Stratifying risk for onset of type 1 diabetes using islet autoantibody trajectory clustering.

ABSTRACT:

Aims/hypothesis

Islet autoantibodies can be detected prior to the onset of type 1 diabetes and are important tools for aetiologic studies, prevention trials and disease screening. Current risk stratification models rely on the positivity status of islet autoantibodies alone, but additional autoantibody characteristics may be important for understanding disease onset. This work aimed to determine if a data-driven model incorporating characteristics of islet autoantibody development, including timing, type and titre, could stratify risk for type 1 diabetes onset.

Methods

Data on autoantibodies against GAD (GADA), tyrosine phosphatase islet antigen-2 (IA-2A) and insulin (IAA) were obtained for 1,415 children enrolled in The Environmental Determinants of Diabetes in the Young st

SUBMITTER: Mistry S 

PROVIDER: S-EPMC10097474 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature