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Mass spectrometry-based identification of new anti-Ly and known antisynthetase autoantibodies
- Source :
- Annals of the rheumatic diseases.
- Publication Year :
- 2022
-
Abstract
- ObjectivesTo discover new and detect known antisynthetase autoantibodies (ASAs) through protein immunoprecipitation combined with gel-free liquid chromatography-tandem mass spectrometry (IP-MS).MethodsIP-MS was performed using sera of individuals showing features of antisynthetase syndrome (ASyS) without (n=5) and with (n=12) previously detected ASAs, and healthy controls (n=4). New candidate aminoacyl-tRNA-synthetase (ARS) autoantigens identified through unbiased IP-MS were confirmed by IP-western blot. A targeted IP-MS assay for various ASA specificities was developed and validated with sera of patients with known ASAs (n=16), disease controls (n=20) and healthy controls (n=25). The targeted IP-MS assay was applied in an additional cohort of patients with multiple ASyS features or isolated myositis without previously detected ASAs (n=26).ResultsAutoantibodies to cytoplasmic cysteinyl-tRNA-synthetase (CARS1) were identified by IP-MS and confirmed by western blot as a new ASA specificity, named anti-Ly, in the serum of a patient with ASyS features. Rare ASAs, such as anti-OJ, anti-Zo and anti-KS, and common ASAs could also be identified by IP-MS. A targeted IP-MS approach for ASA detection was developed and validated. Application of this method in an additional cohort identified an additional patient with anti-OJ autoantibodies that were missed by line and dot immunoassays.DiscussionCARS1 is the dominant cognate ARS autoantigen of the newly discovered anti-Ly ASA specificity. Rare and common ASA specificities could be detected by both unbiased and targeted IP-MS. Unbiased and targeted IP-MS are promising methods for discovery and detection of autoantibodies, especially autoantibodies that target complex autoantigens.
Details
- ISSN :
- 14682060
- Database :
- OpenAIRE
- Journal :
- Annals of the rheumatic diseases
- Accession number :
- edsair.doi.dedup.....4bf1db58631fd96f50cbed05367d5880