Biomarker discovery for inflammatory bowel disease, using proteomic serum profiling
Biomarker discovery for inflammatory bowel disease, using proteomic serum profiling
复制标题
DOI：
10.1016/j.bcp.2006.12.019
复制
发表时间：
2007-05-01
影响因子：
5.8
通讯作者：
Merville, Marie-Paule
中科院分区：
文献类型：
--
作者：
Meuwis, Marie-Alice;Fillet, Marianne;Merville, Marie-Paule
克罗恩病和溃疡性结肠炎（IBD）是胃肠道的慢性免疫炎症性疾病。这些疾病是多因素、多基因的且病因不明。临床表现是非特异性的，诊断基于临床、内窥镜、放射学和组织学标准。需要新的标记物来改善这些病理的早期诊断和分类。我们进行了一项研究，收集了 120 份血清样本，这些样本根据公认的标准分为 4 组（30 名克罗恩病患者、30 名溃疡性结肠炎患者、30 名炎症对照者和 30 名健康对照者）。我们比较了通过表面增强激光解吸电离飞行时间质谱仪 (SELDI-TOF-MS) 获得的蛋白质血清谱。使用单变量过程和基于多个决策树算法的多变量统计方法进行数据分析使我们能够选择一些潜在的生物标志物。其中四种是通过质谱和基于抗体的方法鉴定的。多变量分析生成的模型可以以良好的敏感性和特异性（至少 80%）对样本进行分类，从而区分患者群体。该分析被用作根据患者不同类别的光谱水平差异对峰进行分类的工具。纯化、鉴定了四种具有重要诊断价值的生物标志物（PF4、MRP8、FIBA 和 Hp α 2），其中两种：PF4 和 Hp α 2 通过经典方法在血清中检测到。 SELDI-TOF-MS 技术和多决策树方法的使用导致蛋白质生物标志物模式分析，并允许选择潜在的个体生物标志物。它们的下游鉴定可能有助于 IBD 分类和病因学理解。 (c) 2007 Elsevier Inc. 保留所有权利。
Crohn's disease and ulcerative colitis known as inflammatory bowel diseases (IBD) are chronic immuno-inflammatory pathologies of the gastrointestinal tract. These diseases are multifactorial, polygenic and of unknown etiology. Clinical presentation is non-specific and diagnosis is based on clinical, endoscopic, radiological and histological criteria. Novel markers are needed to improve early diagnosis and classification of these pathologies. We performed a study with 120 serum samples collected from patients classified in 4 groups (30 Crohn, 30 ulcerative colitis, 30 inflammatory controls and 30 healthy controls) according to accredited criteria. We compared protein sera profiles obtained with a Surface Enhanced Laser Desorption Ionization-Time of Flight-Mass Spectrometer (SELDI-TOF-MS). Data analysis with univariate process and a multivariate statistical method based on multiple decision trees algorithms allowed us to select some potential biomarkers. Four of them were identified by mass spectrometry and antibody based methods. Multivariate analysis generated models that could classify samples with good sensitivity and specificity (minimum 80%) discriminating groups of patients. This analysis was used as a tool to classify peaks according to differences in level on spectra through the dour categories of patients. Four biomarkers showing important diagnostic value were purified, identified (PF4, MRP8, FIBA and Hp alpha 2) and two of these: PF4 and Hp alpha 2 were detected in sera by classical methods. SELDI-TOF-MS technology and use of the multiple decision trees method led to protein biomarker patterns analysis and allowed the selection of potential individual biomarkers. Their downstream identification may reveal to be helpful for IBD classification and etiology understanding. (c) 2007 Elsevier Inc. All rights reserved.