Vanhoutte Kurt J A, Laarakkers Coby, Marchiori Elena, Pickkers Peter, Wetzels Jack F M, Willems Johannes L, van den Heuvel Lambert P, Russel Frans G M, Masereeuw Rosalinde
Department of Pharmacology and Toxicology (149), Nijmegen Centre for Molecular Life Sciences/Radboud University Nijmegen Medical Centre, PO Box 9101, 6500 HB Nijmegen, the Netherlands.
Nephrol Dial Transplant. 2007 Oct;22(10):2932-43. doi: 10.1093/ndt/gfm170. Epub 2007 Jul 5.
Urine proteomics is one of the key emerging technologies to discover new biomarkers for renal disease, which may be used in the early diagnosis, prognosis and treatment of patients. In the present study, we validated surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) for biomarker discovery in patients with mild ischaemic kidney injury.
We used first-morning mid-stream urine samples from healthy volunteers, and from intensive care unit patients we collected urine 12-24 h after coronary artery bypass graft (CABG) surgery. Samples of 50 volunteers were mixed to establish a reference sample (master pool). Urine samples were analysed with constant creatinine levels.
The average intra- and interchip variation was found to be in the normal experimental range (CV of 10 to 30%). Computational analysis revealed (i) low intra-individual day-to-day variation in individual healthy volunteers; (ii) high concordance between the master pool sample and individual samples. Machine learning techniques for classification of CABG condition vs healthy patients showed that (iii) in the 3-20 kDa range, the joint activity of four protein peaks effectively discriminated the two classes, (iv) in the 20-70 kDa range, a single m/z marker was sufficient to achieve perfect separation.
Our results substantiate the effectiveness of Seldi-TOF MS-based computational analysis as a tool for discovering potential biomarkers in urine samples associated with early renal injury.
尿液蛋白质组学是发现肾脏疾病新生物标志物的关键新兴技术之一，这些生物标志物可用于患者的早期诊断、预后评估和治疗。在本研究中，我们验证了表面增强激光解吸/电离飞行时间质谱（SELDI-TOF MS）在轻度缺血性肾损伤患者中发现生物标志物的能力。
我们使用了健康志愿者晨尿中段样本，对于重症监护病房患者，我们在冠状动脉搭桥术（CABG）后12 - 24小时收集尿液。将50名志愿者的样本混合以建立一个参考样本（主库）。对肌酐水平恒定的尿液样本进行分析。
发现芯片内和芯片间的平均变异在正常实验范围内（变异系数为10%至30%）。计算分析显示：（i）个体健康志愿者个体内每日变异较低；（ii）主库样本与个体样本之间具有高度一致性。用于区分CABG患者与健康患者的机器学习技术表明：（iii）在3 - 20 kDa范围内，四个蛋白峰的联合活性有效区分了这两类；（iv）在20 - 70 kDa范围内，单个m/z标记足以实现完美分离。
我们的结果证实了基于Seldi-TOF MS的计算分析作为发现与早期肾损伤相关尿液样本中潜在生物标志物工具的有效性。
