The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.
Seroconversion to Multiple Islet Autoantibodies and Risk of Progression to Diabetes in Children
Open accessAbstract
IMPORTANCE: Type 1 diabetes usually has a preclinical phase identified by circulating islet autoantibodies, but the rate of progression to diabetes after seroconversion to islet autoantibodies is uncertain. OBJECTIVE: To determine the rate of progression to diabetes after islet autoantibody seroconversion. DESIGN, SETTING, AND PARTICIPANTS: Data were pooled from prospective cohort studies performed in Colorado (recruitment, 1993-2006), Finland (recruitment, 1994-2009), and Germany (recruitment, 1989-2006) examining children genetically at risk for type 1 diabetes for the development of insulin autoantibodies, glutamic acid decarboxylase 65 (GAD65) autoantibodies, insulinoma antigen 2 (IA2) autoantibodies, and diabetes. Participants were all children recruited and followed up in the 3 studies (Colorado, 1962; Finland, 8597; Germany, 2818). Follow-up assessment in each study was concluded by July 2012. MAIN OUTCOMES AND MEASURES: The primary analysis was the diagnosis of type 1 diabetes in children with 2 or more autoantibodies. The secondary analysis was the diagnosis of type 1 diabetes in children with 1 autoantibody or no autoantibodies. RESULTS: Progression to type 1 diabetes at 10-year follow-up after islet autoantibody seroconversion in 585 children with multiple islet autoantibodies was 69.7% (95% CI, 65.1%-74.3%), and in 474 children with a single islet autoantibody was 14.5% (95% CI, 10.3%-18.7%). Risk of diabetes in children who had no islet autoantibodies was 0.4% (95% CI, 0.2%-0.6%) by the age of 15 years. Progression to type 1 diabetes in the children with multiple islet autoantibodies was faster for children who had islet autoantibody seroconversion younger than age 3 years (hazard ratio [HR], 1.65 [95% CI, 1.30-2.09; P < .001]; 10-year risk, 74.9% [95% CI, 69.7%-80.1%]) vs children 3 years or older (60.9% [95% CI, 51.5%-70.3%]); for children with the human leukocyte antigen (HLA) genotype DR3/DR4-DQ8 (HR, 1.35 [95% CI, 1.09-1.68; P = .007]; 10-year risk, 76.6% [95% CI, 69.2%-84%]) vs other HLA genotypes (66.2% [95% CI, 60.2%-72.2%]); and for girls (HR, 1.28 [95% CI, 1.04-1.58; P = .02];10-year risk, 74.8% [95% CI, 68.0%-81.6%]) vs boys (65.7% [95% CI, 59.3%-72.1%]). CONCLUSIONS AND RELEVANCE: The majority of children at risk of type 1 diabetes who had multiple islet autoantibody seroconversion progressed to diabetes over the next 15 years. Future prevention studies should focus on this high-risk population.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source doesn’t support the claim as written.
In the citing paper
“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 [408]
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Most people with a single autoantibody do not progress to type 1 diabetes, but seroconversion to the presence of two or more serum autoantibodies in children is associated with an 84% risk of clinical type 1 diabetes by the age of 18 years (figure 2A).16”
From Type 1 diabetes (2018) · cites this paper as [16]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Because of the low prevalence of type 1 diabetes (approximately 0.3% in the general population), the positive predictive value of a single islet autoantibody is low (408).”
From Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus (2023) · cites this paper as [408]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Most individuals without diabetes who have only one autoantibody will not develop type 1 diabetes, as the 10-year risk is about 15% (408).”
From Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus (2023) · cites this paper as [408]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“It is clear from prospective studies that the persistent presence of two or more islet autoantibodies is a nearcertain predictor of clinical diabetes (42).”
From 2. Diagnosis and Classification of Diabetes: Standards of Care in Diabetes—2024 (2024) · cites this paper as [42]
Experimental — accuracy not yet measured
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Of the 585 children who developed more than two autoantibodies, nearly 70% developed type 1 diabetes within 10 years and 84% within 15 years (42).”
From 2. Diagnosis and Classification of Diabetes: Standards of Care in Diabetes—2024 (2024) · cites this paper as [42]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“It is clear from prospective studies that the persistent presence of two or more islet autoantibodies is a near-certain predictor of clinical diabetes (40).”
From 2. Diagnosis and classification of diabetes: standards of care in diabetes-2025 (2025) · cites this paper as [40]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Of the 585 children who developed more than two autoantibodies, nearly 70% developed type 1 diabetes within 10 years and 84% within 15 years (40).”
From 2. Diagnosis and classification of diabetes: standards of care in diabetes-2025 (2025) · cites this paper as [40]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“A seminal analysis of four different birth cohorts from the USA, Finland and Germany demonstrated that the presence of a single islet autoantibody is associated with a 13% risk of developing type 1 diabetes over 15 years. In contrast, having two or more antibodies is associated with a 70% risk over 10 years of observation and an 84% risk over 15 years63.”
From 100 years of insulin: celebrating the past, present and future of diabetes therapy (2021) · cites this paper as [63]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“However, studies of the offspring of people with diabetes show that young children with multiple autoantibodies develop diabetes during childhood [ 12 ]”
From Islet autoantibody profiles associated with higher diabetes risk in Lithuanian compared with English schoolchildren (2020) · cites this paper as [12]
The cited source says what the claim attributes to it.
In the citing paper
“In children with only one persistent islet autoantibody, the risk of diabetes within 10 years is 15% while two or more islet autoantibodies predict type 1 diabetes in 70% within 10 years (408,409).”
From Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus (2023) · cites this paper as [408]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Eisenbarth (1986) · doi:10.1056/nejm198605223142106 · Cited by 1,659
Self-citationEffects of insulin in relatives of patients with type 1 diabetes mellitus
(2002) · New England Journal of Medicine · doi:10.1056/nejmoa012350 · Cited by 836
Ziegler, A., Hummel, M., Schenker, M., & Bonifacio, E. E. (1999) · Diabetes · doi:10.2337/diabetes.48.3.460 · Cited by 640
Self-citationGale, E. A. (2004) · The Lancet · doi:10.1016/s0140-6736(04)15786-3 · Cited by 534
Rewers, M., Bugawan, T. L., Norris, J. M., Blair, A., Beaty, B., Hoffman, M., McDuffie, R. S., Hamman, R. F., Klingensmith, G., Eisenbarth, G. S., et al. (1996) · Diabetologia · doi:10.1007/s001250050514 · Cited by 422
Self-citationNäntö-Salonen, K., Kupila, A., Simell, S., Siljander, H., Salonsaari, T., Hekkala, A., Korhonen, S., Erkkola, R., Sipilä, J. I., Haavisto, L., et al. (2008) · The Lancet · doi:10.1016/s0140-6736(08)61309-4 · Cited by 382
Self-citationQuantification of islet-cell antibodies and prediction of insulin-dependent diabetes
Bonifacio, E. E., Shattock, M., Dean, B. M., Bottazzo, G. F., Bingley, P. J., Gale, E., & Dunger, D. B. (1990) · The Lancet · doi:10.1016/0140-6736(90)90013-u · Cited by 344
Self-citationStratification 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
Self-citationOrban, 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-citationPREDICTING INSULIN-DEPENDENT DIABETES
Tarn, A., Dean, B., Schwarz, G., Thomas, J. M., Ingram, D., Bottazzo, G. F., & Gale, E. M. (1988) · The Lancet · doi:10.1016/s0140-6736(88)91601-7 · Cited by 260
Flagged first, then by citations
Cited by
Sorted by citations
Items 601–700 of 1,001
Tiberti, C., Panimolle, F., Borghini, R., Montuori, M., Trovato, C. M., Filardi, T., Lenzi, A., & Picarelli, A. (2020) · Scandinavian Journal of Gastroenterology · doi:10.1080/00365521.2020.1754898 · Cited by 16
Detecting insulitis in type 1 diabetes with ultrasound phase-change contrast agents
Ramirez, D. G., Ciccaglione, M., Upadhyay, A., Pham, V. T., Borden, M. A., & Benninger, R. K. P. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2022523118 · Cited by 13
Screening children for type 1 diabetes
Besser, R. E. J., Ng, S. M., & Robertson, E. J. (2021) · BMJ · doi:10.1136/bmj-2021-067937 · Cited by 14
Calhoun, P. M., Spanbauer, C., Steck, A. K., Frohnert, B. I., Herman, M. A., Keymeulen, B., Veijola, R., Toppari, J., Desouter, A. K., Gorus, F., et al. (2025) · Diabetologia · doi:10.1007/s00125-025-06362-1 · Cited by 12
Self-citationGuertin, K. A., Repaske, D. R., Taylor, J. F., Williams, E. S., Önengüt-Gümüşcü, S., Chen, W., Boggs, S. R., Yu, L., Allen, L., Botteon, L., et al. (2024) · Genome Medicine · doi:10.1186/s13073-024-01305-8 · Cited by 13
Cell-Surface ZnT8 Antibody Prevents and Reverses Autoimmune Diabetes in Mice
Kasinathan, D., Guo, Z., Sarver, D. C., Wong, G. W., Yun, S., Michels, A. W., Yu, L., Sona, C., Poy, M. N., Golson, M. L., et al. (2024) · Diabetes · doi:10.2337/db23-0568 · Cited by 12
Data-Driven Phenotyping of Presymptomatic Type 1 Diabetes Using Longitudinal Autoantibody Profiles
Ghalwash, M. F., Anand, V., Ng, K., Dunne, J. L., Lou, O., Lundgren, M., Hagopian, W., Rewers, M., Ziegler, A. G., Veijola, R., et al. (2024) · Diabetes Care · doi:10.2337/dc24-0198 · Cited by 16
Self-citationScudder, C. L., Townson, J. K., Gillespie, K. M., Bowen‐Morris, J., Evans, P. H., Jones, S., Thomas, N. P. B., Stanford, J., Fox, R. A., Todd, J. A., et al. (2024) · Archives of Disease in Childhood · doi:10.1136/archdischild-2023-326697 · Cited by 12
Thomson, R. L., Oakey, H., Haynes, A., Craig, M. E., Harrison, L. C., Wentworth, J. M., Anderson, A. J., Ashwood, P., Barry, S. C., Brittain, B., et al. (2024) · BMJ Open Diabetes Research & Care · doi:10.1136/bmjdrc-2024-004130 · Cited by 12
Nicholas, C. A., Tensun, F., Evans, S. A., Toole, K. P., Prendergast, J. E., BRONCUCIA, H. C., Hesselberth, J. R., Gottlieb, P. A., Wells, K. L., & Smith, M. J. (2025) · Cell Reports · doi:10.1016/j.celrep.2025.115425 · Cited by 13
Early signs of disease in type 1 diabetes
Moulder, R., & Lahesmaa, R. (2016) · Pediatric Diabetes · doi:10.1111/pedi.12329 · Cited by 14
García‐Pérez, D., Ruiz-Ortiz, M., Panero, I., Eiriz, C., Moreno, L. M., García‐Reyne, A., García, A., Martín-Medina, P., Salvador-Álvarez, E., Hernández‐Laín, A., et al. (2020) · Journal of Neuropathology & Experimental Neurology · doi:10.1093/jnen/nlaa097 · Cited by 12
Zinc transporter 8 autoantibody testing requires age-related cut-offs
Grace, S. L., Cooper, A., Jones, A. G., & McDonald, T. J. (2021) · BMJ Open Diabetes Research & Care · doi:10.1136/bmjdrc-2021-002296 · Cited by 13
Pöllänen, P. M., Härkönen, T., Ilonen, J., Toppari, J., Veijola, R., Siljander, H., & Knip, M. (2021) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/clinem/dgab816 · Cited by 12
Self-citationAssociation of High-Affinity Autoantibodies With Type 1 Diabetes High-Risk HLA Haplotypes
Triolo, T. M., Pyle, L. L., BRONCUCIA, H. C., Armstrong, T., Yu, L., Gottlieb, P. A., & Steck, A. K. (2021) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/clinem/dgab853 · Cited by 13
Self-citationThe heterogeneity of type 1 diabetes: From immunopathology to immune intervention
Infante, M., Alejandro, R., Fabbri, A., & Ricordi, C. (2022) · Elsevier eBooks · doi:10.1016/b978-0-12-824466-1.00001-7 · Cited by 12
Recognition of mRNA Splice Variant and Secretory Granule Epitopes by CD4+ T Cells in Type 1 Diabetes
Guyer, P., Arribas-Layton, D., Manganaro, A., Speake, C., Lord, S. M., Eizirik, D. L., Kent, S. C., Mallone, R., & James, E. A. (2022) · Diabetes · doi:10.2337/db22-0191 · Cited by 12
Galderisi, A., Evans‐Molina, C., Martino, M., Caprio, S., Cobelli, C., & Moran, A. (2022) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/clinem/dgac740 · Cited by 13
Islet Autoantibody Detection by Electrochemiluminescence (ECL) Assay
Gu, Y., Zhao, Z., High, H., Yang, T., & Yu, L. (2017) · Journal of Clinical & Cellular Immunology · doi:10.4172/2155-9899.1000531 · Cited by 13
Follicular T Helper Cells: A New Marker of Type 1 Diabetes Risk?
Heuts, F. W. H., Edner, N. M., & Walker, L. S. K. (2017) · Diabetes · doi:10.2337/dbi16-0062 · Cited by 12
Screening for asymptomatic β-cell autoimmunity in young children
Ziegler, A., Hoffmann, G. F., Hasford, J., Larsson, H. E., Danne, T., Berner, R., Penno, M. A. S., Koralova, A., Dunne, J. L., & Bonifacio, E. E. (2019) · The Lancet Child & Adolescent Health · doi:10.1016/s2352-4642(19)30028-8 · Cited by 12
Self-citationThe Evolution of Type 1 Diabetes
Skyler, J. S., & Sosenko, J. M. (2013) · JAMA · doi:10.1001/jama.2013.6286 · Cited by 12
Syed, F., Krishnan, P., Chang, G., Langlais, S. R., Hati, S., Yamada, K., Lam, A. K., Talware, S., Liu, X., Sardar, R., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.06.15.545170 · Cited by 12
From Prediction to Prevention: The Intricacies of Islet Autoantibodies in Type 1 Diabetes
Khine, A., & Quandt, Z. (2025) · Current Diabetes Reports · doi:10.1007/s11892-025-01595-1 · Cited by 12
Quinn, L. M., Narendran, P., Randell, M. J., Bhavra, K., Boardman, F., Greenfield, S., & Litchfield, I. J. (2023) · Diabetic Medicine · doi:10.1111/dme.15131 · Cited by 11
Antigen-specific T cell responses in autoimmune diabetes
Dwyer, A. J., Shaheen, Z. R., & Fife, B. T. (2024) · Frontiers in Immunology · doi:10.3389/fimmu.2024.1440045 · Cited by 12
microRNAs in Type 1 Diabetes: Roles, Pathological Mechanisms, and Therapeutic Potential
Cho, H., Ha, S. E., Singh, R., Kim, D., & Ro, S. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms26073301 · Cited by 12
National Asthma Education and Prevention Program 2020 Guidelines: What’s Important for Primary Care
Murphy, M. (2021) · The Journal of Family Practice · doi:10.12788/jfp.0219 · Cited by 14
Immunogenetic Epidemiology of Type 1 Diabetes in 14 Continental Western European Countries
James, L. M., & Georgopoulos, A. P. (2021) · Journal of Immunological Sciences · doi:10.29245/2578-3009/2021/3.1219 · Cited by 11
Karpen, S. R., Dunne, J. L., Frohnert, B. I., Marinac, M., Richard, C., David, S. E., & O’Doherty, I. M. (2022) · Diabetologia · doi:10.1007/s00125-022-05751-0 · Cited by 12
Kim, Y. K., Walters, J. A., Moss, N. D., Wells, K. L., Sheridan, R. M., Miranda, J. G., Benninger, R. K. P., Pyle, L. L., O’Brien, R. M., Sussel, L., et al. (2022) · Molecular Metabolism · doi:10.1016/j.molmet.2022.101632 · Cited by 11
Monitoring immunomodulation strategies in type 1 diabetes
Krishnamurthy, B., Lacorcia, M., Kay, T. W. H., Thomas, H. E., & Mannering, S. I. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1206874 · Cited by 12
Attenuated humoral responses in HLA-A*24-positive individuals at risk of type 1 diabetes
Ye, Y., Long, A. E., Pearson, J. A., Taylor, H., Bingley, P. J., Williams, A. J. K., & Gillespie, K. M. (2015) · Diabetologia · doi:10.1007/s00125-015-3702-9 · Cited by 12
Neuropeptide Y is a minor autoantigen in newly diagnosed type 1 diabetes patients
Skärstrand, H., Vaziri‐Sani, F., Delli, A. J., Törn, C., Larsson, H. E., Ivarsson, S. A., Agardh, D., Lernmark, Å., & the Skåne study group (2014) · Pediatric Diabetes · doi:10.1111/pedi.12222 · Cited by 11
Battaglia, M., Nigi, L., & Dotta, F. (2015) · Current Diabetes Reports · doi:10.1007/s11892-015-0690-6 · Cited by 11
Kawasaki, E., Oikawa, Y., Okada, A., Kanatsuna, N., Kawamura, T., Kikuchi, T., Terasaki, J., Miura, J., Itoh, Y., & Hanafusa, T. (2020) · Journal of Diabetes Investigation · doi:10.1111/jdi.13370 · Cited by 13
Kuusela, S., Keskinen, P., Pokka, T. M.-L., Knip, M., Ilonen, J., Vähäsalo, P., & Veijola, R. (2020) · Pediatric Diabetes · doi:10.1111/pedi.13122 · Cited by 11
Self-citationNovel genetic risk factors influence progression of islet autoimmunity to type 1 diabetes
Önengüt-Gümüşcü, S., Paila, U., Chen, W., Ratan, A., Zhu, Z., Steck, A. K., Frohnert, B. I., Waugh, K., Webb‐Robertson, B., Norris, J. M., et al. (2020) · Scientific Reports · doi:10.1038/s41598-020-75690-6 · Cited by 11
Self-citationType 1 diabetes mellitus and its oral tolerance therapy
Mao, R., Chen, Y., Zhang, J., Chang, X., & Wang, Y. (2020) · World Journal of Diabetes · doi:10.4239/wjd.v11.i10.400 · Cited by 11
Argyropoulos, T., Korakas, E., Gikas, A., Kountouri, A., Kostaridou, S., Raptis, A. E., & Lambadiari, V. (2021) · Frontiers in Pediatrics · doi:10.3389/fped.2021.670976 · Cited by 11
Insulin immunotherapy for pretype 1 diabetes
Jacobsen, L. M., & Schatz, D. (2021) · Current Opinion in Endocrinology Diabetes and Obesity · doi:10.1097/med.0000000000000648 · Cited by 11
the DiAPREV-IT study group, Larsson, H. E., Larsson, C., & Lernmark, Å. (2014) · Acta Diabetologica · doi:10.1007/s00592-014-0680-1 · Cited by 11
Characterizing Subgroups of Type 1 Diabetes
Skyler, J. S. (2014) · Diabetes · doi:10.2337/db14-1160 · Cited by 13
Emerging Biomarkers and Nanobiosensing Strategies in Diabetes
Baranwal, A., Bansal, V., & Shukla, R. (2025) · Biosensors · doi:10.3390/bios15100639 · Cited by 14
Hussain, S., Tree, T. I. M., Mathieu, C., Klupa, T., Tuomaala, A., de Wit, M. V. M., Kordonouri, O., Braune, K., Pall, J., Castano, L., et al. (2026) · Diabetes Obesity and Metabolism · doi:10.1111/dom.70569 · Cited by 11
The relationship between GAD65 autoantibody and the risk of T1DM onset
Keshavarzi, E., Noveiry, B. B., & Rezaei, N. (2022) · Journal of Diabetes & Metabolic Disorders · doi:10.1007/s40200-022-01098-w · Cited by 11
Effective assay technologies fit for large-scale population screening of type 1 diabetes
Jia, X., & Yu, L. (2023) · Frontiers in Clinical Diabetes and Healthcare · doi:10.3389/fcdhc.2022.1034698 · Cited by 10
Li, J., Liu, J., Shi, W., & Guo, J. (2024) · Medicine · doi:10.1097/md.0000000000037844 · Cited by 10
Quinn, L. M., Dias, R. P., Bidder, C., Bhowmik, S., Bumke, K., Ganapathi, J., Gorman, S., Hind, E., Karandikar, S., Kumar, K. B., et al. (2024) · BMJ Open Diabetes Research & Care · doi:10.1136/bmjdrc-2024-004480 · Cited by 16
Emerging Concepts and Success Stories in Type 1 Diabetes Research: A Road Map for a Bright Future
Mallone, R., Sims, E. K., Achenbach, P., Mathieu, C., Pugliese, A., Atkinson, M. A., Dutta, S., Evans‐Molina, C., Klatzmann, D., Koralova, A., et al. (2024) · Diabetes · doi:10.2337/db24-0439 · Cited by 10
Self-citationEvaluation of Candidate Biomarkers of Type 1 Diabetes via the Core for Assay Validation
Speake, C., & Odegard, J. (2015) · Biomarker Insights · doi:10.4137/bmi.s29697 · Cited by 10
Zhao, L. P., Skyler, J. S., Papadopoulos, G. K., Pugliese, A., Najera, J. A., Bondinas, G. P., Moustakas, A. K., Wang, R., Pyo, C., Nelson, W. C., et al. (2022) · Diabetes Care · doi:10.2337/dc21-1628 · Cited by 11
Kwon, B. C., Achenbach, P., Anand, V., Frohnert, B. I., Hagopian, W., Hu, J., Koski, E., Lernmark, Å., Lou, O., Martin, F., et al. (2022) · Diabetes · doi:10.2337/db22-0360 · Cited by 10
Self-citationIntegrated Physiology of the Exocrine and Endocrine Compartments in Pancreatic Diseases
Mastracci, T. L., Apte, M. V., Amundadottir, L. T., Alvarsson, A., Artandi, S. E., Bellin, M. D., Bernal‐Mizrachi, E., Caicedo, A., Campbell‐Thompson, M., Cruz‐Monserrate, Z., et al. (2022) · Pancreas · doi:10.1097/mpa.0000000000002170 · Cited by 10
Effects of the genome on immune regulation in type 1 diabetes
Pociot, F., Kaur, S., & Nielsen, L. B. (2016) · Pediatric Diabetes · doi:10.1111/pedi.12336 · Cited by 10
Simmons, K. M., Fouts, A., Pyle, L. L., Clark, P. L., Dong, F., Yu, L., Usmani‐Brown, S., Gottlieb, P. A., Herold, K. C., Steck, A. K., et al. (2019) · International Journal of Molecular Sciences · doi:10.3390/ijms20163857 · Cited by 10
Self-citationTiming of Immunotherapy in Type 1 Diabetes: The Earlier, the Better?
Felton, J. L. (2021) · ImmunoHorizons · doi:10.4049/immunohorizons.2000105 · Cited by 10
Exocrine pancreas function is impaired in adult relatives of patients with type 1 diabetes
Giovenzana, A., Vecchio, F., Cugnata, F., Nonis, A., Mandelli, A., Stabilini, A., Mazzi, B. A., Pellegrin, M. D., Laurenzi, A., Bonfanti, R., et al. (2021) · Acta Diabetologica · doi:10.1007/s00592-021-01819-2 · Cited by 10
Podichetty, J. T., Lang, P. M., O’Doherty, I. M., David, S. E., Muse, R., Karpen, S. R., Song, L. S., Romero, K., & Burton, J. K. (2022) · Clinical Pharmacology & Therapeutics · doi:10.1002/cpt.2559 · Cited by 10
Kanatsuna, N., Delli, A. J., Andersson, C. K., Nilsson, A. ‐., Vaziri‐Sani, F., Larsson, K., Carlsson, A., Cedervall, E., Jönsson, B., Neiderud, J., et al. (2015) · Scandinavian Journal of Immunology · doi:10.1111/sji.12325 · Cited by 10
Arif, Z., Neelofar, K., Arfat, M. Y., Zaman, A., Tarannum, A., Parveen, I., Ahmad, S., Khan, M. A., Badar, A., & Islam, S. N. (2017) · International Journal of Biological Macromolecules · doi:10.1016/j.ijbiomac.2017.10.091 · Cited by 11
Regulation of T Follicular Helper Cells in Islet Autoimmunity
Serr, I., & Daniel, C. (2018) · Frontiers in Immunology · doi:10.3389/fimmu.2018.01729 · Cited by 10
Kick, K., Assfalg, R., Aydin, S., Pozza, S. B., Böcker, D., Braig, S., Bunk, M., Dunstheimer, D., Durmashkina, A., Ermer, U., et al. (2018) · Contemporary Clinical Trials Communications · doi:10.1016/j.conctc.2018.08.004 · Cited by 10
Self-citationAllostasis and the origins of adult-onset diabetes
Leslie, R. D., & Vartak, T. (2019) · Diabetologia · doi:10.1007/s00125-019-05048-9 · Cited by 10
Toward Primary Prevention of Type 1 Diabetes
Skyler, J. S. (2015) · JAMA · doi:10.1001/jama.2015.2054 · Cited by 10
Hassan, M. H., Galal, O., Sakhr, H. M., Kamaleldeen, E. B., Zekry, N. F., Fateen, E., & Toghan, R. (2023) · Biomedical Chromatography · doi:10.1002/bmc.5747 · Cited by 9
Oron, T., Cortez, F. D. J., Shtaif, B., Robinson, P. V., Yackobovitch‐Gavan, M., Tandel, D., Seftel, D., Phillip, M., Tsai, C., & Gat‐Yablonski, G. (2024) · Pediatric Diabetes · doi:10.1155/2024/4238394 · Cited by 9
The Current Landscape for Screening and Monitoring of Early‐Stage Type 1 Diabetes
Narayan, K., Mikler, K., Maguire, A., Craig, M. E., & Bell, K. J. (2025) · Journal of Paediatrics and Child Health · doi:10.1111/jpc.70016 · Cited by 10
Besser, R. E. J., Campbell, F., Damazer, K., Elleri, D., Gillespie, K. M., Hambling, C. E., Martin, R., Mehta, F., Millar, S., Sachdev, P., et al. (2025) · Diabetic Medicine · doi:10.1111/dme.70117 · Cited by 10
Kick, K., Hoffmann, V. S., Lange, K., Lang, M., Laub, O., Pozza, S. B., Böcker, D., Braig, S., Dietz, B., Dunstheimer, D., et al. (2018) · Journal of Public Health · doi:10.1007/s10389-018-0981-x · Cited by 9
Self-citationFelton, J. L., Cuthbertson, D. D., WARNOCK, M. V., Lohano, K., Meah, F. A., Wentworth, J. M., Sosenko, J. M., Evans‐Molina, C., & for the Type 1 Diabetes TrialNet Study Group (2021) · Diabetologia · doi:10.1007/s00125-021-05573-6 · Cited by 9
100 years post-insulin: immunotherapy as the next frontier in type 1 diabetes
Pearson, J. A., McKinney, E. F., & Walker, L. S. K. (2021) · Immunotherapy Advances · doi:10.1093/immadv/ltab024 · Cited by 9
A Monovalent Mt10-CVB3 Vaccine Prevents CVB4-Accelerated Type 1 Diabetes in NOD Mice
Rasquinha, M. T., Lasrado, N., Sur, M., Mone, K., Qiu, H., Riethoven, J.-J. M., Sobel, R. A., & Reddy, J. (2022) · Vaccines · doi:10.3390/vaccines11010076 · Cited by 11
Vandewalle, J., Desouter, A. K., der Auwera, B. J. R. V., Tenoutasse, S., Gillard, P., Block, C. E. M. D., Keymeulen, B., Gorus, F., de Casteele, M. V., & the Belgian Diabetes Registry (2023) · Clinical & Experimental Immunology · doi:10.1093/cei/uxad002 · Cited by 9
Önengüt-Gümüşcü, S., Webb‐Robertson, B., Sarkar, S., Manichaikul, A. W., Hu, X., Frazer‐Abel, A. A., Holers, V. M., Rewers, M., & Rich, S. S. (2023) · Diabetes/Metabolism Research and Reviews · doi:10.1002/dmrr.3716 · Cited by 8
Self-citationWei, Y., Edstorp, J., Feychting, M., Andersson, T., & Carlsson, S. (2023) · The Lancet Regional Health - Europe · doi:10.1016/j.lanepe.2023.100775 · Cited by 10
Hummel, S., Rosenberger, S., Berge, T. V. D., Besser, R. E. J., Casteels, K., Hommel, A., Kordonouri, O., Larsson, H. E., Lundgren, M., Marcus, B. A., et al. (2024) · Diabetologia · doi:10.1007/s00125-023-06079-z · Cited by 10
Self-citationUntangling the genetics of beta cell dysfunction and death in type 1 diabetes
Robertson, C. C., Elgamal, R. M., Henry-Kanarek, B. A., Arvan, P., Chen, S., Dhawan, S., Eizirik, D. L., Kaddis, J. S., Vahedi, G., Parker, S. C. J., et al. (2024) · Molecular Metabolism · doi:10.1016/j.molmet.2024.101973 · Cited by 12
Have we pushed the needle for treatment of Type 1 diabetes?
Naushad, N., Perdigoto, A. L., Rui, J., & Herold, K. C. (2017) · Current Opinion in Immunology · doi:10.1016/j.coi.2017.09.004 · Cited by 9
100 YEARS OF INSULIN: Arresting or curing type 1 diabetes: an elusive goal, but closing the gap
Martens, P.-J., Gysemans, C. A., & Mathieu, C. (2021) · Journal of Endocrinology · doi:10.1530/joe-20-0552 · Cited by 8
Carry, P. M., Vanderlinden, L. A., Johnson, R. K., Buckner, T., Fiehn, O., Steck, A. K., Kechris, K. J., Yang, I. V., Fingerlin, T. E., Rewers, M., et al. (2021) · Diabetes · doi:10.2337/db20-1251 · Cited by 10
Self-citationOvercoming Obstacles in the Development of Antigen-Specific Immunotherapies for Type 1 Diabetes
Thomas, R., Carballido, J. M., Wesley, J. D., & Ahmed, S. T. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.730414 · Cited by 9
Clinical and experimental treatment of type 1 diabetes
Long, S. A., & Buckner, J. H. (2022) · Clinical & Experimental Immunology · doi:10.1093/cei/uxac077 · Cited by 9
Translational immunology: Applying fundamental discoveries to human health and autoimmune diseases
Buckner, J. H. (2023) · European Journal of Immunology · doi:10.1002/eji.202250197 · Cited by 11
Definition, Klassifikation, Diagnostik und Differenzialdiagnostik des Diabetes mellitus: Update 2023
Pleus, S., Tytko, A., Landgraf, R., Heinemann, L., Werner, C., Müller‐Wieland, D., Ziegler, A., Müller, U., Freckmann, G., Kleinwechter, H. J., et al. (2023) · Diabetologie und Stoffwechsel · doi:10.1055/a-2075-9943 · Cited by 9
Self-citationKoskinen, M. K., Lempainen, J., Löyttyniemi, E., Helminen, O., Hekkala, A., Härkönen, T., Kiviniemi, M., Simell, O., Knip, M., Ilonen, J., et al. (2017) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2017-02040 · Cited by 9
Self-citationA Question of Tolerance—Antigen-Specific Immunotherapy for Type 1 Diabetes
Naranjo, J. D. L., Bergot, A., Buckle, I., & Hamilton‐Williams, E. E. (2020) · Current Diabetes Reports · doi:10.1007/s11892-020-01363-3 · Cited by 9
The extra-islet pancreas supports autoimmunity in human type 1 diabetesPreprint
Barlow, G. L., Schürch, C. M., Bhate, S. S., Phillips, D. J., Young, A., Dong, S., Martinez, H. A., Kaber, G., Nagy, N., Ramachandran, S., et al. (2024) · eLife · doi:10.7554/elife.100535 · Cited by 12
Martinenghi, S., Merolla, A., Grogan, P., Bianconi, E., Senni, E., Goncharova, A., Massara, F., Ragogna, F., Bazzigaluppi, E., Pastore, M. R., et al. (2025) · Diabetologia · doi:10.1007/s00125-025-06461-z · Cited by 13
Danese, E., Piona, C. A., Rizza, M., Tiziani, E., Pighi, L., Morotti, E., Salvagno, G. L., Mattiuzzi, C., Maffeis, C., & Lippi, G. (2025) · Diagnostics · doi:10.3390/diagnostics15131695 · Cited by 9
Chen, Y., Wang, X., & Duan, S. (2026) · Frontiers in Endocrinology · doi:10.3389/fendo.2025.1679751 · Cited by 9
Continuous glucose monitoring as a tool in early-stage type 1 diabetes
Carr, A. L. J., Sutton, H., Agesen, R. M., Bonifacio, E., Bosi, E., Gillard, P., Swaby, R., Vercauteren, J., & Besser, R. E. J. (2026) · Diabetologia · doi:10.1007/s00125-026-06707-4 · Cited by 8
Self-citationScreening Children for Early-Stage Type 1 Diabetes
Winkler, C., Friedl, N., Abt, R., Ackermann, K., Bently, J., Braig, S., Brämswig, S., Dunstheimer, D., Ermer, U., Ewald, D., et al. (2026) · JAMA · doi:10.1001/jama.2026.6085 · Cited by 9
Self-citationSteenbuck, N., Damond, N., Engler, S., Kusmartseva, I., Posgai, A. L., Drotar, D. M., Williams, M. D., de Souza, N., Brusko, T. M., Brusko, M., et al. (2026) · Nature Metabolism · doi:10.1038/s42255-026-01559-z · Cited by 12
Loss of β-cell mass — an acute event before T1DM presentation?
Knip, M. (2017) · Nature Reviews Endocrinology · doi:10.1038/nrendo.2017.33 · Cited by 8
Self-citationA stochastic epigenetic Mendelian oligogenic disease model for type 1 diabetes
Alper, C. A., Larsen, C. E., Trautwein, M. R., & Alford, D. R. (2018) · Journal of Autoimmunity · doi:10.1016/j.jaut.2018.09.006 · Cited by 8
Cari, L., Montanucci, P., Basta, G., Petrillo, M. G., Ricci, E., Pescara, T., Greco, A., Cipriani, S., Shimizu, J., Migliorati, G., et al. (2020) · Diabetes · doi:10.2337/db19-0087 · Cited by 8
Oakey, H., Giles, L. C., Thomson, R. L., Cao, K. L., Ashwood, P., Brown, J. D., Knight, E. J., Barry, S. C., Craig, M. E., Colman, P. G., et al. (2023) · Annals of Medicine · doi:10.1080/07853890.2023.2198255 · Cited by 11
Mistry, S., Gouripeddi, R., Raman, V. S., & Facelli, J. C. (2023) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2023.104385 · Cited by 8
Evaluation of plasma IL-21 as a potential biomarker for type 1 diabetes progression
Schroderus, A., Poorbaugh, J., McElyea, S. D., Beasley, S., Zhang, L., Näntö‐Salonen, K., Rintamäki, R. M., Pihlajamäki, J., Knip, M., Veijola, R., et al. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1157265 · Cited by 8
Self-citation
Metadata
- Authors
- Ziegler, A. G., Rewers, M., Simell, O., Simell, T., Lempainen, J., Steck, A., Winkler, C., Ilonen, J., Veijola, R., Knip, M., Bonifacio, E., & Eisenbarth, G. S.
- Affiliations
- TUM Klinikum (DE)
- University of Helsinki (FI)
- ORCID
- Venue
- JAMA
- Publisher
- American Medical Association (AMA)
- Published
- 2013-06-19
- Volume
- 309
- Issue
- 23
- Pages
- 2473
- ISSN
- 0002-9955 (ISSN-L)
- 0098-7484
- PMC
- PMC4878912
- OpenAlex
- W2095256598
- Semantic Scholar
- 5a7a8cb24a1d4a727e23b19c717a8328b3ce09d6
- Cited by
- 1,312
- References
- 29
- Citations by year
- 2026: 118 · 2025: 133 · 2024: 103 · 2023: 124 · 2022: 107 · 2021: 127 · 2020: 83 · 2019: 92 · 2018: 92 · 2017: 86 · 2016: 89 · 2015: 83 · 2014: 55 · 2013: 18
- FWCI
- 54.19
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- JAMA (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- mediaTUM (Technical University of Munich) (submittedVersion)
- Site cant be reached (submittedVersion)
- Funders
- Juvenile Diabetes Research Foundation International (4‐1999‐731, 4‐2001‐435)
- Deutsche Forschungsgemeinschaft (/14-2, /14-1)
- Bundesministerium für Bildung und Forschung
- Novo Nordisk
- Lastentautien Tutkimussäätiö
- National Institutes of Health (DK32493)
- National Institute of Diabetes and Digestive and Kidney Diseases (R01DK32493, R01DK032493, U01DK063821)
- 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
- type 1 diabetes, islet autoantibodies, seroconversion, multiple autoantibodies, progression to diabetes, insulin autoantibodies, GAD65 antibodies, IA-2 autoantibodies, preclinical diabetes, risk prediction, age at seroconversion, islet transplantation
- MeSH terms
- Adolescent, Autoantibodies, Child, Child, Preschool, Colorado, Diabetes Mellitus, Type 1, Female, Finland, Follow-Up Studies, Genotype, Germany, Glutamate Decarboxylase, Humans, Infant, Insulin, Islets of Langerhans, Male, Prospective Studies, Risk, Disease Progression, Genetic Predisposition to Disease, Receptor-Like Protein Tyrosine Phosphatases, Class 8
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
