ReviewDiabetologia2018
Immunological biomarkers for the development and progression of type 1 diabetes.
Review in Diabetologia, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
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The trial behind it
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Who cites it
38 citing papers in PubMed.
- Social Support Mechanisms in an Online Type 1 Diabetes Community: Social Network Analysis of Stakeholder Diversity and Disease Duration.Journal of medical Internet research · 2026Observational
- Capillary Electrophoresis Immunoassay for Detection of Anti-insulin Antibodies.Journal of separation science · 2026Article
- Application of monoclonal antibodies in diabetes: A bibliometric analysis from 2004-2024.Human vaccines & immunotherapeutics · 2025Article
- Emerging phenotype: Maturity-onset diabetes of the young type 5 (MODY-5) - mechanisms, clinical spectrum, and unmet needs.Diabetology & metabolic syndrome · 2025Review
- Type 1 Diabetes TrialNet: Leading the Charge in Disease Prediction, Prevention, and Immunotherapeutic Mechanistic Understanding.Diabetes care · 2025Review
- Longitudinal pathway analysis using structural information with case studies in early type 1 diabetes.Scientific reports · 2025Article
- IA-2A positivity increases risk of progression within and across established stages of type 1 diabetes.Diabetologia · 2025Article
- Unveiling Gestational Diabetes: An Overview of Pathophysiology and Management.International journal of molecular sciences · 2025Review
- Observational study protocol: the faecal microbiome in the acute stage of new-onset paediatric type 1 diabetes in an Irish cohort.BMJ open · 2025Article
- Enhanced Electrochemiluminescence from Ruthenium-Tagged Immune Complex at Flexible Chains for Sensitive Analysis of Glutamate Decarboxylase Antibody.Biosensors · 2025Article
- Autoimmune Type 1 Diabetes: An Early Approach Appraisal for Spain by the AGORA Diabetes Collaborative Group.Journal of clinical medicine · 2025Review
- Identification and validation of endoplasmic reticulum stress-related diagnostic biomarkers for type 1 diabetic cardiomyopathy based on bioinformatics and machine learning.Frontiers in endocrinology · 2025Article
- A set of circulating microRNAs belonging to the 14q32 chromosome locus identifies two subgroups of individuals with recent-onset type 1 diabetes.Cell reports. Medicine · 2024Article
- Utility of genetic risk scores in type 1 diabetes.Diabetologia · 2023Review
- Plasma protein biomarkers predict the development of persistent autoantibodies and type 1 diabetes 6 months prior to the onset of autoimmunity.Cell reports. Medicine · 2023Article
- Type 1Micromachines · 2023Review
- Exploration of Immune Targets for Type 1 Diabetes and Latent Autoimmune Disease Immunotherapy.ImmunoTargets and therapy · 2023Review
- Exploring Computational Data Amplification and Imputation for the Discovery of Type 1 Diabetes (T1D) Biomarkers from Limited Human Datasets.Biomolecules · 2022Article
- Screening for Type 1 Diabetes in the General Population: A Status Report and Perspective.Diabetes · 2022Review
- Guidelines for standardizing T-cell cytometry assays to link biomarkers, mechanisms, and disease outcomes in type 1 diabetes.European journal of immunology · 2022Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Immune biomarkers of type 1 diabetes are many and diverse. Some of these, such as the autoantibodies, are well established but not discriminative enough to deal with the heterogeneity inherent to type 1 diabetes progression. As an alternative, high hopes are placed on T cell assays, which give insight into the cells that actually target the beta cell or play a crucial role in maintaining tolerance. These assays are approaching a level of robustness that may allow for solid conclusions on both disease progression and therapeutic efficacy of immune interventions. In addition, 'omics' approaches to biomarker discovery are rapidly progressing. The potential emergence of novel biomarkers creates a need for the introduction of bioinformatics and 'big data' analysis systems for the integration of the multitude of biomarker data that will be available, to translate these data into clinical tools. It is worth noting that it is unlikely that the same markers will apply to all individuals. Instead, individualised signatures of biomarkers, combining autoantibodies, T cell profiles and other biomarkers, will need to be used to classify at-risk patients into various categories, thus enabling personalised prediction, prevention and treatment approaches. To achieve this goal, the standardisation of assays for biomarker discovery, the integration of analyses and data from biomarker studies and, most importantly, the careful clinical characterisation of individuals providing samples for these studies are critical. Longitudinal sample-collection initiatives, like INNODIA, should lead to novel biomarker discovery, not only providing a better understanding of type 1 diabetes onset and progression, but also yielding biomarkers of therapeutic efficacy of interventions to prevent or arrest type 1 diabetes.
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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.