TrialNet is an international collaborative network that aims to prevent, delay and reverse the progression of type 1 diabetes, involving United States, Canada, Finland, United Kingdom, Italy, Germany, Australia and New Zealand.

TrialNet in Australia/New Zealand is led by A/Prof John Wentworth at Walter & Eliza Hall Institute (WEHI) in collaboration with Prof Peter Colman AM.

JDRF funded researcher A/Prof Wentworth was a previous T1DCRN Mentored Clinician Researcher Fellowship (MCRF) recipient and is also involved in a major T1DCRN supported study, the Environmental Determinants of Islet Autoimmunity (ENDIA) study.

Two recent publications from the TrialNet group, summarised below, have important findings for stratification of risk and design of future prevention trials. TrialNet is funded by the NIH, JDRF, American Diabetes Association and Helmsley Charitable Trust.

Impact of age and antibody type on progression from single to multiple autoantibodies in T1D relatives. The Journal of Clinical Endocrinology and Metabolism

Islet autoimmunity defined by the detection of islet autoantibodies develops and progresses silently, sometimes over many years, before dysglycaemia occur. The number of autoantibody types present is crucial for prediction of disease. Detection of a single autoantibody confers a low risk while presence of multiple major islet autoantibodies is predictive of progression to clinical disease. Developing multiple persistent autoantibodies appears to be a “point of no return” in the pathogenic process.

This study aimed to determine whether age and antibody type affected progress from single to multiple autoantibodies. The authors found that the interaction between age and risk of progression from single to multiple autoantibodies differs according to whether the initial autoantibody is GADA or insulin (IAA).

The team examined 994 relatives of individuals with type 1 diabetes, with normal glucose tolerance and positive for a single autoantibody, followed prospectively in the TrialNet Pathway to Prevention. The TrialNet Pathway to Prevention study offers free screening to relatives of people with T1D to evaluate their personal risk of developing the disease. This unique screening can identify the early stages of T1D years before any symptoms appear.

Autoantibodies to GADA, IAA, islet antigen 2 (IA-2A), zinc transporter 8 (ZnT8A) and ICA were tested every 6-12 months. The primary outcome was confirmed development of multiple autoantibodies, as detected on at least two occasions. Age was initially categorized as <8yr; 8-11yr; 12-17yr; ≥18yr.This was re-categorised post-hoc according to risk of progression.

After median follow-up of 2 years, 141 relatives had developed ≥ 1 additional autoantibody. Five-year risk was inversely related to age, but the pattern differed by antibody type: relatives with GADA showed a gradual decrease in risk over the four age groups, while relatives with IAA showed a sharp decrease above the age of 8 years. Age breakpoints were identified at 14 years in relatives with GADA and at 4 years in relatives with IAA. This means that those with GADA as the initial autoantibody had a higher risk of progressing to multiple autoantibody positive state before 14 years compared to after 14 years. Similarly, those with IAA as the primary autoantibody under the age of 4 had a higher risk of progression. Specific age breakpoints were very different in those initially positive for IAA compared to those with GADA.

In relatives with IAA, spread of islet autoimmunity is largely limited to early childhood, while immune responses initially directed at GADA can mature over a longer period of time. These differences have important implications for monitoring these subjects and for designing prevention trials. Early interventions targeting single autoantibody positive individuals at risk for T1D may differ in their effectiveness at different ages, depending on initial autoantibody present, and provides guidance as to the length of trial and age group required.

Can non-HLA single nucleotide polymorphisms help stratify risk in TrialNet relatives at risk for T1D? The Journal of Clinical Endocrinology and Metabolism

Type 1 diabetes has a strong genetic component. The human leukocyte antigen (HLA) region of chromosome 6 is a gene complex encoding cell-surface proteins that are responsible for the regulation of the immune system in humans.

It is well characterised that particular HLA types increase risk of developing T1D. In the past 20 years there has been an increase in incidence of T1D in people without the high risk HLA types. This suggests that there are other genes involved in T1D development.

It is becoming increasingly evident that a range of phenotypes and genotypes are likely to contribute to the different presentations of diabetes (e.g. age of onset, severity of presentation).

Genome-wide association studies have identified more than 50 T1D associated non-HLA loci. The purpose of this study was to assess the contribution of non-HLA single nucleotide polymorphisms (SNPs) to risk of disease progression. 53 diabetes-associated, non-HLA SNPs in 1,016 antibody positive at risk relatives were analysed in the largest cohort of antibody positive subjects to date.

They found that factors involved in progression from single to multiple antibodies included age at screening, relationship to the relative (sibling was related to higher likelihood to progress to T1D), HLA genotypes and SNP rs3087243 (CTLA4 gene).

Significant factors for progression to T1D included age at screening, antibody number, HLA genotypes, SNP rs6476839 (GLIS3) and SNP rs3184504(SH2B3). When glucose AUC was included, factors involved in disease progression included glucose AUC, age at screening, antibody number, relationship to sibling proband, HLA genotypes, rs6476839 (GLIS3) and rs7221109 (CCR7).

This study has identified five non-HLA SNPs associated with increased risk of progression from antibody positivity to disease. This may improve risk stratification for prevention trials.

To find out more about TrialNet or to get involved, head to their website. The more we can find out about how T1D progresses and how to monitor this progression, the closer we get to being able to prevent the disease in future generations.

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