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Improved Specificity of Glutamate Decarboxylase 65 Autoantibody Measurement Using Luciferase-Based Immunoprecipitation System Assays

Research output: Contribution to journalArticle (Academic Journal)peer-review

12 Citations (Scopus)
77 Downloads (Pure)

Abstract

Autoantibodies to glutamate decarboxylase (GADA) are widely used in the prediction and classification of type 1 diabetes. GADA radiobinding assays (RBAs) using N-terminally truncated antigens offer improved specificity but radioisotopes limit the high-throughput potential for population screening. Luciferase-based Immunoprecipitation System (LIPS) assays are sensitive and specific alternatives to RBAs with the potential to improve risk stratification. The performance of assays using the Luciferase (Nluc-) conjugated GAD65 constructs, Nluc-GAD65(96-585) and full length Nluc-GAD65(1-585) were evaluated in 434 well-characterised sera from recent-onset type 1 diabetes patients and first-degree relatives. Non-radioactive, high-throughput LIPS assays are quicker and require less serum than RBAs. Of 171 relatives previously tested single autoantibody positive for autoantibodies to full-length GAD65 by RBA but had not progressed to diabetes, fewer retested positive by LIPS using either truncated (n=72) or full-length (n=111) antigen. The Nluc-GAD65(96-585) truncation demonstrated the highest specificity in LIPS assays overall but in contrast to RBA, N-terminus truncations did not result in a significant increase in disease-specificity compared with the full-length antigen. This suggests that binding of non-specific antibodies is affected by the conformational changes resulting from addition of the Nluc antigen. Nluc-GAD65(96-585) LIPS assays offer low blood volume, high specificity GADA tests for screening and diagnostics.
Original languageEnglish
Pages (from-to)565-571
Number of pages7
JournalDiabetes
Volume73
Issue number4
Early online date17 Jan 2024
DOIs
Publication statusPublished - 1 Apr 2024

Bibliographical note

Publisher Copyright:
© 2024 by the American Diabetes Association.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Research Groups and Themes

  • Bristol BioDesign Institute

Keywords

  • synthetic biology

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