Meier Matthias, Kaiser Thorsten, Herrmann Alena, Knueppel Stefan, Hillmann Meike, Koester Peer, Danne Thomas, Haller Hermann, Fliser Danilo, Mischak Harald
Department of Nephrology, Hannover Medical School, Carl-Neuberg-Strasse 1, Hannover D-30625, Germany.
J Diabetes Complications. 2005 Jul-Aug;19(4):223-32. doi: 10.1016/j.jdiacomp.2004.10.002.
Diabetic nephropathy is the main cause of morbidity and mortality in patients with Type 1 diabetes mellitus. Microalbuminuria has been established as a risk factor for the development and the progression of diabetic renal disease. A strong demand exists for better technologies to provide accurate diabetic nephropathy risk estimates before renal functional or structural disturbances already become established. Here, we present the application of a novel proteomics technology identifying urinary polypeptides and proteins. In this pilot study, we investigated 44 Type 1 diabetic patients with more than 5 years of diabetes duration compared with an age-matched control group. Random spot urine samples were examined utilizing high-resolution capillary electrophoresis (CE), coupled to mass spectrometry (MS). More than 1000 different polypeptides, characterized by their separation time and mass, were found between 800 Da and 66.5 kDa. Mathematical analysis revealed specific clusters of 54 polypeptides only found in Type 1 diabetic patients and an additional 88 polypeptides present or absent in patients with beginning nephropathy defined by the albumin-to-creatinine ratio (ACR; >35 mg/mmol). We observed polypeptide patterns characteristic for healthy controls and diabetic patients and subdivision of patients according to the excretion of polypeptides typical for diabetic nephropathy. Our study revealed that the urinary proteome contains a much greater variety of polypeptides than previously recognized and demonstrated the successful application of a novel high-throughput technology towards the human urinary proteome. Future prospective studies with the application of this technique may enable the earlier and more accurate detection of individuals at high risk to develop diabetic nephropathy.
糖尿病肾病是1型糖尿病患者发病和死亡的主要原因。微量白蛋白尿已被确认为糖尿病肾病发生和进展的危险因素。在肾功能或结构紊乱形成之前,迫切需要更好的技术来提供准确的糖尿病肾病风险评估。在此,我们展示了一种鉴定尿多肽和蛋白质的新型蛋白质组学技术的应用。在这项初步研究中,我们调查了44名糖尿病病程超过5年的1型糖尿病患者,并与年龄匹配的对照组进行比较。利用高分辨率毛细管电泳(CE)结合质谱(MS)对随机采集的尿样进行检测。在800 Da至66.5 kDa之间发现了1000多种不同的多肽,根据其分离时间和质量进行了表征。数学分析揭示了仅在1型糖尿病患者中发现的54种多肽的特定簇,以及根据白蛋白与肌酐比值(ACR;>35 mg/mmol)定义的早期肾病患者中存在或不存在的另外88种多肽。我们观察到了健康对照和糖尿病患者特有的多肽模式,并根据糖尿病肾病典型多肽的排泄情况对患者进行了细分。我们的研究表明,尿蛋白质组中含有的多肽种类比以前认识到的要多得多,并证明了一种新型高通量技术在人类尿蛋白质组研究中的成功应用。未来应用该技术的前瞻性研究可能能够更早、更准确地检测出有患糖尿病肾病高风险的个体。