Beijing Institute of Geriatrics, Xuanwu Hospital of Capital University of Medical Sciences, Key Laboratory for Neurodegenerative Diseases of Ministry of Education, Beijing, China.
Eur Neurol. 2011;65(2):105-11. doi: 10.1159/000323427. Epub 2011 Jan 27.
Biomarkers for neurodegenerative diseases are essential to facilitate disease diagnosis. Application of proteomics has greatly hastened the search for novel biomarkers. In this study, new potential biomarkers were discovered, and a diagnostic pattern was established for idiopathic Parkinson's disease (PD) by using proteomic technology.
Serum proteins from PD patients and controls were captured by magnetic bead-based weak cation exchange. The molecular weight of the proteins in bead-binding fraction was detected by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). Biomarker Wizard 3.1 and Biomarker Patterns Software were used for data analysis and constructing a model of biomarkers. A blinded testing set was used to validate the model.
A total of 17 discriminating m/z peaks related to PD were identified. The model based on the 5 biomarkers generated an excellent separation between PD and healthy controls with 98.36% for the sensitivity and 83.05% for the specificity. Blind test data demonstrated the model could recognize patients with PD with a sensitivity of 85.0% and a specificity of 70.0%.
The preliminary data suggested a potential application of MALDI-TOF-MS combined with magnetic beads. The model comprising 5 promising biomarkers can differentiate individuals with PD and the healthy subjects precisely.
神经退行性疾病的生物标志物对于促进疾病诊断至关重要。蛋白质组学的应用极大地加速了对新型生物标志物的寻找。在这项研究中，我们应用蛋白质组学技术发现了新的潜在生物标志物，并建立了特发性帕金森病（PD）的诊断模式。
采用基于磁珠的弱阳离子交换技术捕获 PD 患者和对照者的血清蛋白。采用基质辅助激光解吸电离飞行时间质谱（MALDI-TOF-MS）检测磁珠结合部分的蛋白质分子量。使用 Biomarker Wizard 3.1 和 Biomarker Patterns 软件进行数据分析和构建生物标志物模型。使用盲法测试集验证模型。
共鉴定出 17 个与 PD 相关的有差异的 m/z 峰。基于 5 个生物标志物的模型对 PD 与健康对照者进行了极好的区分，其敏感性为 98.36%，特异性为 83.05%。盲法测试数据表明，该模型可以识别出 PD 患者，敏感性为 85.0%，特异性为 70.0%。
初步数据表明 MALDI-TOF-MS 联合磁珠具有潜在的应用价值。该模型包含 5 个有前途的生物标志物，可精确地区分 PD 患者和健康受试者。
