Academic Journal

Islet autoantibodies as precision diagnostic tools to characterize heterogeneity in type 1 diabetes: a systematic review

التفاصيل البيبلوغرافية
العنوان: Islet autoantibodies as precision diagnostic tools to characterize heterogeneity in type 1 diabetes: a systematic review
المؤلفون: Jamie L. Felton, Maria J. Redondo, Richard A. Oram, Cate Speake, S. Alice Long, Suna Onengut-Gumuscu, Stephen S. Rich, Gabriela S. F. Monaco, Arianna Harris-Kawano, Dianna Perez, Zeb Saeed, Benjamin Hoag, Rashmi Jain, Carmella Evans-Molina, Linda A. DiMeglio, Heba M. Ismail, Dana Dabelea, Randi K. Johnson, Marzhan Urazbayeva, John M. Wentworth, Kurt J. Griffin, Emily K. Sims, On behalf of the ADA/EASD PMDI
المصدر: Communications Medicine, Vol 4, Iss 1, Pp 1-18 (2024)
بيانات النشر: Nature Portfolio, 2024.
سنة النشر: 2024
المجموعة: LCC:Medicine
مصطلحات موضوعية: Medicine
الوصف: Abstract Background Islet autoantibodies form the foundation for type 1 diabetes (T1D) diagnosis and staging, but heterogeneity exists in T1D development and presentation. We hypothesized that autoantibodies can identify heterogeneity before, at, and after T1D diagnosis, and in response to disease-modifying therapies. Methods We systematically reviewed PubMed and EMBASE databases (6/14/2022) assessing 10 years of original research examining relationships between autoantibodies and heterogeneity before, at, after diagnosis, and in response to disease-modifying therapies in individuals at-risk or within 1 year of T1D diagnosis. A critical appraisal checklist tool for cohort studies was modified and used for risk of bias assessment. Results Here we show that 152 studies that met extraction criteria most commonly characterized heterogeneity before diagnosis (91/152). Autoantibody type/target was most frequently examined, followed by autoantibody number. Recurring themes included correlations of autoantibody number, type, and titers with progression, differing phenotypes based on order of autoantibody seroconversion, and interactions with age and genetics. Only 44% specifically described autoantibody assay standardization program participation. Conclusions 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.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2730-664X
Relation: https://doaj.org/toc/2730-664X
DOI: 10.1038/s43856-024-00478-y
URL الوصول: https://doaj.org/article/113aed4f5d484c8ca50fd405d635e3a3
رقم الانضمام: edsdoj.113aed4f5d484c8ca50fd405d635e3a3
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:2730664X
DOI:10.1038/s43856-024-00478-y