Antigen microarray profiling of autoantibodies in rheumatoid arthritis
Antigen microarray profiling of autoantibodies in rheumatoid arthritis
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DOI：
10.1002/art.21269
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发表时间：
2005-09-01
影响因子：
--
通讯作者：
Robinson, WH
中科院分区：
文献类型：
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作者：
Hueber, W;Kidd, BA;Robinson, WH
Objective.由于类风湿性关节炎（RA）是一种异质性自身免疫性疾病的疾病表现，临床结果和治疗反应，我们开发和应用了一种新的抗原微阵列技术，以确定不同的血清抗体谱RA患者。滑膜蛋白质组微阵列，含有225肽和蛋白质，代表候选和对照抗原，开发。这些阵列用于分析来自2个不同患者组群的随机选择的血清中的自身抗体：斯坦福大学关节炎中心初始组群，包括18名确诊RA的患者和38名对照，以及关节炎、风湿病和衰老医学信息系统组群，包括58名临床诊断为RA持续时间< 6个月的患者。采用微阵列算法的显著性分析、微阵列算法的预测分析和集群软件对数据进行分析。结果。抗原微阵列表明，自身反应性B细胞反应的瓜氨酸化抗原决定簇，目前在一个子集的早期RA患者的功能预测严重的RA的发展。相反，自体免疫靶向的天然表位包含在滑膜阵列，包括几个人软骨gp39肽和II型胶原蛋白，与功能预测较轻的RA。自身抗体反应性的蛋白质组学分析提供了诊断信息，并允许将早期RA患者分层为临床相关疾病亚群。
Objective. Because rheumatoid arthritis (RA) is a heterogeneous autoimmune disease in terms of disease manifestations, clinical outcomes, and therapeutic responses, we developed and applied a novel antigen microarray technology to identify distinct serum antibody profiles in patients with RA.Methods. Synovial proteome microarrays, containing 225 peptides and proteins that represent candidate and control antigens, were developed. These arrays were used to profile autoantibodies in randomly selected sera from 2 different cohorts of patients: the Stanford Arthritis Center inception cohort, comprising 18 patients with established RA and 38 controls, and the Arthritis, Rheumatism, and Aging Medical Information System cohort, comprising 58 patients with a clinical diagnosis of RA of < 6 months duration. Data were analyzed using the significance analysis of microarrays algorithm, the prediction analysis of microarrays algorithm, and Cluster software.Results. Antigen microarrays demonstrated that autoreactive B cell responses targeting citrullinated epitopes were present in a subset of patients with early RA with features predictive of the development of severe RA. In contrast, autoimmune targeting of the native epitopes contained on synovial arrays, including several human cartilage gp39 peptides and type II collagen, were associated with features predictive of less severe RA.Conclusion. Proteomic analysis of autoantibody reactivities provides diagnostic information and allows stratification of patients with early RA into clinically relevant disease subsets.