Mechanisms and Current Therapeutic Targets of Podocyte Damage in Diabetic Kidney Disease.
INTRODUCTION Diabetic Kidney Disease (DKD) is a leading cause of end-stage kidney disease, and podocyte injury is a pivotal driver of albuminuria, glomerulosclerosis, and progressive loss of kidney function. METHODS A targeted narrative search of PubMed/MEDLINE, Scopus, and Web of Science was performed, primarily covering 2015-2025 and supplemented by seminal earlier studies. Inclusion criteria prioritized human studies, randomized and translational studies, and mechanistic work directly addressing podocyte injury or podocyte-relevant therapeutic effects in DKD. Studies with limited mechanistic or translational relevance were excluded or deprioritized. RESULTS Diabetic metabolic and hemodynamic stress activates AGE/PKC/RAAS signaling and downstream TGF-β/Smad, NF-κB, PI3K/Akt/mTOR, TRPC6-Ca2+, and mitochondrial stress pathways. These pathways converge on slit diaphragm disruption, actin cytoskeletal remodeling, impaired autophagy, ER stress, apoptosis, detachment, and progressive podocyte depletion. Current standard-of-care therapies, including RAAS blockade, SGLT2 inhibitors, GLP-1 receptor agonists, and finerenone, provide partial podocyte-relevant renoprotection, whereas endothelin receptor antagonists, anti-TGF-β/CTGF approaches, JAK/STAT inhibitors, TRPC6 blockade, redox-targeted therapies, RNA-based strategies, and extracellular vesicle approaches remain at different stages of clinical readiness. DISCUSSION The available evidence supports a layered model in which systemic metabolic and hemodynamic therapies reduce upstream stress, while emerging podocyte-directed strategies aim to stabilize cytoskeletal, slit diaphragm, inflammatory, fibrotic, calcium, and organelle-stress pathways. Combination therapy is biologically plausible but should be guided by albuminuria, eGFR, cardiometabolic phenotype, tolerability, and validated podocyte-related biomarkers. CONCLUSION A podocyte-centered framework that links mechanisms, biomarkers, evidence tiering, and patient stratification may improve translation of targeted and combination strategies. However, clinical implementation requires stronger biomarker validation, optimized human-relevant models, and long-term safety and outcome data.