Islet autoantibodies as precision diagnostic tools to characterize heterogeneity in type 1 diabetes: a systematic review
dc.contributor.author | Felton, JL | |
dc.contributor.author | Redondo, MJ | |
dc.contributor.author | Oram, RA | |
dc.contributor.author | Speake, C | |
dc.contributor.author | Long, SA | |
dc.contributor.author | Onengut-Gumuscu, S | |
dc.contributor.author | Rich, SS | |
dc.contributor.author | Monaco, GSF | |
dc.contributor.author | Harris-Kawano, A | |
dc.contributor.author | Perez, D | |
dc.contributor.author | Saeed, Z | |
dc.contributor.author | Hoag, B | |
dc.contributor.author | Jain, R | |
dc.contributor.author | Evans-Molina, C | |
dc.contributor.author | DiMeglio, LA | |
dc.contributor.author | Ismail, HM | |
dc.contributor.author | Dabelea, D | |
dc.contributor.author | Johnson, RK | |
dc.contributor.author | Urazbayeva, M | |
dc.contributor.author | Wentworth, JM | |
dc.contributor.author | Griffin, KJ | |
dc.contributor.author | Sims, EK | |
dc.contributor.author | ADA/EASD PMDI | |
dc.date.accessioned | 2024-06-20T09:32:51Z | |
dc.date.issued | 2024-04-06 | |
dc.date.updated | 2024-06-18T16:18:31Z | |
dc.description.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. | en_GB |
dc.description.sponsorship | DiabDocs K12 program | en_GB |
dc.description.sponsorship | Leona M. & Harry B. Helmsley Charitable Trust | en_GB |
dc.description.sponsorship | NIH NIDDK | en_GB |
dc.description.sponsorship | Diabetes UK | en_GB |
dc.description.sponsorship | National Institute of Diabetes and Digestive and Kidney Diseases | en_GB |
dc.description.sponsorship | National Institutes of Health | en_GB |
dc.identifier.citation | Vol. 4, No. 1, article 66 | en_GB |
dc.identifier.doi | https://doi.org/10.1038/s43856-024-00478-y | |
dc.identifier.grantnumber | 1K12DK133995- 01 | en_GB |
dc.identifier.grantnumber | 2307-06126 | en_GB |
dc.identifier.grantnumber | R01DK124395 | en_GB |
dc.identifier.grantnumber | 16/0005529 | en_GB |
dc.identifier.grantnumber | NIH R01 DK121843–01 | en_GB |
dc.identifier.grantnumber | U01DK127382–01 | en_GB |
dc.identifier.grantnumber | 3-SRA-2019–827-S-B | en_GB |
dc.identifier.grantnumber | 2-SRA-2022–1261-S-B | en_GB |
dc.identifier.grantnumber | 2-SRA-2002–1259- S-B | en_GB |
dc.identifier.grantnumber | 3-SRA-2022–1241-S-B | en_GB |
dc.identifier.grantnumber | 2-SRA-2022–1258-M-B | en_GB |
dc.identifier.grantnumber | R01 AI141952 | en_GB |
dc.identifier.grantnumber | R01 CA231226 | en_GB |
dc.identifier.grantnumber | R01HL149676 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/136357 | |
dc.language.iso | en | en_GB |
dc.publisher | Nature Research | en_GB |
dc.relation.url | https://www.ncbi.nlm.nih.gov/pubmed/38582818 | en_GB |
dc.rights | © The Author(s) 2024. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. | en_GB |
dc.subject | Diagnostic markers | en_GB |
dc.subject | Endocrine system and metabolic diseases | en_GB |
dc.subject | Type 1 diabetes | en_GB |
dc.title | Islet autoantibodies as precision diagnostic tools to characterize heterogeneity in type 1 diabetes: a systematic review | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2024-06-20T09:32:51Z | |
exeter.article-number | 66 | |
exeter.place-of-publication | England | |
dc.description | This is the final version. Available on open access from Nature Research via the DOI in this record. | en_GB |
dc.description | Data availability: All studies reviewed were identified and can be accessed via publicly available databases (PubMed and Embase). Source data can be found in Supplementary Data 3. A full list of included studies is available in Supplementary Data 6. Article review data supporting the findings of this study are available upon reasonable request from the corresponding author. | en_GB |
dc.identifier.eissn | 2730-664X | |
dc.identifier.journal | Communications Medicine | en_GB |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2024-03-05 | |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2024-04-06 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2024-06-20T09:19:32Z | |
refterms.versionFCD | VoR | |
refterms.dateFOA | 2024-06-20T09:32:59Z | |
refterms.panel | A | en_GB |
refterms.dateFirstOnline | 2024-04-06 |
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