Advances in the Identification of Novel Urinary Biomarkers for Diabetic Kidney Disease

Diabetic kidney disease (DKD) is a major microvascular complication of diabetes and remains one of the leading causes of end-stage renal disease, significantly affecting patients' survival rates and quality of life. Currently, commonly used clinical assessment indicators include proteinuria and estimated glomerular filtration rate (eGFR); however, these indicators have limited sensitivity, making it difficult to detect early kidney damage in a timely manner and to accurately monitor disease progression. This review provides a comprehensive overview of recent progress in identifying various urinary biomarkers that reflect renal tubular injury, oxidative stress, inflammatory responses, fibrotic remodeling, metabolic dysregulation, and exosomal components. Furthermore, we discuss the potential clinical applications of these biomarkers in DKD early diagnosis, disease stratification, and prognostic evaluation. Looking ahead to the future and the ongoing development of multiomics integration and artificial intelligence-assisted modeling, urinary biomarkers are expected to drive DKD diagnosis and management toward a future characterized by early detection, precision, dynamic monitoring, and noninvasive assessment.