Skin autofluorescence is associated with glycemic variability in type 2 diabetes patients.

Type 2 diabetes mellitus (T2DM) is a chronic disorder characterized by insulin resistance and hyperglycemia. To prevent diabetic complications, blood glucose levels should be maintained within a target range. While glycated hemoglobin (HbA1c) is widely used to assess long-term glycemic control, it does not provide information on glycemic variability (GV), which contributes to diabetes-related complications. Measuring skin autofluorescence (SAF) is a non-invasive method for measuring advanced glycation end-products (AGEs) in skin tissue and the accumulation of AGE is accelerated under hyperglycemic conditions. However, the relationship between SAF and GV in T2DM is not explored. This study examines the correlation between SAF and GV in T2DM patients and address the potential of SAF as a biomarker to alleviate the risk of diabetic complications. Fifty T2DM patients and fifty non-diabetic controls were recruited. SAF was measured using an AGE reader, and GV was assessed through continuous glucose monitoring (CGM) for 14 days. CGM metrics, including Mean Amplitude of Glycemic Excursions (MAGE) and Coefficient of Variation (CV), were analyzed. Serum AGE levels were measured via ELISA. Bivariate and multivariate associations between SAF and GV were examined using Pearson correlation analysis and multiple linear regression. T2DM patients exhibited higher SAF and GV compared to controls. SAF was positively correlated with GV metrics, including CV and MAGE, in diabetic patients, even after adjusting for confounding factors. No significant correlation was found between GV and serum AGE levels both in normal and T2DM subjects. SAF correlates with GV in T2DM, suggesting its potential as a non-invasive biomarker for glycemic fluctuations and associated risk. Unlike serum AGEs, SAF reflects localized AGE accumulation, which may be a complementary biomarker to HbA1c in assessing glycemic variability related with diabetes complication. Further research, such as longitudinal study, is needed to confirm its clinical utility in predicting long-term outcomes.