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Licensed Unlicensed Requires Authentication Published by De Gruyter April 6, 2013

Automated indirect immunofluorescence antinuclear antibody analysis is a standardized alternative for visual microscope interpretation

Carolien Bonroy, Charlotte Verfaillie, Vanessa Smith, Lies Persijn, Evy De Witte, Filip De Keyser and Katrien Devreese


Background: Screening for antinuclear antibodies (ANA) is a basic tool in the serological work-up of systemic rheumatic disorders. Despite the emergence of alternative screening methods and the difficulties in standardization, indirect immunofluorescence (IIF) remains the recommended method for ANA detection. This study aimed to assess the reliability of automated ANA IIF analysis as a standardized alternative for the conventional manual approach.

Methods: ANA testing on HEp-2000 cells was performed on 304 consecutive routine sera, 28 serumbank samples displaying rare staining patterns, 219 samples of well-defined disease cohorts [141 systemic sclerosis (SSc), 13 polymyalgia rheumatica, 22 osteoarthritis, 5 ANCA-associated vasculitis and 38 spondyloarthritis] and 100 healthy donors. All samples were analyzed by automated IIF (Zenit G-sight), by conventional visual IIF microscopy and two ANA screening enzyme immunoassays (EIA).

Results: Automated and conventional ANA IIF analysis were comparable for negative/positive interpretation as well as intensity assessment (>90% agreement). In contrast, the accuracy of pattern recognition (26%) was limited. Likelihood ratios (LR) for SSc on results intervals of both Zenit G-sight and EIA increased with increasing level of positivity. Sensitivity within the SSc-associated antibody subsets was higher for Zenit G-sight (97%–100%) than EIA (10%–96%). A significant correlation between the quantitative result obtained by Zenit G-sight and the conventional end-point titer was found.

Conclusions: The use of Zenit G-sight for automated ANA IIF analysis offers opportunities to improve standardization. However, a complementary role of the expert technicians remains, especially for pattern recognition and classification of uncertain/negative samples.

Corresponding author: Carolien Bonroy, Ghent University Hospital (2P8), De Pintelaan 185, 9000 Ghent, Belgium, Phone: +32 9 3323631, Fax: +32 9 3324985

The technical assistance of Ms. Virgie Baert, Ms. Annette Heirwegh, Ms. Vicky Mortier, Ms. Elke Lecocq, Ms. Hanan Khajou and Ms. Hanife Kofur is greatly acknowledged.

Conflict of interest statement

Authors’ conflict of interest disclosure: The authors stated that there are no conflicts of interest regarding the publication of this article.

Research funding: Carolien Bonroy is supported by a research grant from the Fund for Scientific Research, Flanders.

Employment or leadership: None declared.

Honorarium: None declared.


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Received: 2013-1-4
Accepted: 2013-3-14
Published Online: 2013-04-06
Published in Print: 2013-09-01

©2013 by Walter de Gruyter Berlin Boston

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