1.Optimization of oral fat tolerance test
Yilin HOU ; Qian MA ; Guangyao SONG ; Xiaoyu HOU ; Yamin LU ; Peipei TIAN ; Tingxue ZHANG ; Dandan LIU ; Shaojing ZENG ; Jinrui JI ; Luping REN
Chinese Journal of Endocrinology and Metabolism 2024;40(3):204-211
Objective:To compare the effects of different test meals on postprandial triglycerides and to optimize the standard meal composition and the blood sampling protocol for the oral fat tolerance test.Methods:This study is a prospective, open-label, randomized, cross-over trial. In March 2023, 36 volunteers were recruited in Hebei General Hospital. They underwent a health examination and oral glucose tolerance test. Twenty-six healthy volunteers(11 males and 15 females) were included in this study, with an average age of(39.08±4.56) years. Each volunteer received 75 g protein meal, 75 g fat meal, 700 kcal fixed-calorie high-fat mixed meal, and a high-fat mixed meal with energy adjusted based on 10 kcal/kg body weight. A one-week washout period of regular diet was applied before each trial. Blood was collected at fasting status and 1, 2, 3, 4, 5, and 6 hours after a meal to detect serum triglycerides, total cholesterol, low density lipoprotein-cholesterol(LDL-C), high density lipoprotein-cholesterol(HDL-C), glucose, and insulin. The variations of postprandial metabolic indicators over time following the consumption of different test meals were analyzed. The disparities in postprandial metabolic responses between the two types of mixed meals were compared.Results:The protein meal, fat meal, fixed-calorie high-fat mixed meal, and adjusted-calorie high-fat mixed meal resulted in postprandial triglyceride increases of 22.45%, 115.40%, 77.14%, and 63.63%, and insulin increase of 560.43%, 85.69%, 554.18%, and 598.97%, respectively, and with reductions in total cholesterol, LDL-C, and HDL-C ranging from 5.64%-21.81%, respectively. The blood glucose changed slightly. Changes in metabolic indicators mainly occured within 4 hours. The comparison of the characteristics of postprandial triglycerides between the two high-fat mixed meals showed no statistically significant differences( P>0.05). Conclusion:A standardize protocol with a 700 kcal fixed-calorie high-fat mixed meal as test meal, and blood lipid levels measured at fasting and at 1, 2, 3, and 4 hours after consumption, can serve as an optimized approach for oral fat tolerance test.
2.Metformin activates chaperone-mediated autophagy and improves disease pathologies in an Alzheimer disease mouse model.
Xiaoyan XU ; Yaqin SUN ; Xufeng CEN ; Bing SHAN ; Qingwei ZHAO ; Tingxue XIE ; Zhe WANG ; Tingjun HOU ; Yu XUE ; Mengmeng ZHANG ; Di PENG ; Qiming SUN ; Cong YI ; Ayaz NAJAFOV ; Hongguang XIA
Protein & Cell 2021;12(10):769-787
Chaperone-mediated autophagy (CMA) is a lysosome-dependent selective degradation pathway implicated in the pathogenesis of cancer and neurodegenerative diseases. However, the mechanisms that regulate CMA are not fully understood. Here, using unbiased drug screening approaches, we discover Metformin, a drug that is commonly the first medication prescribed for type 2 diabetes, can induce CMA. We delineate the mechanism of CMA induction by Metformin to be via activation of TAK1-IKKα/β signaling that leads to phosphorylation of Ser85 of the key mediator of CMA, Hsc70, and its activation. Notably, we find that amyloid-beta precursor protein (APP) is a CMA substrate and that it binds to Hsc70 in an IKKα/β-dependent manner. The inhibition of CMA-mediated degradation of APP enhances its cytotoxicity. Importantly, we find that in the APP/PS1 mouse model of Alzheimer's disease (AD), activation of CMA by Hsc70 overexpression or Metformin potently reduces the accumulated brain Aβ plaque levels and reverses the molecular and behavioral AD phenotypes. Our study elucidates a novel mechanism of CMA regulation via Metformin-TAK1-IKKα/β-Hsc70 signaling and suggests Metformin as a new activator of CMA for diseases, such as AD, where such therapeutic intervention could be beneficial.
3.Correction to: Metformin activates chaperone-mediated autophagy and improves disease pathologies in an Alzheimer disease mouse model.
Xiaoyan XU ; Yaqin SUN ; Xufeng CEN ; Bing SHAN ; Qingwei ZHAO ; Tingxue XIE ; Zhe WANG ; Tingjun HOU ; Yu XUE ; Mengmeng ZHANG ; Di PENG ; Qiming SUN ; Cong YI ; Ayaz NAJAFOV ; Hongguang XIA
Protein & Cell 2022;13(3):227-229