Abstract
Kidney function parameters including estimated glomerular filtration rate (eGFR) and urine albumin excretion are commonly used to diagnose chronic kidney disease (CKD). However, these parameters are relatively insensitive, limiting their utility for screening and early detection of kidney disease. Studies have suggested that urinary proteomic profiles differ by eGFR stage, offering potential insights into kidney disease pathogenesis alongside opportunities to increase the sensitivity of current testing strategies. In this study, we characterized and compared the urinary proteome across different eGFR stages in a Black African cohort from rural Mpumalanga Province, South Africa. We stratified 81 urine samples by eGFR stage (mL/min/1.73 m(2)): Stage G1 (eGFR ≥ 90; n = 36), Stage G2 (eGFR 60-89; n = 35), and Stage G3-G5 (eGFR < 60; n = 10). Urine proteomic analysis was performed using an Evosep One liquid chromatography system coupled to a Sciex 5600 TripleTOF in data-independent acquisition mode. Nonparametric multivariate analysis and receiver operating characteristic (ROC) curves were used to assess the performance of differentially abundant proteins (DAPs). Pathway analysis was performed on DAPs. Creatinine-based eGFR was calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation. In this study, thirty-eight urinary proteins were differentially abundant for eGFR Stages 3-5 when compared to Stages G1 (AUC = 0.95; CI: 0.86-1) and G2 (AUC = 0.84; CI: 0.64-0.98). Notably, only six urinary proteins (Cystatin M (CST6), glutathione hydrolase 6 (GGT6), sushi domain containing 2 (SUSD2), insulin-like growth factor binding protein 6 (IGFBP6), heat shock protein 90 beta family member 1 (HSP90B1), and mannosidase alpha class 1A member 1 (MAN1A1)) were differentially abundant when comparing Stage G1 and Stage G2 with a modest AUC = 0.81 (CI: 0.67-0.92). Pathway analysis indicated that DAPs were associated with haemostasis and fibrin clot formation. In a rural cohort from South Africa, the urinary proteome differed by eGFR stage, and we identified six differentially abundant proteins which, in combination, could help to differentiate earlier eGFR stages with higher predictive accuracy than the currently available tests.