Literature DB >> 21812815

Strategies for the prevention of autoimmune type 1 diabetes.

J A Todd1, M Knip, C Mathieu.   

Abstract

European experts on autoimmune Type 1 diabetes met for 2 days in October 2010 in Cambridge, to review the state-of-the-art and to discuss strategies for prevention of Type 1 diabetes (http://www-gene.cimr.cam.ac.uk/todd/sub_pages/T1D_prevention_Cambridge_workshop_20_21Oct2010.pdf). Meeting sessions examined the epidemiology of Type 1 diabetes; possible underlying causes of the continuing and rapid increase in Type 1 diabetes incidence at younger ages; and lessons learned from previous prevention trials. Consensus recommendations from the meeting were: 1. Resources such as national diabetes registries and natural history studies play an essential role in developing and refining assays to be used in screening for risk factors for Type 1 diabetes. 2. It is crucial to dissect out the earliest physiological events after birth, which are controlled by the susceptibility genes now identified in Type 1 diabetes, and the environmental factors that might affect these phenotypes, in order to bring forward a mechanistic approach to designing future prevention trials. 3. Current interventions at later stages of disease, such as in newly diagnosed Type 1 diabetes, have relied mainly on non-antigen-specific mechanisms. For primary prevention-preventing the onset of autoimmunity-interventions must be based on knowledge of the actual disease process such that: participants in a trial would be stratified according the disease-associated molecular phenotypes; the autoantigen(s) and immune responses to them; and the manipulation of the environment, as early as possible in life. Combinations of interventions should be considered as they may allow targeting different components of disease, thus lowering side effects while increasing efficacy.
© 2011 The Authors. Diabetic Medicine © 2011 Diabetes UK.

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Year:  2011        PMID: 21812815      PMCID: PMC3206219          DOI: 10.1111/j.1464-5491.2011.03400.x

Source DB:  PubMed          Journal:  Diabet Med        ISSN: 0742-3071            Impact factor:   4.359


Type 1 diabetes occurs when the body's immune system turns against itself so that, in a very specific and targeted way, it destroys the pancreatic islet β-cells, the only cells in the body that produce the vital hormone insulin. This autoimmune destruction is irreversible and the disease incurable. If new pancreas or islets are transplanted they too are destroyed, unless heavy immunosuppression is applied. Recent genetics and mechanistic studies in humans are indicating major pathways that play roles in early disease development, especially in the interleukin-2 (IL-2) and type 1 interferon systems, probably in concert with the immune response to preproinsulin [1,2]. Longitudinal studies of children born with high genetic risk of Type 1 diabetes showed that circulating autoantibodies to islet antigens can be seen as early as 6 months. A large proportion of childhood cases has seroconverted by age 3 years, and almost all cases by age 7 years, even although median age-at-diagnosis is approximately 12 years [3,4]. Children who will go on to develop Type 1 diabetes in the future must be born with the first precursors of the disease. A child aged under age 5 years with a family history of Type 1 diabetes, carrying the highest risk human leukocyte antigen (HLA) class II genotypes and persistently positive for two or more autoantibody types, has a more than 90% chance of being diagnosed with the disease [5]. By making the connection between gene variant and phenotype, genetics provides a way to identify pathways leading to Type 1 diabetes, including the earliest physiological events after birth, and the earliest events in the disease process, including clues about what may be environmental factors or accelerators of disease [4,6]. National diabetes registries, especially those with available biosamples, provide Europe with important population-based research resources, for studying disease epidemiology, or for testing hypotheses about disease initiation and progression. Registry data where available provide evidence that the incidence of Type 1 diabetes in children under age 15 years has increased. However, there is a shortage of data on Type 1 diabetes over age 15, although at least half of new cases occur after age 15. Data from registries should be accessible to all bona fide researchers, provided that necessary confidentiality protections are in place. Common standards regarding data fields would add value and also aid data access. The appearance of autoantibodies, the first of which chronologically are usually against insulin itself, is a secondary or downstream event in the autoimmune process. Identification and validation of biomarkers that precede autoantibody appearance are urgently required. Incentives to provide access to these collections should be implemented [7]. Useful information to provide possible investigators with includes limitations of the informed consent, types and amounts of material available and storage conditions. Efforts should be made to extend collections of samples of at-risk individuals and persons with newly diagnosed diabetes. Funding opportunities should be implemented to encourage investigators to develop assays that could be used retrospectively, to employ new technologies and to use smaller assay volumes for studying markers. Despite the limited success of previous prevention trials, they have provided valuable lessons, combined with correctly interpreted data from the animal models. Predictions of the natural history of disease based on combined genetic (HLA) and serological markers (autoantibodies) are accurate. C-peptide is a surrogate marker for loss of β-cell function and progression to diabetes; and the oral glucose tolerance test is a sensitive screening tool for detecting individuals with diabetes before fasting blood sugar or HbA1c levels become abnormal. Screening for risk of diabetes can avoid suffering in children, as diabetic ketoacidosis prevalence was 4% in children enrolled in prevention trials compared with 15–20% in new-onset children in the general population [8]. Interventions at later stages of disease, such as in newly diagnosed Type 1 diabetes, have used mainly non-antigen-specific drugs, with the promising studies having used doses at the edge of safety. Successfully preventing the onset of autoimmunity—true primary prevention— must include antigen-specific tolerance approaches [2]. It is important to begin now to accurately establish doses, timing and best route of administration, whilst analysing mechanistic effects.
  8 in total

Review 1.  Etiology of type 1 diabetes.

Authors:  John A Todd
Journal:  Immunity       Date:  2010-04-23       Impact factor: 31.745

2.  CTLs are targeted to kill beta cells in patients with type 1 diabetes through recognition of a glucose-regulated preproinsulin epitope.

Authors:  Ania Skowera; Richard J Ellis; Ruben Varela-Calviño; Sefina Arif; Guo Cai Huang; Cassie Van-Krinks; Anna Zaremba; Chloe Rackham; Jennifer S Allen; Timothy I M Tree; Min Zhao; Colin M Dayan; Andrew K Sewell; Wendy W Unger; Wendy Unger; Jan W Drijfhout; Ferry Ossendorp; Bart O Roep; Mark Peakman
Journal:  J Clin Invest       Date:  2008-10       Impact factor: 14.808

Review 3.  Environmental triggers and determinants of type 1 diabetes.

Authors:  Mikael Knip; Riitta Veijola; Suvi M Virtanen; Heikki Hyöty; Outi Vaarala; Hans K Akerblom
Journal:  Diabetes       Date:  2005-12       Impact factor: 9.461

4.  Nasal insulin to prevent type 1 diabetes in children with HLA genotypes and autoantibodies conferring increased risk of disease: a double-blind, randomised controlled trial.

Authors:  Kirsti Näntö-Salonen; Antti Kupila; Satu Simell; Heli Siljander; Tiina Salonsaari; Anne Hekkala; Sari Korhonen; Risto Erkkola; Jukka I Sipilä; Lotta Haavisto; Marja Siltala; Juhani Tuominen; Jari Hakalax; Heikki Hyöty; Jorma Ilonen; Riitta Veijola; Tuula Simell; Mikael Knip; Olli Simell
Journal:  Lancet       Date:  2008-09-22       Impact factor: 79.321

5.  Progression to type 1 diabetes in islet cell antibody-positive relatives in the European Nicotinamide Diabetes Intervention Trial: the role of additional immune, genetic and metabolic markers of risk.

Authors:  P J Bingley; E A M Gale
Journal:  Diabetologia       Date:  2006-03-03       Impact factor: 10.122

6.  An interferon-induced helicase (IFIH1) gene polymorphism associates with different rates of progression from autoimmunity to type 1 diabetes.

Authors:  Christiane Winkler; Claudia Lauber; Kerstin Adler; Harald Grallert; Thomas Illig; Anette-Gabriele Ziegler; Ezio Bonifacio
Journal:  Diabetes       Date:  2011-02       Impact factor: 9.461

7.  The Environmental Determinants of Diabetes in the Young (TEDDY): genetic criteria and international diabetes risk screening of 421 000 infants.

Authors:  William A Hagopian; Henry Erlich; Ake Lernmark; Marian Rewers; Anette G Ziegler; Olli Simell; Beena Akolkar; Robert Vogt; Alan Blair; Jorma Ilonen; Jeffrey Krischer; JinXiong She
Journal:  Pediatr Diabetes       Date:  2011-05-12       Impact factor: 3.409

8.  Predictive characteristics of diabetes-associated autoantibodies among children with HLA-conferred disease susceptibility in the general population.

Authors:  Heli T A Siljander; Satu Simell; Anne Hekkala; Jyrki Lähde; Tuula Simell; Paula Vähäsalo; Riitta Veijola; Jorma Ilonen; Olli Simell; Mikael Knip
Journal:  Diabetes       Date:  2009-09-15       Impact factor: 9.461

  8 in total
  3 in total

1.  Novel autoantigens in type 1 diabetes.

Authors:  Shuhong Han; William Donelan; Hai Wang; Westley Reeves; Li-Jun Yang
Journal:  Am J Transl Res       Date:  2013-05-24       Impact factor: 4.060

2.  Current concepts on the pathogenesis of type 1 diabetes--considerations for attempts to prevent and reverse the disease.

Authors:  Mark A Atkinson; Matthias von Herrath; Alvin C Powers; Michael Clare-Salzler
Journal:  Diabetes Care       Date:  2015-06       Impact factor: 19.112

Review 3.  Optimal Tolerogenic Dendritic Cells in Type 1 Diabetes (T1D) Therapy: What Can We Learn From Non-obese Diabetic (NOD) Mouse Models?

Authors:  David P Funda; Lenka Palová-Jelínková; Jaroslav Goliáš; Zuzana Kroulíková; Alena Fajstová; Tomáš Hudcovic; Radek Špíšek
Journal:  Front Immunol       Date:  2019-05-14       Impact factor: 7.561

  3 in total

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