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Updated: Jan 13, 2026

A Zebrafish Model of Diabetes Mellitus and Metabolic Memory
Published on: February 28, 2013
[Associations of metabolic memory burden with chronic complication in type 1 diabetes: a baseline study of the
1Department of Metabolism and Endocrinology, the Second Xiangya Hospital of Central South University, National Clinical Research Center for Endocrine and Metabolic Diseases, Key Laboratory of Diabetes Immunology, Ministry of Education, Changsha 410011, China.
Abstract:
Objective: To investigate the multidimensional glycemic profiles and their associations with chronic complications in patients with type 1 diabetes (T1D) of over 10 years' duration. Methods: This cross-sectional study used data from the prospective Peer Support for Long-standing T1D (PS-LT1D) cohort. T1D patients with a disease duration of 10-30 years were enrolled from the Chinese Type 1 Diabetes Consortium between 2022 and 2024. In addition to hemoglobin A1c (HbA1c) and continuous glucose monitoring metrics, advanced glycation end products (AGEs) were non-invasively measured as a surrogate marker for cumulative metabolic memory. Logistic regression analysis was employed to identify potential correlations between multidimensional glycemic indicators and diabetic microvascular/macrovascular complications. K-Means clustering was then applied to explore characteristic differences in complication prevalence across distinct glycemic patterns. Results: A total of 128 patients (median age 31.5 years; 41 men, 87 women) with a median disease duration of 14.3 years were included. Despite a median time-in-range (TIR) of 70.9%, the prevalence of microvascular complications remained high (42.2%, 54/128). Logistic regression analysis revealed that an elevated metabolic memory burden, represented by skin AGEs, was a significant risk factor for both microvascular and macrovascular complications (OR=1.04, 95%CI 1.01-1.07, P=0.009; OR=1.06, 95%CI 1.03-1.10, P=0.001, respectively), whereas TIR or HbA1c were not. Based on the clustering of multidimensional glycemic indicators, patients were categorized into three glycemic control phenotypes. The subgroup characterized by a high metabolic memory burden demonstrated the highest risks of retinopathy and macrovascular complications. Conclusions: A significant "metabolic memory" effect persists in patients with T1D even during the mid-to-long term course of the disease. AGEs are strongly associated with the risk of chronic complications. Complication risks vary markedly across glycemic control patterns. In assessing complication risk among patients with long-duration T1D, AGE accumulation, serving as a cumulative metabolic memory indicator, holds greater predictive value than short-to-medium term glycemic markers such as HbA1c.
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