Urinary proteomic shifts over time and their associations with eGFR decline in chronic kidney disease

Abstract

Chronic kidney disease (CKD) is a progressive condition characterized by declining renal function, with limited biomarkers to predict its progression. The early identification of prognostic biomarkers is crucial for improving patient care and therapeutic strategies. This follow-up study investigated urinary proteomics and clinical outcomes in 18 CKD patients (stages 1-3) and 15 healthy controls using liquid chromatography-mass spectrometry and Mascot-SwissProt for protein identification. The exponentially modified protein abundance index (emPAI) was used for peptide quantification. Regression analyses were used to evaluate relationships between urinary proteins and the estimated glomerular filtration rate (eGFR), adjusting for proteinuria. At baseline, 171 proteins (median emPAI 86) were identified in CKD patients, and 271 were identified (median emPAI 47) in controls. At follow-up, 285 proteins (median emPAI 44.8) were identified in CKD patients, and 252 were identified (median emPAI 34.2) in controls. FBN1 was positively associated with eGFR, while FETUA showed a significant negative correlation at baseline. At follow-up, VTDB shifted from a negative baseline to a positive association with eGFR over time. CD44 and FBN1 shifted from a positive baseline to a negative association over time. These findings highlight VTDB, FBN1, and CD44 as potential prognostic biomarkers, providing insights into CKD progression and therapeutic targets.