Treg gene signatures predict and measure type 1 diabetes trajectory

JCI Insight. 2019 Mar 21;4(6):e123879. doi: 10.1172/jci.insight.123879.


Background: Multiple therapeutic strategies to restore immune regulation and slow type 1 diabetes (T1D) progression are in development and testing. A major challenge has been defining biomarkers to prospectively identify subjects likely to benefit from immunotherapy and/or measure intervention effects. We previously found that, compared with healthy controls, Tregs from children with new-onset T1D have an altered Treg gene signature (TGS), suggesting that this could be an immunoregulatory biomarker.

Methods: nanoString was used to assess the TGS in sorted Tregs (CD4+CD25hiCD127lo) or peripheral blood mononuclear cells (PBMCs) from individuals with T1D or type 2 diabetes, healthy controls, or T1D recipients of immunotherapy. Biomarker discovery pipelines were developed and applied to various sample group comparisons.

Results: Compared with controls, the TGS in isolated Tregs or PBMCs was altered in adult new-onset and cross-sectional T1D cohorts, with sensitivity or specificity of biomarkers increased by including T1D-associated SNPs in algorithms. The TGS was distinct in T1D versus type 2 diabetes, indicating disease-specific alterations. TGS measurement at the time of T1D onset revealed an algorithm that accurately predicted future rapid versus slow C-peptide decline, as determined by longitudinal analysis of placebo arms of START and T1DAL trials. The same algorithm stratified participants in a phase I/II clinical trial of ustekinumab (αIL-12/23p40) for future rapid versus slow C-peptide decline.

Conclusion: These data suggest that biomarkers based on measuring TGSs could be a new approach to stratify patients and monitor autoimmune activity in T1D.

Funding: JDRF (1-PNF-2015-113-Q-R, 2-PAR-2015-123-Q-R, 3-SRA-2016-209-Q-R, 3-PDF-2014-217-A-N), the JDRF Canadian Clinical Trials Network, the National Institute of Allergy and Infectious Diseases of the National Institutes of Health (UM1AI109565 and FY15ITN168), and BCCHRI.

Keywords: Bioinformatics; Diabetes; Endocrinology; Immunology; Tolerance.

Publication types

  • Clinical Trial, Phase I
  • Clinical Trial, Phase II
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Algorithms
  • Biomarkers / analysis*
  • Canada
  • Computational Biology
  • Cross-Sectional Studies
  • Diabetes Mellitus, Type 1 / genetics
  • Diabetes Mellitus, Type 1 / immunology*
  • Diabetes Mellitus, Type 1 / therapy
  • Diabetes Mellitus, Type 2
  • Gene Expression Regulation
  • Genotype
  • Humans
  • Immunotherapy
  • Leukocytes, Mononuclear
  • RNA, Messenger / metabolism
  • T-Lymphocytes, Regulatory / immunology*
  • Young Adult


  • Biomarkers
  • RNA, Messenger