Proteomics analysis reveals age-related proteins in the urine of chronic kidney disease patients.

Chronic kidney disease (CKD) is closely linked to the aging process, making the identification of protein biomarkers that reflect aging in specific organs and tissues crucial for a deeper understanding of this phenomenon. This study aimed to identify potential aging-related proteins present in the urine of CKD patients. Utilizing liquid chromatography-tandem mass spectrometry (LC-MS/MS) proteomic analysis, we identified a total of 1,712 proteins in the urine samples from both healthy controls and CKD patients in our discovery cohort. Among the 845 proteins that overlapped, we found that 161 proteins were associated with aging. By applying a threshold of  < 0.05 and |log2 (fold change) | > 1.5, we classified 114 proteins as differentially expressed proteins (DEPs). The analyzes conducted using the Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes revealed that DEPs were significantly enriched in several clusters related to aging. In the validation cohort, we demonstrated that patients with CKD exhibited lower urinary levels of L-selectin (SELL), uromodulin (UMOD), and epidermal growth factor (EGF). Additionally, a significant negative correlation was found between age and EGF levels. The estimated glomerular filtration rate (eGFR) showed a significant positive correlation with SELL, UMOD, and EGF, while 24-h proteinuria showed a significant negative correlation with both UMOD and EGF. Furthermore, both UMOD and EGF were significantly negatively correlated with tubulointerstitial fibrosis, and EGF was significantly negatively correlated with glomerulosclerosis. In conclusion, this study emphasizes the promise of LC-MS/MS-based urine proteomics analysis in identifying aging-related protein markers. Specifically, SELL, UMOD, and EGF have been recognized as promising indicators of aging in patients with CKD.