Serum advanced glycation end products as a putative biomarker in Type2 DKD patients' prognosis.

Abstract

Aim: Advanced glycation end products (AGEs) are pivotal mediators in diabetic kidney disease (DKD). However, their prognostic utility remains underexplored. This study introduced corrected lgAGEs [novel biomarker derived by adjusting logarithmically transformed AGEs (lgAGEs) levels based on serum albumin (ALB) levels] to enhance the prediction of adverse renal outcomes in patients with type 2 DKD (T2DKD).

Methods: In this prospective cohort study, 196 T2DKD patients were followed up longitudinally. Serum AGEs levels were log-transformed and adjusted for ALB to calculate corrected lgAGEs. Participants were stratified into the high- and low-level groups based on the median corrected lgAGEs. The association between corrected lgAGEs and renal outcomes was assessed using Cox proportional hazards models. Receiver operating characteristic (ROC) curve was utilized to evaluate the predictive performance of corrected lgAGEs alone and in combination with the urinary albumin-to-creatinine ratio (UACR).

Results: High level of corrected lgAGEs was independently associated with adverse renal outcomes [hazard ratio (HR), 3.252; 95% confidence interval (CI), 1.461-7.243; p = 0.003]. Kaplan-Meier analysis demonstrated that patients in the high-level group (12 months) exhibited significantly shorter median survival times compared with those in the low-level group (50 months). ROC analysis showed that UACR alone had an area under the curve (AUC) of 0.782 (95% CI, 0.705-0.858), with 82.8% sensitivity and 61.5% specificity. Corrected lgAGEs achieved an AUC of 0.725 (95% CI, 0.637-0.814), with 69.0% sensitivity and 76.9% specificity. Combining UACR and corrected lgAGEs improved the specificity to 75.6%, with an AUC of 0.764 (95% CI, 0.682-0.847), while maintaining a sensitivity of 70.7%.

Conclusion: Corrected lgAGEs are novel and independent biomarkers for predicting adverse renal outcomes in T2DKD. Combining UACR with corrected lgAGEs could enhance risk stratification by improving the specificity, highlighting its potential application in early identification of high-risk patients. These findings should be validated in broader populations in future research.