Islet autoantibodies as precision diagnostic tools to characterize heterogeneity in type 1 diabetes: a systematic review.
Jamie L FeltonMaria J RedondoRichard A OramCate SpeakeSarah Alice LongSuna Onngut-GumuscuStephen S RichGabriela S F MonacoArianna Harris-KawanoDianna PerezZeb SaeedBenjamin HoagRashmi JainCarmella Evans-MolinaLinda A DiMeglioHeba M IsmailDana DabeleaRandi K JohnsonMarzhan UrazbayevaJohn M WentworthKurt J GriffinEmily K Simsnull nullPublished in: Communications medicine (2024)
Current evidence most strongly supports the application of autoantibody features to more precisely define T1D before diagnosis. Our findings support continued use of pre-clinical staging paradigms based on autoantibody number and suggest that additional autoantibody features, particularly in relation to age and genetic risk, could offer more precise stratification. To improve reproducibility and applicability of autoantibody-based precision medicine in T1D, we propose a methods checklist for islet autoantibody-based manuscripts which includes use of precision medicine MeSH terms and participation in autoantibody standardization workshops.