Application of skin advanced glycosylation end products: a non-invasive detection technology in early screening of community diabetes mellitus

Objective To evaluate the application value of skin advanced glycosylation end products (AGEs), a non-invasive detection technology for the early screening in community diabetes mellitus. Methods A total of 701 people without history of diabetes mellitus were recruited from community health check-up center between Jan. 2018 and Jan. 2019 and divided into normal glucose tolerance group (n=443), impaired glucose regulation group (n=198) and newly diagnosed diabetes group (n=60) according to the results of oral glucose tolerance test (OGTT). Upper arm skin AGEs were detected by diabetes mellitus scan (DM Scan). Parameters of fasting plasma glucose (FPG), 2-hour postprandial blood glucose (2 h PG), glycosylated hemoglobin (HbA1c), insulin (INS), C-peptide (C-P), total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), creatinine (Cr), urea (UREA) were tested. Additionally, AGEs levels were compared in<45 years old, 45 to 59 years old and ≥60 years old age groups. One-way analysis of variance was used to compare the differences of parameters and skin AGEs levels among 3 groups, and Pearson correlation analysis and logistic regression analysis were performed. Results The levels of AGEs in prediabetes and diabetic patients in different ages were higher than those in healthy controls respectively (P<0.05). Pearson correlation analysis showed that skin AGEs were correlated with FPG and HbA1c (r=0.215 and 0.233, P<0.01). Multivariate logistic regression analysis showed that AGEs were independent risk factors for prediabetes and diabetes risk [OR (95%CI): 1.054 (1.025-1.084), 1.116 (1.071-1.163)]. The area under the receiver operator characteristic curve of DM Scan for identifying diabetes was 0.721 [95%CI (0.658-0.783)], with a sensitivity of 73.3% and specificity of 61.3%. The area under receiver operator characteristic curve of DM Scan for pre-diabetes was 0.601 [95%CI (0.551-0.652)], with a sensitivity of 35.4% and specificity of 87.1%. Conclusion Non-invasive detection of skin AGEs may be useful for assessing the risk of diabetes, but it may not be suitable for screening early diabetes mellitus. Key words: Diabetes mellitus; Pre-diabetes; Advanced glycation end products; Diabetes mellitus scan; Community screening