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Urinary proteomics in chronic kidney disease: diagnosis and risk of progression beyond albuminuria

机译:慢性肾脏疾病中的泌尿蛋白质组学:诊断和进展超过蛋白尿的风险

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Background: The contrast between a high prevalence of chronic kidney disease (CKD) and the low incidence of end-stage renal disease highlights the need for new biomarkers of progression beyond albuminuria testing. Urinary proteomics is a promising method, but more studies focusing on progression rate and patients with hypertensive nephropathy are needed. Results: We analyzed urine samples with capillary electrophoresis coupled to a mass-spectrometer from 18 well characterized patients with CKD stage 4-5 (of whom six with hypertensive nephropathy) and 17 healthy controls. Classification scores based on a previously developed panel of 273 urinary peptides were calculated and compared to urine albumin dipstick results. Urinary proteomics classified CKD with a sensitivity of 0.95 and specificity of 1.00. Overall diagnostic accuracy (area under ROC curve) was 0.98, which was better than for albuminuria (0.85, p = 0.02). Results for hypertensive nephropathy were similar to other CKD diagnoses. Adding the proteomic score to an albuminuria model improved detection of rapid kidney function decline (>4 ml/min/1.73 m~2 per year) substantially: area under ROC curve increased from 0.762 to 0.909 (p = 0.042), and 38% of rapid progressors were correctly reclassified to a higher risk and 55% of slow progressors were correctly reclassified to a lower risk category. Reduced excretion of collagen types l-lll, uromodulin, and other indicators of interstitial inflammation, fibrosis and tubular dysfunction were associated with CKD diagnosis and rapid progression. Patients with hypertensive nephropathy displayed the same findings as other types of CKD. Conclusions: Urinary proteomic analyses had a high diagnostic accuracy for CKD, including hypertensive nephropathy, and strongly improved identification of patients with rapid kidney function decline beyond albuminuria testing.
机译:背景:慢性肾脏病(CKD)的高流行与终末期肾脏病的低发生率之间的对比突出表明,除了蛋白尿测试外,还需要新的生物标志物进行疾病进展。尿蛋白质组学是一种有前途的方法,但是需要更多的研究来关注进展率和高血压肾病患者。结果:我们采用毛细管电泳结合质谱仪分析了来自18例特征明确的CKD 4-5期患者(其中6例患有高血压肾病)和17例健康对照患者的尿液样本。计算基于先前开发的273种尿肽的分类评分,并将其与尿白蛋白试纸结果进行比较。尿蛋白质组学对CKD的敏感性为0.95,特异性为1.00。总体诊断准确性(ROC曲线下的面积)为0.98,优于白蛋白尿(0.85,p = 0.02)。高血压肾病的结果与其他CKD诊断相似。将蛋白质组学分数添加到蛋白尿模型中,可显着改善肾脏功能快速下降(> 4 ml / min / 1.73 m〜2每年)的检测:ROC曲线下的面积从0.762增至0.909(p = 0.042),占38%快速进展者被正确地重新分类为较高的风险,慢进展者中的55%被正确地重新分类为较低的风险类别。 CKD诊断和快速进展与减少的l-11型胶原蛋白,尿调节蛋白和其他间质性炎症,纤维化和肾小管功能障碍指标的排泄有关。高血压肾病患者表现出与其他类型的CKD相同的发现。结论:尿蛋白质组学分析对CKD(包括高血压性肾病)的诊断准确性很高,并且对肾功能快速下降的患者(白蛋白尿测试除外)的识别能力大大提高。

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