheral B cell subsets in risk subjects (Fig. 8C). The elevated BAFFR levels in risk subjects were unlikely to reflect differences in available cytokine, because we have previously reported that nonrisk and risk subjects exhibit similar serum levels of BAFF (10) However, it remained possible that the reduced frequency of self-reactive 9G4+ B cells in risk subjects might reflect an impaired ability to compete for available BAFF. To test for this possibility, we compared surface BAFFR levels among 9G4+ (representing predominantly self-reactive BCRs) or 9G4 (representing a more heterogeneous population) peripheral B cell subsets in nonrisk and risk subjects. Strikingly, relative to nonrisk subjects, PTPN22CT subjects exhibited a global increase (or trend for increase) in BAFFR levels across all populations, including 9G4 and 9G4+ cells within the transitional, naive, and IgM memory B cell compartments (Fig. 8D). Overall, these data imply that, in risk subjects, BCR and/or other coordinate signals promote increased BAFFR expression, thereby permitting such cells to compete more effectively for BAFF family survival and differentiation signals.

Our findings in the Ptpn22TT murine models indicate that, although negative selection mechanisms are intact, enhanced BCR and/or coreceptor signaling programs promote increased positive selection of transitional B cells (including cells with a range of self-reactive specificities) into the FM B cell compartment. Moreover, the counterselection of VH4-34+–expressing cells in human carriers, coupled with global increases in BAFFR and CD40 coreceptor expression described in this article and in a previous study (11), respectively, support a similar role for the risk variant in human B cell selection. Our combined datasets imply that the risk variant facilitates a subtle, yet widespread, increase in positive selection signaling programs throughout BM and transitional B cell development. These combined events ultimately allow for a broader range of autoreactive B cells to compete for survival into the mature naive B cell compartment. Although additional work is required to definitively assess the specific biochemical impact(s) of the PTPN22 C1858T variant on BCR and/or coreceptor signaling pathways in developing B cells, our findings strongly suggest that similar mechanisms alter central and peripheral B cell tolerance in murine and human immune development.

As described earlier, multiple studies in murine models and human subjects support the idea that the PTPN22 variant alters B cell–tolerance mechanisms (7, 10, 11). However, it remained unknown whether this defect was B cell intrinsic. To eliminate the potential impact of disrupted T cell tolerance and homeostasis present in Ptpn22 variant mice and human subjects (7, 12, 47), our BM chimera studies restricted variant expression predominantly to B cells. Our finding that Ptpn22TT-expressing B cells exhibit a competitive advantage at key developmental checkpoints in the BM and periphery highlights the importance of B cell–intrinsic signaling pathways in regulating these events. Consistent with this, we found an identical competitive advantage for variant-expressing B cells in competitive chimeras depleted of CD4 T cells (data not shown).

To better address the key question regarding how the Ptpn22 risk variant alters BCR signaling in murine B cells, we used the newly described Nur77-GFP model (20). This model has the advantage of permitting assessment of BCR signaling directly ex vivo at discrete stages of B cell development. Our results indicate that risk variant expression promotes a greater proportion of B cells to survive tolerance mechanisms throughout development; this is mediated, in part, through stronger BCR signals. Taken as a whole, these data provide compelling evidence that the Ptpn22 variant modulates key survival programs that are dependent upon BCR signals in vivo and that engagement with self-antigen in the periphery can promote these events.

Although BCR signaling serves as a master regulator of B cell tolerance, its synergy with key coreceptor pathways, predominantly BAFFR and CD40, ultimately determines the developmental fate of a given B cell (21, 48). Each of these coreceptor pathways, in turn, plays an important role in promoting positive selection in the periphery (1316). In addition, a growing body of work, including our own, suggests that they serve a similar function in the BM (16, 23, 25, 49). Our finding that Ptpn22TT mice exhibit slightly augmented BCR and coreceptor signals is consistent with subtle signaling changes whereby the variant promotes greater positive selection throughout immature and naive B cell development.

Although the complexity of receptor cross-talk (21) prevented us from fully dissecting the relative contributions of the BCR and coreceptor signals in mediating selection, our studies demonstrate how subtle fluctuations in these signaling networks can influence the mature repertoire, and they may do so in distinct ways. For instance, the enhanced positive selection observed in Ptpn22 risk variant mice differs from other autoimmune settings. Unlike models in which a Tg self-reactive BCR (50) or a specific self-reactive BCR family (18) facilitates positive selection at the T2 stage via clonal expansion, the Ptpn22 risk variant impacts a broad range of BCR specificities during BM and splenic transitional B cell development, allowing multiple self-reactive B cells to compete for BAFF and CD40L signals. Thus, although highly specific VH family skewing is evident in mice and humans with defects in the Wiskott–Aldrich syndrome gene, an autoimmune setting of augmented BCR and TLR signals (18), we did not observe major differences in IgH CDR3 profiles or VH family use in Ptpn22TT mature B cells. We further propose that the broad impact of the Ptpn22 variant limited the relative expansion of individual (including self-reactive) VH families. Although the implication of these subtle distinctions in dual BCR/TLR versus BCR/BAFFR/CD40-mediated positive selection in distinct models remains to be determined (including implications likely beyond autoimmunity), they nevertheless illustrate the usefulness of our integrated approach in assessing the naive repertoire.

This integrated approach also helped us to identify an unexpected bias for selection into the FM compartment of Ptpn22TT mice, including of several self-reactive specificities. Several lines of evidence led to this idea. First, a larger proportion of FM cells relative to MZ cells was observed in polyclonal and insulin-specific Ptpn22TT murine models, and MZp cells exhibited a significant decrease in Notch2 expression and in Notch target gene transcripts. Second, and consistent with a preferential bias for selection into the FM compartment, our single-cell BCR-cloning studies revealed an increased proportion of self-reactive and polyreactive BCRs within the FM compartment. In parallel, we observed the opposite finding in the MZ, with decreases in self-reactive and polyreactive specificities in individual MZ B cells. These observations support the conclusion that the Ptpn22 risk variant skews the naive FM B cell compartment toward self-reactivity, while revealing an additional novel role for restricting MZ development and/or fate. Although the mechanistic basis for these surprising observations with respect to MZ B cell development remains unclear, these findings align with recent studies in which BCR and Notch2 signaling exhibit cross-talk that critically regulates MZ lineage commitment (51).

Notably, although we were unable to directly study human splenic B cell subsets, we made progress in translating our murine findings to human subjects. Our observations provide an alternative interpretation of the prevailing model for how the PTPN22 variant impacts human B cell development. As noted above, previous human studies suggest that PTPN22 C1858T carriers exhibit an attenuated BCR signal, promoting relaxed negative selection and subsequent enrichment of self-reactive B cells within the naive compartment (10, 11, 52, 53). Interestingly, these previous studies have proposed that hyporesponsive BCR signals in risk subjects leads to increased numbers of self-reactive new emigrant (transitional) B cells (10, 53) and a seemingly paradoxical aberrant activation of these cells, as demonstrated by elevated BCR target genes involved in cell activation, proliferation, and survival (11). Most notably, previous work described higher levels of CD40 transcripts and expression and increased CD40 signaling in risk variant new emigrant B cells (11). Thus, although the interpretation differs from our conclusions, these earlier findings indicate that healthy subjects with the risk allele exhibit an increase in the CD40 coreceptor program in transitional B cells. Consistent with these observations, our murine studies revealed intact negative selection and evidence for augmented BCR and/or BAFFR and CD40 coreceptor signals in Ptpn22 variant mice, leading to broadly enhanced positive selection and preferential skewing for several self-reactive specificities into the FM compartment. Thus, although the end result appears the same, explanations for how a greater proportion of self-reactive B cells enters the naive repertoire differ with respect to previous human and our current murine studies.

As a means to begin to test whether our findings of broadly enhanced positive selection in murine models also applied to human carriers, we used a flow-based assay to track the selection of a polyreactive VH family in peripheral blood (VH4–34; identified as 9G4+) (46). Our observation that healthy PTPN22 variant subjects had fewer 9G4+ B cells, yet exhibited increased BAFFR levels in all peripheral B subsets, including 9G4+ and 9G4 cell populations, is most consistent with a model in which positive selection is globally enhanced, thereby reducing the relative contribution of this single family VH family. Finally, an additional (but not mutually exclusive) interpretation for the reduced proportion of 9G4+ B cells in PTPN22 carriers is that this may reflect impaired MZ fate/development, an untested, yet intriguing, possibility given our murine findings of impaired Notch2 signaling, as well as the presumed enrichment of 9G4+ B cells into an MZ-like B cell subset within human peripheral blood (18, 46).

In summary, our collective murine and human data provide an alternative model for how the PTPN22 C1858T variant promotes self-reactivity into the naive B cell repertoire and, consequently, is likely to increase the probability of triggering autoimmune B cell responses in at-risk individuals. Our studies highlight the importance of synergistic BCR and coreceptor signaling pathways in regulating these events and, in doing so, identifies novel pathways for future study.

We thank J. Thomas for providing 125-Tg mice, A. Weiss for Nur77-GFP–Tg mice, D. Hamm (Adaptive Biotechnologies) for expert assistance with sequencing analysis, and S. Khim and K. Sommer for animal and technical assistance. In addition, we thank the Benaroya Research Institute Clinical Core and subjects that participated in the Benaroya Research Institute Immune-Mediated Disease Biorepository.

This work was supported by National Heart, Lung, and Blood Institute, National Institute of Diabetes and Digestive and Kidney Diseases, and National Institute of Allergy and Infectious Diseases (National Institutes of Health) Grants R01HL075453, R01A1084457, R01A1071163, and DP3DK111802 (to D.J.R.), DP3DK097672 (to D.J.R. and J.H.B.), and DP3DK097672-01S1 (to G.M.). Additional support was provided by the Benaroya Family Gift Fund (to D.J.R.) and a Howard Hughes Medical Institute/National Institutes of Health Molecular Medicine Training Grant (to G.M.).

The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

The online version of this article contains supplemental material.

Abbreviations used in this article:

     
  • BAFF

    B cell–activating factor

  •  
  • BAFFR

    B cell–activating factor receptor

  •  
  • BM

    bone marrow

  •  
  • FM

    follicular mature

  •  
  • HC

    H chain

  •  
  • HEL

    hen egg lysozyme

  •  
  • HTS

    high-throughput sequencing

  •  
  • β2M

    β2-microglobulin

  •  
  • MDA-LDL

    malondialdehyde-modified low-density lipoprotein

  •  
  • MFI

    mean fluorescent intensity

  •  
  • mHEL

    membrane-bound hen egg lysozyme

  •  
  • μMT

    IgM deficient

  •  
  • MZ

    marginal zone

  •  
  • MZp

    MZ precursor

  •  
  • PC

    phosphorylcholine

  •  
  • PTPN22/Ptpn22

    protein tyrosine phosphatase nonreceptor type 22

  •  
  • sHEL

    soluble hen egg lysozyme

  •  
  • smRNP

    Smith and nuclear ribonucleoprotein

  •  
  • T2

    late transitional.

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DOI: 10.1126/sciimmunol.aaf7153.

The authors have no financial conflicts of interest.

Supplementary data