Top

Published in:

Open Access 22-03-2024 | Type 1 Diabetes | Article

The INNODIA Type 1 Diabetes Natural History Study: a European cohort of newly diagnosed children, adolescents and adults

Authors: M. Loredana Marcovecchio, A. Emile J. Hendriks, Carl Delfin, Tadej Battelino, Thomas Danne, Mark L. Evans, Jesper Johannesen, Simranjeet Kaur, Mikael Knip, Lut Overbergh, Flemming Pociot, John A. Todd, Bart Van der Schueren, Linda S. Wicker, Mark Peakman, Chantal Mathieu, on behalf of the INNODIA consortium

Published in: Diabetologia | Issue 6/2024

Abstract

Aims/hypothesis

Type 1 diabetes is an heterogenous condition. Characterising factors explaining differences in an individual’s clinical course and treatment response will have important clinical and research implications. Our aim was to explore type 1 diabetes heterogeneity, as assessed by clinical characteristics, autoantibodies, beta cell function and glycaemic outcomes, during the first 12 months from diagnosis, and how it relates to age at diagnosis.

Methods

Data were collected from the large INNODIA cohort of individuals (aged 1.0–45.0 years) newly diagnosed with type 1 diabetes, followed 3 monthly, to assess clinical characteristics, C-peptide, HbA_1c and diabetes-associated antibodies, and their changes, during the first 12 months from diagnosis, across three age groups: <10 years; 10–17 years; and ≥18 years.

Results

The study population included 649 individuals (57.3% male; age 12.1±8.3 years), 96.9% of whom were positive for one or more diabetes-related antibodies. Baseline (IQR) fasting C-peptide was 242.0 (139.0–382.0) pmol/l (AUC 749.3 [466.2–1106.1] pmol/l × min), with levels increasing with age (p<0.001). Over time, C-peptide remained lower in participants aged <10 years but it declined in all age groups. In parallel, glucose levels progressively increased. Lower baseline fasting C-peptide, BMI SD score and presence of diabetic ketoacidosis at diagnosis were associated with lower stimulated C-peptide over time. HbA_1c decreased during the first 3 months (p<0.001), whereas insulin requirement increased from 3 months post diagnosis (p<0.001).

Conclusions/interpretation

In this large cohort with newly diagnosed type 1 diabetes, we identified age-related differences in clinical and biochemical variables. Of note, C-peptide was lower in younger children but there were no main age differences in its rate of decline.

Graphical Abstract

Available only for authorised users

den Hollander NHM, Roep BO (2022) From disease and patient heterogeneity to precision medicine in type 1 diabetes. Front Med (Lausanne) 9:932086. https://doi.org/10.3389/fmed.2022.932086CrossRef

Quattrin T, Mastrandrea LD, Walker LSK (2023) Type 1 diabetes. Lancet 401(10394):2149–2162. https://doi.org/10.1016/s0140-6736(23)00223-4CrossRefPubMed

Battaglia M, Ahmed S, Anderson MS et al (2020) Introducing the endotype concept to address the challenge of disease heterogeneity in type 1 diabetes. Diabetes Care 43(1):5–12. https://doi.org/10.2337/dc19-0880CrossRefPubMed

Redondo MJ, Morgan NG (2023) Heterogeneity and endotypes in type 1 diabetes mellitus. Nat Rev Endocrinol 19(9):542–554. https://doi.org/10.1038/s41574-023-00853-0CrossRefPubMed

Inshaw JRJ, Cutler AJ, Crouch DJM, Wicker LS, Todd JA (2020) Genetic variants predisposing most strongly to type 1 diabetes diagnosed under age 7 years lie near candidate genes that function in the immune system and in pancreatic β-cells. Diabetes Care 43(1):169–177. https://doi.org/10.2337/dc19-0803CrossRefPubMed

Parviainen A, Härkönen T, Ilonen J, But A, Knip M (2022) Heterogeneity of type 1 diabetes at diagnosis supports existence of age-related endotypes. Diabetes Care 45(4):871–879. https://doi.org/10.2337/dc21-1251CrossRefPubMed

Arif S, Leete P, Nguyen V et al (2014) Blood and islet phenotypes indicate immunological heterogeneity in type 1 diabetes. Diabetes 63(11):3835–3845. https://doi.org/10.2337/db14-0365CrossRefPubMedPubMedCentral

Leete P, Oram RA, McDonald TJ et al (2020) Studies of insulin and proinsulin in pancreas and serum support the existence of aetiopathological endotypes of type 1 diabetes associated with age at diagnosis. Diabetologia 63(6):1258–1267. https://doi.org/10.1007/s00125-020-05115-6CrossRefPubMedPubMedCentral

Roep BO, Wheeler DCS, Peakman M (2019) Antigen-based immune modulation therapy for type 1 diabetes: the era of precision medicine. Lancet Diabetes Endocrinol 7(1):65–74. https://doi.org/10.1016/S2213-8587(18)30109-8CrossRefPubMed

10.

Dunger DB, Bruggraber SFA, Mander AP et al (2022) INNODIA master protocol for the evaluation of investigational medicinal products in children, adolescents and adults with newly diagnosed type 1 diabetes. Trials 23(1):414. https://doi.org/10.1186/s13063-022-06259-zCrossRefPubMedPubMedCentral

11.

ElSayed NA, Aleppo G, Aroda VR et al (2022) 2. Classification and diagnosis of diabetes: standards of care in diabetes—2023. Diabetes Care 46(Supplement_1):S19–S40. https://doi.org/10.2337/dc23-S002CrossRefPubMedCentral

12.

Knip M, Korhonen S, Kulmala P et al (2010) Prediction of type 1 diabetes in the general population. Diabetes Care 33(6):1206–1212. https://doi.org/10.2337/dc09-1040CrossRefPubMedPubMedCentral

13.

Barker JM, Triolo TM, Aly TA et al (2008) Two single nucleotide polymorphisms identify the highest-risk diabetes HLA genotype: potential for rapid screening. Diabetes 57(11):3152–3155. https://doi.org/10.2337/db08-0605CrossRefPubMedPubMedCentral

14.

Jia X, Han B, Onengut-Gumuscu S et al (2013) Imputing amino acid polymorphisms in human leukocyte antigens. PLoS One 8(6):e64683. https://doi.org/10.1371/journal.pone.0064683CrossRefPubMedPubMedCentral

15.

Cole TJ (1990) The LMS method for constructing normalized growth standards. Eur J Clin Nutr 44(1):45–60PubMed

16.

Mortensen HB, Hougaard P, Swift P et al (2009) New definition for the partial remission period in children and adolescents with type 1 diabetes. Diabetes Care 32(8):1384–1390. https://doi.org/10.2337/dc08-1987CrossRefPubMedPubMedCentral

17.

Greenbaum CJ, Beam CA, Boulware D et al (2012) Fall in C-peptide during first 2 years from diagnosis: evidence of at least two distinct phases from composite type 1 diabetes TrialNet Data. Diabetes 61(8):2066–2073. https://doi.org/10.2337/db11-1538CrossRefPubMedPubMedCentral

18.

Gitelman SE, Evans-Molina C, Guolo A, Mari A, Ferrannini E (2023) β-cell glucose sensitivity to assess changes in β-cell function in recent-onset stage 3 type 1 diabetes. Diabetes 72(9):1289–1296. https://doi.org/10.2337/db23-0196CrossRefPubMedPubMedCentral

19.

Hao W, Gitelman S, DiMeglio LA, Boulware D, Greenbaum CJ (2016) Fall in C-peptide during first 4 years from diagnosis of type 1 diabetes: variable relation to age, hba1c, and insulin dose. Diabetes Care 39(10):1664–1670. https://doi.org/10.2337/dc16-0360CrossRefPubMedPubMedCentral

20.

Gale EA, Gillespie KM (2001) Diabetes and gender. Diabetologia 44(1):3–15. https://doi.org/10.1007/s001250051573CrossRefPubMed

21.

Misra S, Barron E, Vamos E et al (2021) Temporal trends in emergency admissions for diabetic ketoacidosis in people with diabetes in England before and during the COVID-19 pandemic: a population-based study. Lancet Diabetes Endocrinol 9(10):671–680. https://doi.org/10.1016/s2213-8587(21)00208-4CrossRefPubMedPubMedCentral

22.

Birkebaek NH, Kamrath C, Grimsmann JM et al (2022) Impact of the COVID-19 pandemic on long-term trends in the prevalence of diabetic ketoacidosis at diagnosis of paediatric type 1 diabetes: an international multicentre study based on data from 13 national diabetes registries. Lancet Diabetes Endocrinol 10(11):786–794. https://doi.org/10.1016/S2213-8587(22)00246-7CrossRefPubMedPubMedCentral

23.

D’Souza D, Empringham J, Pechlivanoglou P, Uleryk EM, Cohen E, Shulman R (2023) Incidence of diabetes in children and adolescents during the COVID-19 pandemic: a systematic review and meta-analysis. JAMA Network Open 6(6):e2321281–e2321281. https://doi.org/10.1001/jamanetworkopen.2023.21281CrossRefPubMedPubMedCentral

24.

Knip M, Parviainen A, Turtinen M et al (2023) SARS-CoV-2 and type 1 diabetes in children in Finland: an observational study. Lancet Diabetes Endocrinol 11(4):251–260. https://doi.org/10.1016/s2213-8587(23)00041-4CrossRefPubMed

25.

Misra S (2022) Rise in diabetic ketoacidosis during the COVID-19 pandemic: several questions remain. Lancet Diabetes Endocrinol 10(11):763–765. https://doi.org/10.1016/S2213-8587(22)00272-8CrossRefPubMedPubMedCentral

26.

Rugg-Gunn CEM, Dixon E, Jorgensen AL et al (2022) Factors associated with diabetic ketoacidosis at onset of type 1 diabetes among pediatric patients: a systematic review. JAMA Pediatr 176(12):1248–1259. https://doi.org/10.1001/jamapediatrics.2022.3586CrossRefPubMed

27.

Cherubini V, Marino M, Carle F, Zagaroli L, Bowers R, Gesuita R (2021) Effectiveness of ketoacidosis prevention campaigns at diagnosis of type 1 diabetes in children: a systematic review and meta-analysis. Diabetes Res Clin Pract 175:108838. https://doi.org/10.1016/j.diabres.2021.108838CrossRefPubMed

28.

Sims EK, Besser REJ, Dayan C et al (2022) Screening for type 1 diabetes in the general population: a status report and perspective. Diabetes 71(4):610–623. https://doi.org/10.2337/dbi20-0054CrossRefPubMedPubMedCentral

29.

Mortensen HB, Swift PG, Holl RW et al (2010) Multinational study in children and adolescents with newly diagnosed type 1 diabetes: association of age, ketoacidosis, HLA status, and autoantibodies on residual beta-cell function and glycemic control 12 months after diagnosis. Pediatr Diabetes 11(4):218–226. https://doi.org/10.1111/j.1399-5448.2009.00566.xCrossRefPubMed

30.

Samuelsson U, Lindblad B, Carlsson A et al (2013) Residual beta cell function at diagnosis of type 1 diabetes in children and adolescents varies with gender and season. Diabetes Metab Res Rev 29(1):85–89. https://doi.org/10.1002/dmrr.2365CrossRefPubMedPubMedCentral

31.

Carr ALJ, Inshaw JRJ, Flaxman CS et al (2022) Circulating c-peptide levels in living children and young people and pancreatic β-cell loss in pancreas donors across type 1 diabetes disease duration. Diabetes 71(7):1591–1596. https://doi.org/10.2337/db22-0097CrossRefPubMedPubMedCentral

32.

Shields BM, McDonald TJ, Oram R et al (2018) C-peptide decline in type 1 diabetes has two phases: an initial exponential fall and a subsequent stable phase. Diabetes Care 41(7):1486–1492. https://doi.org/10.2337/dc18-0465CrossRefPubMed

33.

Davis AK, DuBose SN, Haller MJ et al (2015) Prevalence of detectable C-peptide according to age at diagnosis and duration of type 1 diabetes. Diabetes Care 38(3):476–481. https://doi.org/10.2337/dc14-1952CrossRefPubMed

34.

Ludvigsson J, Carlsson A, Deli A et al (2013) Decline of C-peptide during the first year after diagnosis of type 1 diabetes in children and adolescents. Diabetes Res Clin Pract 100(2):203–209. https://doi.org/10.1016/j.diabres.2013.03.003CrossRefPubMed

35.

Buckingham B, Beck RW, Ruedy KJ et al (2013) Effectiveness of early intensive therapy on β-cell preservation in type 1 diabetes. Diabetes Care 36(12):4030–4035. https://doi.org/10.2337/dc13-1074CrossRefPubMedPubMedCentral

36.

Greenbaum CJ, Anderson AM, Dolan LM et al (2009) Preservation of beta-cell function in autoantibody-positive youth with diabetes. Diabetes Care 32(10):1839–1844. https://doi.org/10.2337/dc08-2326CrossRefPubMedPubMedCentral

37.

Dabelea D, Mayer-Davis EJ, Andrews JS et al (2012) Clinical evolution of beta cell function in youth with diabetes: the SEARCH for Diabetes in Youth study. Diabetologia 55(12):3359–3368. https://doi.org/10.1007/s00125-012-2719-6CrossRefPubMedPubMedCentral

38.

Lachin JM, McGee P, Palmer JP (2014) Impact of C-peptide preservation on metabolic and clinical outcomes in the Diabetes Control and Complications Trial. Diabetes 63(2):739–748. https://doi.org/10.2337/db13-0881CrossRefPubMedPubMedCentral

39.

Sørensen JS, Johannesen J, Pociot F et al (2013) Residual β-cell function 3–6 years after onset of type 1 diabetes reduces risk of severe hypoglycemia in children and adolescents. Diabetes Care 36(11):3454–3459. https://doi.org/10.2337/dc13-0418CrossRefPubMedPubMedCentral

40.

Harsunen M, Haukka J, Harjutsalo V et al (2023) Residual insulin secretion in individuals with type 1 diabetes in Finland: longitudinal and cross-sectional analyses. Lancet Diabetes Endocrinol 11(7):465–473. https://doi.org/10.1016/S2213-8587(23)00123-7CrossRefPubMed

41.

de Bock M, Codner E, Craig ME et al (2022) ISPAD Clinical Practice Consensus Guidelines 2022: glycemic targets and glucose monitoring for children, adolescents, and young people with diabetes. Pediatr Diabetes 23(8):1270–1276. https://doi.org/10.1111/pedi.13455CrossRefPubMedPubMedCentral

42.

Dunger D, Ahmed L, Ong K (2002) Growth and body composition in type 1 diabetes mellitus. Horm Res 58(Suppl 1):66–71. https://doi.org/10.1159/000064762CrossRefPubMed

43.

Williams CL, Fareed R, Mortimer GLM et al (2022) The longitudinal loss of islet autoantibody responses from diagnosis of type 1 diabetes occurs progressively over follow-up and is determined by low autoantibody titres, early-onset, and genetic variants. Clin Exp Immunol 210(2):151–162. https://doi.org/10.1093/cei/uxac087CrossRefPubMedPubMedCentral

44.

Long AE, George G, Williams CL (2021) Persistence of islet autoantibodies after diagnosis in type 1 diabetes. Diabet Med 38(12):e14712. https://doi.org/10.1111/dme.14712CrossRefPubMed

45.

Hermann R, Knip M, Veijola R et al (2003) Temporal changes in the frequencies of HLA genotypes in patients with type 1 diabetes–indication of an increased environmental pressure? Diabetologia 46(3):420–425. https://doi.org/10.1007/s00125-003-1045-4CrossRefPubMed

46.

Vehik K, Hamman RF, Lezotte D et al (2008) Trends in high-risk HLA susceptibility genes among Colorado youth with type 1 diabetes. Diabetes Care 31(7):1392–1396. https://doi.org/10.2337/dc07-2210CrossRefPubMedPubMedCentral

Title: The INNODIA Type 1 Diabetes Natural History Study: a European cohort of newly diagnosed children, adolescents and adults
Authors: M. Loredana Marcovecchio
A. Emile J. Hendriks
Carl Delfin
Tadej Battelino
Thomas Danne
Mark L. Evans
Jesper Johannesen
Simranjeet Kaur
Mikael Knip
Lut Overbergh
Flemming Pociot
John A. Todd
Bart Van der Schueren
Linda S. Wicker
Mark Peakman
Chantal Mathieu
on behalf of the INNODIA consortium
Publication date: 22-03-2024
Publisher: Springer Berlin Heidelberg
Keywords: Type 1 Diabetes
Insulins
Insulins
Published in: Diabetologia / Issue 6/2024
Print ISSN: 0012-186X
Electronic ISSN: 1432-0428
DOI: https://doi.org/10.1007/s00125-024-06124-5

Live Webinar | 27-06-2024 | 18:00 (CEST)

Keynote webinar | Spotlight on medication adherence

Reserve your place

Live: Thursday 27th June 2024, 18:00-19:30 (CEST)

WHO estimates that half of all patients worldwide are non-adherent to their prescribed medication. The consequences of poor adherence can be catastrophic, on both the individual and population level.

Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.

Prof. Kevin Dolgin

Prof. Florian Limbourg

Prof. Anoop Chauhan

Developed by: Springer Medicine

Obesity Clinical Trial Summary

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.

Developed by: Springer Medicine

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Aims/hypothesis

Methods

Results

Conclusions/interpretation

Graphical Abstract

Please log in to get access to this content

Other articles of this Issue 6/2024

Transcutaneous vagal nerve stimulation for treating gastrointestinal symptoms in individuals with diabetes: a randomised, double-blind, sham-controlled, multicentre trial

A ketone monoester drink reduces postprandial blood glucose concentrations in adults with type 2 diabetes: a randomised controlled trial

No association between long-chain n-3 fatty acid intake during pregnancy and risk of type 1 diabetes in offspring in two large Scandinavian pregnancy cohorts

Incidence trend of type 2 diabetes from 2012 to 2021 in Germany: an analysis of health claims data of 11 million statutorily insured people

Relationship of device measured physical activity type and posture with cardiometabolic health markers: pooled dose–response associations from the Prospective Physical Activity, Sitting and Sleep Consortium

Assisting the implementation of screening for type 1 diabetes by using artificial intelligence on publicly available data

Keynote webinar | Spotlight on medication adherence

Live: Thursday 27th June 2024, 18:00-19:30 (CEST)

At a glance: The STEP trials