Division of Immunology and Rheumatology, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
Arthritis Res Ther. 2011 Jun 24;13(3):R102. doi: 10.1186/ar3383.
INTRODUCTION: The aim of this study was to develop a clinical-grade, automated, multiplex system for the differential diagnosis and molecular stratification of rheumatoid arthritis (RA). METHODS: We profiled autoantibodies, cytokines, and bone-turnover products in sera from 120 patients with a diagnosis of RA of < 6 months' duration, as well as in sera from 27 patients with ankylosing spondylitis, 28 patients with psoriatic arthritis, and 25 healthy individuals. We used a commercial bead assay to measure cytokine levels and developed an array assay based on novel multiplex technology (Immunological Multi-Parameter Chip Technology) to evaluate autoantibody reactivities and bone-turnover markers. Data were analyzed by Significance Analysis of Microarrays and hierarchical clustering software. RESULTS: We developed a highly reproducible, automated, multiplex biomarker assay that can reliably distinguish between RA patients and healthy individuals or patients with other inflammatory arthritides. Identification of distinct biomarker signatures enabled molecular stratification of early-stage RA into clinically relevant subtypes. In this initial study, multiplex measurement of a subset of the differentiating biomarkers provided high sensitivity and specificity in the diagnostic discrimination of RA: Use of 3 biomarkers yielded a sensitivity of 84.2% and a specificity of 93.8%, and use of 4 biomarkers a sensitivity of 59.2% and a specificity of 96.3%. CONCLUSIONS: The multiplex biomarker assay described herein has the potential to diagnose RA with greater sensitivity and specificity than do current clinical tests. Its ability to stratify RA patients in an automated and reproducible manner paves the way for the development of assays that can guide RA therapy.
简介:本研究旨在开发一种临床级、自动化、多重系统,用于类风湿关节炎(RA)的鉴别诊断和分子分层。
方法:我们分析了 120 例病程<6 个月的 RA 患者、27 例强直性脊柱炎患者、28 例银屑病关节炎患者和 25 例健康个体血清中的自身抗体、细胞因子和骨转换产物。我们使用商业珠粒测定法测量细胞因子水平,并开发了一种基于新型多重技术(免疫多参数芯片技术)的阵列测定法,以评估自身抗体反应和骨转换标志物。数据分析采用 Significance Analysis of Microarrays 和层次聚类软件。
结果:我们开发了一种高度可重复、自动化的多重生物标志物测定法,能够可靠地区分 RA 患者与健康个体或其他炎症性关节炎患者。鉴定出独特的生物标志物特征,使早期 RA 能够进行分子分层为具有临床相关性的亚型。在这项初步研究中,使用部分区分性生物标志物的多重测量在 RA 的诊断鉴别中提供了高灵敏度和特异性:使用 3 种生物标志物的灵敏度为 84.2%,特异性为 93.8%,使用 4 种生物标志物的灵敏度为 59.2%,特异性为 96.3%。
结论:与当前的临床检测相比,本文描述的多重生物标志物测定法具有更高的敏感性和特异性诊断 RA 的潜力。它能够以自动化和可重复的方式对 RA 患者进行分层,为开发能够指导 RA 治疗的检测方法铺平了道路。
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