运用蛋白指纹图谱技术筛选类风湿关节炎患者血清特异性标志物

目的: 用纳米磁珠与基质辅助激光解吸电离飞行时间质谱(MALDI-TOF-MS)技术检测类风湿关节炎(RA)患者血清蛋白质组,筛选候选蛋白标志物并建立诊断模型,初步探讨所建立的诊断模型在RA早期诊断中的临床意义。方法: 采用弱阳离子(WCX)纳米磁性微球捕获60例RA患者、35例骨性关节炎(OA)患者和36名健康体检者血清中的蛋白质。所获蛋白经PBSⅡ-C蛋白质芯片阅读仪绘制蛋白指纹图谱。这些蛋白指纹图谱经Ciphergen ProteinChip和Biomarker Wizard软件分析之后,再用Biomarker Patterns 软件进行识别,最终筛选出RA的特异性蛋白标志物,并优化组合建立诊断模型。结果: 在RA患者和对照组之间共找到33个差异蛋白峰(P<0.05)。其中质荷比(m/z)为15 715.5D、7 771.4D、8 959.4D、8 469.8D和8 710.8D的蛋白峰用于建立RA诊断模型。经双盲实验验证,该模型对RA诊断的敏感性为86.7%,特异性为90.0%。结论: 采用WCX纳米磁性微球联用MALDI-TOF-MS技术可检出RA患者血清中的特异性蛋白标志物,并建立敏感性和特异性均较高的RA诊断模型。

Screening for specific biomarkers in serum of patients with rheumatoid arthritis using proteomic fingerprint techniques

AIM: To detect the serum protein biomarkers and establish a diagnostic model for rheumatoid arthritis (RA) adopting matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) combined with weak cationic exchange (WCX) magnetic beads, and to study the clinical significance of the model in early diagnosis of RA. METHODS: The serum samples from 60 patients with RA, 35 patients with osteoarthritis (OA) and 36 healthy controls were prepared with WCX magnetic beads, and then analyzed on PBSⅡ-C mass spectrometer reader. The protein spectra of the serum samples were normalized by Ciphergen ProteinChip software. The peak labeling was performed by Biomarker Wizard software. The specific protein biomarkers were screened by Biomarker Pattern software to construct a diagnostic model for RA. RESULTS: Totally 33 discriminative mass-to-charge (m/z) ratio were identified to be related with RA (P<0.05). Among these, the m/z peaks at 15 715.5D, 7 771.4D, 8 959.4D, 8 469.8D and 8 710.8D were used to construct a diagnostic model in a training set. In a test set, the sensitivity and specificity of the model were 86.7%and 90.0%, respectively. CONCLUSION: The potential protein biomarkers for RA are discovered in serum by MALDI-TOF-MS combined with WCX magnetic beads. The model of multiple biomarkers provides a powerful and reliable diagnostic method for RA diagnosis with high sensitivity and specificity.