Grupo de Investigación de Reumatología, Unidad de Proteomica, INIBIC-Complejo Hospitalario Universitario A Coruña, SERGAS, Universidad de A Coruña, A Coruña, Spain.
Grupo de Epidemiología Clínica y Bioestadística, INIBIC-Complejo Hospitalario Universitario A Coruña, SERGAS, Universidad de A Coruña, A Coruña, Spain.
Ann Rheum Dis. 2019 Dec;78(12):1699-1705. doi: 10.1136/annrheumdis-2019-215325. Epub 2019 Aug 30.
To find autoantibodies (AAbs) in serum that could be useful to predict incidence of radiographic knee osteoarthritis (KOA).
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.
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.
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.
寻找可用于预测放射学膝骨关节炎（KOA）发病的血清自身抗体（AAbs）。
使用核酸可编程蛋白阵列（NAPPA）平台，在基线时从属于骨关节炎倡议（OAI）发病和未暴露亚队列且无放射学 KOA 的参与者的血清中，针对 2125 个人类蛋白进行 AAbs 筛查，这些参与者在 96 个月的随访期间发展或未发展为放射学 KOA。进行 NAPPA-ELISA 分析以检测针对蛋氨酸腺苷转移酶 2β（MAT2β）的反应性，并在来自相同亚队列的 327 名参与者中验证结果。通过结合几种稳健的生物统计学分析（逻辑回归、接收者操作特征和 Kaplan-Meier 曲线），评估 MAT2β-AAb 水平与 KOA 发病的相关性。该预测模型在 OAI 进展亚队列的样本中进行了复制。
在筛选阶段，在发病与未发病参与者的样本中，有 6 种 AAb 在基线时差异显著。在验证阶段，高水平的 MAT2β-AAb 与 KOA 的未来发病显著相关，并且与疾病的早期发展相关。将该 AAb 纳入用于预测新发放射学 KOA 的临床模型中，显著改善了对可能发生该疾病的患者的识别/分类。该模型在不同的 OAI 亚队列中用于预测放射学 KOA 的有效性得到了验证。
血清中针对 MAT2β 的 AAbs 的测量可能对改善 OA 发病的预测以及估计发病时间非常有用。
