Targeted MRM Quantification of Urinary Proteins in Chronic Kidney Disease Caused by Glomerulopathies
Alexey S. Kononikhin,
Alexander G. Brzhozovskiy,
Anna E. Bugrova,
Natalia V. Chebotareva,
Natalia V. Zakharova,
Savva Semenov,
Anatoliy Vinogradov,
Maria I. Indeykina,
Sergey Moiseev,
Irina M. Larina,
Evgeny N. Nikolaev
Affiliations
Alexey S. Kononikhin
Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Bolshoy Boulevard 30, Bld. 1, 121205 Moscow, Russia
Alexander G. Brzhozovskiy
Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Bolshoy Boulevard 30, Bld. 1, 121205 Moscow, Russia
Anna E. Bugrova
Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology of the Ministry of Health, 117997 Moscow, Russia
Natalia V. Chebotareva
Nephrology Department, Sechenov First Moscow State Medical University, Trubezkaya 8, 119048 Moscow, Russia
Natalia V. Zakharova
Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Bolshoy Boulevard 30, Bld. 1, 121205 Moscow, Russia
Savva Semenov
Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Bolshoy Boulevard 30, Bld. 1, 121205 Moscow, Russia
Anatoliy Vinogradov
Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Bolshoy Boulevard 30, Bld. 1, 121205 Moscow, Russia
Maria I. Indeykina
Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Bolshoy Boulevard 30, Bld. 1, 121205 Moscow, Russia
Sergey Moiseev
Nephrology Department, Sechenov First Moscow State Medical University, Trubezkaya 8, 119048 Moscow, Russia
Irina M. Larina
Institute of Biomedical Problems, Russian Federation State Scientific Research Center, Russian Academy of Sciences, Khoroshevskoe Shosse 76A, 123007 Moscow, Russia
Evgeny N. Nikolaev
Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Bolshoy Boulevard 30, Bld. 1, 121205 Moscow, Russia
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).