iTRAQ-based comparative proteomics analysis reveals specific urinary biomarkers for various kidney diseases

Abstract

Background Urinary proteomics has been extensively applied to investigate renal diseases including acute kidney injury (AKI), chronic kidney disease (CKD), IgA nephropathy (IgAN) and diabetic CKD. However, differential urinary proteome studies have not been reported for multiple diseases. The present study was aimed to explore early clinical diagnosis biomarkers for patients with AKI, AKI+CKD, diabetic CKD, non-diabetic CKD with IgAN and non-diabetic CKD without IgAN. Methods Differentially expressed proteins (DEPs) were screened by iTRAQ labeling and 2-D LC-MS/MS. Bioinformatics analysis was performed by subsequent GO enrichment and KEGG pathway analysis. DEPs were authenticated by ELISA assay. Results 156, 156, 286, 187 and 184 differentially abundant proteins were identified in patients with AKI, AKI+CKD, diabetic CKD, and non-diabetic CKD with or without IgAN. Comparative analysis indicated that 34, 35 and 17 unique DEPs were found in AKI, AKI+CKD and CKD samples, respectively. 91 and 14 specific DEPs were screened out in diabetic CKD and non-diabetic CKD. In comparison with Non-diabetic CKD with IgAN (38 DEPs), 47 unique urinary proteins were found in Non-diabetic CKD without IgAN. Among these DEPs, urinary SAA1 and HGFAC were only unregulated in AKI and Non-diabetic CKD without IgAN implying that they might be employed as the potential indicators of the two diseases. C5, APOC1 and Reg3A upregulation was not exclusively expressed in each disease which suggested that they could not be used for biomarker to distinguish one disease from the other. Conclusion Collectively, this research contributes to the urinary biomarker discovery from multiple renal diseases.