Liu Xu, Zhang Xiaoying, Kang Yu-Jian, Huang Fei, Liu Shuang, Guo Yixue, Li Yingni, Yin Changcheng, Liu Mingling, Han Qimao, Wang Qingwen, Ye Hua, Yao Haihong, Li Chun, Li Jiahe, Pingcuo Wangzha, Zhang Yan, Su Yin, Gao Ge, Li Zhanguo, Sun Xiaolin
Department of Rheumatology and Immunology Peking University People's Hospital & Beijing Key Laboratory for Rheumatism Mechanism and Immune Diagnosis (BZ0135) Beijing China.
Chongqing Key Laboratory of Intelligent Oncology for Breast Cancer Cancer Hospital School of Medicine Chongqing University Chongqing China.
MedComm (2020). 2024 Aug 11;5(8):e679. doi: 10.1002/mco2.679. eCollection 2024 Aug.
Precise diagnostic biomarkers of anticitrullination protein antibody (ACPA)-negative and early-stage RA are still to be improved. We aimed to screen autoantibodies in ACPA-negative patients and evaluated their diagnostic performance. The human genome-wide protein arrays (HuProt arrays) were used to define specific autoantibodies from the sera of 182 RA patients and 261 disease and healthy controls. Statistical analysis was performed with SPSS 17.0. In Phase I study, 51 out of 19,275 recombinant proteins covering the whole human genome were selected. In Phase II validation study, anti-ANAPC15 (anaphase promoting complex subunit 15) exhibited 41.8% sensitivity and 91.5% specificity among total RA patients. There were five autoantibodies increased in ACPA-negative RA, including anti-ANAPC15, anti-LSP1, anti-APBB1, anti-parathymosin, and anti-UBL7. Anti-parathymosin showed the highest prevalence of 46.2% ( = 0.016) in ACPA-negative early stage (<2 years) RA. To further improve the diagnostic efficacy, a prediction model was constructed with 44 autoantibodies. With increased threshold for RA calling, the specificity of the model is 90.8%, while the sensitivity is 66.1% (87.8% in ACPA-positive RA and 23.8% in ACPA-negative RA) in independent testing patients. Therefore, HuProt arrays identified RA-associated autoantibodies that might become possible diagnostic markers, especially in early stage ACPA-negative RA.
抗瓜氨酸化蛋白抗体（ACPA）阴性及早期类风湿关节炎（RA）的精确诊断生物标志物仍有待改进。我们旨在筛选ACPA阴性患者的自身抗体并评估其诊断性能。使用人类全基因组蛋白阵列（HuProt阵列）从182例RA患者以及261例疾病对照和健康对照的血清中确定特异性自身抗体。采用SPSS 17.0进行统计分析。在I期研究中，从覆盖整个人类基因组的19,275种重组蛋白中筛选出51种。在II期验证研究中，抗后期促进复合体亚基15（ANAPC15）在所有RA患者中表现出41.8%的敏感性和91.5%的特异性。在ACPA阴性的RA中有5种自身抗体增加，包括抗ANAPC15、抗淋巴细胞特异性蛋白1（LSP1）、抗淀粉样前体蛋白结合蛋白B1（APBB1）、抗胸腺素原和抗泛素样修饰蛋白7（UBL7）。抗胸腺素原在ACPA阴性的早期（<2年）RA中患病率最高，为46.2%（P = 0.016）。为进一步提高诊断效能，构建了一个包含44种自身抗体的预测模型。在独立测试患者中，随着RA判定阈值的提高，该模型的特异性为90.8%，而敏感性为66.1%（ACPA阳性RA中为87.8%，ACPA阴性RA中为23.8%）。因此，HuProt阵列鉴定出了可能成为诊断标志物的RA相关自身抗体，尤其是在早期ACPA阴性的RA中。
