Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Bolshoy Boulevard 30, Bld. 1, 121205 Moscow, Russia.
Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology of the Ministry of Health, 117997 Moscow, Russia.
Molecules. 2023 Apr 9;28(8):3323. doi: 10.3390/molecules28083323.
Glomerulopathies with nephrotic syndrome that are resistant to therapy often progress to end-stage chronic kidney disease (CKD) and require timely and accurate diagnosis. Targeted quantitative urine proteome analysis by mass spectrometry (MS) with multiple-reaction monitoring (MRM) is a promising tool for early CKD diagnostics that could replace the invasive biopsy procedure. However, there are few studies regarding the development of highly multiplexed MRM assays for urine proteome analysis, and the two MRM assays for urine proteomics described so far demonstrate very low consistency. Thus, the further development of targeted urine proteome assays for CKD is actual task. Herein, a BAK270 MRM assay previously validated for blood plasma protein analysis was adapted for urine-targeted proteomics. Because proteinuria associated with renal impairment is usually associated with an increased diversity of plasma proteins being present in urine, the use of this panel was appropriate. Another advantage of the BAK270 MRM assay is that it includes 35 potential CKD markers described previously. Targeted LC-MRM MS analysis was performed for 69 urine samples from 46 CKD patients and 23 healthy controls, revealing 138 proteins that were found in ≥2/3 of the samples from at least one of the groups. The results obtained confirm 31 previously proposed CKD markers. Combination of MRM analysis with machine learning for data processing was performed. As a result, a highly accurate classifier was developed (AUC = 0.99) that enables distinguishing between mild and severe glomerulopathies based on the assessment of only three urine proteins (GPX3, PLMN, and A1AT or SHBG).
肾小球疾病伴有肾病综合征,对治疗有抗性,通常会进展为终末期慢性肾脏病(CKD),需要及时准确的诊断。通过质谱(MS)多反应监测(MRM)进行靶向定量尿液蛋白质组分析是一种很有前途的早期 CKD 诊断工具,可以替代有创的活检程序。然而,目前关于用于尿液蛋白质组分析的高度多重 MRM 分析的研究很少,而且迄今为止描述的两种尿液蛋白质组学 MRM 分析显示出非常低的一致性。因此,进一步开发用于 CKD 的靶向尿液蛋白质组分析是一项实际任务。在此,我们对以前用于血浆蛋白质分析的 BAK270 MRM 分析进行了改编,用于尿液靶向蛋白质组学。由于与肾功能损害相关的蛋白尿通常与存在于尿液中的更多种类的血浆蛋白相关,因此使用该面板是合适的。BAK270 MRM 分析的另一个优点是它包括了 35 个以前描述的潜在 CKD 标志物。对来自 46 名 CKD 患者和 23 名健康对照者的 69 个尿液样本进行了靶向 LC-MRM MS 分析,结果发现了 138 种蛋白质,它们至少存在于 1/3 的样本中。所得结果证实了 31 种以前提出的 CKD 标志物。对 MRM 分析与数据处理的机器学习进行了组合。结果,开发了一种高度准确的分类器(AUC = 0.99),可以仅基于对三种尿液蛋白质(GPX3、PLMN 和 A1AT 或 SHBG)的评估来区分轻度和重度肾小球疾病。