Abstract
Recent success in clinical trials to delay the onset of type 1 diabetes has heralded a new era of type 1 diabetes research focused on the most accurate methods to predict risk and progression rate in the general population. Risk prediction for type 1 diabetes has been ongoing since the 1970s and 1980s when human leucocyte antigen (HLA) variants and islet autoantibodies associated with type 1 diabetes were first described. Development of prediction methodologies has relied on well-characterised cohorts and samples. The Bart's Oxford (BOX) study of type 1 diabetes has been recruiting children with type 1 diabetes and their first (and second)-degree relatives since 1985. In this review, we use the timeline of the study to review the accompanying basic science developments which have facilitated improved prediction by genetic (HLA analysis through to genetic risk scores) and biochemical strategies (islet cell autoantibodies through to improved individual tests for antibodies to insulin, glutamate decarboxylase, the tyrosine phosphatase IA-2, zinc transporter 8 and tetraspanin 7). The type 1 diabetes community are poised to move forward using the best predictive markers to predict and delay the onset of type 1 diabetes.
| Original language | English |
|---|---|
| Article number | e14717 |
| Number of pages | 7 |
| Journal | Diabetic Medicine |
| Volume | 38 |
| Issue number | 12 |
| Early online date | 16 Oct 2021 |
| DOIs | |
| Publication status | Published - 1 Dec 2021 |
Bibliographical note
Funding Information:This review is dedicated to Dr Alistair John Kerr Williams (1959-2020, awarded a posthumous PhD in 2021) who devoted decades to optimising islet autoantibody tests to accurately predict type 1 diabetes in collaboration with other researchers worldwide with the ultimate aim of preventing type 1 diabetes. We are grateful to the study co-ordinators, nurses, physicians, Local Clinical Research Network teams and in particular, the families in the Oxford region for taking part in the BOX study without whom some of the experimental work described in this review would not have been possible. The authors also thank Dr Anna Long for reading the final version and providing helpful comments.
Publisher Copyright:
© 2021 Diabetes UK.
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This is the accepted author manuscript (AAM). The final published version (version of record) is available online via Wiley at https://doi.org/10.1111/dme.14717. Please refer to any applicable terms of use of the publisher.