Cited by 351Diabetes and associated disordersDiabetes Management and ResearchPancreatic function and diabetes

Introducing the Endotype Concept to Address the Challenge of Disease Heterogeneity in Type 1 Diabetes

Open access
Battaglia, Manuela, Ahmed, Simi, Anderson, Mark S., Atkinson, Mark A., Becker, Dorothy, Bingley, Polly J., Bosi, Emanuele, Brusko, Todd M. +24 more·2020·Diabetes Care

Abstract

The clinical diagnosis of new-onset type 1 diabetes has, for many years, been considered relatively straightforward. Recently, however, there is increasing awareness that within this single clinical phenotype exists considerable heterogeneity: disease onset spans the complete age range; genetic susceptibility is complex; rates of progression differ markedly, as does insulin secretory capacity; and complication rates, glycemic control, and therapeutic intervention efficacy vary widely. Mechanistic and immunopathological studies typically show considerable patchiness across subjects, undermining conclusions regarding disease pathways. Without better understanding, type 1 diabetes heterogeneity represents a major barrier both to deciphering pathogenesis and to the translational effort of designing, conducting, and interpreting clinical trials of disease-modifying agents. This realization comes during a period of unprecedented change in clinical medicine, with increasing emphasis on greater individualization and precision. For complex disorders such as type 1 diabetes, the option of maintaining the “single disease” approach appears untenable, as does the notion of individualizing each single patient’s care, obliging us to conceptualize type 1 diabetes less in terms of phenotypes (observable characteristics) and more in terms of disease endotypes (underlying biological mechanisms). Here, we provide our view on an approach to dissect heterogeneity in type 1 diabetes. Using lessons from other diseases and the data gathered to date, we aim to delineate a roadmap through which the field can incorporate the endotype concept into laboratory and clinical practice. We predict that such an effort will accelerate the implementation of precision medicine and has the potential for impact on our approach to translational research, trial design, and clinical management.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.2337/dc19-0880

Cites

7 of 7 references verified0 citation errors · 0 not checkable

Statistics

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.

A few free checks a day · papers already verified open instantly · results are public

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?

  • Contemporary and large natural history studies have shown that type 1 diabetes is a heterogeneous disorder and that features beyond autoimmunity, including metabolic factors, exocrine function and environmental exposures, impact progression to clinical disease.

    “Contemporary and large natural history studies assembled based on HLA genotypes and family history have shown that type 1 diabetes is a heterogenous disorder and that features beyond autoimmunity, including metabolic factors, exocrine function and environmental exposures, impact progression to clinical disease61.”

    From 100 years of insulin: celebrating the past, present and future of diabetes therapy (2021) · cites this paper as [61]

    Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 54

  1. Lötvall J, Akdis CA, Bacharier LB, et al. Asthma endotypes: a new approach to classification of disease entities within the asthma syndrome. J Allergy Clin Immunol 2011;127:355-360
  2. Greenbaum C, VanBuecken D, Lord S. Disease- modifying therapies in type 1 diabetes: a look into the future of diabetes practice. Drugs 2019; 79:43-61
  3. Ludvigsson J. Time to leave rigid traditions in type 1 diabetes research. Immunotherapy 2017; 9:619-621
  4. Woittiez NJC, Roep BO. Impact of disease heterogeneity on treatment efficacy of immu- notherapy in type 1 diabetes: different shades of gray. Immunotherapy 2015;7:163-174
  5. Agache I, Akdis CA. Precision medicine and phenotypes, endotypes, genotypes, regiotypes, and theratypes of allergic diseases. J Clin Invest 2019;130:1493-1503
  6. Sherry N, Hagopian W, Ludvigsson J, et al.; Protégé Trial Investigators. Teplizumab for treat- ment of type 1 diabetes (Protégé study): 1-year results from a randomised, placebo-controlled trial. Lancet 2011;378:487-497
  7. Writing Committee for the Type 1 Diabetes TrialNet Oral Insulin Study Group, Krischer JP, Schatz DA, Bundy B, Skyler JS, Greenbaum CJ. Effect of oral insulin on prevention of diabetes in relatives of patients with type 1 diabetes: a randomized clinical trial. JAMA 2017;318:1891-1902
  8. Atkinson MA, Roep BO, Posgai A, Wheeler DCS, Peakman M. The challenge of modulating b-cell autoimmunity in type 1 diabetes. Lancet Diabetes Endocrinol 2019;7:52-64
  9. Kuruvilla ME, Lee FE, Lee GB. Understanding asthma phenotypes, endotypes, and mecha- nisms of disease. Clin Rev Allergy Immunol 2019;56:219-233
  10. Battaglia M, Anderson MS, Buckner JH, et al. Understanding and preventing type 1 diabetes through the unique working model of TrialNet. Diabetologia 2017;60:2139-2147
  11. Rewers M, Hyöty H, Lernmark Å, et al.; TEDDY Study Group. The Environmental Deter- minants of Diabetes in the Young (TEDDY) study: 2018 update. Curr Diab Rep 2018;18:136
  12. Mathieu C, Lahesmaa R, Bonifacio E, Achenbach P, Tree T. Immunological biomarkers for the de- velopment and progression of type 1 diabetes. Diabetologia 2018;61:2252-2258
  13. Ziegler R, Alper CA, Awdeh ZL, et al. Specific association of HLA-DR4 with increased preva- lence and level of insulin autoantibodies in first- degree relatives of patients with type I diabetes. Diabetes 1991;40:709-714
  14. Roep BO, Wheeler DCS, Peakman M. Anti- gen-based immune modulation therapy for type 1 diabetes: the era of precision medicine. Lancet Diabetes Endocrinol 2019;7:65-74
  15. Ilonen J, Lempainen J, Hammais A, et al.; Finnish Pediatric Diabetes Register. Primary islet autoantibody at initial seroconversion and auto- antibodies at diagnosis of type 1 diabetes as markers of disease heterogeneity. Pediatr Di- abetes 2018;19:284-292
  16. Arif S, Leete P, Nguyen V, et al. Blood and islet phenotypes indicate immunological heterogeneity in type 1 diabetes. Diabetes 2014;63:3835-3845
  17. Leete P, Willcox A, Krogvold L, et al. Differ- ential insulitic profiles determine the extent of b-cell destruction and the age at onset of type 1 diabetes. Diabetes 2016;65:1362-1369
  18. Tosato F, Bucciol G, Pantano G, et al. Lym- phocytes subsets reference values in childhood. Cytometry A 2015;87:81-85
  19. McCarthy MI. Painting a new picture of personalised medicine for diabetes. Diabetologia 2017;60:793-799
  20. Cabrera SM, Engle S, Kaldunski M, et al.; Type 1 Diabetes TrialNet CTLA4-Ig (Abatacept) Study Group. Innate immune activity as a predictor of persistent insulin secretion and association with re- sponsiveness to CTLA4-Ig treatment in recent-onset type 1 diabetes. Diabetologia 2018;61:2356-2370
  21. Orban T, Beam CA, Xu P, et al.; Type 1 Di- abetes TrialNet Abatacept Study Group. Reduc- tion in CD4 central memory T-cell subset in costimulation modulator abatacept-treated pa- tients with recent-onset type 1 diabetes is as- sociated with slower C-peptide decline. Diabetes 2014;63:3449-3457
  22. Malmegrim KCR, de Azevedo JTC, Arruda LCM, et al. Immunological balance is associated with clinical outcome after autologous hemato- poietic stem cell transplantation in type 1 di- abetes. Front Immunol 2017;8:167
  23. Redondo MJ, Steck AK, Sosenko J, et al.; Type 1 Diabetes TrialNet Study Group. Transcription factor 7-like 2 (TCF7L2) gene polymorphism and progression from single to multiple autoantibody positivity in individuals at risk for type 1 diabetes. Diabetes Care 2018;41:2480-2486
  24. Tosur M, Geyer SM, Rodriguez H, Libman I, Baidal DA, Redondo MJ; Type 1 Diabetes TrialNet Study Group. Ethnic differences in progression of islet autoimmunity and type 1 diabetes in relatives at risk. Diabetologia 2018;61:2043- 2053
  25. Leete P, Mallone R, Richardson SJ, Sosenko JM, Redondo MJ, Evans-Molina C. The effect of age on the progression and severity of type 1 diabetes: potential effects on disease mecha- nisms. Curr Diab Rep 2018;18:115
  26. Cousminer DL, Ahlqvist E, Mishra R, et al.; Bone Mineral Density in Childhood Study. First genome-wide association study of latent auto- immune diabetes in adults reveals novel insights linking immune and metabolic diabetes. Diabe- tes Care 2018;41:2396-2403
  27. Kahaly GJ, Hansen MP. Type 1 diabetes associated autoimmunity. Autoimmun Rev 2016; 15:644-648
  28. Oram RA, Jones AG, Besser REJ, et al. The majority of patients with long-duration type 1 diabetes are insulin microsecretors and have functioning beta cells. Diabetologia 2014;57: 187-191
  29. Greenbaum CJ, Beam CA, Boulware D, et al.; Type 1 Diabetes TrialNet Study Group. Fall in C-peptide during first 2 years from diagnosis: evidence of at least two distinct phases from composite type 1 Diabetes TrialNet data. Di- abetes 2012;61:2066-2073
  30. Rodriguez-Calvo T, Richardson SJ, Pugliese A. Pancreas pathology during the natural history of type 1 diabetes. Curr Diab Rep 2018;18:124
  31. Simell S, Hoppu S, Simell T, et al. Age at development of type 1 diabetes-and celiac disease-associated antibodies and clinical dis- ease in genetically susceptible children observed from birth. Diabetes Care 2010;33:774-779
  32. Beyerlein A, Bonifacio E, Vehik K, et al.; TEDDY Study Group. Progression from islet au- toimmunity to clinical type 1 diabetes is influ- enced by genetic factors: results from the prospective TEDDY study. J Med Genet 2019; 56:602-605
  33. Krischer JP, Liu X, Lernmark Å, et al.; TEDDY Study Group. The influence of type 1 diabetes genetic susceptibility regions, age, sex, and fam- ily history on the progression from multiple autoantibodies to type 1 diabetes: a TEDDY study report. Diabetes 2017;66:3122-3129
  34. Steck AK, Dong F, Waugh K, et al. Predictors of slow progression to diabetes in children with multiple islet autoantibodies. J Autoimmun 2016;72:113-117
  35. Bonifacio E, Beyerlein A, Hippich M, et al.; TEDDY Study Group. Genetic scores to stratify risk of developing multiple islet autoantibodies and type 1 diabetes: a prospective study in children. PLoS Med 2018;15:e1002548 40. Redondo MJ, Geyer S, Steck AK, et al.; Type 1 Diabetes TrialNet Study Group. A type 1 di- abetes genetic risk score predicts progression of islet autoimmunity and development of type 1 diabetes in individuals at risk. Diabetes Care 2018;41:1887-1894
  36. So M, Elso CM, Tresoldi E, et al. Proinsulin C-peptide is an autoantigen in people with type 1 diabetes. Proc Natl Acad Sci U S A 2018;115: 10732-10737
  37. Arif S, Moore F, Marks K, et al. Peripheral and islet interleukin-17 pathway activation charac- terizes human autoimmune diabetes and pro- motes cytokine-mediated b-cell death. Diabetes 2011;60:2112-2119
  38. Achenbach P, Lampasona V, Landherr U, et al. Autoantibodies to zinc transporter 8 and SLC30A8 genotype stratify type 1 diabetes risk. Diabetologia 2009;52:1881-1888
  39. Achenbach P, Koczwara K, Knopff A, Naserke H, Ziegler A-G, Bonifacio E. Mature high-affinity immune responses to (pro)insulin anticipate the autoimmune cascade that leads to type 1 di- abetes. J Clin Invest 2004;114:589-597
  40. Vecchio F, Lo Buono N, Stabilini A, et al.; DRI_Biorepository Group; Type 1 Diabetes Trial- Net Study Group. Abnormal neutrophil signature in the blood and pancreas of presymptomatic and symptomatic type 1 diabetes. JCI Insight 2018;3: 122146
  41. Ferreira RC, Guo H, Coulson RMR, et al. A type I interferon transcriptional signature pre- cedes autoimmunity in children genetically at risk for type 1 diabetes. Diabetes 2014;63:2538- 2550
  42. Kallionpää H, Elo LL, Laajala E, et al. Innate immune activity is detected prior to serocon- version in children with HLA-conferred type 1 diabetes susceptibility. Diabetes 2014;63:2402- 2414
  43. Cabrera SM, Chen Y-G, Hagopian WA, Hessner MJ. Blood-based signatures in type 1 diabetes. Diabetologia 2016;59:414-425
  44. Coppieters KT, Dotta F, Amirian N, et al. Demonstration of islet-autoreactive CD8 T cells in insulitic lesions from recent onset and long-term type 1 diabetes patients. J Exp Med 2012;209: 51-60
  45. Arif S, Tree TI, Astill TP, et al. Autoreactive T cell responses show proinflammatory polari- zation in diabetes but a regulatory phenotype in health. J Clin Invest 2004;113:451-463
  46. Kenefeck R, Wang CJ, Kapadi T, et al. Fol- licular helper T cell signature in type 1 diabetes. J Clin Invest 2015;125:292-303
  47. Viisanen T, Ihantola E-L, Näntö-Salonen K, et al. Circulating CXCR5 1 PD-1 1 ICOS 1 follicular T helper cells are increased close to the diagnosis of type 1 diabetes in children with multiple auto- antibodies. Diabetes 2017;66:437-447 care.diabetesjournals.org Battaglia and Associates 11
  48. Long SA, Cerosaletti K, Bollyky PL, et al. Defects in IL-2R signaling contribute to dimin- ished maintenance of FOXP3 expression in CD4 1 CD25 1 regulatory T-cells of type 1 diabetic subjects. Diabetes 2010;59:407-415
  49. Schwedhelm K, Thorpe J, Murray SA, et al. Attenuated IL-2R signaling in CD4 memory T cells of T1D subjects is intrinsic and dependent on activation state. Clin Immunol 2017;181: 67-74
  50. Yang JHM, Cutler AJ, Ferreira RC, et al. Natural variation in interleukin-2 sensitivity in- fluences regulatory T-cell frequency and function in individuals with long-standing type 1 diabetes. Diabetes 2015;64:3891-3902
  51. Yeo L, Woodwyk A, Sood S, et al. Autoreactive T effector memory differentiation mirrors b cell function in type 1 diabetes. J Clin Invest 2018;128: 3460-3474
  52. Roshandel D, Gubitosi-Klug R, Bull SB, et al.; DCCT/EDIC Research Group. Meta- genome-wide association studies identify a locus on chromosome 1 and multiple variants in the MHC region for serum C-peptide in type 1 diabetes. Diabetologia 2018;61:1098-1111
  53. Fløyel T, Brorsson C, Nielsen LB, et al. CTSH regulates b-cell function and disease progr- ession in newly diagnosed type 1 diabetes patients. Proc Natl Acad Sci U S A 2014;111: 10305-10310
  54. Redondo MJ, Geyer S, Steck AK, et al.; Type 1 Diabetes TrialNet Study Group. TCF7L2 ge- netic variants contribute to phenotypic hetero- geneity of type 1 diabetes. Diabetes Care 2018; 41:311-317

Cited by

Sorted by citations

Authors
Battaglia, M., Ahmed, S., Anderson, M. S., Atkinson, M. A., Becker, D., Bingley, P. J., Bosi, E., Brusko, T. M., DiMeglio, L. A., Evans-Molina, C., Gitelman, S. E., Greenbaum, C. J., Gottlieb, P. A., Herold, K. C., Hessner, M. J., Knip, M., Jacobsen, L., Krischer, J. P., Long, S. A., Lundgren, M., McKinney, E. F., Morgan, N. G., Oram, R. A., Pastinen, T., Peters, M. C., Petrelli, A., Qian, X., Redondo, M. J., Roep, B. O., Schatz, D., Skibinski, D., & Peakman, M.
Affiliations
  • IRCCS Ospedale San Raffaele (IT)
  • Breakthrough T1D (US)
  • University of California, San Francisco (US)
  • University of Florida Health (US)
  • Children's Hospital of Pittsburgh (US)
  • University of Bristol (GB)
  • Vita-Salute San Raffaele University (IT)
  • Indiana University Indianapolis (US)
  • Herman B Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN
  • Benaroya Research Institute (US)
  • University of Colorado Anschutz (US)
  • Yale University (US)
  • Medical College of Wisconsin (US)
  • University of Helsinki (FI)
  • University of South Florida (US)
  • Lund University (SE)
  • University of Cambridge (GB)
  • University of Exeter (GB)
  • Children's Mercy Hospital (US)
  • Texas A&M University System (US)
  • Baylor College of Medicine (US)
  • City Of Hope National Medical Center (US)
  • King's College London (GB)
Corresponding author
  • Battaglia, Manuela
  • Peakman, Mark
Venue
Diabetes Care
Published
2019-12-12
Volume
43
Issue
1
Pages
5-12
ISSN
  • 0149-5992 (ISSN-L)
  • 1935-5548
OpenAlex
W2991077754
Cited by
351
References
7
Citations by year
2026: 31 · 2025: 52 · 2024: 48 · 2023: 61 · 2022: 57 · 2021: 69 · 2020: 32 · 2018: 1
FWCI
23.81
Type
journal article
Language
en
Open access
Locations
  • Diabetes Care (publishedVersion)
  • Europe PMC (PubMed Central) (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • eScholarship (California Digital Library) (submittedVersion)
  • Archivio Istituzionale della Ricerca - Università Vita-Salute San Raffaele (submittedVersion)
  • Research Portal (King's College London) (submittedVersion)
  • Lund University Publications (Lund University) (submittedVersion)
  • Royal Devon and Exeter Research Repository (Royal Devon and Exeter) (submittedVersion)
  • Bristol Research (University of Bristol) (submittedVersion)
  • IUScholarWorks (Indiana University) (submittedVersion)
  • Purdue University Indianapolis (Indiana University) (submittedVersion)
Funders
  • U.S. Department of Veterans Affairs (I01-BX001733)
  • Leona M. and Harry B. Helmsley Charitable Trust
  • University of South Florida
  • Wellcome Trust (104064/Z/14/Z)
  • University of Oxford
  • Novo Nordisk Fonden (NNF19OC0056748)
  • National Institutes of Health (UL1TR001863)
  • Medical Research Council (MC_PC_15047)
  • National Institute of Allergy and Infectious Diseases (P01AI042288)
  • National Institute of Diabetes and Digestive and Kidney Diseases (U01DK103153, U01DK061010, U01DK103180, P30DK097512, P30DK045735)
  • National Center for Advancing Translational Sciences
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, disease endotypes, disease heterogeneity, precision medicine, disease-modifying therapy, clinical trial design, pathogenesis, insulin secretion, disease progression, genetic susceptibility
MeSH terms
Biological Variation, Population, Blood Glucose, Diabetes Mellitus, Type 1, Humans, Insulin, Phenotype, Disease Progression, Precision Medicine

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