Prediction of progression to type 1 diabetes with dynamic biomarkers and risk scores
Publikation: Bidrag til tidsskrift › Review › Forskning › fagfællebedømt
Identifying biomarkers of functional β-cell loss is an important step in the risk stratification of type 1 diabetes. Genetic risk scores (GRS), generated by profiling an array of single nucleotide polymorphisms, are a widely used type 1 diabetes risk-prediction tool. Type 1 diabetes screening studies have relied on a combination of biochemical (autoantibody) and GRS screening methodologies for identifying individuals at high-risk of type 1 diabetes. A limitation of these screening tools is that the presence of autoantibodies marks the initiation of β-cell loss, and is therefore not the best biomarker of progression to early-stage type 1 diabetes. GRS, on the other hand, represents a static biomarker offering a single risk score over an individual's lifetime. In this Personal View, we explore the challenges and opportunities of static and dynamic biomarkers in the prediction of progression to type 1 diabetes. We discuss future directions wherein newer dynamic risk scores could be used to predict type 1 diabetes risk, assess the efficacy of new and emerging drugs to retard, or prevent type 1 diabetes, and possibly replace or further enhance the predictive ability offered by static biomarkers, such as GRS.
Originalsprog | Engelsk |
---|---|
Tidsskrift | The Lancet Diabetes and Endocrinology |
Vol/bind | 12 |
Udgave nummer | 7 |
Sider (fra-til) | 483-492 |
ISSN | 2213-8587 |
DOI | |
Status | Udgivet - 2024 |
Bibliografisk note
Funding Information:
We thank the funding agencies especially, the Juvenile Diabetes Research Foundation (JDRF) International, JDRF Australia, National Health and Medical Research Council, Australia, and the Helmsley Charitable Trust, all of our clinical and academic collaborators, and study participants for the opportunities provided to assess several static and dynamic biomarkers of type 1 diabetes, which led to the conception of this Personal View.
Publisher Copyright:
© 2024 Elsevier Ltd
ID: 395133008