The Effect of Liraglutide Treatment on Postprandial Chylomicron and VLDL Kinetics, Liver Fat and de Novo Lipogenesis

Before vs after intervention (Liraglutide or placebo): mean liver fat content was measured by magnetic resonance imaging. Results from Matikainen et al. Diabetes Obes Metab 21:84-94; 2019.

Before vs after intervention (Liraglutide or placebo): postprandial plasma TG summary measured using the trapezoidal rule and expressed as AUC (at fasting and at 0.5, 1, 2, 3, 4, 6 and 8 hours) after oral fat tolerance test. Results from Matikainen et al. Diabetes Obes Metab 21:84-94; 2019.

Before vs after intervention (Liraglutide or placebo): Change in body weight. Results from Matikainen et al. Diabetes Obes Metab 21:84-94; 2019.

Before vs after intervention (Liraglutide or placebo): Change in B -Hemoglobiini-A1c level in plasma. Results from Matikainen et al. Diabetes Obes Metab 21:84-94; 2019.

Before vs after intervention (Liraglutide or placebo): concentration of fasting plasma glucose measured using the hexokinase method. Results from Matikainen et al. Diabetes Obes Metab 21:84-94; 2019.

Before vs after intervention (Liraglutide or placebo): Concentration of insulin level in plasma measured using electrochemiluminescence. Results from Matikainen et al. Diabetes Obes Metab 21:84-94; 2019.

Before vs after intervention (Liraglutide or placebo): Matsuda index was calculated for assessment of insulin sensitivity in plasma at time points 0, 30, 60 and 120 minutes using formula 10,000/square root of [fasting glucose x fasting insulin] x [mean glucose x mean insulin during oral glucose tolerance test]. The Matsuda index is considered to be the gold standard to determine insulin sensitivity without glucose clamp studies (Matsuda M, DeFronzo RA. Diabetes Care. 22:1462-70). Subjects who don't have insulin resistance have values of Matsuda Index of 2.5 or higher (Kerman WN et al. Stroke 34:1431;2003). Results from Matikainen et al. Diabetes Obes Metab 21:84-94; 2019.

Before vs after intervention (Liraglutide or placebo): visceral adipose tissue area measured by magnetic resonance imaging (MRI). Results from Matikainen et al. Diabetes Obes Metab 21:84-94; 2019.

Before vs after intervention (Liraglutide or placebo): subcutaneous adipose tissue area measured by magnetic resonance imaging (MRI). Results from Matikainen et al. Diabetes Obes Metab 21:84-94; 2019.

Before vs after intervention (Liraglutide or placebo): apolipoprotein CIII concentration in plasma measured by using turbidimetric immunoassay. Results from Matikainen et al. Diabetes Obes Metab 21:84-94; 2019.

Before vs after intervention (Liraglutide or placebo): Hepatic DNL is calculated from enrichment of deuterated water ingested during the kinetic study at specified time points (0, 4 and 8 hrs.). Results from Matikainen et al. Diabetes Obes Metab 21:84-94; 2019.

Before vs after intervention (Liraglutide or placebo): systolic blood pressure measurements. Results from Matikainen et al. Diabetes Obes Metab 21:84-94; 2019.

Before vs after intervention (Liraglutide or placebo): ApoB48 total production in plasma measured by using multicompartmental modeling. The power of mathematical modelling to describe the metabolic pathways of lipid and lipoprotein metabolism was demonstrated by Zech L et al (JCI 63:1262;1979) and have been widely used over 30yrs. So far few studies have focused on the modelling of apo B48 and apo B100 after a meal that is more physiological than the fasting state (Björnson E et al. JIM 285:562;2019). Production rates for apo B48, apo B100 and triglycerides in chylomicrons, VLDL1 and VLDL2 were derived from samples taken before and after the tracer injection and after the meal at 0, 30, 45, 60, 75, 90,120, 150 min and at 3, 4, 5, 6, 8, 10, 24 hrs and averages for 24 hrs. Analysis of tracer/ tracee curves of stable isotopes was used to derived the estimates of kinetic parameters using a new mathematical modeling per day. Results from Taskinen et al. Diabetes Obes Metab. 23:1191; 2021.

Before vs after intervention (Liraglutide or placebo): Change in mean production rate of ApoB48 in chylomicrons isolated from plasma samples and measured by multicompartmental modeling assay. The power of mathematical modelling to describe the metabolic pathways of lipid and lipoprotein metabolism was demonstrated by Zech L et al (JCI 1979). So far few studies have focused on the modelling of apo B48 and apo B100 after a meal that is more physiological than the fasting state (Björnson E et al. JIM 2019). Production rates for apo B48, apo B100 and triglycerides in chylomicrons, VLDL1 and VLDL2 were derived from samples taken before and after the tracer injection and after the meal at 0, 30, 45, 60, 75, 90,120, 150 min and at 3, 4, 5, 6, 8, 10, 24 hrs and averages for 24 hrs. Analysis of tracer/ tracee curves of stable isotopes was used to derived the estimates of kinetic parameters using a new mathematical modeling per day. Results from Taskinen et al.

Before vs after intervention (Liraglutide or placebo): Change in apoB48 chylomicron fractional transfer rate to VLDL1 isolated from plasma by ultracentrifugation and by liquid chromatography/mass spectrometry and calculated with multicompartmental modeling assay. So far few studies have focused on the modelling of apo B48 and apo B100 after a meal that is more physiological than the fasting state (Björnson E et al. JIM 2019). Production rates for apo B48, apo B100 and triglycerides in chylomicrons, VLDL1 and VLDL2 were derived from samples taken before and after the tracer injection and after the meal at 0, 30, 45, 60, 75, 90,120, 150 min and at 3, 4, 5, 6, 8, 10, 24 hrs and averages for 24 hrs. Analysis of tracer/ tracee curves of stable isotopes was used to derived the estimates of kinetic parameters using a new mathematical modeling per day. Results from Taskinen et al. 2021.

Before vs after intervention (Liraglutide or placebo): Change in triglycerides fractional catabolic rates in isolated chylomicrons from plasma samples measured by multicompartmental modeling assay. The power of mathematical modelling to describe the metabolic pathways of lipid and lipoprotein metabolism was demonstrated by Zech L et al (JCI 1979). So far few studies have focused on the modelling of apo B48 and apo B100 after a meal that is more physiological than the fasting state (Björnson E et al. JIM 2019). Production rates for apo B48, apo B100 and triglycerides in chylomicrons, VLDL1 and VLDL2 were derived from samples taken before and after the tracer injection and after the meal at 0, 30, 45, 60, 75, 90,120, 150 min and at 3, 4, 5, 6, 8, 10, 24 hrs and averages for 24 hrs. Analysis of tracer/ tracee curves of stable isotopes was used to derived the estimates of kinetic parameters using a new mathematical modeling per day. Results from Taskinen et al. DOM 2021.

Before vs after intervention (Liraglutide or placebo): Change in chylomicron fractional direct clearance rates of apoB48 measured from plasma by liquid chromatography - mass spectrometry with multicompartmental modeling assay. The power of mathematical modelling to describe the metabolic pathways of lipid and lipoprotein metabolism was demonstrated by Zech L et al (1979). So far few studies have focused on the modelling of apo B48 and apo B100 after a meal that is more physiological than the fasting state (Björnson E et al. 2019). Production rates for apo B48, apo B100 and triglycerides in chylomicrons, VLDL1 and VLDL2 were derived from samples taken before and after the tracer injection and after the meal at 0, 30, 45, 60, 75, 90,120, 150 min and at 3, 4, 5, 6, 8, 10, 24 hrs and averages for 24 hrs. Analysis of tracer/ tracee curves of stable isotopes was used to derived the estimates of kinetic parameters using a new mathematical modeling per day. Results from Taskinen et al. 2021.

Before vs after intervention (Liraglutide or placebo): Direct apoB48 clearance rates in isolated chylomicrons and measured by liquid chromatography - mass spectrometry and calculated by multicompartmental modeling assay. The power of mathematical modelling to describe the metabolic pathways of lipid and lipoprotein metabolism was demonstrated by Zech L et al (1979). So far few studies have focused on the modelling of apo B48 and apo B100 after a meal that is more physiological than the fasting state (Björnson E et al. 2019). Production rates for apo B48, apo B100 and triglycerides in chylomicrons, VLDL1 and VLDL2 were derived from samples taken before and after the tracer injection and after the meal at 0, 30, 45, 60, 75, 90,120, 150 min and at 3, 4, 5, 6, 8, 10, 24 hrs and averages for 24 hrs. Analysis of tracer/ tracee curves of stable isotopes was used to derived the estimates of kinetic parameters using a new mathematical modeling per day. Results from Taskinen et al. 2021.

Before vs after intervention (Liraglutide or placebo): Change in chylomicron-apoB48 transfer rates to VLDL1 isolated from plasma by ultracentrifugation and measured using multicompartmental modeling. The power of mathematical modelling to describe the metabolic pathways of lipid and lipoprotein metabolism was demonstrated by Zech L et al (1979). So far few studies have focused on the modelling of apo B48 and apo B100 after a meal that is more physiological than the fasting state (Björnson E et al. 2019). Production rates for apo B48, apo B100 and triglycerides in chylomicrons, VLDL1 and VLDL2 were derived from samples taken before and after the tracer injection and after the meal at 0, 30, 45, 60, 75, 90,120, 150 min and at 3, 4, 5, 6, 8, 10, 24 hrs and averages for 24 hrs. Analysis of tracer/ tracee curves of stable isotopes was used to derived the estimates of kinetic parameters using a new mathematical modeling per day. Results from Taskinen et al. 2021.

Before vs after intervention (Liraglutide or placebo): Change in VLDL1 production rates measured from isolated VLDL from plasma samples by ultracentrifugation and measured using mathematical modeling. The power of mathematical modelling to describe the metabolic pathways of lipid and lipoprotein metabolism was demonstrated by Zech L et al (JCI 1979). So far few studies have focused on the modelling of apo B48 and apo B100 after a meal that is more physiological than the fasting state (Björnson E et al. JIM 2019). Production rates for apo B48, apo B100 and triglycerides in chylomicrons, VLDL1 and VLDL2 were derived from samples taken before and after the tracer injection and after the meal at 0, 30, 45, 60, 75, 90,120, 150 min and at 3, 4, 5, 6, 8, 10, 24 hrs and averages for 24 hrs. Analysis of tracer/ tracee curves of stable isotopes was used to derived the estimates of kinetic parameters using a new mathematical modeling per day. Results from Taskinen et al. DOM 2021.

Before vs after intervention (Liraglutide or placebo): Change in VLDL2-apoB100 fractional catabolic rates measured from isolated VLDL2 from plasma by ultracentrifugation and measured using mathematical modeling. The power of mathematical modelling to describe the metabolic pathways of lipid and lipoprotein metabolism was demonstrated by Zech L et al (JCI 1979). So far few studies have focused on the modelling of apo B48 and apo B100 after a meal that is more physiological than the fasting state (Björnson E et al. JIM 2019). Production rates for apo B48, apo B100 and triglycerides in chylomicrons, VLDL1 and VLDL2 were derived from samples taken before and after the tracer injection and after the meal at 0, 30, 45, 60, 75, 90,120, 150 min and at 3, 4, 5, 6, 8, 10, 24 hrs and averages for 24 hrs. Analysis of tracer/ tracee curves of stable isotopes was used to derived the estimates of kinetic parameters using a new mathematical modeling per day. Results from Taskinen et al. DOM 2021.