自身抗体
免疫分析
化学发光
小岛
1型糖尿病
化学发光免疫分析
医学
抗体
色谱法
糖尿病
内科学
免疫学
化学
内分泌学
作者
Elisa Danese,Claudia Piona,Mariateresa Rizza,Elena Tiziani,Laura Pighi,Elisa Morotti,Gian Luca Salvagno,Camilla Mattiuzzi,Claudio Maffeis,Giuseppe Lippi
出处
期刊:Diagnostics
[Multidisciplinary Digital Publishing Institute]
日期:2025-07-03
卷期号:15 (13): 1695-1695
标识
DOI:10.3390/diagnostics15131695
摘要
Background: The early detection of type 1 diabetes (T1D) through screening for major islet autoantibodies is receiving increasing attention as a public health strategy, exemplified by the recent implementation of a pilot pediatric screening program in Italy. The transition from research-based screening to large-scale population initiatives needs automated and standardized assays that are capable of processing extensive sample volumes. Hence, this study aimed to evaluate the analytical performance and comparability of a fully automated chemiluminescence immunoassay (CLIA) compared to a conventional enzyme-linked immunosorbent assay (ELISA) for the detection of three classes of major islet antibodies-anti-GAD (GADA), anti-IA-2 (IA-2A), and anti-ZnT8 (ZnT8A). Methods: A total of 104 serum specimens were analyzed for each autoantibody using both ELISA (RSR and Medyzim, DYNES, DSX) and CLIA (MAGLUMI 800). Assay precision and linearity were assessed through intra-assay variability studies and dilution protocols. Methods agreement was evaluated with Passing-Bablok regression, Spearman's correlation, Bland-Altman analysis, and Cohen's kappa statistics. Results: The CLIA showed good precision and excellent linearity across clinically relevant concentration ranges of all islet antibodies. Correlation coefficients and categorical agreement between CLIA and ELISA were high (r > 0.96 and Cohen's kappa >0.8 for all), with ZnT8A exhibiting the highest concordance. However, proportional biases were found, as CLIA systematically underestimated GADA and ZnT8A levels, while overestimated IA-2A compared to the ELISA. Conclusions: The CLIA displayed satisfactory precision and agreement with ELISA for GADA, IA-2A, and ZnT8A detection. Our findings support the use of these automated immunoassays in large-scale population initiatives for diagnosing T1D, but we also highlight the need for further efforts to achieve better inter-assay harmonization.
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