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Yang JHM, Ward-Hartstonge KA, Perry DJ, et al. Guidelines for standardizing T cell cytometry assays to link biomarkers, mechanisms, and disease outcomes in type 1 diabetes. Eur J Immunol. 2022;doi: 10.1002/eji.202049067.
Yang, J. H. M., Ward-Hartstonge, K. A., Perry, D. J., Blanchfield, J. L., Posgai, A. L., Wiedeman, A. E., Diggins, K., Rahman, A., Tree, T. I. M., Brusko, T. M., Levings, M. K., James, E. A., Kent, S. C., Speake, C., Homann, D., Long, S. A. (2022). Guidelines for standardizing T cell cytometry assays to link biomarkers, mechanisms, and disease outcomes in type 1 diabetes. European journal of immunology, . https://doi.org/10.1002/eji.202049067
Yang, Jennie H M, et al. "Guidelines for standardizing T cell cytometry assays to link biomarkers, mechanisms, and disease outcomes in type 1 diabetes." European journal of immunology vol. (2022). doi: https://doi.org/10.1002/eji.202049067
Yang JHM, Ward-Hartstonge KA, Perry DJ, Blanchfield JL, Posgai AL, Wiedeman AE, Diggins K, Rahman A, Tree TIM, Brusko TM, Levings MK, James EA, Kent SC, Speake C, Homann D, Long SA. Guidelines for standardizing T cell cytometry assays to link biomarkers, mechanisms, and disease outcomes in type 1 diabetes. Eur J Immunol. 2022 Jan 13; doi: 10.1002/eji.202049067. Epub 2022 Jan 13. PMID: 35025103.
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Eur J Immunol. 2022 Jan 13; doi: 10.1002/eji.202049067. Epub 2022 Jan 13.

Guidelines for standardizing T cell cytometry assays to link biomarkers, mechanisms, and disease outcomes in type 1 diabetes.

European journal of immunology

Jennie H M Yang, Kirsten A Ward-Hartstonge, Daniel J Perry, J Lori Blanchfield, Amanda L Posgai, Alice E Wiedeman, Kirsten Diggins, Adeeb Rahman, Timothy I M Tree, Todd M Brusko, Megan K Levings, Eddie A James, Sally C Kent, Cate Speake, Dirk Homann, S Alice Long,

Affiliations

  1. Department of Immunobiology, Faculty of Life Sciences & Medicine, King's College London, London, UK.
  2. National Institute of Health Research Biomedical Research Centre at Guy's and St. Thomas' National Health Service Foundation Trust and King's College London, London, UK.
  3. Department of Surgery, The University of British Columbia, Vancouver, CA.
  4. BC Children's Hospital Research Institute, British Columbia, Vancouver, CA.
  5. Department of Pathology and Laboratory Medicine, University of Florida Diabetes Institute, Gainesville, FL, USA.
  6. Center for Translational Research, Benaroya Research Institute at Virginia Mason, Seattle, WA, USA.
  7. Human Immune Monitoring Center, Hess Center for Science and Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  8. School of Biomedical Engineering, The University of British Columbia, CA.
  9. Diabetes Center of Excellence, University of Massachusetts Medical School, Worcester, MA, USA.
  10. Center for Interventional Immunology, Benaroya Research Institute at Virginia Mason, Seattle, WA, USA.
  11. Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  12. Diabetes, Obesity & Metabolism Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

PMID: 35025103 DOI: 10.1002/eji.202049067

Abstract

Cytometric immunophenotyping is a powerful tool to discover and implement T cell biomarkers of type 1 diabetes (T1D) progression and response to clinical therapy. Although many discovery-based T cell biomarkers have been described, to date, no such markers have been widely adopted in standard practice. The heterogeneous nature of T1D and lack of standardized assays and experimental design across studies is a major barrier to the broader adoption of T cell immunophenotyping assays. There is an unmet need to harmonize the design of immunophenotyping assays, including those that measure antigen-agnostic cell populations, such that data collected from different clinical trial sites and T1D cohorts are comparable, yet account for cohort-specific features and different drug mechanisms of action. In these Guidelines, we aim to provide expert advice on how to unify aspects of study design and practice. We provide recommendations for defining cohorts, method implementation, as well as tools for data analysis and reporting by highlighting and building on selected successes. Harmonization of cytometry-based T cell assays will allow researchers to better integrate findings across trials, ultimately enabling the identification and validation of biomarkers of disease progression and treatment response in T1D. This article is protected by copyright. All rights reserved.

This article is protected by copyright. All rights reserved.

Keywords: T cells; biomarkers; flow cytometry; immune monitoring; type 1 diabetes

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