Replacement of standard immunofluorescence methods with bead-based assays for antinuclear antibody (ANA) testing is a new clinical option. The aim of this study was to evaluate a large, multiethnic cohort of patients with systemic lupus erytematosus (SLE), blood relatives, and unaffected control individuals for familial aggregation and subset clustering of autoantibodies by high-throughput serum screening technology and traditional methods.
Serum samples (1,540 SLE patients, 1,154 unaffected relatives, and 906 healthy, population-based controls) were analyzed for SLE autoantibodies using a bead-based assay, indirect immunofluorescence (IIF), and immunodiffusion. Autoantibody prevalence, sensitivity for disease detection, clustering of autoantibodies, and associations between newer methods and standard immunodiffusion results were evaluated.
The frequencies of ANAs in the sera from African American, Hispanic, and European American patients with SLE were 89%, 73%, and 67%, respectively, by BioPlex 2200 bead-based assay and 94%, 84%, and 86%, respectively, by IIF. When comparing the serum prevalence of 60-kd Ro, La, Sm, nuclear RNP A, and ribosomal P autoantibodies across assays, the sensitivity of detection ranged from 0.92 to 0.83 and the specificity ranged from 0.90 to 0.79. Autoantibody cluster analysis showed associations of autoantibody specificities in 3 subsets: 1) 60 kd Ro, 52-kd Ro, and La, 2) spliceosomal proteins, and 3) double-stranded DNA (dsDNA), chromatin, and ribosomal P. Familial aggregation of Sm/RNP, ribosomal P, and 60-kd Ro in SLE patient sibling pairs was observed (P ≤ 0.004). Simplex-pedigree SLE patients had a greater prevalence of dsDNA (P = 0.0003) and chromatin (P = 0.005) autoantibodies compared to patients with a multiplex SLE pedigree.
The frequencies of ANAs detected by a bead-based assay are lower than those detected by IIF in European American patients with SLE. These assays have strong positive predictive values across ethnic groups, provide useful information for clinical care, and provide unique insights into familial aggregation and autoantibody clustering.