Literature DB >> 29196783

Combinatorial detection of autoreactive CD8+ T cells with HLA-A2 multimers: a multi-centre study by the Immunology of Diabetes Society T Cell Workshop.

Eddie A James1, Joana R F Abreu2, John W McGinty3, Jared M Odegard3, Yvonne E Fillié2, Claire N Hocter4, Slobodan Culina5, Kristin Ladell4, David A Price4, Aimon Alkanani6, Marynette Rihanek6, Lisa Fitzgerald-Miller6, Ania Skowera7, Cate Speake3, Peter Gottlieb6, Howard W Davidson6, F Susan Wong4, Bart Roep8, Roberto Mallone5.   

Abstract

AIMS/HYPOTHESIS: Validated biomarkers are needed to monitor the effects of immune intervention in individuals with type 1 diabetes. Despite their importance, few options exist for monitoring antigen-specific T cells. Previous reports described a combinatorial approach that enables the simultaneous detection and quantification of multiple islet-specific CD8+ T cell populations. Here, we set out to evaluate the performance of a combinatorial HLA-A2 multimer assay in a multi-centre setting.
METHODS: The combinatorial HLA-A2 multimer assay was applied in five participating centres using centralised reagents and blinded replicate samples. In preliminary experiments, samples from healthy donors were analysed using recall antigen multimers. In subsequent experiments, samples from healthy donors and individuals with type 1 diabetes were analysed using beta cell antigen and recall antigen multimers.
RESULTS: The combinatorial assay was successfully implemented in each participating centre, with CVs between replicate samples that indicated good reproducibility for viral epitopes (mean %CV = 33.8). For beta cell epitopes, the assay was very effective in a single-centre setting (mean %CV = 18.4), but showed sixfold greater variability across multi-centre replicates (mean %CV = 119). In general, beta cell antigen-specific CD8+ T cells were detected more commonly in individuals with type 1 diabetes than in healthy donors. Furthermore, CD8+ T cells recognising HLA-A2-restricted insulin and glutamate decarboxylase epitopes were found to occur at higher frequencies in individuals with type 1 diabetes than in healthy donors. CONCLUSIONS/
INTERPRETATION: Our results suggest that, although combinatorial multimer assays are challenging, they can be implemented in multiple laboratories, providing relevant T cell frequency measurements. Assay reproducibility was notably higher in the single-centre setting, suggesting that biomarker analysis of clinical trial samples would be most successful when assays are performed in a single laboratory. Technical improvements, including further standardisation of cytometry platforms, will likely be necessary to reduce assay variability in the multi-centre setting.

Entities:  

Keywords:  Assay methods; Basic science; Biomarker; CD8+ T cell; Clinical immunology; Diabetes; HLA multimer; Human; Multi-centre

Mesh:

Substances:

Year:  2017        PMID: 29196783     DOI: 10.1007/s00125-017-4508-8

Source DB:  PubMed          Journal:  Diabetologia        ISSN: 0012-186X            Impact factor:   10.122


  9 in total

1.  Standardizing T-Cell Biomarkers in Type 1 Diabetes: Challenges and Recent Advances.

Authors:  Simi Ahmed; Karen Cerosaletti; Eddie James; S Alice Long; Stuart Mannering; Cate Speake; Maki Nakayama; Timothy Tree; Bart O Roep; Kevan C Herold; Todd M Brusko
Journal:  Diabetes       Date:  2019-07       Impact factor: 9.461

2.  Autoreactive CD8+ T cell exhaustion distinguishes subjects with slow type 1 diabetes progression.

Authors:  Alice E Wiedeman; Virginia S Muir; Mario G Rosasco; Hannah A DeBerg; Scott Presnell; Bertrand Haas; Matthew J Dufort; Cate Speake; Carla J Greenbaum; Elisavet Serti; Gerald T Nepom; Gabriele Blahnik; Anna M Kus; Eddie A James; Peter S Linsley; S Alice Long
Journal:  J Clin Invest       Date:  2020-01-02       Impact factor: 14.808

3.  A composite immune signature parallels disease progression across T1D subjects.

Authors:  Cate Speake; Samuel O Skinner; Dror Berel; Elizabeth Whalen; Matthew J Dufort; William Chad Young; Jared M Odegard; Anne M Pesenacker; Frans K Gorus; Eddie A James; Megan K Levings; Peter S Linsley; Eitan M Akirav; Alberto Pugliese; Martin J Hessner; Gerald T Nepom; Raphael Gottardo; S Alice Long
Journal:  JCI Insight       Date:  2019-12-05

4.  Preclinical evaluation of a precision medicine approach to DNA vaccination in type 1 diabetes.

Authors:  Jorge Postigo-Fernandez; Rebuma Firdessa-Fite; Rémi J Creusot
Journal:  Proc Natl Acad Sci U S A       Date:  2022-04-06       Impact factor: 12.779

5.  Systematic Assessment of Immune Marker Variation in Type 1 Diabetes: A Prospective Longitudinal Study.

Authors:  Cate Speake; Henry T Bahnson; Johnna D Wesley; Nikole Perdue; David Friedrich; Minh N Pham; Erinn Lanxon-Cookson; William W Kwok; Birgit Sehested Hansen; Matthias von Herrath; Carla J Greenbaum
Journal:  Front Immunol       Date:  2019-09-13       Impact factor: 7.561

6.  Human islet T cells are highly reactive to preproinsulin in type 1 diabetes.

Authors:  Amanda M Anderson; Laurie G Landry; Aimon A Alkanani; Laura Pyle; Alvin C Powers; Mark A Atkinson; Clayton E Mathews; Bart O Roep; Aaron W Michels; Maki Nakayama
Journal:  Proc Natl Acad Sci U S A       Date:  2021-10-12       Impact factor: 12.779

7.  Failed Genetic Protection: Type 1 Diabetes in the Presence of HLA-DQB1*06:02.

Authors:  Kimber M Simmons; Angela M Mitchell; Aimon A Alkanani; Kristen A McDaniel; Erin E Baschal; Taylor Armstrong; Laura Pyle; Liping Yu; Aaron W Michels
Journal:  Diabetes       Date:  2020-05-21       Impact factor: 9.461

8.  Slow progressors to type 1 diabetes lose islet autoantibodies over time, have few islet antigen-specific CD8+ T cells and exhibit a distinct CD95hi B cell phenotype.

Authors:  Stephanie J Hanna; Wendy E Powell; Anna E Long; Emma J S Robinson; Joanne Davies; Clare Megson; Alexandra Howell; Taz J Jones; Kristin Ladell; David A Price; Colin M Dayan; Alistair J K Williams; Kathleen M Gillespie; F Susan Wong
Journal:  Diabetologia       Date:  2020-03-10       Impact factor: 10.122

9.  Phenotypic Analysis of Human Lymph Nodes in Subjects With New-Onset Type 1 Diabetes and Healthy Individuals by Flow Cytometry.

Authors:  Jennie H M Yang; Leena Khatri; Marius Mickunas; Evangelia Williams; Danijela Tatovic; Mohammad Alhadj Ali; Philippa Young; Penelope Moyle; Vishal Sahni; Ryan Wang; Rejbinder Kaur; Gillian M Tannahill; Andrew R Beaton; Danielle M Gerlag; Caroline O S Savage; Antonella Napolitano Rosen; Frank Waldron-Lynch; Colin M Dayan; Timothy I M Tree
Journal:  Front Immunol       Date:  2019-10-31       Impact factor: 7.561

  9 in total

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