ArticleScience translational medicine2021
Transcriptional networks in at-risk individuals identify signatures of type 1 diabetes progression.
Article in Science translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
38 citing papers in PubMed, 49 citations in OpenAlex.
- Evolving epigenomics of immune cells at single-nucleus resolution in children en route to type 1 diabetes.Nature communications · 2026Article
- Stratifying the Rate of Disease Progression by Progression Likelihood Scores in Children and Adolescents With Stage 1 and Stage 2 Type 1 Diabetes in Germany.Diabetes care · 2026Article
- IL-21 mediates crosstalk between T cells and NK cells during the remission of type 1 diabetes.Nature metabolism · 2026Article
- Profiling associations of interactive ligand-receptors (HLA class I and KIR gene products) with the progression to type 1 diabetes among seroconverted participants.Diabetologia · 2025Article
- Unfolding the Mystery of Autoimmunity: The Environmental Determinants of Diabetes in the Young (TEDDY) Study.Diabetes care · 2025Review
- Pharmacological inhibition of tyrosine protein-kinase 2 reduces islet inflammation and delays type 1 diabetes onset in mice.EBioMedicine · 2025Article
- Immune perturbations in human pancreas lymphatic tissues prior to and after type 1 diabetes onset.Nature communications · 2025Article
- Systems Human Immunology and AI: Immune Setpoint and Immune Health.Annual review of immunology · 2025Review
- Age-dependent gene expression trajectories during early childhood in children at increased risk for type 1 diabetes.Genes and immunity · 2025Article
- Looking back at the TEDDY study: lessons and future directions.Nature reviews. Endocrinology · 2025Review
- Emerging Concepts and Success Stories in Type 1 Diabetes Research: A Road Map for a Bright Future.Diabetes · 2025Article
- Bayesian clustering with uncertain data.PLoS computational biology · 2024Article
- A Review of Stage 0 Biomarkers in Type 1 Diabetes: The Holy Grail of Early Detection and Prevention?Journal of personalized medicine · 2024Review
- Integrating Omics into Functional Biomarkers of Type 1 Diabetes.Cold Spring Harbor perspectives in medicine · 2024Review
- Monocytes in type 1 diabetes families exhibit high cytolytic activity and subset abundances that correlate with clinical progression.Science advances · 2024Article
- Pharmacological inhibition of tyrosine protein-kinase 2 reduces islet inflammation and delays type 1 diabetes onset in mice.bioRxiv : the preprint server for biology · 2024Article
- Distinct cellular immune responses in children en route to type 1 diabetes with different first-appearing autoantibodies.Nature communications · 2024Article
- imply: improving cell-type deconvolution accuracy using personalized reference profiles.Genome medicine · 2024Article
- Systematic immune cell dysregulation and molecular subtypes revealed by single-cell RNA-seq of subjects with type 1 diabetes.Genome medicine · 2024Article
- Distinct transcriptomic profiles in children prior to the appearance of type 1 diabetes-linked islet autoantibodies and following enterovirus infection.Nature communications · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors at 10 institutions in 5 countries.
Funding
Abstract
Type 1 diabetes (T1D) is a disease of insulin deficiency that results from autoimmune destruction of pancreatic islet β cells. The exact cause of T1D remains unknown, although asymptomatic islet autoimmunity lasting from weeks to years before diagnosis raises the possibility of intervention before the onset of clinical disease. The number, type, and titer of islet autoantibodies are associated with long-term disease risk but do not cause disease, and robust early predictors of individual progression to T1D onset remain elusive. The Environmental Determinants of Diabetes in the Young (TEDDY) consortium is a prospective cohort study aiming to determine genetic and environmental interactions causing T1D. Here, we analyzed longitudinal blood transcriptomes of 2013 samples from 400 individuals in the TEDDY study before both T1D and islet autoimmunity. We identified and interpreted age-associated gene expression changes in healthy infancy and age-independent changes tracking with progression to both T1D and islet autoimmunity, beginning before other evidence of islet autoimmunity was present. We combined multivariate longitudinal data in a Bayesian joint model to predict individual risk of T1D onset and validated the association of a natural killer cell signature with progression and the model's predictive performance on an additional 356 samples from 56 individuals in the independent Type 1 Diabetes Prediction and Prevention study. Together, our results indicate that T1D is characterized by early and longitudinal changes in gene expression, informing the immunopathology of disease progression and facilitating prediction of its course.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.