From: Emerging technologies in autoantibody testing for rheumatic diseases
Strengths | Permits screening of many autoantigen targets simultaneously Uses very small sample volumes Can make use of stored samples May detect multiple antibody classes or subclasses Has high throughput capabilities Permits exploratory approaches to find new targets Applies unbiased analytics Carries generally lower cost per specificity than ELISA Develops insights into autoantibody clusters and relatedness |
Weaknesses | Potentially difficult to optimize all targets in one array Has batch-to-batch variability Generally lacks standardization between laboratories Normalization standards are variable Has diminished sensitivity for low-affinity autoantibodies May miss autoantibodies present at low concentrations Some autoantigens are not suitable as targets Results may be semiquantitative |