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Agreement between local and central anti-synthetase antibodies detection: results from the Classification Criteria of Anti-Synthetase Syndrome project biobank

  • A. Loganathan
  • , G. Zanframundo
  • , A. Yoshida
  • , S. Faghihi-Kashani
  • , I. Bauer Ventura
  • , E. Dourado
  • , F. Bozan
  • , G. Sambataro
  • , Y. Yamano
  • , S. S. Bae
  • , D. Lim
  • , A. Ceribelli
  • , N. Isailovic
  • , C. Selmi
  • , N. Fertig
  • , E. Bravi
  • , Y. Kaneko
  • , A. Pinto Saraiva
  • , V. Jovani
  • , J. Bachiller-Corral
  • J. Cifrian, A. Mera-Varela, S. Moghadam-Kia, V. Wolff, J. Campagne, A. Meyer, M. Giannini, K. Triantafyllias, J. Knitza, L. Gupta, Y. Molad, F. Iannone, I. Cavazzana, M. Piga, G. De Luca, S. Tansley, E. Bozzalla-Cassione, F. Bonella, T. J. Corte, T. J. Doyle, D. Fiorentino, M. A. Gonzalez-Gay, M. Hudson, M. Kuwana, I. E. Lundberg, A. L. Mammen, N. J. McHugh, F. W. Miller, C. Montecucco, C. V. Oddis, J. Rojas-Serrano, J. Schmidt, C. A. Scirè, A. Selva O. Callaghan, V. P. Werth, C. Alpini, S. Bozzini, L. Cavagna, R. Aggarwal

Research output: Contribution to journalArticlepeer-review

Abstract

Objective The CLASS (Classification Criteria of Anti-Synthetase Syndrome) project is a large international multicentre study that aims to create the first data-driven anti-synthetase syndrome (ASSD) classification criteria. Identifying anti-aminoacyl tRNA synthetase antibodies (anti-ARS) is crucial for diagnosis, and several commercial immunoassays are now available for this purpose. However, using these assays risks yielding false-positive or false-negative results, potentially leading to misdiagnosis. The established reference standard for detecting anti-ARS is immunoprecipitation (IP), typically employed in research rather than routine autoantibody testing. We gathered samples from participating centers and results from local anti-ARS testing. As an "ad-interim" study within the CLASS project, we aimed to assess how local immunoassays perform in real-world settings compared to our central definition of anti-ARS positivity. Methods We collected 787 serum samples from participating centres for the CLASS project and their local anti-ARS test results. These samples underwent initial central testing using RNA-IP. Following this, the specificity of ARS was reconfirmed centrally through ELISA, line-blot assay (LIA), and, in cases of conflicting results, protein-IP. The sensitivity, specificity, positive likelihood ratio and positive and negative predictive values were evaluated. We also calculated the inter-rater agreement between central and local results using a weighted ? co-efficient. Results Our analysis demonstrates that local, real-world detection of anti-Jo1 is reliable with high sensitivity and specificity with a very good level of agreement with our central definition of anti-Jo1 antibody positivity. However, the agreement between local immunoassay and central determination of anti-non-Jo1 antibodies varied, especially among results obtained using local LIA, ELISA and "other" methods. Conclusion Our study evaluates the performance of real-world identification of anti-synthetase antibodies in a large cohort of multi-national patients with ASSD and controls. Our analysis reinforces the reliability of real-world anti-Jo1 detection methods. In contrast, challenges persist for anti-non-Jo1 identification, particularly anti-PL7 and rarer antibodies such as anti-OJ/KS. Clinicians should exercise caution when interpreting anti-synthetase antibodies, especially when commercial immunoassays test positive for non-anti-Jo1 antibodies.

Original languageEnglish
Pages (from-to)277-287
Number of pages11
JournalClinical and experimental rheumatology
Volume42
Issue number2
DOIs
Publication statusPublished - 2024 Feb

Keywords

  • ELISA
  • anti-synthetase syndrome
  • classification criteria
  • idiopathic inflammatory myositis
  • immunoprecipitation
  • line immunoblot
  • myositis-associated antibodies
  • myositis-specific antibodies
  • real-world

ASJC Scopus subject areas

  • Rheumatology
  • Immunology and Allergy
  • Immunology

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