URINARY PROTEIN PROFILING USING MASS SPECTROMETRY FOR DETECTION OF CKD BIOMARKERS

Abstract

Proteinuria is a significant risk factor for the progression of chronic kidney disease (CKD) and its complications. The kidneys excrete various individual proteins, some of which may affect CKD progression or serve as biomarkers for disease severity. However, limited data exist regarding specific urinary proteins and their relationship with CKD severity. This thesis aimed to investigate the urinary proteome in CKD patients and healthy controls, examining its connection to kidney function and proteinuria to identify potential diagnostic and prognostic proteins associated with CKD progression in two cohorts. In the initial cross-sectional study, urine samples from 137 individuals (88 CKD patients and 49 healthy controls) were analyzed using mass spectrometry-based proteomics. Protein identification was conducted using Mascot software with the SwissProt database, and statistical analyses included both parametric and non-parametric methods. Peptide quantification was performed using the exponentially modified protein abundance index (emPAI), and regression analyses were conducted to assess associations between urinary proteins and estimated glomerular filtration rate (eGFR), adjusting for proteinuria. A total of 704 individual urinary proteins were detected across the entire cohort, with distinct differences observed between patients and healthy individuals. The emPAI demonstrated a significant variation in total protein levels between CKD patients and controls (p = .007). Notably, specific urinary proteins, including AMBP, VTDB, FETUA, and B2MG, exhibited negative associations with kidney function in CKD patients. In contrast, UROM, SH3L3, RNAS1, OSTP, LV39, KNG1, CERU, CD59, CD44, and A1AG2 were positively associated with kidney function across the entire cohort, while CERU, A1BG, and LV39 consistently demonstrated positive associations in CKD patients compared to controls. These findings suggest that specific urinary proteins can be markers of kidney dysfunction or preservation in CKD. A follow-up study was conducted to further investigate urinary proteomics and its prognostic potential in the progression of CKD among a cohort of 18 CKD patients and 15 healthy individuals. The study revealed significant dynamic shifts in protein associations with eGFR over time. At baseline, urinary proteomic profiles showed distinct differences between CKD patients and controls. FBN1 exhibited a positive correlation with eGFR, while FETUA demonstrated a significant negative association. Over time, VTDB shifted from a negative to a positive correlation with eGFR, whereas FBN1 and CD44 transitioned from a positive to a negative association. These results emphasize CD44, FBN1, and VTDB as promising prognostic biomarkers, offering insights into disease progression. This comprehensive analysis of urinary proteomics highlights the importance of specific proteins as diagnostic and prognostic indicators in CKD. The evolving relationships between urinary proteins and kidney function underscore their potential utility in CKD diagnosis, progression monitoring, and therapeutic interventions.