2017
DOI: 10.1007/s11892-017-0946-4
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T Cell Receptor Profiling in Type 1 Diabetes

Abstract: Purpose of ReviewThe genetic susceptibility and dominant protection for type 1 diabetes (T1D) associated with human leukocyte antigen (HLA) haplotypes, along with minor risk variants, have long been thought to shape the T cell receptor (TCR) repertoire and eventual phenotype of autoreactive T cells that mediate β-cell destruction. While autoantibodies provide robust markers of disease progression, early studies tracking autoreactive T cells largely failed to achieve clinical utility.Recent FindingsAdvances in … Show more

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Cited by 32 publications
(26 citation statements)
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“…In view of the evidence for cross-reactivity of shared sequences selected between disparate thymi and subsets, we hypothesized that shared sequences might be enriched for autoreactivity. We interrogated a previously described list of 1655 T1D-associated autoreactive CDR3βs (20), along with some newer unique CDR3β aa sequences (total of 2208 sequences) associated with T1D, largely from peripheral blood but also found in pancreas, LNs, and spleen of T1D donors from the network for Pancreatic Organ donors with Diabetes (nPOD) program (21). These sequences were derived from a number of assays including sequencing of T cells following FACS proliferation of dye-labeled responding T cells harvested following culture with autoantigens (22), direct MHC tetramer isolation of autoreactive T cells (22)(23)(24)(25), or following isolation and examination of peptide reactivities from islet-infiltrating T cells (26).…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…In view of the evidence for cross-reactivity of shared sequences selected between disparate thymi and subsets, we hypothesized that shared sequences might be enriched for autoreactivity. We interrogated a previously described list of 1655 T1D-associated autoreactive CDR3βs (20), along with some newer unique CDR3β aa sequences (total of 2208 sequences) associated with T1D, largely from peripheral blood but also found in pancreas, LNs, and spleen of T1D donors from the network for Pancreatic Organ donors with Diabetes (nPOD) program (21). These sequences were derived from a number of assays including sequencing of T cells following FACS proliferation of dye-labeled responding T cells harvested following culture with autoantigens (22), direct MHC tetramer isolation of autoreactive T cells (22)(23)(24)(25), or following isolation and examination of peptide reactivities from islet-infiltrating T cells (26).…”
Section: Resultsmentioning
confidence: 99%
“…T1D-reactive TCR list. Our T1D-reactive TCR data set contains 2208 unique CDR3β aa sequences associated with T1D derived from peripheral blood, pancreas, LNs, and spleen of T1D donors from the nPOD program (20). These sequences were derived from several assays including sequencing of T cells following FACS proliferation of dye-labeled responding T cells harvested in response to culture with autoantigens (21), direct MHC tetramer isolation of autoreactive T cells (21)(22)(23)(24), and, in certain situations, an assay following the isolation and examination of peptide reactivities from islet-infiltrating T cells (25).…”
Section: Methodsmentioning
confidence: 99%
“…This recognition leads to the activation and proliferation of antigen-specific T cells (7). Alterations in the T cell receptor (TCR) repertoire have been found in multiple autoimmune diseases, including SLE, rheumatoid arthritis, and Type 1 diabetes mellitus, and are implicated in the breakdown of peripheral immune tolerance (8)(9)(10)(11)(12)(13)(14). Analyzing the repertoire of clonally expanded T cells can potentially reveal specific homing of these T cells based on local antigen-driven activation.…”
Section: Introductionmentioning
confidence: 99%
“…In conjunction with this advancement, there is an urgent need to develop methods to identify antigen specificity of the TCR clonotypes determined by high-throughput single cell sequencing. One approach is to computationally predict peptide motifs recognized by a TCR using machine-learning of big data (43)(44)(45)(46). The major advantage of in-silico analysis is the capability to analyze an astronomical number of TCRs in a short time period.…”
Section: Discussionmentioning
confidence: 99%