ArticleCell reports. Medicine2023
Plasma protein biomarkers predict the development of persistent autoantibodies and type 1 diabetes 6 months prior to the onset of autoimmunity.
Article in Cell reports. Medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 1 of them a synthesis that pooled it.
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Who cites it
36 citing papers in PubMed, 1 synthesis or guideline pooled it, 40 citations in OpenAlex.
- Harnessing Machine Learning, a Subset of Artificial Intelligence, for Early Detection and Diagnosis of Type 1 Diabetes: A Systematic Review.International journal of molecular sciences · 2025Pooled it
- Assessing Extracellular Vesicle Proteins as Predictive Biomarkers for Developing Type 1 Diabetes.Proteomics · 2026Article
- Proteome-wide Mendelian randomization identifies APOM and TNXB as actionable mediators of steroid-sensitive nephrotic syndrome.Pediatric nephrology (Berlin, Germany) · 2026Article
- Toward Personalized Medicine in Type 1 Diabetes: Understanding How Patient Heterogeneity Influences Therapeutic Efficacy.Diabetes, obesity & metabolism · 2026Review
- Unlocking beta cell health: The clinical potential of extracellular vesicles in type 1 diabetes.Clinical and translational medicine · 2026Review
- Review
- Challenges and Opportunities in State-of-the-Art Proteomics Analysis for Biomarker Development From Plasma Extracellular Vesicles.Proteomics · 2026Review
- A set of serum proteomic biomarkers differentiates celiac children from age and human leukocyte antigen-matched healthy controls.Journal of pediatric gastroenterology and nutrition · 2026Article
- Longitudinal monitoring of type 1 diabetes progression to disease onset.Science advances · 2026Article
- The inflammatory path toward type 1 diabetes begins during pregnancy.Nature communications · 2026Article
- Stress-driven remodeling of antigen presentation and chemokine signaling in pancreatic β-cells: implications for type 1 diabetes.Frontiers in immunology · 2026Review
- Circulating senescence-associated secretory phenotype factors across the stages of type 1 diabetes in a cross-sectional cohort.Scientific reports · 2025Article
- Single-Islet Proteomics Maps Pseudo-Temporal Islet Immune Responses and Dysfunction in Stage 1 Type 1 Diabetes.bioRxiv : the preprint server for biology · 2025Article
- Blood methylome signatures in children exposed to maternal type 1 diabetes are linked to protection against islet autoimmunity.Nature metabolism · 2025Article
- Frequent longitudinal blood microsampling and proteome monitoring identify disease markers and enable timely intervention in a mouse model of type 1 diabetes.Diabetologia · 2025Article
- Genetic mapping of complement system proteins for islet autoimmunity in children with high risk of T1D.Communications biology · 2025Article
- NIDDK: Celebrating 75 Years of Advancing Diabetes Research.Diabetes · 2025Article
- NIDDK: Celebrating 75 Years of Advancing Diabetes Research.Diabetes care · 2025Article
- Unfolding the Mystery of Autoimmunity: The Environmental Determinants of Diabetes in the Young (TEDDY) Study.Diabetes care · 2025Review
- Targeted serum proteomics of longitudinal samples from newly diagnosed youth with type 1 diabetes affirms markers of disease.Diabetologia · 2025Article
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Authors and funding
26 authors at 7 institutions in 4 countries.
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Abstract
Type 1 diabetes (T1D) results from autoimmune destruction of β cells. Insufficient availability of biomarkers represents a significant gap in understanding the disease cause and progression. We conduct blinded, two-phase case-control plasma proteomics on the TEDDY study to identify biomarkers predictive of T1D development. Untargeted proteomics of 2,252 samples from 184 individuals identify 376 regulated proteins, showing alteration of complement, inflammatory signaling, and metabolic proteins even prior to autoimmunity onset. Extracellular matrix and antigen presentation proteins are differentially regulated in individuals who progress to T1D vs. those that remain in autoimmunity. Targeted proteomics measurements of 167 proteins in 6,426 samples from 990 individuals validate 83 biomarkers. A machine learning analysis predicts if individuals would remain in autoimmunity or develop T1D 6 months before autoantibody appearance, with areas under receiver operating characteristic curves of 0.871 and 0.918, respectively. Our study identifies and validates biomarkers, highlighting pathways affected during T1D development.
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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.