Autoantibody-Negative Type 1 Diabetes: A Neglected Subtype. (May 2021)

• Record Type: Journal Article
• Authors: Patel, Shivani K.; Ma, Cindy S.; Fourlanos, Spiros; Greenfield, Jerry R.
• Is Part Of: Trends in endocrinology and metabolism. Volume 32:Number 5(2021)
• Page Start: 295
• Page End: 305
• Publication Date: 2021-05
• Subjects: autoantibody-negative -- type 1 diabetes -- autoimmune diabetes -- immunophenotype -- characterisation; Endocrinology -- Periodicals; Metabolism -- Periodicals; Metabolism; 616.4
• DOI: 10.1016/j.tem.2021.02.001
• Languages: English
• ISSNs: 1043-2760

Abstract

Abstract : Up to 15% of individuals with a clinical phenotype of type 1 diabetes (T1D) do not have evidence of seropositivity for pancreatic islet autoantibodies. On this basis, they are classified as nonimmune or idiopathic, and remain an understudied population, as they are excluded from T1D immunomodulatory trials. Our limited understanding of the disease aetiopathogenesis in autoantibody-negative T1D hinders our ability to improve diagnostic pathways and discover novel therapeutic agents; particularly as we progress towards an era of precision medicine. This review summarises the current understanding and challenges in studying autoantibody-negative T1D. We review the literature regarding T1D classification, and the role of autoimmunity and defects in the immunogenic pathway that may distinguish autoantibody-positive and -negative T1D. Highlights: Autoantibody-negative type 1 diabetes (T1D) has been neglected from our diagnostic and management framework. Subsequently, this cohort has been excluded from novel T1D immunotherapy trials. While studying this subtype has inherent challenges, there has been minimal effort in the literature to recognise and characterise this group, understand underlying disease mechanisms and discover novel and/or adjunct therapies. Elucidating if and how this cohort differs from classic T1D will unravel and emphasise the need to discover alternate immune-based biomarkers (to aid disease prediction, diagnosis, severity, and monitoring of treatment response) as we strive towards precision medicine.