Type 1 diabetes risk factors, risk prediction and presymptomatic detection: Evidence and guidance for screening

Abstract

Type 1 diabetes is recognized as a chronic disease with a presymptomatic phase that does not require insulin therapy and a clinical phase where insulin treatment becomes necessary. The presymptomatic phase is characterized by the presence of autoantibodies targeting pancreatic islet beta cell antigens (islet autoantibodies). This phase is further classified into three stages: Stage 1, defined by normoglycaemia; Stage 2, characterized by dysglycaemia; and Stage 3, marked by hyperglycaemia, which typically presents clinically and necessitates insulin therapy. The prospect of therapies to delay the onset of clinical disease and insulin treatment has been a driver of research into the presymptomatic phase since the discovery of islet autoantibodies. With the recent approval of teplizumab as a therapy to delay disease progression, attention has increasingly focused on diagnosing individuals with Stage 1 and Stage 2 type 1 diabetes. However, diagnosing an asymptomatic condition that affects fewer than 1 in 200 individuals poses significant challenges. As we enter this new era of diagnosis, it is crucial to refine diagnostic approaches to ensure accuracy and effectiveness. This review summarizes current evidence and guidance while emphasizing the need for continued research alongside broader application of screening.

Plain Language Summary

Type 1 diabetes is an autoimmune disease that affects approximately 0.5% of individuals. In this publication, the authors provide a comprehensive overview of strategies for identifying individuals in the pre-symptomatic, early stages of the disease. Early-stage type 1 diabetes can be detected by the presence of autoantibodies against specific proteins in the blood, signaling an ongoing disease process before clinical symptoms appear. Genetic factors also contribute to the development of these autoantibodies and the disease itself. The paper explores how these markers are used for early identification, emphasizing optimal screening ages and the role of confirmation tests in preventing misdiagnosis. A key consideration in early diagnosis is that disease progression varies–some individuals develop clinical diabetes rapidly, while others may take many years. The authors discuss additional tests that can help predict how soon a diagnosed individual may require insulin treatment. Finally, the paper highlights ongoing challenges in optimizing screening for wider application and the complexities of integrating research-based screening into routine clinical practice.