Autoreactive T cell receptors with shared germline-like α chains in type 1 diabetes

Linsley, Peter S.; Barahmand-pour-Whitman, Fariba; Balmas, Elisa; DeBerg, Hannah A.; Flynn, Kaitlin J.; Hu, Alex; Rosasco, Mario G.; Chen, Janice; O’Rourke, Colin; Serti, Elisavet; Gersuk, Vivian H.; Motwani, Keshav; Seay, Howard R.; Brusko, Todd M.; Kwok, William W.; Speake, Cate; Greenbaum, Carla J.; Nepom, Gerald T.; Cerosaletti, Karen

doi:10.1172/jci.insight.151349

Cited by 27 publications

(76 citation statements)

References 63 publications

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“…The two TCRs, which we will term: “Lower Avidity TCR” or L-TCR, and “Higher Avidity TCR” or H-TCR, were found to trigger significantly different rates of proliferation across a range of peptide doses, consistent with their reported avidity (Fig. 3, C)(43). As the highest peptide dose reliably produced efficient proliferation in all donors tested, we used this dose for activation of PTPN22 edited cells.…”

Section: Resultsmentioning

confidence: 76%

“…Previous work has detailed the sequencing of multiple TCRs from T1D patients that are reactive against the pancreatic islet autoantigen IGRP (42, 43), and recent work has shown that gene edited primary human T cells can be rendered antigen specific through the lentiviral delivery of these TCRs prior to electroporation with RNPs (50). To study the impact of PTPN22 loss of function on antigen specific TCR responses, we transduced human cord blood CD4 T cells with lentiviral vectors (LV) encoding for alternative TCRs that respond to the same 20mer epitope of IGRP when presented by HLA-DRB1 04:01; and subsequently modified these LV transduced populations using the HDR-based gene editing (Fig.…”

Section: Resultsmentioning

confidence: 99%

“…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 EC 50 (43) and triggered proliferative response to an identical IGRP derived peptide (Fig. 3, C) (43).…”

Section: Discussionmentioning

confidence: 99%

“…Antigen specific TCRs utilized in this study have been previously described ((42, 43), T1D2 herein described as “Lower Avidity TCR” (L-TCR) with an EC50 of 0.97 μg/mL and T1D5-2 herein described as “Higher Avidity TCR” (H-TCR), EC50 0.09 μg/mL. TCR coding sequences were cloned into lentiviral backbones using InFusion HD (Takara), with oligonucleotides synthesized by IDT, and a cis-linked (T2A) eGFP was inserted into the 3’ end of the alpha constant region.…”

Section: Methodsmentioning

confidence: 99%

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PTPN22 R620W Gene Editing in T Cells Enhances Low Avidity TCR Responses

Anderson¹,

Barahmand-pour-Whitman²,

Linsley³

et al. 2022

Preprint

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A genetic variant in the gene PTPN22 (R620W, rs2476601) is strongly associated with increased risk for multiple autoimmune diseases and has been linked to altered TCR regulation. Here, we utilize Crispr/Cas9 gene editing with donor DNA repair templates in human cord blood-derived, naive T cells to generate PTPN22 risk edited, non-risk edited (silent modification), or knock out T cells from the same donor. PTPN22 risk edited cells exhibited increased activation marker expression following non-specific TCR engagement, findings that mimicked PTPN22 KO cells. Next, using lentiviral delivery of T1D patient-derived islet-antigen specific TCRs, we demonstrate that loss of PTPN22 function led to enhanced signaling in T cells expressing a lower avidity self-reactive TCR. In this setting, loss of PTPN22 mediated enhanced proliferation and Th1 skewing. Importantly, expression of the risk variant in association with a lower avidity TCR also increased proliferation relative to PTPN22 non-risk T cells. Together, these findings suggest that, in primary human T cells, PTPN22 rs2476601 contributes to autoimmunity risk by permitting increased TCR signaling in mildly self-reactive T cells, thereby potentially expanding the self-reactive T cell pool and skewing this population toward an inflammatory phenotype.

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Section: Resultsmentioning

confidence: 76%

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

PTPN22 R620W Gene Editing in T Cells Enhances Low Avidity TCR Responses

Anderson¹,

Barahmand-pour-Whitman²,

Linsley³

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

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“…The NGS dataset of GSE182870 [22] were obtained from the National Centre of Biotechnology Information (NCBI) Gene Expression Omnibus database (GEO, https://www.ncbi.nlm.nih.gov/geo/) [23]. GSE182870, which comprises a total of 780 samples, including 600 T1DM samples, and 180 normal control samples, was based on the platform of the GPL18573 Illumina NextSeq 500 (Homo sapiens).…”

Section: Methodsmentioning

confidence: 99%

Bioinformatics Analysis of next generation sequencing data for Risk Prediction in Patients with Type 1 diabetes mellitus

Vastrad¹,

Vastrad²

2022

Preprint

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Type 1 diabetes mellitus (T1DM) comprise the most common forms of autoimmune disease. The aim of this investigation was to apply a bioinformatics approach to reveal related pathways or genes involved in the development of T1DM. The next generation sequencing (NGS) dataset GSE182870 was downloaded from the gene expression omnibus (GEO) database. Differentially expressed gene (DEG) analysis was performed using DESeq2. The g:Profiler was utilized to analyze the functional enrichment, gene ontology (GO) and REACTOME pathway of the differentially expressed genes. Protein-protein interaction (PPI) network, modules, miRNA-hub gene regulatory network, and TF-hub gene regulatory network were conducted via comprehensive target prediction and network analyses. Finally, hub genes were validated by using receiver operating characteristic curve analysis. A total of 860 DEGs were screened out from NGS dataset, among which 477 genes were up regulated and 383 genes were down regulated. GO enrichment analysis indicated that up regulated genes were mainly involved in cellular metabolic process, intracellular anatomical structure and catalytic activity, and the down regulated genes were significantly enriched in cellular nitrogen compound biosynthetic process, protein containing complex and heterocyclic compound binding. REACTOME pathway enrichment analysis showed that the up regulated genes were mainly enriched in metabolism of carbohydrates and the down regulated genes were significantly enriched in metabolism of RNA. A PPI network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network were constructed, and hub genes (MAPK14, RHOC, MAD2L1, TAF1, TRAF2, HSP90AA1, TP53, HSP90AB1, UBA52 and RACK1) were identified. This study provides further insights into the underlying pathogenesis of T1DM.

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Analysis of thymic generation of shared T‐cell receptor α repertoire associated with recognition of tumor antigens shows no preference for neoantigens over wild‐type antigens

et al. 2023

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Background The number of mutations in cancer cells is an important predictor of a positive response to cancer immunotherapy. It has been suggested that the neoantigens produced by these mutations are more immunogenic than nonmutated tumor antigens, which are likely to be protected by immunological tolerance. However, the mechanisms of tolerance as regards tumor antigens are incompletely understood. Methods Here, we have analyzed the impact of thymic negative selection on shared T‐cell receptor (TCR) repertoire associated with the recognition of either mutated or nonmutated tumor antigens by comparing previously known TCR—antigen—pairs to TCR repertoires of 21 immunologically healthy individuals. Results Our results show that TCRα chains associated with either type of tumor antigens are readily generated in the thymus, at a frequency similar to TCRα chains associated with nonself. In the peripheral repertoire, the relative clone size of nonself‐associated chains is higher than that of the tumor antigens, but importantly, there is no difference between TCRα chains associated with mutated or nonmutated tumor antigens. Conclusion This suggests that the tolerance mechanisms protecting nonmutated tumor antigens are non‐deletional and therefore potentially reversible. As unmutated antigens are, unlike mutations, shared by a large number of patients, they may offer advantages in designing immunological approaches to cancer treatment.

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Autoreactive T cell receptors with shared germline-like α chains in type 1 diabetes

Abstract: Conflict of interest: TMB declares that he is a consultant for Repertoire Immune Medicines and has a collaborative grant (in-kind services) with Adaptive Biotechnologies.

Cited by 27 publications

References 63 publications

PTPN22 R620W Gene Editing in T Cells Enhances Low Avidity TCR Responses

PTPN22 R620W Gene Editing in T Cells Enhances Low Avidity TCR Responses

Bioinformatics Analysis of next generation sequencing data for Risk Prediction in Patients with Type 1 diabetes mellitus

Analysis of thymic generation of shared T‐cell receptor α repertoire associated with recognition of tumor antigens shows no preference for neoantigens over wild‐type antigens

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