Overgaard Anne Julie, Thingholm Tine E, Larsen Martin R, Tarnow Lise, Rossing Peter, McGuire James N, Pociot Flemming
Clin Proteomics. 2010 Dec;6(4):105-114. doi: 10.1007/s12014-010-9053-0. Epub 2010 Sep 10.
As part of a clinical proteomics programme focused on diabetes and its complications, it was our goal to investigate the proteome of plasma in order to find improved candidate biomarkers to predict diabetic nephropathy. METHODS: Proteins derived from plasma from a cross-sectional cohort of 123 type 1 diabetic patients previously diagnosed as normoalbuminuric, microalbuminuric or macroalbuminuric were enriched with hexapeptide library beads and subsequently pooled within three groups. Proteins from the three groups were compared by online liquid chromatography and tandem mass spectrometry in three identical repetitions using isobaric mass tags (iTRAQ). The results were further analysed with ingenuity pathway analysis. Levels of apolipoprotein A1, A2, B, C3, E and J were analysed and validated by a multiplex immunoassay in 20 type 1 diabetic patients with macroalbuminuria and 10 with normoalbuminuria. RESULTS: A total of 112 proteins were identified in at least two out of three replicates. The global protein ratios were further evaluated by ingenuity pathway analysis, resulting in the recognition of apolipoprotein A2, B, C3, D and E as key nodes in the top-rated network. The multiplex immunoassay confirmed the overall protein expression patterns observed by the iTRAQ analysis. CONCLUSION: The candidate biomarkers discovered in this cross-sectional cohort may turn out to be progression biomarkers and might have several clinical applications in the treatment and monitoring of diabetic nephropathy; however, they need to be confirmed in a longitudinal cohort. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s12014-010-9053-0) contains supplementary material, which is available to authorized users.
作为一项专注于糖尿病及其并发症的临床蛋白质组学计划的一部分,我们的目标是研究血浆蛋白质组,以寻找更好的候选生物标志物来预测糖尿病肾病。方法:从123名先前被诊断为正常白蛋白尿、微量白蛋白尿或大量白蛋白尿的1型糖尿病患者的横断面队列中获取血浆蛋白,用六肽文库磁珠进行富集,随后分为三组。使用等压质量标签(iTRAQ),通过在线液相色谱和串联质谱对三组蛋白质进行三次相同的重复比较。结果用 Ingenuity 通路分析进一步分析。通过多重免疫测定法对20名患有大量白蛋白尿的1型糖尿病患者和10名正常白蛋白尿患者的载脂蛋白A1、A2、B、C3、E和J水平进行分析和验证。结果:在三次重复中的至少两次中总共鉴定出112种蛋白质。通过 Ingenuity通路分析进一步评估整体蛋白质比率,结果识别出载脂蛋白A2、B、C3、D和E是顶级网络中的关键节点。多重免疫测定法证实了iTRAQ分析观察到的整体蛋白质表达模式。结论:在这个横断面队列中发现的候选生物标志物可能会成为疾病进展生物标志物,并且在糖尿病肾病的治疗和监测中可能有多种临床应用;然而,它们需要在纵向队列中得到证实。电子补充材料:本文的在线版本(doi:10.1007/s12014-010-9053-0)包含补充材料,授权用户可以获取。