Type 2 Diabetes
Conditions
Brief summary
This study aims to evaluate the mechanisms underlying the effect of incretin therapy on lipoprotein metabolism in subjects with type 2 diabetes and to study the effect of liraglutide on hepatic de novo lipogenesis.
Detailed description
The well recognized dyslipidemia in people with type 2 diabetes consists of high fasting and non-fasting plasma triglycerides (TG), low high-density lipoprotein (HDL) -cholesterol and preponderance of small dense low-density lipoprotein (LDL) particles nominated as the atherogenic lipid triad. Humans are mostly in a postprandial rather than fasting state and therefore non-fasting TG values reflect more accurately the continuous exposure of arterial wall to triglyceride rich lipoproteins (TRLs) and more importantly, to substantial cholesterol load that these particles deliver. Postprandial lipemia is highly prevalent even in type 2 diabetes patients with normal fasting TG concentrations. Intestinal overproduction of chylomicrons (CMs) and the structural protein apolipoprotein (apo)-B48 has been identified as an integral feature of postprandial lipemia in type 2 diabetes and insulin resistance. It is clinically important to elucidate the mechanism for delayed postprandial lipemia and the interactions between dysglycemia and dyslipidemia in type 2 diabetes patients.
Interventions
DRUGLiraglutide
DRUGPlacebo
Sponsors
Göteborg University
Helsinki University Central Hospital
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
TREATMENT
Masking
SINGLE (Subject)
Eligibility
Sex/Gender
ALL
Age
30 Years to 75 Years
Healthy volunteers
No
Inclusion criteria
* Subjects with type 2 diabetes treated with a lifestyle or metformin (any dose) * waist circumference \> 88 cm in women and \> 92 cm in men * BMI 27-40 kg/m2 * triglycerides between 1.0 - 4.0 mmol/L * LDL \< 4.5 mmol/l
Exclusion criteria
* Type 1 diabetes * Apo E2/2 phenotype * ALT/AST \> 3x ULN * GFR \< 60 ml/min, clinically significant TSH outside normal range * Lipid-lowering drugs other than statins within 6 months * Current treatment with pioglitazone, insulin, sulphonylureas, gliptins, glinides, SGLT-2 inhibitors or thiazide diuretics (at a dose of \> 25 mg / day) * Blood pressure \> 160 mmHg systolic and/or \> 105 diastolic * History of pancreatitis or stomach / other major bleeding, thyroid neoplasia, persistent hypothyroidism or persistent hyperthyroidism * Any medical condition that puts the patient in the risk of dehydration * Concurrent medical condition that may interfere with the interpretation of efficacy and safety data during the study. * Females of childbearing potential who are not using adequate contraceptive methods * Subjects who have experienced side-effects previously from GLP-1 agonists * Non-compliance or withdrawal of consent * Any information or clinical event described in liraglutide SPC that is a contraindication for the use of liraglutide
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Change in Liver Fat Content | Baseline and after 16 weeks | 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. |
| Plasma Triglyceride (TG) Area Under Curve (AUC) | Baseline and after 16 weeks | 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. |
| Body Weight | Baseline and after 16 weeks | Before vs after intervention (Liraglutide or placebo): Change in body weight. Results from Matikainen et al. Diabetes Obes Metab 21:84-94; 2019. |
| Change in HbA1c Level | Baseline and after 16 weeks | 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. |
| Change in fP-glucose Level | Baseline and after 16 weeks | 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. |
| Change in Insulin Level | Baseline and after16 weeks | 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. |
| Change in Matsuda Index | Baseline and after 16 weeks | 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. |
| Change in VAT Area | Baseline and after 16 weeks | 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. |
| Change in SAT Area | Baseline and after 16 weeks | 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. |
| Change in ApoCIII Level | Baseline and after 16 weeks | 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. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Change in Hepatic de Novo Lipogenesis | Baseline and after 16 weeks | 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. |
| Mean Fractional Catabolic Rate of VLDL2-apoB100 | Baseline and after 16 weeks | 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. |
| Change in Systolic RR | Baseline and after 16 weeks | Before vs after intervention (Liraglutide or placebo): systolic blood pressure measurements. Results from Matikainen et al. Diabetes Obes Metab 21:84-94; 2019. |
| Mean Total Production of apoB48 | Baseline and after 16 weeks | 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. |
| Mean Production Rate of apoB48 in CM | Baseline and after 16 weeks | 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. |
| Mean apoB48 FTR to VLDL1 Particles | Baseline and after 16 weeks | 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. |
| Mean TG Fractional Catabolic Rates in CM | Baseline and after 16 weeks | 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. |
| Mean CM FDC of apoB48 | Baseline and after 16 weeks | 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. |
| Change in Direct CM-apoB48 Clearance | Baseline and after 16 weeks | 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. |
| Mean CM-apoB48 Transfer Rates to VLDL1 | Baseline and after 16 weeks | 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. |
| Mean VLDL1-TG Production Rates | Baseline and after16 weeks | 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. |
Countries
Finland
Participant flow
Recruitment details
In total, 54 subjects were assessed for eligibility, of whom 31 were excluded because of failure to meet inclusion criteria (n = 28) or declining to participate (n = 1), or for other reasons (n = 2).
Participants by arm
| Arm | Count |
|---|---|
| Liraglutide Liraglutide subcutaneous injection once daily with following dose escalation:
liraglutide 0.6 mg once daily for one week; liraglutide 1.2 mg once daily for one week and thereafter liraglutide 1.8 mg once daily for 3.5 months.
Liraglutide | 16 |
| Placebo Placebo subcutaneous injection once daily with following dose escalation:
placebo 0.1 ml once daily for one week; placebo 0.2 ml once daily for one week and thereafter placebo 0.3 ml once daily for 3.5 months. | 7 |
| Total | 23 |
Withdrawals & dropouts
| Period | Reason | FG000 | FG001 |
|---|---|---|---|
| Overall Study | Nausea | 1 | 0 |
Baseline characteristics
| Characteristic | Liraglutide | Placebo | Total |
|---|---|---|---|
| Age, Categorical <=18 years | 0 Participants | 0 Participants | 0 Participants |
| Age, Categorical >=65 years | 0 Participants | 0 Participants | 0 Participants |
| Age, Categorical Between 18 and 65 years | 16 Participants | 7 Participants | 23 Participants |
| Race (NIH/OMB) American Indian or Alaska Native | 0 Participants | 0 Participants | 0 Participants |
| Race (NIH/OMB) Asian | 0 Participants | 0 Participants | 0 Participants |
| Race (NIH/OMB) Black or African American | 0 Participants | 0 Participants | 0 Participants |
| Race (NIH/OMB) More than one race | 0 Participants | 0 Participants | 0 Participants |
| Race (NIH/OMB) Native Hawaiian or Other Pacific Islander | 0 Participants | 0 Participants | 0 Participants |
| Race (NIH/OMB) Unknown or Not Reported | 0 Participants | 0 Participants | 0 Participants |
| Race (NIH/OMB) White | 16 Participants | 7 Participants | 23 Participants |
| Region of Enrollment Finland | 16 participants | 7 participants | 23 participants |
| Sex: Female, Male Female | 2 Participants | 4 Participants | 6 Participants |
| Sex: Female, Male Male | 14 Participants | 3 Participants | 17 Participants |
Adverse events
| Event type | EG000 affected / at risk | EG001 affected / at risk |
|---|---|---|
| deaths Total, all-cause mortality | 0 / 16 | 0 / 7 |
| other Total, other adverse events | 4 / 16 | 1 / 7 |
| serious Total, serious adverse events | 0 / 16 | 0 / 7 |
Outcome results
Primary
Body Weight
Before vs after intervention (Liraglutide or placebo): Change in body weight. Results from Matikainen et al. Diabetes Obes Metab 21:84-94; 2019.
Time frame: Baseline and after 16 weeks
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Liraglutide | Body Weight | 16 weeks | 96.1 kg | Standard Deviation 11.2 |
| Liraglutide | Body Weight | Baseline | 98.6 kg | Standard Deviation 11 |
| Placebo | Body Weight | 16 weeks | 89.8 kg | Standard Deviation 6.3 |
| Placebo | Body Weight | Baseline | 92.0 kg | Standard Deviation 7.4 |
p-value: 0.002Wilcoxon (Mann-Whitney)
p-value: 0.128Wilcoxon (Mann-Whitney)
Primary
Change in ApoCIII Level
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.
Time frame: Baseline and after 16 weeks
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Liraglutide | Change in ApoCIII Level | Baseline | 12.0 mg/dL | Standard Deviation 4.4 |
| Liraglutide | Change in ApoCIII Level | 16 weeks | 9.9 mg/dL | Standard Deviation 3.7 |
| Placebo | Change in ApoCIII Level | Baseline | 9.7 mg/dL | Standard Deviation 2.8 |
| Placebo | Change in ApoCIII Level | 16 weeks | 8.6 mg/dL | Standard Deviation 1.8 |
p-value: 0.018Wilcoxon (Mann-Whitney)
p-value: 0.578Wilcoxon (Mann-Whitney)
Primary
Change in fP-glucose Level
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.
Time frame: Baseline and after 16 weeks
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Liraglutide | Change in fP-glucose Level | Baseline | 8.3 mmol/L | Standard Deviation 2.4 |
| Liraglutide | Change in fP-glucose Level | 16 weeks | 6.4 mmol/L | Standard Deviation 1.2 |
| Placebo | Change in fP-glucose Level | Baseline | 6.5 mmol/L | Standard Deviation 0.8 |
| Placebo | Change in fP-glucose Level | 16 weeks | 6.4 mmol/L | Standard Deviation 0.9 |
p-value: 0.001Wilcoxon (Mann-Whitney)
p-value: 0.865Wilcoxon (Mann-Whitney)
Primary
Change in HbA1c Level
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.
Time frame: Baseline and after 16 weeks
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Liraglutide | Change in HbA1c Level | Baseline | 7.0 HbA1c % | Standard Deviation 1 |
| Liraglutide | Change in HbA1c Level | 16 weeks | 6.4 HbA1c % | Standard Deviation 0.7 |
| Placebo | Change in HbA1c Level | Baseline | 6.3 HbA1c % | Standard Deviation 0.3 |
| Placebo | Change in HbA1c Level | 16 weeks | 6.4 HbA1c % | Standard Deviation 0.5 |
p-value: 0.005Wilcoxon (Mann-Whitney)
p-value: 0.343Wilcoxon (Mann-Whitney)
Primary
Change in Insulin Level
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.
Time frame: Baseline and after16 weeks
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Liraglutide | Change in Insulin Level | 16 weeks | 14.5 μU/mL | Standard Deviation 4.9 |
| Liraglutide | Change in Insulin Level | Baseline | 13.9 μU/mL | Standard Deviation 4.8 |
| Placebo | Change in Insulin Level | 16 weeks | 14.1 μU/mL | Standard Deviation 5.5 |
| Placebo | Change in Insulin Level | Baseline | 13.8 μU/mL | Standard Deviation 6.9 |
p-value: 0.532Wilcoxon (Mann-Whitney)
p-value: 0.735Wilcoxon (Mann-Whitney)
Primary
Change in Liver Fat Content
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.
Time frame: Baseline and after 16 weeks
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Liraglutide | Change in Liver Fat Content | Baseline | 14.8 fat % | Standard Deviation 7.4 |
| Liraglutide | Change in Liver Fat Content | 16 weeks | 10.7 fat % | Standard Deviation 6.3 |
| Placebo | Change in Liver Fat Content | Baseline | 16.1 fat % | Standard Deviation 9.3 |
| Placebo | Change in Liver Fat Content | 16 weeks | 13.9 fat % | Standard Deviation 9.7 |
p-value: 0.001Wilcoxon (Mann-Whitney)
p-value: 0.028Wilcoxon (Mann-Whitney)
Primary
Change in Matsuda Index
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.
Time frame: Baseline and after 16 weeks
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Liraglutide | Change in Matsuda Index | Baseline | 2.5 index | Standard Deviation 1 |
| Liraglutide | Change in Matsuda Index | 16 weeks | 3.5 index | Standard Deviation 1.8 |
| Placebo | Change in Matsuda Index | Baseline | 3.1 index | Standard Deviation 1.7 |
| Placebo | Change in Matsuda Index | 16 weeks | 3.1 index | Standard Deviation 1.3 |
p-value: 0.017Wilcoxon (Mann-Whitney)
p-value: 0.753Wilcoxon (Mann-Whitney)
Primary
Change in SAT Area
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.
Time frame: Baseline and after 16 weeks
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Liraglutide | Change in SAT Area | Baseline | 4043 cm3 | Standard Deviation 1129 |
| Liraglutide | Change in SAT Area | 16 weeks | 3792 cm3 | Standard Deviation 1185 |
| Placebo | Change in SAT Area | Baseline | 5400 cm3 | Standard Deviation 1598 |
| Placebo | Change in SAT Area | 16 weeks | 5161 cm3 | Standard Deviation 1653 |
p-value: 0.004Wilcoxon (Mann-Whitney)
p-value: 0.128Wilcoxon (Mann-Whitney)
Primary
Change in VAT Area
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.
Time frame: Baseline and after 16 weeks
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Liraglutide | Change in VAT Area | Baseline | 3403 cm3 | Standard Deviation 941 |
| Liraglutide | Change in VAT Area | 16 weeks | 3185 cm3 | Standard Deviation 1014 |
| Placebo | Change in VAT Area | Baseline | 2710 cm3 | Standard Deviation 836 |
| Placebo | Change in VAT Area | 16 weeks | 2600 cm3 | Standard Deviation 825 |
p-value: 0.047Wilcoxon (Mann-Whitney)
p-value: 0.499Wilcoxon (Mann-Whitney)
Primary
Plasma Triglyceride (TG) Area Under Curve (AUC)
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.
Time frame: Baseline and after 16 weeks
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Liraglutide | Plasma Triglyceride (TG) Area Under Curve (AUC) | Baseline | 22.0 mmol/l per h | Standard Deviation 7.4 |
| Liraglutide | Plasma Triglyceride (TG) Area Under Curve (AUC) | 16 weeks | 17.1 mmol/l per h | Standard Deviation 5 |
| Placebo | Plasma Triglyceride (TG) Area Under Curve (AUC) | Baseline | 17.5 mmol/l per h | Standard Deviation 4.8 |
| Placebo | Plasma Triglyceride (TG) Area Under Curve (AUC) | 16 weeks | 19.0 mmol/l per h | Standard Deviation 6.2 |
p-value: 0.011Wilcoxon (Mann-Whitney)
p-value: 0.612Wilcoxon (Mann-Whitney)
Secondary
Change in Direct CM-apoB48 Clearance
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.
Time frame: Baseline and after 16 weeks
Population: 18 subjects only volunteered to the kinetic study.
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Liraglutide | Change in Direct CM-apoB48 Clearance | Baseline | 106 mg/day | Standard Deviation 63 |
| Liraglutide | Change in Direct CM-apoB48 Clearance | 16 weeks | 3.8 mg/day | Standard Deviation 2.5 |
| Placebo | Change in Direct CM-apoB48 Clearance | Baseline | 20 mg/day | Standard Deviation 3.8 |
| Placebo | Change in Direct CM-apoB48 Clearance | 16 weeks | 17 mg/day | Standard Deviation 12 |
p-value: <0.001Wilcoxon (Mann-Whitney)
p-value: 0.79Wilcoxon (Mann-Whitney)
Secondary
Change in Hepatic de Novo Lipogenesis
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.
Time frame: Baseline and after 16 weeks
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Liraglutide | Change in Hepatic de Novo Lipogenesis | Baseline | 15.4 μmol/L | Standard Deviation 7.4 |
| Liraglutide | Change in Hepatic de Novo Lipogenesis | 16 weeks | 19.1 μmol/L | Standard Deviation 13.1 |
| Placebo | Change in Hepatic de Novo Lipogenesis | 16 weeks | 13.8 μmol/L | Standard Deviation 11.2 |
| Placebo | Change in Hepatic de Novo Lipogenesis | Baseline | 12.6 μmol/L | Standard Deviation 7.5 |
p-value: 0.152Wilcoxon (Mann-Whitney)
p-value: 0.866Wilcoxon (Mann-Whitney)
Secondary
Change in Systolic RR
Before vs after intervention (Liraglutide or placebo): systolic blood pressure measurements. Results from Matikainen et al. Diabetes Obes Metab 21:84-94; 2019.
Time frame: Baseline and after 16 weeks
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Liraglutide | Change in Systolic RR | Baseline | 135 mm Hg | Standard Deviation 14 |
| Liraglutide | Change in Systolic RR | 16 weeks | 139 mm Hg | Standard Deviation 11 |
| Placebo | Change in Systolic RR | Baseline | 145 mm Hg | Standard Deviation 10 |
| Placebo | Change in Systolic RR | 16 weeks | 137 mm Hg | Standard Deviation 11 |
p-value: 0.173Wilcoxon (Mann-Whitney)
p-value: 0.018Wilcoxon (Mann-Whitney)
Secondary
Mean apoB48 FTR to VLDL1 Particles
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.
Time frame: Baseline and after 16 weeks
Population: 18 subjects only volunteered to the kinetic study.
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Liraglutide | Mean apoB48 FTR to VLDL1 Particles | Baseline | 12 pools/day | Standard Deviation 4 |
| Liraglutide | Mean apoB48 FTR to VLDL1 Particles | 16 weeks | 26 pools/day | Standard Deviation 13 |
| Placebo | Mean apoB48 FTR to VLDL1 Particles | Baseline | 34 pools/day | Standard Deviation 12 |
| Placebo | Mean apoB48 FTR to VLDL1 Particles | 16 weeks | 30 pools/day | Standard Deviation 10 |
p-value: <0.001Wilcoxon (Mann-Whitney)
p-value: 0.13Wilcoxon (Mann-Whitney)
Secondary
Mean CM-apoB48 Transfer Rates to VLDL1
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.
Time frame: Baseline and after 16 weeks
Population: 18 subjects only volunteered to the kinetic study.
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Liraglutide | Mean CM-apoB48 Transfer Rates to VLDL1 | Baseline | 127 mg/day | Standard Deviation 120 |
| Liraglutide | Mean CM-apoB48 Transfer Rates to VLDL1 | 16 weeks | 110 mg/day | Standard Deviation 57 |
| Placebo | Mean CM-apoB48 Transfer Rates to VLDL1 | Baseline | 170 mg/day | Standard Deviation 38 |
| Placebo | Mean CM-apoB48 Transfer Rates to VLDL1 | 16 weeks | 150 mg/day | Standard Deviation 50 |
p-value: 0.017Wilcoxon (Mann-Whitney)
p-value: 0.79Wilcoxon (Mann-Whitney)
Secondary
Mean CM FDC of apoB48
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.
Time frame: Baseline and after 16 weeks
Population: 18 subjects only volunteered to the kinetic study.
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Liraglutide | Mean CM FDC of apoB48 | Baseline | 9 pools/day | Standard Deviation 5 |
| Liraglutide | Mean CM FDC of apoB48 | 16 weeks | 0.8 pools/day | Standard Deviation 0.4 |
| Placebo | Mean CM FDC of apoB48 | Baseline | 4.4 pools/day | Standard Deviation 1.6 |
| Placebo | Mean CM FDC of apoB48 | 16 weeks | 3.2 pools/day | Standard Deviation 2.5 |
p-value: <0.001Wilcoxon (Mann-Whitney)
p-value: 0.13Wilcoxon (Mann-Whitney)
Secondary
Mean Fractional Catabolic Rate of VLDL2-apoB100
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.
Time frame: Baseline and after 16 weeks
Population: 18 subjects only volunteered to the kinetic study.
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Liraglutide | Mean Fractional Catabolic Rate of VLDL2-apoB100 | Baseline | 6.7 pools/day | Standard Deviation 2.6 |
| Liraglutide | Mean Fractional Catabolic Rate of VLDL2-apoB100 | 16 weeks | 5.6 pools/day | Standard Deviation 2.2 |
| Placebo | Mean Fractional Catabolic Rate of VLDL2-apoB100 | Baseline | 4.5 pools/day | Standard Deviation 2 |
| Placebo | Mean Fractional Catabolic Rate of VLDL2-apoB100 | 16 weeks | 5.1 pools/day | Standard Deviation 2.1 |
p-value: 0.068Wilcoxon (Mann-Whitney)
p-value: 0.63Wilcoxon (Mann-Whitney)
Secondary
Mean Production Rate of apoB48 in CM
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.
Time frame: Baseline and after 16 weeks
Population: 18 subjects only volunteered to the kinetic study.
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Liraglutide | Mean Production Rate of apoB48 in CM | Baseline | 284 mg/day | Standard Deviation 130 |
| Liraglutide | Mean Production Rate of apoB48 in CM | 16 weeks | 113 mg/day | Standard Deviation 53 |
| Placebo | Mean Production Rate of apoB48 in CM | 16 weeks | 160 mg/day | Standard Deviation 57 |
| Placebo | Mean Production Rate of apoB48 in CM | Baseline | 190 mg/day | Standard Deviation 35 |
p-value: <0.001Wilcoxon (Mann-Whitney)
p-value: 0.79Wilcoxon (Mann-Whitney)
Secondary
Mean TG Fractional Catabolic Rates in CM
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.
Time frame: Baseline and after 16 weeks
Population: 18 subjects only volunteered to the kinetic study.
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Liraglutide | Mean TG Fractional Catabolic Rates in CM | Baseline | 33 pools/day | Standard Deviation 13 |
| Liraglutide | Mean TG Fractional Catabolic Rates in CM | 16 weeks | 46 pools/day | Standard Deviation 20 |
| Placebo | Mean TG Fractional Catabolic Rates in CM | Baseline | 64 pools/day | Standard Deviation 15 |
| Placebo | Mean TG Fractional Catabolic Rates in CM | 16 weeks | 59 pools/day | Standard Deviation 12 |
p-value: 0.13Wilcoxon (Mann-Whitney)
p-value: 0.011Wilcoxon (Mann-Whitney)
Secondary
Mean Total Production of apoB48
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.
Time frame: Baseline and after 16 weeks
Population: 18 subjects only volunteered to the kinetic study.
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Liraglutide | Mean Total Production of apoB48 | Baseline | 490 mg/day | Standard Deviation 190 |
| Liraglutide | Mean Total Production of apoB48 | 16 weeks | 329 mg/day | Standard Deviation 140 |
| Placebo | Mean Total Production of apoB48 | Baseline | 570 mg/day | Standard Deviation 68 |
| Placebo | Mean Total Production of apoB48 | 16 weeks | 530 mg/day | Standard Deviation 120 |
p-value: 0.002Wilcoxon (Mann-Whitney)
p-value: 1Wilcoxon (Mann-Whitney)
Secondary
Mean VLDL1-TG Production Rates
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.
Time frame: Baseline and after16 weeks
Population: 18 subjects only volunteered to the kinetic study.
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Liraglutide | Mean VLDL1-TG Production Rates | 16 weeks | 35 g/day | Standard Deviation 9.8 |
| Liraglutide | Mean VLDL1-TG Production Rates | Baseline | 51 g/day | Standard Deviation 21 |
| Placebo | Mean VLDL1-TG Production Rates | Baseline | 43 g/day | Standard Deviation 1.7 |
| Placebo | Mean VLDL1-TG Production Rates | 16 weeks | 35 g/day | Standard Deviation 10 |
p-value: 0.017Wilcoxon (Mann-Whitney)
p-value: 0.18Wilcoxon (Mann-Whitney)