Hyperuricemia and Diabetic Kidney Disease: A Mechanistic Exploration and Clinical Translation Study Based on Multi-Omics Integration and Real-World Evidence

Background Diabetic kidney disease (DKD), a severe microvascular complication of diabetes. Emerging evidence implicates hyperuricemia (HUA) as a critical yet underexplored contributor to DKD pathogenesis. Methods This study integrates cross-sectional data from the National Health and Nutrition Examination Survey (NHANES), transcriptomic analysis from the Gene Expression Omnibus (GEO) database, and single-center real-world longitudinal cohort data. Using multivariate regression models, machine learning algorithms, differential gene expression analysis, and the individual slope method, we systematically investigated the association between HUA and DKD and its underlying mechanisms. Results Among 5,766 diabetic patients from NHANES, the prevalence of HUA was 38.7% in the DKD group. After multivariate adjustment, HUA independently increased the risk of DKD. Real-world data analysis of diabetic patients revealed the prevalence of HUA was 37.6% ,and a significant negative correlation between baseline serum uric acid levels and the annual estimated glomerular filtration rate (eGFR) decline rate. Patients with HUA had an increased risk of rapid renal function decline. Transcriptomic analysis identified eight uric acid metabolism-related differentially expressed genes (DEGs). To assess clinical relevance, we analysed correlations between urate-related genes and DKD traits via Nephroseq v5. Our findings suggest that HUA may accelerate DKD progression via multi-aspect. Conclusion Hyperuricemia accelerates DKD progression through multiple molecular mechanisms. Personalized uric acid management strategies based on real-world evidence hold significant clinical importance.