科研之友
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摘要
Background: The age-related dysfunction of glucose and lipid metabolism has a long-standing relationship with cardiovascular and neurodegenerative disease. However, the effects of metabolic dysfunction on men and women are different. Reasons for these sex differences remains unclear. Cynomolgus monkeys have been used, in the past, for the study of human metabolic diseases due to their biologically proximity to humans. Nevertheless, few studies to date have focused on both age-and sex-related differences in glucose and lipid metabolism. The present study was designed to specifically address these questions by using a large cohort of cynomolgus monkeys (N = 1,399) including 433 males and 966 females with ages ranging 4 to 24 years old. Methods: Fasting plasma glucose (FPG) and lipid parameters including total cholesterol (T-Cho), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) were measured. All these parameters were compared between ages and sexes. Results: Among the entire cohort, age was strongly correlated with levels of FPG, TG and HDL. Consequently, sex-related analysis revealed that females had significantly higher average levels of FPG, T-Cho, TG, HDL-C and LDL-C than their male counterparts. In addition, more female (28.5 %) than male (16 %) monkeys qualified for impaired fasting plasma glucose (IFPG). In those IFPG animals, sex-related differences were also detected i.e. females had significantly increased levels of T-Cho, TG and LDL-C. Conclusions: The result, for the first time, demonstrated the similarities and differences in detail between male and female cynomolgus monkeys in relationship to age-related glucose and lipoprotein metabolisms, and differences under various physiological conditions. The detailed glucose and lipoprotein profiling should provide additional and important insights for prediabetic conditions. Cynomolgus monkeys appear to be an excellent model for translational research of diabetes and for novel therapeutic strategies testing to overt diabetes.
