Objective To find autoantibodies (AAbs) in serum that could be useful to predict incidence of radiographic knee osteoarthritis (KOA).
Design A Nucleic-acid Programmable Protein Arrays (NAPPA) platform was used to screen AAbs against 2125 human proteins in sera at baseline from participants free of radiographic KOA belonging to the incidence and non-exposed subcohorts of the Osteoarthritis Initiative (OAI) who developed or not, radiographic KOA during a follow-up period of 96 months. NAPPA-ELISA were performed to analyse reactivity against methionine adenosyltransferase two beta (MAT2β) and verify the results in 327 participants from the same subcohorts. The association of MAT2β-AAb levels with KOA incidence was assessed by combining several robust biostatistics analysis (logistic regression, Receiver Operating Characteristic and Kaplan-Meier curves). The proposed prognostic model was replicated in samples from the progression subcohort of the OAI.
Results In the screening phase, six AAbs were found significantly different at baseline in samples from incident compared with non-incident participants. In the verification phase, high levels of MAT2β-AAb were significantly associated with the future incidence of KOA and with an earlier development of the disease. The incorporation of this AAb in a clinical model for the prognosis of incident radiographic KOA significantly improved the identification/classification of patients who will develop the disorder. The usefulness of the model to predict radiographic KOA was confirmed on a different OAI subcohort.
Conclusions The measurement of AAbs against MAT2β in serum might be highly useful to improve the prediction of OA development, and also to estimate the time to incidence.
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Handling editor Josef S Smolen
Contributors Conception and design: MC-E, JvD, JQ, JLB, CR-R and FJB. Acquisition, analysis and interpretation of data: MC-E, VB-B, FP, IR-P, JvD, JQ, MF, JLB, CR-R and FJB. Drafting the article: MC-E, VB-B, IR-P, CR-R and FJB. Final approval of the article: All authors.
Funding The Proteomics Unit belongs to ProteoRed, PRB3- ISCIII, supported by grant PT17/0019/0014. This work has been funded by grants from Fondo Investigación Sanitaria-Spain (PI14/01707, PI16/02124, PI17/00404, DTS17/00200, CIBER-BBN CB06/01/0040, CIBER-ONC CB16/12/00400, RETIC-RIER-RD12/0009/0018), a part of the National Plan for Scientific Program Development and Technological Innovation 2013-2016, funded by the ISCIII-General Subdirection of Assessment and Promotion of Research - European Regional Development Fund (FEDER) "A way of making Europe" . MC-E is supported by the Xunta de Galicia and the European Union (European Social Fund – ESF) through a predoctoral fellowship (IN606A-2016/012). IR-P and CR-R were supported by the Miguel Servet II programme from Fondo Investigación Sanitaria-Spain (CPII17/0026 and CPII15/00013, respectively).
Competing interests None declared.
Patient consent for publication Not required.
Provenance and peer review Not commissioned; externally peer reviewed.
Data availability statement All data relevant to the study are included in the article or uploaded as supplementary information.
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