The DOI matches its Crossref record; 101 of the 101 references it cites were found in a registry or an index.
Prediction and Pathogenesis in Type 1 Diabetes
Open accessAbstract
A combination of genetic and immunological features is useful for prediction of autoimmune diabetes. Patterns of immune response correspond to the progression from a preclinical phase of disease to end-stage islet damage, with biomarkers indicating transition from susceptibility to active autoimmunity, and to a final loss of immune regulation. Here, we review the markers that provide evidence for immunological checkpoint failure and that also provide tools for assessment of individualized disease risk. When viewed in the context of genetic variation that influences immune response thresholds, progression from susceptibility to overt disease displays predictable modalities of clinical presentation resulting from a sequential series of failed homeostatic checkpoints for selection and activation of immunity.
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 says what the claim attributes to it.
In the citing paper
“More than 90% of individuals with newly diagnosed type 1 diabetes have one or more of the following autoantibodies at disease onset:53 those reactive to insulin (IAA), glutamic acid decarboxylase (GADA), insulinoma-associated autoantigen 2 (IA2A), and zinc transporter 8 (ZnT8A).65”
From Type 1 diabetes (2014) · cites this paper as [65]
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
Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls
The Wellcome Trust Case Control Consortium, Management Committee, Burton, P. R., Clayton, D. G., Cardon, L. R., Craddock, N., Deloukas, P., Duncanson, A., Kwiatkowski, D. P., McCarthy, M. I., et al. (2007) · Nature · doi:10.1038/nature05911 · Cited by 9,442
Baekkeskov, S., Aanstoot, H.-J., Christgai, S., Reetz, A., Solimena, M., Cascalho, M., Folli, F., Richter-Olesen, H., & Camilli, P.-D. (1990) · Nature · doi:10.1038/347151a0 · Cited by 1,964
Wildin, R. S., Ramsdell, F., Peake, J., Faravelli, F., Casanova, J., Buist, N. R. M., Levy‐Lahad, E., Mazzella, M., Goulet, O., Perroni, L., et al. (2001) · Nature Genetics · doi:10.1038/83707 · Cited by 1,916
Begovich, A. B., Carlton, V. E. H., Honigberg, L. A., Schrodi, S. J., Chokkalingam, A. P., Alexander, H. C., Ardlie, K., Huang, Q., Smith, A. M., Spoerke, J. M., et al. (2004) · The American Journal of Human Genetics · doi:10.1086/422827 · Cited by 1,501
A functional variant of lymphoid tyrosine phosphatase is associated with type I diabetes
Bottini, N., Musumeci, L., Alonso, A., Rahmouni, S., Nika, K., Rostamkhani, M., MacMurray, J. P., Meloni, T., Lucarelli, P., Pellecchia, M., et al. (2004) · Nature Genetics · doi:10.1038/ng1323 · Cited by 1,419
The International Consortium for Systemic Lupus Erythematosus Genetics (SLEGEN), Harley, J. B., Alarcón-Riquelme, M. E., Criswell, L. A., Jacob, C. O., Kimberly, R. P., Moser, K. L., Tsao, B. P., Vyse, T. J., & Langefeld, C. D. (2008) · Nature Genetics · doi:10.1038/ng.81 · Cited by 1,309
Insulin antibodies in insulin-dependent diabetics before insulin treatment
Palmer, J. P., Asplin, C. M., Clemons, P., Lyen, K., Tatpati, O., Raghu, P. K., & Paquette, T. L. (1983) · Science · doi:10.1126/science.6362005 · Cited by 1,078
The cation efflux transporter ZnT8 (Slc30A8) is a major autoantigen in human type 1 diabetes
Wenzlau, J. M., Juhl, K., Yu, L., Moua, O., Sarkar, S. A., Gottlieb, P., Rewers, M., Eisenbarth, G. S., Jensen, J., Davidson, H. W., et al. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0705894104 · Cited by 1,014
Incidence of diabetes in youth in the United States
SEARCH for Diabetes in Youth Study Group*, T. W. G. F. T. (2007) · JAMA · doi:10.1001/jama.297.24.2716 · Cited by 991
Pugliese, A., Zeller, M., Fernandez, A., Zalcberg, L. J., Bartlett, R. J., Ricordi, C., Pietropaolo, M., Eisenbarth, G. S., Bennett, S. T., & Patel, D. D. (1997) · Nature Genetics · doi:10.1038/ng0397-293 · Cited by 945
Flagged first, then by citations
Cited by
Sorted by citations
Items 301–344 of 344
Serr, I., & Daniel, C. (2018) · Der Diabetologe · doi:10.1007/s11428-018-0340-0
Lyu, J. (2019) · Carolina Digital Repository (University of North Carolina at Chapel Hill) · doi:10.17615/2jra-yr02
Physiologie und Pathophysiologie des Typ-1-Diabetes
Danne, T., Kordonouri, O., & Lange, K. (2014) · Springer eBooks · doi:10.1007/978-3-642-24645-6_2
Znaczenie nutrigenomiki w profilaktyce i wspomaganiu leczenia cukrzycy
Syta, E., & Bobrowska‐Korczak, B. (2021) · Postępy Higieny i Medycyny Doświadczalnej · doi:10.5604/01.3001.0014.7834
Predicting Type 1 Diabetes Onset using Novel Survival Analysis with Biomarker Ontology.
Li, Y., Liu, B., Anand, V., Dunne, J. L., Lundgren, M., Ng, K., Rewers, M., Veijola, R., & Ghalwash, M. F. (2020) · PubMed Central
Autoimmunerkrankung Typ-1-Diabetes
Scherm, M. G., & Daniel, C. (2021) · Diabetes aktuell · doi:10.1055/a-1452-1412
Cardiometabolic Risk Reduction: A Review of Clinical Guidelines and the Role of SGLT-2 Inhibitors
Reid (2021) · The Journal of Family Practice · doi:10.12788/jfp.0216
Use of SGLT-2 Inhibitors in Patients with Chronic Kidney Disease
Mottl (2021) · The Journal of Family Practice · doi:10.12788/jfp.0225
Improving Shingles Vaccination Rates in Family Medicine
Luther (2021) · The Journal of Family Practice · doi:10.12788/jfp.0218
The Challenge: Finding the Most Appropriate Statin and Dose for Each Patient
Lillo (2021) · The Journal of Family Practice · doi:10.12788/jfp.0224
Pathophysiology and Risk Factors of Diabetes
Kim, H., & Lee, B. (2021) · Stroke revisited · doi:10.1007/978-981-16-5123-6_2
Daniel, C., & Scherm, M. G. (2021) · Diabetologie und Stoffwechsel · doi:10.1055/a-1664-5026
Immunology of β-Cell Destruction
Lernmark, Å., & Torre, D. L. (2014) · Springer eBooks · doi:10.1007/978-94-007-6884-0_18-2
Skyler, J. S. (2018) · Endocrinology · doi:10.1007/978-3-319-45015-5_15
Inflammatory Pathways Linked to β Cell Demise in Diabetes
Imai, Y., Morris, M. A., Dobrian, A. D., Taylor, D., & Nadler, J. L. (2014) · Springer eBooks · doi:10.1007/978-94-007-6686-0_30
Immunology of β-Cell Destruction
Lernmark, Å., & Torre, D. L. (2014) · Springer eBooks · doi:10.1007/978-94-007-6686-0_18
Molekulargenetische Diagnostik des Diabetes mellitus
Grallert, H., & Warncke, K. (2022) · Die Diabetologie · doi:10.1007/s11428-022-00876-7
(2016) · Elsevier eBooks · doi:10.1016/b978-3-437-21833-0.16001-2
Renman, E., Ekici, R., Sundström, M., & Lejon, K. (2022) · Autoimmunity · doi:10.1080/08916934.2022.2117307
Therapeutic peptidomimetics in metabolic diseases
Sirhan, W., & Piran, R. (2022) · Elsevier eBooks · doi:10.1016/b978-0-12-820141-1.00023-6
Autoantibodies against islet cellantigens: Current diagnostic possibilities
Ochocińska, A., Wysocka‐Mincewicz, M., & Cukrowská, B. (2022) · Diagnostyka Laboratoryjna · doi:10.5604/01.3001.0016.3189
Nandhini, L. P., Kamalanathan, S., & Sahoo, J. (2023) · Springer eBooks · doi:10.1007/978-3-031-25519-9_6
Metabolic Control, Morbidity and Mortality in Type 1 Diabetes with Onset in Childhood/Adolescence
Samuelsson, J. (2024) · Linköping University medical dissertations · doi:10.3384/9789180755269
Erstdiagnose eines Typ-1-Diabetes im hohen Alter
Müssig, K., & Harms, M. (2024) · Info Diabetologie · doi:10.1007/s15034-024-4939-5
Ho, C.-L., Yeh, L., Liu, Y.-W., Dong, J.-L., & Sytwu, H. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.06.10.596762
Type 1 diabetes: Prevention and screening in focus
Milicic, T. J., Jotić, A., Lukić, L., Macesic, M. V., Gajović, J. S., Stoiljkovic, M. M., Milovancevic, M. M., Rafailović, Đ., Božović, A., Radisavljević, N., et al. (2024) · Medicinska istrazivanja · doi:10.5937/medi57-49676
Changes in CD4+CD25HIGH T cells and TGFb1 levels in different stages of adult-onset type 1 diabetes
Milicic, T. J., Jotić, A., Marković, I., Popadic, D. M., Lalic, K. S., Uskoković, V., Lukić, L., Macesic, M. V., Gajović, J. S., Stoiljkovic, M. M., et al. (2024) · Journal of Medical Biochemistry · doi:10.5937/jomb0-49868
Ho, C.-L., Yeh, L., Liu, Y.-W., Dong, J.-L., & Sytwu, H. (2024) · eLife · doi:10.7554/elife.99897
Ho, C.-L., Yeh, L., Liu, Y.-W., Dong, J.-L., & Sytwu, H. (2024) · eLife · doi:10.7554/elife.99897.1
(2025) · Elsevier eBooks · doi:10.1016/b978-3-437-21835-4.00116-5
T-Cell Wars, A New Hope: Targeting Bcl6-Expressing T Cells in T1D
Cañete, P. F., & Yu, D. (2025) · Diabetes · doi:10.2337/dbi24-0048
Nayak, D., & Sharma, S. (2025) · Premier journal of science. · doi:10.70389/pjs.2025.100085
Crowder, V., & Brady, V. (2025) · Life · doi:10.3390/life15071063
Persistent urinary metabolic signatures in children with type 1 diabetes
Nakayasu, E. S., Flores, J. E., Bramer, L., Chin, J., Kim, Y., Syed, F., Zink, E., Frohnert, B. I., Evans‐Molina, C., Kaplowitz, P. B., et al. (2025) · Next research. · doi:10.1016/j.nexres.2025.100725
Revival of radioimmunoassay for determination of insulin autoantibodies
Timofeev, A., Galimov, R., Kolesnikova, E., Artyuhov, A., Skoblov, Y., & Taktarov, S. (2025) · Bulletin of Russian State Medical University · doi:10.24075/brsmu.2025.049
Ho, C.-L., Yeh, L., Liu, Y.-W., Dong, J.-L., & Sytwu, H. (2025) · eLife · doi:10.7554/elife.99897.2
Yanovskaya, E. A., & Яновская, М. Е. (2026) · FOCUS Endocrinology · doi:10.62751/2713-0177-2026-7-1-05
Generation of Regulatory T Cells Against Islet Neoantigen
den Hollander, N. H. M., Gootjes, C., Staal, M. G., Joosten, A. M., Nikolić, T., Roep, B. O., & Jansen, D. T. S. L. (2026) · European Journal of Immunology · doi:10.1002/eji.70229
Proffer, M. L., Roy, S., & Piganelli, J. D. (2026) · Immunological Reviews · doi:10.1111/imr.70183
Predictive autoantibodies before the diagnosis of type I diabetes in adults
Burbelo, P. D., Nee, R., Huapaya, J. A., Plasse, R. A., Kim, M., Gordon, S. M., Pasquale, G. D., Chiorini, J. A., & Olson, S. (2026) · PLoS ONE · doi:10.1371/journal.pone.0352531
Metadata
- Authors
- Ziegler, A.-G., & Nepom, G. T.
- Affiliations
- TUM Klinikum (DE)
- Benaroya Research Institute (US)
- Corresponding author
- Ziegler, Anette-G.
- Nepom, Gerald T.
- Venue
- Immunity
- Publisher
- Elsevier BV
- Published
- 2010-04
- Volume
- 32
- Issue
- 4
- Pages
- 468-478
- ISSN
- 1074-7613 (ISSN-L)
- PMC
- PMC2861716
- OpenAlex
- W2047768051
- Cited by
- 346
- References
- 101
- Citations by year
- 2026: 5 · 2025: 21 · 2024: 20 · 2023: 12 · 2022: 15 · 2021: 25 · 2020: 18 · 2019: 19 · 2018: 26 · 2017: 10 · 2016: 26 · 2015: 30 · 2014: 28 · 2013: 29 · 2012: 25
- FWCI
- 3.08
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Immunity (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich) (submittedVersion)
- Site cant be reached (submittedVersion)
- Funders
- Deutsche Forschungsgemeinschaft
- Bundesministerium für Bildung und Forschung
- National Institutes of Health
- Juvenile Diabetes Research Foundation International
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Diabetes and associated disorders
- Life Sciences › Immunology and Microbiology › Immunology › T-cell and B-cell Immunology
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Keywords
- type 1 diabetes, autoimmune diabetes, disease prediction, pathogenesis, genetic susceptibility, immune response, biomarkers, immune checkpoint, immune regulation, islet autoimmunity, disease risk assessment, preclinical stage, immune homeostasis
- MeSH terms
- Animals, Diabetes Mellitus, Type 1, Humans, Risk Factors, Genetic Variation, Biomarkers, Genetic Predisposition to Disease
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
