ArticleDiabetologia2018
Combinatorial detection of autoreactive CD8
Article in Diabetologia, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Phenotypic Analysis of Human Lymph Nodes in Subjects With New-Onset Type 1 Diabetes and Healthy Individuals by Flow Cytometry.Frontiers in immunology · 2019Trial
- Type 1 Diabetes: A Guide to Autoimmune Mechanisms for Clinicians.Diabetes, obesity & metabolism · 2025Review
- Pivotal epitopes for islet antigen-specific CD8Immunologic research · 2025Article
- The immunology of type 1 diabetes.Nature reviews. Immunology · 2024Review
- The pathogenic "symphony" in type 1 diabetes: A disorder of the immune system, β cells, and exocrine pancreas.Cell metabolism · 2023Review
- The need and benefit of immune monitoring to define patient and disease heterogeneity, mechanisms of therapeutic action and efficacy of intervention therapy for precision medicine in type 1 diabetes.Frontiers in immunology · 2023Article
- Monitoring islet specific immune responses in type 1 diabetes clinical immunotherapy trials.Frontiers in immunology · 2023Review
- Preclinical evaluation of a precision medicine approach to DNA vaccination in type 1 diabetes.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Review
- Human islet T cells are highly reactive to preproinsulin in type 1 diabetes.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Article
- Slow progressors to type 1 diabetes lose islet autoantibodies over time, have few islet antigen-specific CD8Diabetologia · 2020Article
- Autoreactive CD8+ T cell exhaustion distinguishes subjects with slow type 1 diabetes progression.The Journal of clinical investigation · 2020Article
- Article
- Article
- Systematic Assessment of Immune Marker Variation in Type 1 Diabetes: A Prospective Longitudinal Study.Frontiers in immunology · 2019Observational
Corrections and comments
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Authors and funding
20 authors.
Funding
Abstract
aims/hypothesisValidated 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
methodsThe 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.
resultsThe 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 CONCLUSIONS/
interpretationOur 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.