Heterogeneity of beta-cell function in subjects with multiple islet autoantibodies in the TEDDY family prevention study - TEFA.
Continuous glucose monitoring
Glucose metabolism
Islet autoantibodies
beta-cell function
Journal
Clinical diabetes and endocrinology
ISSN: 2055-8260
Titre abrégé: Clin Diabetes Endocrinol
Pays: England
ID NLM: 101669619
Informations de publication
Date de publication:
05 Jan 2022
05 Jan 2022
Historique:
received:
26
07
2021
accepted:
29
11
2021
entrez:
5
1
2022
pubmed:
6
1
2022
medline:
6
1
2022
Statut:
epublish
Résumé
Individuals with multiple islet autoantibodies are at increased risk for clinical type 1 diabetes and may proceed gradually from stage to stage complicating the recruitment to secondary prevention studies. We evaluated multiple islet autoantibody positive subjects before randomisation for a clinical trial 1 month apart for beta-cell function, glucose metabolism and continuous glucose monitoring (CGM). We hypothesized that the number and type of islet autoantibodies in combination with different measures of glucose metabolism including fasting glucose, HbA1c, oral glucose tolerance test (OGTT), intra venous glucose tolerance test (IvGTT) and CGM allows for more precise staging of autoimmune type 1 diabetes than the number of islet autoantibodies alone. Subjects (n = 57) at 2-50 years of age, positive for two or more islet autoantibodies were assessed by fasting plasma insulin, glucose, HbA1c as well as First Phase Insulin Response (FPIR) in IvGTT, followed 1 month later by OGTT, and 1 week of CGM (n = 24). Autoantibodies against GAD65 (GADA; n = 52), ZnT8 (ZnT8A; n = 40), IA-2 (IA-2A; n = 38) and insulin (IAA; n = 28) were present in 9 different combinations of 2-4 autoantibodies. Fasting glucose and HbA1c did not differ between the two visits. The estimate of the linear relationship between log2-transformed FPIR as the outcome and log2-transformed area under the OGTT glucose curve (AUC) as the predictor, adjusting for age and sex was - 1.88 (- 2.71, - 1.05) p = 3.49 × 10-5. The direction of the estimates for all glucose metabolism measures was positive except for FPIR, which was negative. FPIR was associated with higher blood glucose. Both the median and the spread of the CGM glucose data were significantly associated with higher glucose values based on OGTT, higher HbA1c, and lower FPIR. There was no association between glucose metabolism, autoantibody number and type except that there was an indication that the presence of at least one of ZnT8(Q/R/W) A was associated with a lower log2-transformed FPIR (- 0.80 (- 1.58, - 0.02), p = 0.046). The sole use of two or more islet autoantibodies as inclusion criterion for Stage 1 diabetes in prevention trials is unsatisfactory. Staging type 1 diabetes needs to take the heterogeneity in beta-cell function and glucose metabolism into account. ClinicalTrials.gov identifier: NCT02605148 , November 16, 2015.
Sections du résumé
BACKGROUND
BACKGROUND
Individuals with multiple islet autoantibodies are at increased risk for clinical type 1 diabetes and may proceed gradually from stage to stage complicating the recruitment to secondary prevention studies. We evaluated multiple islet autoantibody positive subjects before randomisation for a clinical trial 1 month apart for beta-cell function, glucose metabolism and continuous glucose monitoring (CGM). We hypothesized that the number and type of islet autoantibodies in combination with different measures of glucose metabolism including fasting glucose, HbA1c, oral glucose tolerance test (OGTT), intra venous glucose tolerance test (IvGTT) and CGM allows for more precise staging of autoimmune type 1 diabetes than the number of islet autoantibodies alone.
METHODS
METHODS
Subjects (n = 57) at 2-50 years of age, positive for two or more islet autoantibodies were assessed by fasting plasma insulin, glucose, HbA1c as well as First Phase Insulin Response (FPIR) in IvGTT, followed 1 month later by OGTT, and 1 week of CGM (n = 24).
RESULTS
RESULTS
Autoantibodies against GAD65 (GADA; n = 52), ZnT8 (ZnT8A; n = 40), IA-2 (IA-2A; n = 38) and insulin (IAA; n = 28) were present in 9 different combinations of 2-4 autoantibodies. Fasting glucose and HbA1c did not differ between the two visits. The estimate of the linear relationship between log2-transformed FPIR as the outcome and log2-transformed area under the OGTT glucose curve (AUC) as the predictor, adjusting for age and sex was - 1.88 (- 2.71, - 1.05) p = 3.49 × 10-5. The direction of the estimates for all glucose metabolism measures was positive except for FPIR, which was negative. FPIR was associated with higher blood glucose. Both the median and the spread of the CGM glucose data were significantly associated with higher glucose values based on OGTT, higher HbA1c, and lower FPIR. There was no association between glucose metabolism, autoantibody number and type except that there was an indication that the presence of at least one of ZnT8(Q/R/W) A was associated with a lower log2-transformed FPIR (- 0.80 (- 1.58, - 0.02), p = 0.046).
CONCLUSIONS
CONCLUSIONS
The sole use of two or more islet autoantibodies as inclusion criterion for Stage 1 diabetes in prevention trials is unsatisfactory. Staging type 1 diabetes needs to take the heterogeneity in beta-cell function and glucose metabolism into account.
TRIAL REGISTRATION
BACKGROUND
ClinicalTrials.gov identifier: NCT02605148 , November 16, 2015.
Identifiants
pubmed: 34983671
doi: 10.1186/s40842-021-00135-6
pii: 10.1186/s40842-021-00135-6
pmc: PMC8728995
doi:
Banques de données
ClinicalTrials.gov
['NCT02605148']
Types de publication
Journal Article
Langues
eng
Pagination
23Subventions
Organisme : juvenile diabetes research foundation united states of america
ID : 2-SRA-2014-309-M-R
Organisme : foundation for the national institutes of health
ID : 1UO1 DK063861
Organisme : vetenskapsrådet
ID : Dnr 2020-01537
Organisme : stiftelsen för strategisk forskning
ID : Dnr IRC15-0067
Investigateurs
Anita Ramelius
(A)
Ida Jönsson
(I)
Rasmus Bennet
(R)
Birgitta Sjöberg
(B)
Åsa Wimar
(Å)
Jessica Melin
(J)
Maria Ask
(M)
Anne Wallin
(A)
Monika Hansen
(M)
Susanne Hyberg
(S)
Karin Ottosson
(K)
Jenny Bremer
(J)
Ulla-Marie Carlsson
(UM)
Ulrika Ulvenhag
(U)
Anette Sjöberg
(A)
Marielle Lindström
(M)
Lina Fransson
(L)
Fredrik Johansen
(F)
Kobra Rahmati
(K)
Zeliha Mestan
(Z)
Evelyn Tekum-Amboh
(E)
Silvija Jovic
(S)
Joanna Gerardsson
(J)
Emelie Ericson-Hallström
(E)
Sofie Åberg
(S)
Sara Sibthorpe
(S)
Elina Mäntymäki
(E)
Sini Vainionpää
(S)
Minna Romo
(M)
Zhian Othmani
(Z)
Eeva Varjonen
(E)
Sanna Jokipuu
(S)
Satu Ruohonen
(S)
Laura Leppänen
(L)
Petra Rajala
(P)
Eija Riski
(E)
Miia Kähönen
(M)
Minna-Liisa Koivikko
(ML)
Tea Joensuu
(T)
Heidi Alanen
(H)
Teija Mykkänen
(T)
Tiina Latva-Aho
(T)
Minna-Liisa Koivikko
(ML)
Aino Stenius
(A)
Paula Ollikainen
(P)
Marika Korpela
(M)
Katja Multasuo
(K)
Päivi Salmijärvi
(P)
Pieta Kemppainen
(P)
Merja Runtti
(M)
Riitta Päkkilä
(R)
Irene Viinikangas
(I)
Sinikka Pietikäinen
(S)
Tuula Arkkola
(T)
Informations de copyright
© 2022. The Author(s).
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