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Autoimmune Diseases
Volume 2014, Article ID 896787, 6 pages
Research Article

Evaluation of a Multiplex ELISA for Autoantibody Profiling in Patients with Autoimmune Connective Tissue Diseases

1Gennova Research, Gennova Scientific S.L. Seville, Spain
2Pictor Limited, Auckland, New Zealand
3Department of Metabolopathy, Hospital Virgen del Rocio, Seville, Spain

Received 4 October 2013; Accepted 30 October 2013; Published 16 January 2014

Academic Editor: Ricard Cervera

Copyright © 2014 Alejandro Caro Pérez et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The performance of immunoassays for the detection of autoantibodies is of critical importance in the diagnosis and assessment of patients with autoimmune connective tissue diseases (ACTD). Our objective was to compare the features of two multiplexed assays—INNO-LIA ANA and Gennova-PictArray ENA ELISA—for measurement of multiple autoantibodies and their utility as a clinical tool in ACTD diagnosis. The antigens included SS-A/Ro (60 and 52), SSB/La, Sm, Sm/RNP, CENP-B, Jo-1, and Scl-70. Stored sera from 85 ACTD patients and 80 controls consisting of patients with vasculitis, rheumatoid arthritis and infectious diseases, as well as healthy subjects were analyzed jointly with clinical and laboratory data. Agreement between the two methods varied between 58 and 99% (Cohen’s kappa: 0.21–0.71) mostly for SSA and SSB. The frequency of specific autoantibodies measured using the two methods was more variable for SSA, SSB, and RNP/Sm. There were a higher number of ambiguous results when using INNO-LIA. The optimized cut-off values of the Gennova-PictArray resulted in over 99% specificities in samples obtained from the control group. Sensitivity patterns were more accurate in Gennova-PictArray than in INNO-LIA, as suggested in previously reported studies. A third method could be applied to determine which of the two methods is more accurate.