Staging presymptomatic type 1 diabetes: A scientific statement of JDRF, the Endocrine Society, and the American Diabetes Association
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Insights from prospective, longitudinal studies of individuals at risk for developing type 1 diabetes have demonstrated that the disease is a continuum that progresses sequentially at variable but predictable rates through distinct identifiable stages prior to the onset of symptoms. Stage 1 is defined as the presence of β-cell autoimmunity as evidenced by the presence of two or more islet autoantibodies with normoglycemia and is presymptomatic, stage 2 as the presence of β-cell autoimmunity with dysglycemia and is presymptomatic, and stage 3 as onset of symptomatic disease. Adoption of this staging classification provides a standardized taxonomy for type 1 diabetes and will aid the development of therapies and the design of clinical trials to prevent symptomatic disease, promote precision medicine, and provide a framework for an optimized benefit/risk ratio that will impact regulatory approval, reimbursement, and adoption of interventions in the early stages of type 1 diabetes to prevent symptomatic disease.
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Autoantibody markers plus clinical presentation can help distinguish type 1 from type 2 diabetes in children and adults.
“The presence or absence of autoimmune markers (autoantibodies to glutamic acid decarboxylase [GAD65], pancreatic islet b cells [tyrosine phosphatase IA-2], and IA-2b zinc transporter [ZnT8], and/or insulin) in addition to the clinical presentation may help establish the correct diagnosis to distinguish between T1D and T2D in children or adults.22–27”
From American Association of Clinical Endocrinology Clinical Practice Guideline: Developing a Diabetes Mellitus Comprehensive Care Plan-2022 Update. (2022) · cites this paper as [24]
The Stage 1 section identifies insulin, GAD65, IA-2, and ZnT8 autoantibodies as markers of presymptomatic type 1 diabetes; the Overview and Stage 3 sections also describe clinical symptoms at diagnosis. The paper does not say that combining marker results with clinical presentation distinguishes type 1 from type 2 diabetes in children or adults. (LLM, conf=0.83)
Experimental — accuracy not yet measuredAt stage 1 of type 1 diabetes, the 5-year risk of developing symptomatic type 1 diabetes is ~44% overall but varies considerably based on number, titer, and specificity of autoantibodies as well as age of seroconversion and genetic risk.
“At stage 1, the 5-year risk of developing symptomatic type 1 diabetes is 44% overall but varies considerably based on number, titer, and speci fi city of autoantibodies as well as age of seroconversion and genetic risk (47).”
From 2. Diagnosis and Classification of Diabetes: <i>Standards of Care in Diabetes—2024</i> (2024) · cites this paper as [47]
The Overview of Staging, Stage 1 section gives an approximately 44% five-year risk, but specifically for children screened for genetic risk at birth who reached stage 1—not for all people at stage 1. The Stage 1 section supports variation by autoantibody number, titer and type, age at seroconversion, and HLA genotype. Page numbers were not provided in our copy. (LLM, conf=0.85)
Experimental — accuracy not yet measuredAt stage 1 of type 1 diabetes, the 5-year risk of developing symptomatic type 1 diabetes is 44% overall but varies considerably based on number, titer, and specificity of autoantibodies as well as age of seroconversion and genetic risk.
“At stage 1, the 5-year risk of developing symptomatic type 1 diabetes is 44% overall but varies considerably based on number, titer, and specificity of autoantibodies as well as age of seroconversion and genetic risk (45).”
From 2. Diagnosis and classification of diabetes: standards of care in diabetes-2025 (2025) · cites this paper as [45]
The Overview of Staging, Stage 1 section gives an approximately 44% five-year risk for children screened for genetic risk at birth who reach stage 1, not an overall estimate for everyone at stage 1. The Stage 1 section supports variation by autoantibody number, titer and type, age at seroconversion, and HLA genotype. (LLM, conf=0.84)
Experimental — accuracy not yet measuredThree distinct stages of type 1 diabetes have been defined and serve as a framework for research and regulatory decision-making.
“Three distinct stages of type 1 diabetes have been defi ned ( Table 2.3 ) and serve as a framework for research and regulatory decisionmaking (40,47).”
From 2. Diagnosis and Classification of Diabetes: <i>Standards of Care in Diabetes—2024</i> (2024) · cites this paper as [47]
Multiple studies indicate that measuring islet autoantibodies in relatives of those with type 1 diabetes or in children from the general population can effectively identify those who will develop type 1 diabetes.
“Multiple studies indicate that measuring islet autoantibodies in relatives of those with type 1 diabetes (47) or in children from the general population (72,73) can effectively identify those who will develop type 1 diabetes.”
From 2. Diagnosis and Classification of Diabetes: <i>Standards of Care in Diabetes—2024</i> (2024) · cites this paper as [47]
Measuring islet autoantibodies in relatives of those with type 1 diabetes, in children from the general population, or in children from the general population with high genetic risk can identify many individuals who will develop type 1 diabetes.
“Multiple studies indicate that measuring islet autoantibodies in relatives of those with type 1 diabetes (45), in children from the general population (71,72), or in children from the general population with high genetic risk (73) can identify many individuals who will develop type 1 diabetes.”
From 2. Diagnosis and classification of diabetes: standards of care in diabetes-2025 (2025) · cites this paper as [45]
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Self-citationThe prenatal environment and type 1 diabetes
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Familial Risk of Type I diabetes in European Children
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Self-citationDistinguishing Persistent Insulin Autoantibodies With Differential Risk
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Self-citationCord Serum Lipidome in Prediction of Islet Autoimmunity and Type 1 Diabetes
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Self-citationHbA1c Predicts Time to Diagnosis of Type 1 Diabetes in Children at Risk
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Self-citationThe environment and the origins of islet autoimmunity and Type 1 diabetes
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Self-citationTrends in high-risk HLA susceptibility genes among Colorado youth with type 1 diabetes
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Self-citationViruses and type 1 diabetes: a new look at an old story
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Self-citationDevelopment of Autoantibodies in the TrialNet Natural History Study
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Self-citationIncidence of Insulin-Dependent Diabetes Mellitus in Colorado
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Self-citationThe use of intermediate endpoints in the design of type 1 diabetes prevention trials
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HLA-Associated Insulin Autoantibody Formation in Newly Diagnosed Type I Diabetic Patients
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Self-citationGeneral population screening for type 1 diabetes
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Self-citationPerformance of HbA1c as an Early Diagnostic Indicator of Type 1 Diabetes in Children and Youth
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Self-citationDetection of Islet β-Cell Death in Vivo by Multiplex PCR Analysis of Differentially Methylated DNA
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Analysis of β-Cell Death in Type 1 Diabetes by Droplet Digital PCR
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Self-citationMetabolomics in the Studies of Islet Autoimmunity and Type 1 Diabetes
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Self-citationIslet Autoantibody Testing: An End to the Trials and Tribulations?
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Self-citationMetabolic tests to determine risk for type 1 diabetes in clinical trials
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2. Classification and Diagnosis of Diabetes: <i>Standards of Medical Care in Diabetes—2022</i>
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2. Classification and Diagnosis of Diabetes: <i>Standards of Medical Care in Diabetes—2020</i>
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2. Classification and Diagnosis of Diabetes: <i>Standards of Medical Care in Diabetes—2021</i>
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2. Classification and Diagnosis of Diabetes: <i>Standards of Medical Care in Diabetes—2018</i>
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2. Classification and Diagnosis of Diabetes
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Self-citation2. Diagnosis and classification of diabetes: standards of care in diabetes-2025
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An anti-CD3 antibody, teplizumab, in relatives at risk for type 1 diabetes
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Self-citationDifferentiation of diabetes by pathophysiology, natural history, and prognosis
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Self-citationEnvironmental risk factors for type 1 diabetes
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Self-citationGenetic risk factors for type 1 diabetes
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Chung, W. K., Erion, K., Florez, J. C., Hattersley, A. T., Hivert, M.-F., Lee, C. G., McCarthy, M. I., Nolan, J. J., Norris, J. M., Pearson, E. R., et al. (2020) · Diabetes Care · doi:10.2337/dci20-0022 · Cited by 400 · see citing works
Targeted Elimination of Senescent Beta Cells Prevents Type 1 Diabetes
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Self-citation100 years of insulin: celebrating the past, present and future of diabetes therapy
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New frontiers in the treatment of type 1 diabetes
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Redondo, M. J., Steck, A. K., & Pugliese, A. (2018) · Pediatric Diabetes · doi:10.1111/pedi.12597 · Cited by 216 · see citing works
Writing Committee for the Type 1 Diabetes TrialNet Oral Insulin Study Group, Krischer, J. P., Schatz, D. A., Bundy, B., Skyler, J. S., & Greenbaum, C. J. (2017) · JAMA · doi:10.1001/jama.2017.17070 · Cited by 214 · see citing works
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Early prediction of autoimmune (type 1) diabetes.
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Self-citationInsulin Therapy in Adults with Type 1 Diabetes Mellitus: a Narrative Review
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Autoreactive CD8+ T cell exhaustion distinguishes subjects with slow type 1 diabetes progression
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Self-citationCost and cost-effectiveness of large-scale screening for type 1 diabetes in Colorado
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Self-citationJacobsen, L. M., Bocchino, L., Evans-Molina, C., DiMeglio, L., Goland, R., Wilson, D. M., Atkinson, M. A., Aye, T., Russell, W. E., Wentworth, J. M., et al. (2020) · Diabetologia · doi:10.1007/s00125-019-05047-w · Cited by 133 · see citing works
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Self-citationBogun, M. M., Bundy, B. N., Goland, R. S., & Greenbaum, C. J. (2020) · Diabetes Care · doi:10.2337/dc19-2288 · Cited by 72 · see citing works
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“in normoglycaemic individuals who are positive for two or more autoantibodies and who probably retain a large population of viable beta cells [36].”
BackgroundLearning from the nexus of autoimmunity and cancer
Mangani, D., Yang, D., & Anderson, A. C. (2023) · Immunity · doi:10.1016/j.immuni.2023.01.022 · Cited by 33 · see citing works
The Role of Age and Excess Body Mass Index in Progression to Type 1 Diabetes in At-Risk Adults
Ferrara, C. T., Geyer, S. M., Evans-Molina, C., Libman, I. M., Becker, D. J., Wentworth, J. M., Moran, A., Gitelman, S. E., Redondo, M. J., & Type 1 Diabetes TrialNet Study Group (2017) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2017-01490 · Cited by 33 · see citing works
Recent advances in understanding type 1 diabetes
Christoffersson, G., Rodriguez-Calvo, T., & von Herrath, M. (2016) · F1000Research · doi:10.12688/f1000research.7356.1 · Cited by 32 · see citing works
The countdown to type 1 diabetes: when, how and why does the clock start?
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Self-citationNew therapeutic approaches for type 1 diabetes: Disease-modifying therapies
Nagy, G., Szekely, T. E., Somogyi, A., Herold, M., & Herold, Z. (2022) · World Journal of Diabetes · doi:10.4239/wjd.v13.i10.835 · Cited by 23 · see citing works
Yang, J. H. M., Ward‐Hartstonge, K. A., Perry, D. J., Blanchfield, J. L., Posgai, A. L., Wiedeman, A. E., Diggins, K., Rahman, A., Tree, T. I. M., Brusko, T. M., et al. (2022) · European Journal of Immunology · doi:10.1002/eji.202049067 · Cited by 16 · see citing works
A Golden Hour and Golden Opportunity for β-Cell Preservation
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- Authors
- Insel, R. A., Dunne, J. L., Atkinson, M. A., Chiang, J. L., Dabelea, D., Gottlieb, P. A., Greenbaum, C. J., Herold, K. C., Krischer, J. P., Lernmark, Å., Ratner, R. E., Rewers, M. J., Schatz, D. A., Skyler, J. S., Sosenko, J. M., & Ziegler, A.-G.
- Affiliations
- Breakthrough T1D (US)
- University of Florida (US)
- American Diabetes Association (US)
- Colorado School of Public Health (US)
- University of Colorado Health (US)
- Benaroya Research Institute (US)
- Yale University (US)
- University of South Florida (US)
- Lund University (SE)
- University of Miami (US)
- TUM Klinikum (DE)
- Corresponding author
- Insel, Richard A.
- ORCID
- Venue
- Diabetes Care
- Publisher
- American Diabetes Association
- Published
- 2015-09-15
- Volume
- 38
- Issue
- 10
- Pages
- 1964-1974
- ISSN
- 0149-5992 (ISSN-L)
- 1935-5548
- PMC
- PMC5321245
- OpenAlex
- W1942296996
- Cited by
- 1,216
- References
- 134
- Citations by year
- 2026: 149 · 2025: 182 · 2024: 139 · 2023: 151 · 2022: 124 · 2021: 132 · 2020: 82 · 2019: 89 · 2018: 71 · 2017: 50 · 2016: 42 · 2015: 4
- FWCI
- 7.05
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Diabetes Care (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Lund University Publications (Lund University) (submittedVersion)
- Site cant be reached (submittedVersion)
- PuSH - Publication Server of Helmholtz Zentrum München (submittedVersion)
- Funders
- National Institute of Diabetes and Digestive and Kidney Diseases (UC4DK106993, UC4DK097835)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Diabetes and associated disorders
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Health Sciences › Medicine › Surgery › Pancreatic function and diabetes
- Keywords
- type 1 diabetes, presymptomatic disease, disease staging, islet autoimmunity, islet autoantibodies, dysglycemia, disease prevention, precision medicine, clinical trial design, regulatory approval
- MeSH terms
- Autoantibodies, Diabetes Mellitus, Type 1, Humans, Prediabetic State, Prospective Studies, Societies, Medical, United States, Autoimmunity, Disease Progression, Genetic Predisposition to Disease, Early Diagnosis, Insulin-Secreting Cells
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