Urinary Protein Profiling for Potential Biomarkers of Chronic Kidney Disease: A Pilot Study

Abduzhappar Gaipov, Zhalaliddin Makhammajanov, Zhanna Dauyey, Zhannur Markhametova, Kamilla Mussina, Assem Nogaibayeva, Larissa Kozina, Dana Auganova, Pavel Tarlykov, Rostislav Bukasov, Zhandos Utegulov, Duman Turebekov, Maria Jose Soler, Alberto Ortiz, Mehmet Kanbay, Abduzhappar Gaipov, Zhalaliddin Makhammajanov, Zhanna Dauyey, Zhannur Markhametova, Kamilla Mussina, Assem Nogaibayeva, Larissa Kozina, Dana Auganova, Pavel Tarlykov, Rostislav Bukasov, Zhandos Utegulov, Duman Turebekov, Maria Jose Soler, Alberto Ortiz, Mehmet Kanbay

Abstract

Proteinuria is a risk factor for chronic kidney disease (CKD) progression and associated complications. However, there is insufficient information on individual protein components in urine and the severity of CKD. We aimed to investigate urinary proteomics and its association with proteinuria and kidney function in early-stage CKD and in healthy individuals. A 24 h urine sample of 42 individuals (21-CKD and 21-healthy individuals) was used for mass spectrometry-based proteomics analysis. An exponentially modified protein abundance index (emPAI) was calculated for each protein. Data were analyzed by Mascot software using the SwissProt database and bioinformatics tools. Overall, 298 unique proteins were identified in the cohort; of them, 250 proteins belong to the control group with median (IQR) emPAI 39.1 (19−53) and 142 proteins belong to the CKD group with median (IQR) emPAI 67.8 (49−117). The level of 24 h proteinuria positively correlated with emPAI (r = 0.390, p = 0.011). The emPAI of some urinary proteomics had close positive (ALBU, ZA2G, IGKC) and negative (OSTP, CD59, UROM, KNG1, RNAS1, CD44, AMBP) correlations (r < 0.419, p < 0.001) with 24 h proteinuria levels. Additionally, a few proteins (VTDB, AACT, A1AG2, VTNC, and CD44) significantly correlated with kidney function. In this proteomics study, several urinary proteins correlated with proteinuria and kidney function. Pathway analysis identified subpathways potentially related to early proteinuric CKD, allowing the design of prospective studies that explore their response to therapy and their relationship to long-term outcomes.

Keywords: biomarkers; chronic kidney disease; proteinuria; urinary proteomics.

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
A comparison of protein distribution was identified in more than 50% of any group participants. CKD, chronic kidney disease; HC, healthy controls.
Figure 2
Figure 2
GO enrichment analysis of the 29 selected proteins in the CKD group (in red) and 37 proteins in the control group (in blue). (A) protein class. (B) cellular component. (C) biological process.
Figure 2
Figure 2
GO enrichment analysis of the 29 selected proteins in the CKD group (in red) and 37 proteins in the control group (in blue). (A) protein class. (B) cellular component. (C) biological process.
Figure 2
Figure 2
GO enrichment analysis of the 29 selected proteins in the CKD group (in red) and 37 proteins in the control group (in blue). (A) protein class. (B) cellular component. (C) biological process.
Figure 3
Figure 3
A comparison of highly significant pathways of the most relevant proteins in the CKD and healthy control groups (p < 0.003). The color codes denote the different pathway groups. CKD, chronic kidney disease; HC, healthy controls; IGF, insulin-like growth factor; IGFBPs, uptake by insulin-like growth factor binding proteins.

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