Guidelines for standardizing T-cell cytometry assays to link biomarkers, mechanisms, and disease outcomes in type 1 diabetes
Open accessAbstract
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.
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High‐Dimensional Fluorescence Cytometry
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Kent, S. C., Mannering, S. I., Michels, A. W., & Babon, J. A. B. (2017) · Current Diabetes Reports · doi:10.1007/s11892-017-0915-y · Cited by 36 · see citing works
Self-citationProinsulin-Reactive CD4 T Cells in the Islets of Type 1 Diabetes Organ Donors
Landry, L., Anderson, A., Russ, H., Yu, L.-P., Kent, S. C., Atkinson, M., Mathews, C., Michels, A., & Nakayama, M. (2021) · Frontiers in Endocrinology · doi:10.3389/fendo.2021.622647 · Cited by 31 · see citing works
Self-citationEnforcing the checkpoints: harnessing T-cell exhaustion for therapy of T1D
Linsley, P. S., & Long, S. A. (2019) · Current Opinion in Endocrinology Diabetes and Obesity · doi:10.1097/med.0000000000000488 · Cited by 30 · see citing works
Self-citationJames, E. A., Mallone, R., Schloot, N. C., Gagnerault, M., Thorpe, J., Fitzgerald-Miller, L., Reichow, J. L., Wagner, R., Pham, M. N., Jospe, N., et al. (2011) · Diabetes/Metabolism Research and Reviews · doi:10.1002/dmrr.1244 · Cited by 28 · see citing works
Self-citationIhantola, E., Viisanen, T., Gazali, A. M., Näntö‐Salonen, K., Juutilainen, A., Moilanen, L., Rintamäki, R. M., Pihlajamäki, J., Veijola, R., Toppari, J., et al. (2018) · The Journal of Immunology · doi:10.4049/jimmunol.1701199 · Cited by 28 · see citing works
Dynamic Immune Phenotypes of B and T Helper Cells Mark Distinct Stages of T1D Progression
Habib, T., Long, S. A., Samuels, P. L., Brahmandam, A., Tatum, M., Funk, A., Hocking, A. M., Cerosaletti, K. M., Mason, M. J., Whalen, E., et al. (2019) · Diabetes · doi:10.2337/db18-1081 · Cited by 28 · see citing works
Self-citationVera, E. J., Chew, Y. V., Nicholson, L., Burns, H., Anderson, P., Chen, H.-T., Williams, L. J., Keung, K. L., Zanjani, N. T., Dervish, S., et al. (2019) · PLoS ONE · doi:10.1371/journal.pone.0217163 · Cited by 27 · see citing works
Brooks‐Worrell, B., Tree, T. I. M., Mannering, S. I., Durinovic‐Belló, I., James, E. A., Gottlieb, P. A., Wong, F. S., Zhou, Z., Yang, L., Cilio, C., et al. (2011) · Diabetes/Metabolism Research and Reviews · doi:10.1002/dmrr.1245 · Cited by 24 · see citing works
Self-citationBeam, C. A., Wasserfall, C. H., Woodwyk, A., Akers, M., Rauch, H., Blok, T. M., Mason, P., Vos, D. G., Perry, D. J., Brusko, T. M., et al. (2020) · Scientific Reports · doi:10.1038/s41598-019-56951-5 · Cited by 24 · see citing works
Self-citationA phase 1b open-label dose-finding study of ustekinumab in young adults with type 1 diabetes
Marwaha, A., Chow, S., Pesenacker, A. M., Cook, L. E., Sun, A. C., Long, S. A., Yang, J. H. M., Ward‐Hartstonge, K. A., Williams, E., Domingo‐Vila, C., et al. (2021) · Immunotherapy Advances · doi:10.1093/immadv/ltab022 · Cited by 22 · see citing works
Self-citationHLA Class I Epitope Discovery in Type 1 Diabetes
Pinkse, G. G. M., Boîtard, C., Tree, T. I. M., Peakman, M., & Roep, B. O. (2006) · Annals of the New York Academy of Sciences · doi:10.1196/annals.1375.003 · Cited by 21 · see citing works
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A composite immune signature parallels disease progression across T1D subjects
Speake, C., Skinner, S. O., Berel, D., Whalen, E., Dufort, M. J., Young, W. C., Odegard, J., Pesenacker, A. M., Gorus, F., James, E. A., et al. (2019) · JCI Insight · doi:10.1172/jci.insight.126917 · Cited by 20 · see citing works
Self-citationUnbiased transcriptomes of resting human CD 4+ CD 45 RO + T lymphocytes
Westendorf, K., Okhrimenko, A., Grün, J. R., Schliemann, H., Chang, H., Dong, J., & Radbruch, A. (2014) · European Journal of Immunology · doi:10.1002/eji.201344323 · Cited by 18 · see citing works
Yang, J. H. M., Khatri, L., Mickunas, M., Williams, E., Tatović, D., Ali, M. A., Young, P., Moyle, P., Sahni, V., Wang, R., et al. (2019) · Frontiers in Immunology · doi:10.3389/fimmu.2019.02547 · Cited by 18 · see citing works
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Self-citationResponsiveness of the innate immune system and glucose concentrations in the oldest old
Wijsman, C. A., Mooijaart, S. P., Westendorp, R. G. J., & Maier, A. B. (2011) · AGE · doi:10.1007/s11357-011-9292-7 · Cited by 16 · see citing works
Use FlowRepository to share your clinical data upon study publication
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Self-citationMass cytometry and type 1 diabetes research in the age of single-cell data science
Rahman, A. H., & Homann, D. (2020) · Current Opinion in Endocrinology Diabetes and Obesity · doi:10.1097/med.0000000000000549 · Cited by 11 · see citing works
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Flagged first, then by citations
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Cited by
Sorted by citations
T‐cell activation–induced marker assays in health and disease
Poloni, C., Schonhofer, C., Ivison, S. M., Levings, M. K., Steiner, T. S., & Cook, L. E. (2023) · Immunology and Cell Biology · doi:10.1111/imcb.12636 · Cited by 121 · see citing works
“This assay is now being used to monitor diabetogenic antigen-specific T cells in adults (Canadian phase II/III study: NCT03941132) and adolescents (UK phase II study: ISRCTN14274380) being treated with ustekinumab.(84) These data demonstrate AIM assays as a valuable tool in human clinical studies.”
MethodSelf-citationSaggau, C., Bacher, P., Esser, D., Rasa, M., Meise, S., Mohr, N., Kohlstedt, N., Hutloff, A., Schacht, S.-S., Dargvainiene, J., et al. (2024) · Immunity · doi:10.1016/j.immuni.2024.08.005 · Cited by 79 · see citing works
Tatović, D., Marwaha, A., Taylor, P. N., Hanna, S. J., Carter, K., Cheung, W., Luzio, S. D., Dunseath, G. J., Hutchings, H. A., Holland, G., et al. (2024) · Nature Medicine · doi:10.1038/s41591-024-03115-2 · Cited by 43 · see citing works
“The strengths of our data include the randomized double-blind nature of our study, including blinding of laboratory staff and the use of fresh blood flow cytometry, along with strict quality assurance procedures in the assays 59 .”
Self-citationResponders to low-dose ATG induce CD4+ T cell exhaustion in type 1 diabetes
Jacobsen, L. M., Diggins, K. E., Blanchfield, L., McNichols, J., Perry, D. J., Brant, J. O., Dong, X., Bacher, R. L., Gersuk, V. H., Schatz, D. A., et al. (2023) · JCI Insight · doi:10.1172/jci.insight.161812 · Cited by 39 · see citing works
“Flow cytometry panels for T cells, myeloid cells, and NK cells were predetermined (Supplemental Table 2) and published previously (9,54).”
Self-citationHuman immune phenotyping reveals accelerated aging in type 1 diabetes
Shapiro, M. R., Dong, X., Perry, D. J., McNichols, J., Thirawatananond, P., Posgai, A. L., Peters, L. D., Motwani, K., Musca, R. S., MUIR, A. B., et al. (2023) · JCI Insight · doi:10.1172/jci.insight.170767 · Cited by 35 · see citing works
“Samples were shipped or rested overnight in order to standardize duration between collection and evaluation at UF (33).”
Self-citationCasu, A., Grippo, P. J., Wasserfall, C. H., Sun, Z., Linsley, P. S., Hamerman, J. A., Fife, B. T., Lacy‐Hulbert, A., Toledo, F. G. S., Hart, P. A., et al. (2022) · Pancreas · doi:10.1097/mpa.0000000000002076 · Cited by 18 · see citing works
Self-citationFanaropoulou, N. M., Tsatsani, G. C., Koufakis, T., & Kotsa, K. (2023) · Expert Review of Clinical Immunology · doi:10.1080/1744666x.2023.2281990 · Cited by 13 · see citing works
“These biomarkers are necessary to correlate immunological efficacy of the drug to clinical outcomes (disease modification) [32].”
BackgroundConsiderations for Choosing T Cell Assays during a Pandemic
Law, J. C., & Watts, T. H. (2023) · The Journal of Immunology · doi:10.4049/jimmunol.2300129 · Cited by 11 · see citing works
Monitoring immunomodulation strategies in type 1 diabetes
Krishnamurthy, B., Lacorcia, M., Kay, T. W. H., Thomas, H. E., & Mannering, S. I. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1206874 · Cited by 10 · see citing works
“There are excellent recent reviews on factors impeding progress toward the development of effective T-cell biomarkers in T1D (52, 98, 99).”
BackgroundEmerging Concepts and Success Stories in Type 1 Diabetes Research: A Road Map for a Bright Future
Mallone, R., Sims, E. K., Achenbach, P., Mathieu, C., Pugliese, A., Atkinson, M. A., Dutta, S., Evans‐Molina, C., Klatzmann, D., Koralova, A., et al. (2024) · Diabetes · doi:10.2337/db24-0439 · Cited by 10 · see citing works
Self-citationEttinger, R. A., Buitinga, M., Vandamme, C., Afonso, G., Gómez, R., Arribas-Layton, D., Bissenova, S., Speake, C., Reijonen, H., Kinnunen, T. T., et al. (2023) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/clinem/dgad434 · Cited by 8 · see citing works
Self-citationMonitoring islet specific immune responses in type 1 diabetes clinical immunotherapy trials
Arif, S., Domingo‐Vila, C., Pollock, E., Christakou, E., Williams, E., & Tree, T. I. M. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1183909 · Cited by 6 · see citing works
“Although challenges remain around some key areas such as the number of cells required and the need for harmonising assays, technological advances mean that multiparametric information derived from a single sample can be used in coordinated efforts to harmonize biomarker discovery and validation (82, 103).”
BackgroundSelf-citationThe minor spliceosome is a master immune regulatorPreprint
Johnson, M., Russ‐Silsby, J., Blair, P. A., Govier, M., Bonfield, G., Domingo‐Vila, C., Wakeling, M. N., Oram, R. A., Flanagan, S. E., Tree, T. I. M., et al. (2025) · medRxiv · doi:10.1101/2025.09.12.25335567 · Cited by 1 · see citing works
“Leukocyte populations were characterised from fresh whole blood (collected in 2.7 mL EDTA tubes) using five multi-parameter flow cytometry panels previously validated and assessed for technical reproducibility across multiple laboratories (51–53).”
InfluentialSelf-citationDomingo‐Vila, C., Williams, E., Smithmyer, M. E., Benson, B., Ferrat, L. A., Arif, S., Hudson, M., Dobbs, B., Johnson, M. B., Yardley, I. E., et al. (2025) · Frontiers in Immunology · doi:10.3389/fimmu.2025.1618080
Self-citationTracking GAD-specific T cell expansions in type 1 diabetes by intradermal GAD-alum challenge
Hanna, S. J., Robinson, E., Thayer, T. C., Nakayama, M., Landry, L. G., Andrews, R., Dolton, G. M., Davies, J. E., Williams, E., Pearson, J. A., et al. (2026) · JCI Insight · doi:10.1172/jci.insight.203119
Self-citationYang, L., Lindahl, A., & Robben, M. (2026) · Frontiers in Genetics · doi:10.3389/fgene.2026.1833788
“The utility of T cell biomarkers has been previously explored for their use in T1D disease prediction (Ahmed et al., 2019; Nakayama and Michels, 2021; Yang et al., 2022).”
- Authors
- 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., & The Immunology of Diabetes Society T‐Cell Cytometry Group
- Affiliations
- National Health Service (GB)
- University of British Columbia (CA)
- University of Florida Health (US)
- Center for Translational Research Benaroya Research Institute Seattle Washington USA
- Benaroya Research Institute (US)
- Icahn School of Medicine at Mount Sinai (US)
- University of Massachusetts Chan Medical School (US)
- Corresponding author
- Long, S. Alice
- ORCID
- Venue
- European Journal of Immunology
- Publisher
- Wiley
- Published
- 2022-01-28
- Volume
- 52
- Issue
- 3
- Pages
- 372-388
- ISSN
- 0014-2980 (ISSN-L)
- 1521-4141
- PMC
- PMC9006584
- OpenAlex
- W4205423449
- Cited by
- 16
- References
- 104
- Citations by year
- 2026: 2 · 2025: 2 · 2024: 3 · 2023: 8 · 2022: 1
- FWCI
- 2.11
- Type
- journal article
- Language
- en
- Open access
- green
- kclpure.kcl.ac.uk
- Licence
- Locations
- European Journal of Immunology (publishedVersion)
- PubMed (publishedVersion)
- Research Portal (King's College London) (publishedVersion, other-oa)
- PubMed Central (acceptedVersion)
- Funders
- Juvenile Diabetes Research Foundation International (3‐SRA‐2018‐629‐S‐B)
- Diabetes UK (15/0005232, 15/0005233)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Diabetes and associated disorders
- Life Sciences › Immunology and Microbiology › Immunology › T-cell and B-cell Immunology
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Keywords
- type 1 diabetes, T cell phenotyping, assay harmonization, disease progression, treatment response, study design recommendations
- MeSH terms
- Diabetes Mellitus, Type 1, Flow Cytometry, Humans, T-Lymphocytes, Biomarkers, Immunophenotyping
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