Skin autofluorescence and the complexity of complications in patients with type 2 diabetes mellitus: a cross-sectional study

Abstract

Background: The accumulation of advanced glycation end products (AGEs) occurring in skin tissues can be measured as skin autofluorescence (SAF). Here, we assessed the correlation between SAF values and the complexity and severity of type 2 diabetes mellitus (T2DM) complications. Methods: The basic clinical information of 825 patients with T2DM was collected through an electronic system, and SAF was measured by adapting a DM-Scan, a non-invasive optical signal detector. Diabetic complications were diagnosed based on clinical criteria by experienced doctors. Linear regression analysis was used to evaluate the independent determinants of SAF, and multiple logistic regression analysis was performed to assess independent determinants that influence the severity of the complications. Results: SAF was significantly associated with the complexity of T2DM complications. Similarly, independent relationships between SAF and age (β = 0.389, P < 0.001), sex (β = − 2.221, P = 0.004), 2-h C-peptide (β = − 0.182, P = 0.017), aminotransferase (ALT, β = − 0.158, P = 0.041), blood creatinine (BCr, β = 0.206, P = 0.009), and fatty liver (β = 0.161, P = 0.026) were observed. With the increasing number of complications, the SAF values increased significantly after adjusting for related risk factors. The SAF values correlated with diabetic retinopathy, diabetic kidney diseases, cardiovascular disease, and diabetic peripheral neuropathy when compared with patients without any T2DM-associated complications. Moreover, the AGE-based diabetic complication risk score for each complication demonstrated a relationship with the presence or absence of certain complications. Conclusion: SAF is an independent marker for diabetic retinopathy, diabetic kidney diseases, cardiovascular disease, and diabetic peripheral neuropathy, and it is also a predictor of the complexity of T2DM complications. Moreover, the diabetic complication risk score is capable of predicting the risk of diabetic complications in patients with T2DM.