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

Immunology of Diabetes Society T-Cell Cytometry Group, 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

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)372-388
Number of pages17
JournalEuropean Journal of Immunology
Volume52
Issue number3
Early online date28 Jan 2022
DOIs
Publication statusPublished - 4 Mar 2022

Keywords

  • biomarkers
  • flow cytometry
  • immune monitoring
  • T cells
  • type 1 diabetes

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