Trial reportJCI insight2019
Treg gene signatures predict and measure type 1 diabetes trajectory.
Trial report in JCI insight, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
24 citing papers in PubMed, 43 citations in OpenAlex.
- Transcriptomics of type 1 diabetes progression: a validation study in newly diagnosed patients.EBioMedicine · 2026Article
- Regulatory T cells in cancer and inflammation.Signal transduction and targeted therapy · 2026Review
- An endometrial tissue-based predictive model for polycystic ovary syndrome constructed from immuno-metabolic dysregulation features mediated by ACO1.Journal of ovarian research · 2026Article
- Armored human CAR TScience advances · 2025Article
- Immune perturbations in human pancreas lymphatic tissues prior to and after type 1 diabetes onset.Nature communications · 2025Article
- Genetics of circulating proteins in newborn babies at high risk of type 1 diabetes.Nature communications · 2025Article
- Harnessing the biology of regulatory T cells to treat disease.Nature reviews. Drug discovery · 2025Review
- Genetic engineering of regulatory T cells for treatment of autoimmune disorders including type 1 diabetes.Diabetologia · 2024Review
- The beta cell-immune cell interface in type 1 diabetes (T1D).Molecular metabolism · 2023Review
- Tregs with an MHC class II peptide-specific chimeric antigen receptor prevent autoimmune diabetes in mice.The Journal of clinical investigation · 2023Article
- Regulatory T-cell dysfunction and its implication for cell therapy.Clinical and experimental immunology · 2023Article
- Insulin B peptide-MHC class II-specific chimeric antigen receptor-Tregs prevent autoimmune diabetes.bioRxiv : the preprint server for biology · 2023Article
- Radiolabelling of Polyclonally Expanded Human Regulatory T Cells (Treg) withMolecules (Basel, Switzerland) · 2023Article
- Nanotechnology in Immunotherapy for Type 1 Diabetes: Promising Innovations and Future Advances.Pharmaceutics · 2022Review
- Activated but functionally impaired memory Tregs are expanded in slow progressors to type 1 diabetes.Diabetologia · 2022Article
- A phase 1b open-label dose-finding study of ustekinumab in young adults with type 1 diabetes.Immunotherapy advances · 2022Article
- Nature vs. nurture: FOXP3, genetics, and tissue environment shape Treg function.Frontiers in immunology · 2022Review
- Computational Recognition of a Regulatory T-cell-specific Signature With Potential Implications in Prognosis, Immunotherapy, and Therapeutic Resistance of Prostate Cancer.Frontiers in immunology · 2022Article
- Immuno-cardio-oncology: Killing two birds with one stone?Frontiers in immunology · 2022Review
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 6 institutions in 3 countries.
Funding
Abstract
backgroundMultiple 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.
methodsnanoString 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.
resultsCompared 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.
conclusionThese data suggest that biomarkers based on measuring TGSs could be a new approach to stratify patients and monitor autoimmune activity in T1D.
fundingJDRF (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.
Indexed as
Identifiers
What Socratic holds
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 Socratic graph.