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ELISA methods comparison for the detection of auto-antibodies against apolipoprotein A1
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BACKGROUND:
Autoantibodies against apolipoprotein A1 (anti-apoA1 IgG) have emerged as an independent biomarker for cardiovascular disease and mortality. Across studies, different ELISA methods have been used to measure the level of circulating anti-apoA1 IgG which could lead to substantial result differences between assays.
OBJECTIVES:
To make a comparative study of available anti-apoA1 IgG detection methods and to determine whether the choice of matrix sample (serum vs plasma) could influence the results.
METHODS:
Blood samples were obtained from 160 healthy blood donors and collected on 4 different matrixes (serum, plasma-EDTA, -citrate, -lithium-heparinate). Anti-apoA1 IgG was measured using two homemade (Geneva's and Lisbon's) and one commercial ELISA kits. Passing-Bablok and Bland-Altman were used to compare the results. Anti-apoA1 IgG seropositivity cut-offs were defined according to the user's/manufacturer's criterion.
RESULTS:
The current results showed substantial differences between those 3 assays. The dynamic ranges were significantly different, the commercial kit displaying the narrowest one. Passing-Bablok analysis demonstrated important proportional and constant biases between assays. The anti-apoA1 IgG seropositivity rate in Geneva, Lisbon and commercial assays varied between 24.5% and 1.9%. Matrix comparisons demonstrated that the matrix choice (plasma versus serum) influenced anti-apoA1 IgG results as well as the seropositivity rate in an assay-dependent manner. The coating antigen source was identified as important factor underlying results heterogeneity across assays.
CONCLUSIONS:
These results highlight the impact of the method and the cut-off used on anti-apoA1 IgG results and emphasize the need of standardizing existing assays. Given the important matrix influence, we suggest to use serum as matrix of choice.
Descrição
Palavras-chave
Biomarkers Cardiovascular diseases ELISA
Contexto Educativo
Citação
J Immunol Methods. 2019 Jun;469:33-41
Editora
Elsevier