Progression from islet autoimmunity to clinical type 1 diabetes is influenced by genetic factors: results from the prospective TEDDY study.

Autoantibodies / immunology Autoimmunity Child Child, Preschool Diabetes Mellitus, Type 1 / genetics Disease Progression Female Genetic Predisposition to Disease Humans Infant Islets of Langerhans / immunology Male Prospective Studies Risk Assessment Risk Factors
diabetes diagnostics tests epidemiology immunology (including allergy)

Journal

Journal of medical genetics
ISSN: 1468-6244
Titre abrégé: J Med Genet
Pays: England
ID NLM: 2985087R

Informations de publication

Date de publication:
09 2019
Historique:
received: 12 06 2018
revised: 16 08 2018
accepted: 13 09 2018
pubmed: 6 10 2018
medline: 12 6 2020
entrez: 6 10 2018
Statut: ppublish

Résumé

Progression time from islet autoimmunity to clinical type 1 diabetes is highly variable and the extent that genetic factors contribute is unknown. In 341 islet autoantibody-positive children with the human leucocyte antigen (HLA) DR3/DR4-DQ8 or the HLA DR4-DQ8/DR4-DQ8 genotype from the prospective TEDDY (The Environmental Determinants of Diabetes in the Young) study, we investigated whether a genetic risk score that had previously been shown to predict islet autoimmunity is also associated with disease progression. Islet autoantibody-positive children with a genetic risk score in the lowest quartile had a slower progression from single to multiple autoantibodies (p=0.018), from single autoantibodies to diabetes (p=0.004), and by trend from multiple islet autoantibodies to diabetes (p=0.06). In a Cox proportional hazards analysis, faster progression was associated with an increased genetic risk score independently of HLA genotype (HR for progression from multiple autoantibodies to type 1 diabetes, 1.27, 95% CI 1.02 to 1.58 per unit increase), an earlier age of islet autoantibody development (HR, 0.68, 95% CI 0.58 to 0.81 per year increase in age) and female sex (HR, 1.94, 95% CI 1.28 to 2.93). Genetic risk scores may be used to identify islet autoantibody-positive children with high-risk HLA genotypes who have a slow rate of progression to subsequent stages of autoimmunity and type 1 diabetes.

Sections du résumé

BACKGROUND
Progression time from islet autoimmunity to clinical type 1 diabetes is highly variable and the extent that genetic factors contribute is unknown.
METHODS
In 341 islet autoantibody-positive children with the human leucocyte antigen (HLA) DR3/DR4-DQ8 or the HLA DR4-DQ8/DR4-DQ8 genotype from the prospective TEDDY (The Environmental Determinants of Diabetes in the Young) study, we investigated whether a genetic risk score that had previously been shown to predict islet autoimmunity is also associated with disease progression.
RESULTS
Islet autoantibody-positive children with a genetic risk score in the lowest quartile had a slower progression from single to multiple autoantibodies (p=0.018), from single autoantibodies to diabetes (p=0.004), and by trend from multiple islet autoantibodies to diabetes (p=0.06). In a Cox proportional hazards analysis, faster progression was associated with an increased genetic risk score independently of HLA genotype (HR for progression from multiple autoantibodies to type 1 diabetes, 1.27, 95% CI 1.02 to 1.58 per unit increase), an earlier age of islet autoantibody development (HR, 0.68, 95% CI 0.58 to 0.81 per year increase in age) and female sex (HR, 1.94, 95% CI 1.28 to 2.93).
CONCLUSIONS
Genetic risk scores may be used to identify islet autoantibody-positive children with high-risk HLA genotypes who have a slow rate of progression to subsequent stages of autoimmunity and type 1 diabetes.

Identifiants

DOI: 10.1136/jmedgenet-2018-105532 PMID: 30287597 PMC: PMC6690814
pubmed: 30287597
pii: jmedgenet-2018-105532
doi: 10.1136/jmedgenet-2018-105532
pmc: PMC6690814
mid: NIHMS1520789
doi:

Substances chimiques

Autoantibodies 0

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

602-605

Subventions

Organisme : NIDDK NIH HHS
ID : U01 DK063821
Pays : United States
Organisme : NIDDK NIH HHS
ID : UC4 DK063863
Pays : United States
Organisme : NIDDK NIH HHS
ID : P30 DK048520
Pays : United States
Organisme : NIDDK NIH HHS
ID : U01 DK063861
Pays : United States
Organisme : NIDDK NIH HHS
ID : U01 DK063790
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR001082
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR000064
Pays : United States
Organisme : NLM NIH HHS
ID : HHSN267200700014C
Pays : United States
Organisme : NIDDK NIH HHS
ID : U01 DK063836
Pays : United States
Organisme : NIDDK NIH HHS
ID : U01 DK063829
Pays : United States
Organisme : NIDDK NIH HHS
ID : U01 DK063865
Pays : United States
Organisme : NIDDK NIH HHS
ID : UC4 DK095300
Pays : United States
Organisme : NIDDK NIH HHS
ID : UC4 DK063861
Pays : United States
Organisme : NIDDK NIH HHS
ID : UC4 DK063829
Pays : United States
Organisme : NIDDK NIH HHS
ID : UC4 DK063821
Pays : United States
Organisme : NIDDK NIH HHS
ID : UC4 DK117483
Pays : United States
Organisme : NIDDK NIH HHS
ID : UC4 DK063836
Pays : United States
Organisme : NIDDK NIH HHS
ID : UC4 DK112243
Pays : United States
Organisme : NIDDK NIH HHS
ID : UC4 DK063865
Pays : United States
Organisme : NIDDK NIH HHS
ID : U01 DK063863
Pays : United States
Organisme : NIDDK NIH HHS
ID : UC4 DK106955
Pays : United States
Organisme : NIDDK NIH HHS
ID : UC4 DK100238
Pays : United States

Informations de copyright

© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Déclaration de conflit d'intérêts

Competing interests: A patent has been applied for (LU100334) with the title ‘Method the risk to develop type 1 diabetes’ by Helmholtz Zentrum München Deutsches Forschungszentrum für Gesundheit und Umwelt. EB, A-GZ and CW are among the inventors. The patent includes the genetic score that is examined in the manuscript.

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Auteurs

Andreas Beyerlein (A)

Institute of Diabetes Research, Helmholtz Zentrum München, and Forschergruppe Diabetes, Technical University of Munich, at Klinikum rechts der Isar, Munich-Neuherberg, Germany.
ORCID: 0000-0001-6603-5036

Ezio Bonifacio (E)

DFG Center for Regenerative Therapies Dresden, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany.
Forschergruppe Diabetes eV at Helmholtz Zentrum München, Munich-Neuherberg, Germany.

Kendra Vehik (K)

Health Informatics Institute, Morsani College of Medicine, University of South Florida, Tampa, Florida, USA.

Markus Hippich (M)

Institute of Diabetes Research, Helmholtz Zentrum München, and Forschergruppe Diabetes, Technical University of Munich, at Klinikum rechts der Isar, Munich-Neuherberg, Germany.

Christiane Winkler (C)

Institute of Diabetes Research, Helmholtz Zentrum München, and Forschergruppe Diabetes, Technical University of Munich, at Klinikum rechts der Isar, Munich-Neuherberg, Germany.
Forschergruppe Diabetes eV at Helmholtz Zentrum München, Munich-Neuherberg, Germany.

Brigitte I Frohnert (BI)

Barbara Davis Center for Childhood Diabetes, University of Colorado, Aurora, Colorado, USA.

Andrea K Steck (AK)

Barbara Davis Center for Childhood Diabetes, University of Colorado, Aurora, Colorado, USA.

William A Hagopian (WA)

Pacific Northwest Diabetes Research Institute, Seattle, Washington, USA.

Jeffrey P Krischer (JP)

Health Informatics Institute, Morsani College of Medicine, University of South Florida, Tampa, Florida, USA.

Åke Lernmark (Å)

Department of Clinical Sciences, Lund University/CRC, Skåne University Hospital SUS, Malmo, Sweden.

Marian J Rewers (MJ)

Barbara Davis Center for Childhood Diabetes, University of Colorado, Aurora, Colorado, USA.

Jin-Xiong She (JX)

Center for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta University, Augusta, Georgia, USA.

Jorma Toppari (J)

Institute of Biomedicine, Research Centre for Integrative Physiology and Pharmacology, Turku University Hospital, Turku, Finland.
Department of Physiology, University of Turku, Turku, Finland.

Beena Akolkar (B)

National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland, USA.

Stephen S Rich (SS)

Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA.

Anette-G Ziegler (AG)

Institute of Diabetes Research, Helmholtz Zentrum München, and Forschergruppe Diabetes, Technical University of Munich, at Klinikum rechts der Isar, Munich-Neuherberg, Germany.
Forschergruppe Diabetes eV at Helmholtz Zentrum München, Munich-Neuherberg, Germany.

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Classifications MeSH

questionsmedicales.fr › Acides aminés, peptides et protéines › Protéines › Globulines › Sérum-globulines › Immunoglobulines › Anticorps › Autoanticorps › Progression from islet autoimmunity to...
questionsmedicales.fr › Phénomènes du système immunitaire › Immunité › Auto-immunité › Progression from islet autoimmunity to...
questionsmedicales.fr › Personnes › Tranches d'âge › Enfant › Progression from islet autoimmunity to...
questionsmedicales.fr › Personnes › Tranches d'âge › Enfant › Enfant d'âge préscolaire › Progression from islet autoimmunity to...
questionsmedicales.fr › Maladies du système immunitaire › Maladies auto-immunes › Diabète de type 1 › Progression from islet autoimmunity to...
questionsmedicales.fr › États, signes et symptômes pathologiques › Processus pathologiques › Caractéristiques de la maladie › Évolution de la maladie › Progression from islet autoimmunity to...
questionsmedicales.fr › Phénomènes génétiques › Génotype › Prédisposition génétique à une maladie › Progression from islet autoimmunity to...
questionsmedicales.fr › Eucaryotes › Animaux › Chordés › Vertébrés › Mammifères › Eutheria › Primates › Haplorhini › Catarrhini › Hominidae › Humains › Progression from islet autoimmunity to...
questionsmedicales.fr › Personnes › Tranches d'âge › Nourrisson › Progression from islet autoimmunity to...
questionsmedicales.fr › Système endocrine › Glandes endocrines › Ilots pancréatiques › Progression from islet autoimmunity to...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Caractéristiques des études épidémiologiques › Études épidémiologiques › Études de cohortes › Études prospectives › Progression from islet autoimmunity to...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Statistiques comme sujet › Probabilité › Risque › Appréciation des risques › Progression from islet autoimmunity to...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Statistiques comme sujet › Probabilité › Risque › Facteurs de risque › Progression from islet autoimmunity to...