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The risk of progression to type 1 diabetes is highly variable in individuals with multiple autoantibodies following screening
Open accessAbstract
Aims/hypothesis Young children who develop multiple autoantibodies (mAbs) are at very high risk for type 1 diabetes. We assessed whether a population with mAbs detected by screening is also at very high risk, and how risk varies according to age, type of autoantibodies and metabolic status. Methods Type 1 Diabetes TrialNet Pathway to Prevention participants with mAbs ( n = 1815; age, 12.35 ± 9.39 years; range, 1–49 years) were analysed. Type 1 diabetes risk was assessed according to age, autoantibody type/number (insulin autoantibodies [IAA], glutamic acid decarboxylase autoantibodies [GADA], insulinoma-associated antigen-2 autoantibodies [IA-2A] or zinc transporter 8 autoantibodies [ZnT8A]) and Index60 (composite measure of fasting C-peptide, 60 min glucose and 60 min C-peptide). Cox regression and cumulative incidence curves were utilised in this cohort study. Results Age was inversely related to type 1 diabetes risk in those with mAbs (HR 0.97 [95% CI 0.96, 0.99]). Among participants with 2 autoantibodies, those with GADA had less risk (HR 0.35 [95% CI 0.22, 0.57]) and those with IA-2A had higher risk (HR 2.82 [95% CI 1.76, 4.51]) of type 1 diabetes. Those with IAA and GADA had only a 17% 5 year risk of type 1 diabetes. The risk was significantly lower for those with Index60 <1.0 (HR 0.23 [95% CI 0.19, 0.30]) vs those with Index60 values ≥1.0. Among the 12% (225/1815) ≥12.0 years of age with GADA positivity, IA-2A negativity and Index60 <1.0, the 5 year risk of type 1 diabetes was 8%. Conclusions/interpretation Type 1 diabetes risk varies substantially according to age, autoantibody type and metabolic status in individuals screened for mAbs. An appreciable proportion of older children and adults with mAbs appear to have a low risk of progressing to type 1 diabetes at 5 years. With this knowledge, clinical trials of type 1 diabetes prevention can better target those most likely to progress.
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“The presence of multiple islet autoantibodies (IAA, GADA, IA-2A/IA-2bA, or ZnT8A) is associated with a risk of type 1 diabetes of >90% (408,422,423).”
From Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus (2023) · cites this paper as [422]
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Seroconversion to multiple islet autoantibodies and risk of progression to diabetes in children
Ziegler, A. G., Rewers, M., Simell, O., Simell, T., Lempainen, J., Steck, A., Winkler, C., Ilonen, J., Veijola, R., Knip, M., et al. (2013) · JAMA · doi:10.1001/jama.2013.6285 · Cited by 1,312
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., et al. (2015) · Diabetes Care · doi:10.2337/dc15-1419 · Cited by 1,216
Self-citationZiegler, A., Hummel, M., Schenker, M., & Bonifacio, E. E. (1999) · Diabetes · doi:10.2337/diabetes.48.3.460 · Cited by 640
Bonifacio, E., Yu, L., Williams, A. K., Eisenbarth, G. S., Bingley, P. J., Marcovina, S. M., Adler, K., Ziegler, A. G., Mueller, P. W., Schatz, D. A., et al. (2010) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2010-0293 · Cited by 291
Stratification of Type 1 Diabetes Risk on the Basis of Islet Autoantibody Characteristics
Achenbach, P., Warncke, K., Reiter, J., Naserke, H. E., Williams, A. J. K., Bingley, P. J., Bonifacio, E. E., & Ziegler, A. (2004) · Diabetes · doi:10.2337/diabetes.53.2.384 · Cited by 276
Orban, T., Sosenko, J. M., Cuthbertson, D., Krischer, J. P., Skyler, J. S., Jackson, R., Yu, L., Palmer, J. P., Schatz, D., Eisenbarth, G., et al. (2009) · Diabetes Care · doi:10.2337/dc09-0934 · Cited by 260
Self-citationMahon, J. L., Sosenko, J. M., Rafkin‐Mervis, L., Krause-Steinrauf, H. J., Lachin, J. M., Thompson, C. M., Bingley, P. J., Bonifacio, E. E., Palmer, J. P., Eisenbarth, G. S., et al. (2008) · Pediatric Diabetes · doi:10.1111/j.1399-5448.2008.00464.x · Cited by 203
Self-citationKrischer, J. P., Lynch, K. F., Lernmark, Å., Hagopian, W., Rewers, M., She, J., Toppari, J., Ziegler, A., Akolkar, B., & the TEDDY Study Group (2017) · Diabetes Care · doi:10.2337/dc17-0238 · Cited by 189
Steck, A. K., Vehik, K., Bonifacio, E., Lernmark, A., Ziegler, A.-G., Hagopian, W. A., She, J., Simell, O., Akolkar, B., Krischer, J., et al. (2015) · Diabetes Care · doi:10.2337/dc14-2426 · Cited by 185
REDONDO, M. J., Geyer, S. M., Steck, A. K., Sharp, S. A., Wentworth, J. M., Weedon, M. N., Antinozzi, P. A., Sosenko, J. M., Atkinson, M. A., Pugliese, A., et al. (2018) · Diabetes Care · doi:10.2337/dc18-0087 · Cited by 179
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Leeman, T., Richardson, K. P., Tran, P. M. H., & Purohit, S. B. (2022) · IntechOpen eBooks · doi:10.5772/intechopen.108248 · Cited by 2
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REDONDO, M. J., Harrall, K. K., Glueck, D. H., Tosur, M., Uysal, S., MUIR, A. B., Atkinson, E. G., Shapiro, M. R., Yu, L., Winter, W. E., et al. (2023) · Diabetes/Metabolism Research and Reviews · doi:10.1002/dmrr.3744 · Cited by 2
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Soliman, N. A., Soliman, A. T., Ahmed, S., Alyafei, F., AlHumaidi, N., Hamed, N., Alaaraj, N., Yassin, D. K., & Elawwa, A. (2026) · Journal of Pediatric Endocrinology and Diabetes · doi:10.25259/jped_56_2025 · Cited by 1
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Tall, S., Turtinen, M., Parviainen, A., Virtanen, J. M. E., But, A., Härkönen, T., Hepojoki, J., Sironen, T., Iheozor-Ejiofor, R. P., Uğurlu, H., et al. (2026) · PLoS Medicine · doi:10.2139/ssrn.4813676 · Cited by 1
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Akel, O., & Lernmark, Å. (2024) · Wiley eBooks · doi:10.1002/9781119697473.ch14
Alcazar, O., Chuang, S.-T., Ren, G., Ogihara, M., Webb‐Robertson, B., Nakayasu, E. S., Buchwald, P., & Abdulreda, M. H. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.02.09.579673
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Rumano, M., & Sheme, K. (2024) · Journal of Biological Studies · doi:10.62400/jbs.v7i2.9967
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Cebada, A. B., Silva, J. B. Q., Escobar-Morreale, H. F., & Chávez, L. N. (2024) · Medicine - Programa de Formación Médica Continuada Acreditado · doi:10.1016/j.med.2024.10.001
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Rekha, A., Afzal, M., Babu, M. A., Pandey, S. N., Gupta, G., Mishra, R., Raina, D., & Imran, M. (2025) · Clinica Chimica Acta · doi:10.1016/j.cca.2025.120783 · Cited by 1
Sarkar, S., Elliott, E. C., Henry, H. R., Ludovico, I. D., Melchior, J., Frazer‐Abel, A. A., Webb-Robertson, B.-J., Davidson, W. S., Holers, V. M., Rewers, M. J., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26618692
Type 1 diabetes: early diagnosis and treatment prospects
Алимова, И. Л. (2025) · Rossiyskiy Vestnik Perinatologii i Pediatrii (Russian Bulletin of Perinatology and Pediatrics) · doi:10.21508/1027-4065-2025-70-6-5-10
Marzinotto, I., Bazzigaluppi, E., Brigatti, C., Martinenghi, S., Laurenzi, A., ́Ancona, G. D., Angiulli, S., Borgonovo, E., Spanò, A., Pata, G., et al. (2026) · Diabetologia · doi:10.1007/s00125-026-06680-y
Going From Stage 2 to Stage 3 Type 1 Diabetes—Does Not Matter How You Got Here
Jacobsen, L. M., & Sims, E. K. (2026) · Diabetes Care · doi:10.2337/dci25-0118
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Nagarapu, A. N., & Felton, J. L. (2025) · JCEM Case Reports · doi:10.1210/jcemcr/luaf317
Carré, A. (2022) · theses.fr (ABES) · doi:10.70675/28c85b2dz490az44c1zbbc4z061ea62b1e33
Sims, E. K., Skyler, J. S., Jacobsen, L. M., Ismail, H. M., REDONDO, M. J., Nathan, B. M., Cuthbertson, D., & Sosenko, J. M. (2026) · Diabetes Care · doi:10.2337/dci26-0022 · Cited by 1
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Pillai, S. S., Mozumdar, K., & Ashraf, A. P. (2026) · Contemporary Endocrinology · doi:10.1007/978-3-032-17036-1_13
Milicic, T. J., Lalic, N. M., & Jotić, A. (2026) · Diabetology · doi:10.3390/diabetology7050091
Spotlight on the Pathology of Type 1 Diabetes
Ling, E. M., Lemos, J. R. N., Quesada‐Masachs, E., Hirani, K., & von Herrath, M. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-11985-9.00016-0
Abujlambo, A. I., Nabaa, S., Woldemeskel, M., Cutaia, J., Zaidi, M., Ferdous, S., Aung, T., Asfand, S., War, N. N. W., Pulpandi, S., et al. (2026) · The Egyptian Journal of Internal Medicine · doi:10.1186/s43162-026-00687-y
González-Saitz, A., & Kaser, S. (2026) · Frontiers in Endocrinology · doi:10.3389/fendo.2026.1874930
Wyatt, R. C., Brigatti, C., Grace, S. L., Williams, C. L., Marzinotto, I., Gillard, B. T., Bazzigaluppi, E., Shoemark, D. K., Chandler, M. A. ‐., Achenbach, P., et al. (2026) · Diabetic Medicine · doi:10.1111/dme.70471
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Bonifacio, E. (2026) · Diabetologie und Stoffwechsel · doi:10.1055/a-2907-3214
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Galderisi, A., & Bismuth, É. (2026) · Médecine des Maladies Métaboliques · doi:10.1016/j.mmm.2026.09.027
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Eizirik, D. L., Martín-Vázquez, E., Roca-Rivada, A., & Yi, X. (2026) · Nature Reviews Endocrinology · doi:10.1038/s41574-026-01312-2
Metadata
- Authors
- Jacobsen, 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., Boulware, D., Geyer, S., & Sosenko, J. M.
- Affiliations
- University of Florida Health (US)
- University of South Florida (US)
- Indiana University Indianapolis (US)
- Columbia University Irving Medical Center (US)
- Stanford Medicine (US)
- Vanderbilt University Medical Center (US)
- The Royal Melbourne Hospital (AU)
- University of Miami (US)
- Corresponding author
- Jacobsen, Laura M.
- ORCID
- Venue
- Diabetologia
- Published
- 2019-11-25
- Volume
- 63
- Issue
- 3
- Pages
- 588-596
- ISSN
- 0012-186X (ISSN-L)
- 1432-0428
- PMC
- PMC7229995
- OpenAlex
- W2989794873
- Semantic Scholar
- 2d90c1dba261fa6bccc29d5b520df39827c2c14a
- Cited by
- 133
- References
- 35
- Citations by year
- 2026: 20 · 2025: 29 · 2024: 25 · 2023: 25 · 2022: 14 · 2021: 14 · 2020: 6
- FWCI
- 5.12
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Diabetologia (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Minerva Access (University of Melbourne) (submittedVersion)
- IUScholarWorks (Indiana University) (submittedVersion)
- Funders
- TrialNet is supported by NIH and JDRF (U01 DK107013, U01 DK107014, UC4 DK106993, JDRF)
- 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 › Endocrinology, Diabetes and Metabolism › Pancreatic function and diabetes
- Keywords
- multiple autoantibodies, disease progression risk, autoantibody detection, insulin autoantibodies, glutamic acid decarboxylase antibodies, IA-2 autoantibodies, zinc transporter 8 autoantibodies, C-peptide, age as risk factor, young children, TrialNet
- MeSH terms
- Adolescent, Adult, Autoantibodies, Autoimmune Diseases, Child, Child, Preschool, Diabetes Mellitus, Type 1, Female, Follow-Up Studies, Glucose Tolerance Test, Humans, Individuality, Infant, Male, Mass Screening, Middle Aged, Monitoring, Physiologic, Prediabetic State, Prognosis, Risk Factors, Cohort Studies, Disease Progression, Genetic Predisposition to Disease, Young Adult
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