Identification of Potential Urine Biomarkers of Hypertensive Nephropathy for Predicting Disease Progression Based on Metabolomics and Peptidomics

Hypertensive nephropathy (HN) complicates hypertension with subtle early symptoms, hindering diagnosis. To address this, an integrated urinary metabolomics and peptidomics analysis was conducted comparing HN patients to hypertensive (HTN) controls, aiming to identify molecular signatures indicative of disease progression and clarify the pathophysiological mechanisms driving HN development. Urine samples were analyzed from both discovery (51 HTN vs 51 HN patients, including 27 early stage and 24 advanced-stage) and validation (21 HTN vs 21 HN) cohorts. Multivariate statistical analysis identified 40 differential metabolites across various stages: hypertension, early stage HN, and advanced-stage HN. These metabolites were associated with metabolic pathways including amino acid, carbohydrate, short-chain fatty acid, and nucleotide metabolism, such as cysteine and methionine, tyrosine, and nicotinate metabolism. Moreover, 10 differential urinary peptides were linked to coagulation regulation, immune processes, and plasminogen activation. Combining 43 clinical-correlated molecules, a high-performance diagnostic model was developed, demonstrating remarkable discrimination: AUCs of 0.973 (HTN vs early-HN), 0.998 (HTN vs advanced-HN), and 0.941 (early vs advanced-HN) in the discovery cohort, which were maintained at 0.847-0.970 in validation. Advanced-HN detection achieved exceptional accuracy (90.5%), specificity (95.2%), precision (94.7%), and an F1-score of 0.900. These urinary biomarkers aid HN diagnosis and advance mechanistic understanding.