Preventing inappropriate immune responses is critical to the maintenance of peripheral tolerance and the prevention of autoimmunity. The risk of autoimmunity stems from a complex interplay of genetic and environmental factors (Theofilopoulos et al., 2017; Cho and Feldman, 2015). While the greatest risk factor for most autoimmune disease is HLA haplotype (Todd et al., 2007; Bonifacio et al., 2018), an individual’s total genetic risk is determined by a combination of gene variants (Sharma et al., 2018; Cotsapas et al., 2011), many of which cluster near genes responsible for regulating immune responses (Farh et al., 2015). A leading example of such an autoimmune risk variant is found in the gene protein tyrosine phosphatase non-receptor 22 (PTPN22).

While the phosphatase encoded by PTPN22 can function to modulate a range of immune signaling programs, it has been best studied in lymphocyte antigen receptor regulation (Cohen et al., 1999; Wu et al., 2006; Hill et al., 2002). An arginine to tryptophan substitution (R620W) resulting from a single nucleotide polymorphism (SNP; rs2476601) within PTPN22 is broadly associated with a large number of autoimmune diseases (Zheng et al., 2012; Tizaoui et al., 2019). PTPN22 R620W, hereafter referred to as the PTPN22 risk variant, is one of the strongest, non-HLA, genetic risk factors for autoimmune diseases, nearly doubling a carrier’s risk of type 1 diabetes, systemic lupus erythematosus, or rheumatoid arthritis (Bottini et al., 2004; Begovich et al., 2004; Kyogoku et al., 2004). As PTPN22 plays a role in multiple autoimmune diseases, it has been argued that this SNP potentially highlights a common pathway that alters immune tolerance and might serve as a potential point of intervention to prevent and/or delay disease (Rawlings et al., 2015).

In T cells, PTPN22 functions to dephosphorylate key activating tyrosine residues within the proximal tyrosine kinase effectors, LCK and ZAP70, in the TCR signaling pathway (Wu et al., 2006; Bottini et al., 2004). This function is mediated in concert with activity through PTPN22’s binding partner, C-terminal Src kinase (CSK), which also regulates LCK activity (Cloutier and Veillette, 1999). Co-association of PTPN22 and CSK results in residence of both proteins within the cytosolic plasma membrane of resting T cells through the association of CSK with another TCR inhibitory protein, PAG (Davidson et al., 2016; Simoncelli et al., 2020). The R620W substitution in PTPN22 is located within a proline rich, C-terminal domain and reduces the interaction of PTPN22 with CSK leading to altered localization of PTPN22 (Bottini et al., 2004). The functional outcome of disrupted PTPN22 protein interactions has led to significant debate as to the mechanism by which the PTPN22 risk variant contributes to altered T cell function and self-tolerance, namely whether the human PTPN22 risk variant mediates a gain- vs. a loss-of-function impact on TCR regulation.

Primary T cells isolated from carriers of the PTPN22 risk variant display significantly weaker responses to TCR engagement, as measured by calcium flux, cytokine release, and other metrics (Rieck et al., 2007; Vang et al., 2005; Arechiga et al., 2009; Vang et al., 2013). However, in murine models, expression of the risk variant leads to enhanced TCR responses, as measured by the same metrics in addition to increased T cell proliferation and survival (Zhang et al., 2011; Dai et al., 2013; Lin et al., 2016). In contrast, genetic ablation of PTPN22 in both mouse and human primary T cells results in enhanced TCR signaling relative to PTPN22 wild type cells; findings similar to murine risk model yet opposite of the phenotypes described in human carriers of the risk variant (Hasegawa et al., 2004; Anderson et al., 2019). Furthermore, genetic ablation of ptpn22 in a fixed TCR murine model has shown that loss of PTPN22 preferentially impacts T cells responses to low-avidity antigens, but not high-avidity antigens (Salmond et al., 2014); driving increased proliferation and skewing toward a Th1 phenotype in ptpn22 KO T cells. While these observations suggest an important potential mechanism for how the PTPN22 risk variant promotes autoimmunity, this concept has not been tested in primary human T cells.

Both human carriers and murine models of the PTPN22 risk variant share important traits. For instance, the risk variant is associated with an increase in memory lymphocyte populations and expanded pro-inflammatory/Th1 T cells and both exhibit increased risk of autoimmune manifestations (Vang et al., 2013; Dai et al., 2013; Sanchez-Blanco et al., 2018). Thus, it remains surprising that murine and human carriers exhibit these key similarities despite the published differences in the TCR signaling responses described human vs. mouse T cells. Notably, the murine and human T cell populations used for previous studies exhibit fundamental differences. First, most data for human PTPN22 risk variant phenotype have utilized mature T cells isolated from adult donors, while T cells from murine studies utilize donor mice with minimal environmental exposures. Studies of PTPN22 using human cord blood-derived T cells have been limited (Rawlings et al., 2015). Also, murine models of the ptpn22 risk variant are conducted in genetically homogenous, autoimmune-prone strains or models with a fixed TCR repertoire (Dai et al., 2013; Lin et al., 2016; Salmond et al., 2014; Maine et al., 2016), conditions difficult to mimic in a primary human T cell setting. Further, in vitro human T cell line models of the PTPN22 risk variant lead to discrepant results, indicating that the impact(s) of the variant are context dependent, further complicating efforts to study the variant in human T cells (Vang et al., 2005; Zikherman et al., 2009).

Recently, Crispr/Cas9 gene editing has allowed for precise manipulation of genetic loci in primary human T cells. Delivery of recombinant ribonucleoproteins (RNPs [Anderson et al., 2019; Schumann et al., 2015; Okamoto et al., 2019] containing Cas9 complexed with sequence specific guide RNA sequences) via electroporation into primary T cells efficiently mediates site-specific DNA double stranded breaks (DSBs) near a protospacer adjacent motif (PAM) site (Jinek et al., 2012). Such DNA breaks trigger a series of events driving 5’ to 3’ exonuclease activity at the broken DNA ends as the cell prepares to mend the break through potential repair pathways (Scully et al., 2019; Xue and Greene, 2021). When DSBs are generated in the presence of a single stranded oligo deoxynucleotides (ssODNs) (co-delivered with RNP), DNA repair pathways can utilize regions of homology within an ssODN as a repair template for precise genetic modification by homology directed repair (HDR) (Richardson et al., 2016; Richardson et al., 2018). This approach has previously been used to integrate a premature stop codon in the PTPN22 locus of primary human T cells with high efficiency (Anderson et al., 2019).

In this study, we utilized a combination of HDR-based gene editing and TCR co-delivery in naïve cord blood T cells to establish a platform to better understand the role of the PTPN22 risk variant in primary human T cells. Through Crispr/Cas9 gene editing we find the PTPN22 risk variant T cells mimicked PTPN22 KO T cells, with enhanced expression of surface activation markers in response to TCR stimulation. Further, using transgenic TCR stimulation in concert with gene edited cells, we found that the PTPN22 risk variant accentuates the response of low-avidity primary human T cells to antigen, implying a key role for these events in the progressive loss of T cell tolerance in human autoimmune diseases associated with this risk allele.

In this paper we utilized a robust gene editing platform in primary human cord blood CD4 T cells to efficiently alter PTPN22 non-risk T cells to express the PTPN22 R620W risk variant as well as relevant control, non-risk, or KO edited cell populations. This gene editing approach should be applicable to many cell types and broadly applicable to study the impact of candidate disease associated alleles (identified by GWAS or other sequencing strategies) within primary human cell populations. Notably, our data clearly demonstrate that PTPN22 risk variant expressing T cells exhibit a phenotype similar to PTPN22 KO T cells, leading to increased expression of TCR induced activation responses markers. Further, using transgenic TCR delivery and cognate peptide-mediated activation, in tandem with our gene editing platform, we show that PTPN22 deficiency predominantly impacts T cells activated in response to low-avidity TCR engagement. In contrast, PTPN22 function is largely dispensable in T cells receiving a high-avidity TCR signal. Together, these data suggest that the PTPN22 risk variant may contribute to autoimmune responses, at least in part, by selectively expanding the pool of lower avidity, self-reactive T cells and skewing such cells toward a pro-inflammatory phenotype. Our findings are consistent with previous work in a fixed TCR murine model that also found loss of ptpn22 to preferentially impact low-avidity TCR stimulation (Salmond et al., 2014). Importantly, our study models function of the PTPN22 regulatory pathway in a fully human gene edited primary cell setting.

Our editing platform utilizes a designer nuclease that generates a dsDNA break in close proximity to the target site for HDR editing. This combined approach allows for: (a) generation of edited cells with high rates of HDR; (b) equivalent HDR rates for alternative coding changes within the target gene via use of a series of ssODN donors; and (c) achieving editing outcomes while controlling for the overall HDR/NHEJ ratio. An additional strength is that the location and small editing footprint allows for physiological expression via use of the endogenous promoter, local enhancers, and 3’ UTR. Also, editing in this location is unlikely to disrupt the formation of natural PTPN22 splice variants. Of note, PTPN22 risk and non-risk ssODNs, while producing identical HDR rates, demonstrated reduced HDR relative to editing using the PTPN22 KO ssODN. This modest difference likely reflects the requirement to replace endogenous nucleotides immediately 5’ and 3’ to the DNA cut site to achieve risk or non-risk edits, while the KO ssODN only required insertion of new nucleotides. These minor differences aside, our editing platform should be readily adaptable for the study of multiple loci across the genome in future studies of human primary cell populations.

We demonstrate that expression of the PTPN22 risk variant can increase proliferation of primary human T cells expressing a low-avidity TCR, findings that mimic PTPN22 KO T cells. Furthermore, we show that loss of PTPN22 regulation promotes the development of a pro-inflammatory phenotype in T cells using a low-avidity TCR. These combined findings are consistent with in vivo functional impacts observed in human and mouse studies. Indeed, while previous human data and mouse models have led to contradictory conclusions regarding the impact of the risk variant on proximal TCR signaling, both humans and mice with the PTPN22 risk variant exhibit expanded memory T cell and Th1 populations (Rieck et al., 2007; Vang et al., 2013; Dai et al., 2013; Salmond et al., 2014). Importantly, PTPN22 is expressed in multiple immune and hematopoietic subsets and has been shown to have multiple functions (Rawlings et al., 2015; Stanford and Bottini, 2014; Armitage et al., 2021). Therefore, our dataset informs on a single signaling program and PTPN22 may contribute to autoimmune disease via other pathways.

While our editing design provides a useful means to address questions related to TCR engagement, this approach has limitations including assessing early intracellular signaling events. While gene edited cells exhibited proximal phosphorylation changes in response to antibody-based stimulation, biochemical changes were not detected until 24 hr post peptide-based stimulation. Future work may find a path around this technical challenge allowing better insight into early signaling events. Also, while our findings provide an important bridge between inconsistencies connecting PTPN22 to autoimmune risk in previous mouse vs. primary human cell data, it should not be viewed as a replacement for mouse models. Our study relies on ex vivo culturing of T cells, outside of optimal physiological conditions and supportive niches, features that may have key impacts on protein tyrosine phosphatase functions. Also, though our gene KO model reached 100% as measured by ddPCR, western quantification data (Figure 1E) may suggest residual expression of PTPN22, a consideration not of relevant for mouse models. Finally, as our model is restricted to peripheral mature T cells, it is inadequate to assess the role for PTPN22 in T cell development. For example, while mouse models suggest that the PTPN22 risk variant alters thymic selection (Dai et al., 2013) others have shown that PTPN22 KO has no impact on the TCR repertories (Hasegawa et al., 2004; Salmond et al., 2014; Sanchez-Blanco et al., 2018; Maine et al., 2012). Because our study shows the risk variant functions similarly in human T cells in comparison with published murine models, it suggests that returning to these models to investigate specific contexts where PTPN22 might impact selection and tolerance is likely to be informative and critical for full understanding of this variant.

While T cells expressing a lower avidity TCR were primarily impacted in our studies, we cannot eliminate potential alternative impacts of the TCRs studied in our models. The TCRs evaluated exhibited distinct differences in both EC₅₀ (Linsley et al., 2021) and triggered proliferative response to an identical IGRP derived peptide (Figure 3C; Linsley et al., 2021). However, while these data points support a working hypothesis of TCR avidity determining the functional impact, we cannot rule out the role for possible differences in TCR disassociation rates and/or overall duration of TCR engagement. Further, while our approach provides a robust system to assess the impact of the risk variant in primary human T cells, our findings are derived from a comparison of only two specific TCRs. The identification of similar pairs of ‘higher’ and ‘lower’ avidity TCRs recognizing identical self-peptides will be useful in assessing our model and its interpretation across a broader pool of TCR interactions. Notably, in this study we explored the impacts of the PTPN22 risk variant and KO specifically in cord blood CD4 T cells. CD4 T cells were chosen for this study based on well-documented use in gene editing models and likely key roles in PTPN22 associated autoimmune diseases (Zheng et al., 2012). Cord blood was used to minimize differences in environmental impact between T cell donors. Although previous work has revealed similar findings regarding the phenotype of PTPN22 KO in adult T cells (Anderson et al., 2019), it remains possible that similar risk variant editing experiments using adult peripheral blood may yield different results.

Consistent with our findings, recent work using lentiviral-based overexpression in primary human T cells also revealed hypomorphic function of the PTPN22 risk variant (Perry et al., 2021). Further, that study and others Sanchez-Blanco et al., 2018; Burn et al., 2016 have suggested that PTPN22 may modulate pathways other than the TCR including LFA-1-mediated integrin signals, stabilizing immunological synapses that promote T cell proliferation and Th1 skewing. Our data using low dose CD3 stimulation (Figure 2) support the conclusion that both the variant and PTPN22 KO can impact T cell activation through altered regulation of the TCR. Notably, our CD3 studies were performed in the absence of co-stimulation to better mimic sub-optimal TCR engagement. Thus, the relevance of our findings based on endogenous-level expression compared to lentiviral-based PTPN22 over-expression in association with CD3/CD28 co-stimulation are difficult to compare. Together, our findings that the risk variant preferentially modulates low avidity TCR engagement, with the observations of these previous studies suggests that the PTPN22 risk variant may exert its impact on T cells both via altering TCR signaling and by modulating additional signals including LFA-1 pathway regulation.

Through gene editing we demonstrate that PTPN22 risk variant expression in human T cells mediates at least a partial loss of function phenotype that mirrors findings derived from mouse models. This data, however, does not explain the marked differences in T cell responses described in mouse models vs. natural carriers of the PTPN22 risk variant. Natural carriers of the risk variant exhibit hyporesponsive T cells, with reduced TCR induced activation, and reduced cytokine responses (Rieck et al., 2007; Vang et al., 2005). In previous work, we showed that loss of function in another key negative regularity pathway in T cells leads to overexpression of functionally related proteins to maintain homeostasis. For example, KO of the IL-2 regulatory gene, PTPN2, in primary human T cells results in a transient increase in IL-2 signaling, but expansion of PTPN2 KO cells in high cytokine media leads to reduced IL-2 responses due to overexpression of the regulatory protein SOCS3 (Anderson et al., 2019). Similar compensatory events may be operable in T cells in carriers of the PTPN22 risk variant, where reduced proximal negative regulatory events might lead to expression of alternative regulatory proteins. Recent work using optogenically controlled TCR signaling has shown that T cell activation is dynamic, requiring optimal frequencies of TCR engagement relative to cessation of signal to mediate CD69 expression and subsequent activation; however, events that limit T cell responses may be more static, with expression of TIM3, for example, increasing regardless of signaling frequency (O’Donoghue et al., 2021). As loss of PTPN22 function specifically augments low-avidity TCR signaling, it is possible that tonic TCR signaling is also impacted and may drive additional events that function to limit TCR signals in carriers of the risk variant over time. Finally, it is important to highlight the environmental differences between murine models and primary human T cell donors. As opportunity for exposure to antigen increases, this may drive T cells from human carriers toward a reduced responsiveness to TCR engagement via impacts that are not operative in SPF murine models.

In summary, the data presented within this study supports a model where the PTPN22 R620W risk variant impacts human T cell function via a reduction in negative regulation of TCR signaling; findings similar to murine models, but in contrast to the T cell signaling phenotype in carriers with the risk variant. In association with previous human studies, our findings suggest that the impact of the risk variant on T cell function is likely dynamic, leading to the generation of populations of hyperresponsive T cells, but also allowing for secondary impacts on T cell gene expression that may lead to hyporesponsive T cells over time or after environmental exposures. This would help explain how PTPN22 could influence risk of diverse autoimmune diseases such as type 1 diabetes and rheumatoid arthritis, diseases with distinct ages of onset and tissue targets. Taken together, these observations suggest that PTPN22 contributes to autoimmunity by establishing temporal windows of risk for specific diseases that coincide with periods of altered T cell responsiveness.

Prism files containing the numerical data and statistical tests used to generate all figures has been provided.

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Author details

1. Warren Anderson

   Center for Immunity and Immunotherapies, Seattle Children's Research Institute, Seattle, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Validation, Investigation, Methodology, Writing - original draft, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-9315-5233

2. Fariba Barahmand-pour-Whitman

   Benaroya Research Institute at Virginia Mason, Seattle, United States

   Contribution

   Conceptualization, Resources, Investigation, Methodology, Writing - review and editing

   Competing interests

   No competing interests declared

3. Peter S Linsley

   Benaroya Research Institute at Virginia Mason, Seattle, United States

   Contribution

   Conceptualization, Resources, Methodology, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-8960-4307

4. Karen Cerosaletti

   Benaroya Research Institute at Virginia Mason, Seattle, United States

   Contribution

   Conceptualization, Resources, Methodology, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-7403-6239

5. Jane H Buckner

   Benaroya Research Institute at Virginia Mason, Seattle, United States

   Contribution

   Conceptualization, Resources, Methodology, Writing - review and editing

   Competing interests

   No competing interests declared

6. David J Rawlings

   Department of Pediatrics and Immunology, University of Washington, Seattle, United States

   Contribution

   Conceptualization, Resources, Supervision, Funding acquisition, Methodology, Project administration, Writing - review and editing

   For correspondence

   drawling@u.washington.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-0810-1776

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