Prediction of progression to type 1 diabetes with dynamic biomarkers and risk scores

Lancet Diabetes Endocrinol. 2024 Jul;12(7):483-492. doi: 10.1016/S2213-8587(24)00103-7. Epub 2024 May 23.

Abstract

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.

Publication types

  • Review

MeSH terms

  • Autoantibodies
  • Biomarkers*
  • Diabetes Mellitus, Type 1* / blood
  • Diabetes Mellitus, Type 1* / diagnosis
  • Risk Assessment / methods

Substances

  • Biomarkers
  • Autoantibodies