- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT02765399
The Effect of Liraglutide Treatment on Postprandial Chylomicron and VLDL Kinetics, Liver Fat and de Novo Lipogenesis
The Effect of Liraglutide Treatment on Postprandial Chylomicron and VLDL Kinetics, Liver Fat and de Novo Lipogenesis - a Single-center Randomized Controlled Study
Study Overview
Status
Conditions
Intervention / Treatment
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.
Study Type
Enrollment (Actual)
Phase
- Phase 4
Contacts and Locations
Study Locations
-
-
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Helsinki, Finland, 00029
- Helsinki University Central Hospital
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-
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Description
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
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Treatment
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: Single
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
|---|---|
|
Experimental: 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. |
Other Names:
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Placebo Comparator: 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. |
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Change in Liver Fat Content
Time Frame: 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.
|
Baseline and after 16 weeks
|
|
Plasma Triglyceride (TG) Area Under Curve (AUC)
Time Frame: 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.
|
Baseline and after 16 weeks
|
|
Body Weight
Time Frame: 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.
|
Baseline and after 16 weeks
|
|
Change in HbA1c Level
Time Frame: 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.
|
Baseline and after 16 weeks
|
|
Change in fP-glucose Level
Time Frame: 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.
|
Baseline and after 16 weeks
|
|
Change in Insulin Level
Time Frame: 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.
|
Baseline and after16 weeks
|
|
Change in Matsuda Index
Time Frame: 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.
|
Baseline and after 16 weeks
|
|
Change in VAT Area
Time Frame: 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.
|
Baseline and after 16 weeks
|
|
Change in SAT Area
Time Frame: 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.
|
Baseline and after 16 weeks
|
|
Change in ApoCIII Level
Time Frame: 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.
|
Baseline and after 16 weeks
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Change in Hepatic de Novo Lipogenesis
Time Frame: 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.
|
Baseline and after 16 weeks
|
|
Change in Systolic RR
Time Frame: 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.
|
Baseline and after 16 weeks
|
|
Mean Total Production of apoB48
Time Frame: 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.
|
Baseline and after 16 weeks
|
|
Mean Production Rate of apoB48 in CM
Time Frame: 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.
|
Baseline and after 16 weeks
|
|
Mean apoB48 FTR to VLDL1 Particles
Time Frame: 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.
|
Baseline and after 16 weeks
|
|
Mean TG Fractional Catabolic Rates in CM
Time Frame: 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.
|
Baseline and after 16 weeks
|
|
Mean CM FDC of apoB48
Time Frame: 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.
|
Baseline and after 16 weeks
|
|
Change in Direct CM-apoB48 Clearance
Time Frame: 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.
|
Baseline and after 16 weeks
|
|
Mean CM-apoB48 Transfer Rates to VLDL1
Time Frame: 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.
|
Baseline and after 16 weeks
|
|
Mean VLDL1-TG Production Rates
Time Frame: 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.
|
Baseline and after16 weeks
|
|
Mean Fractional Catabolic Rate of VLDL2-apoB100
Time Frame: 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.
|
Baseline and after 16 weeks
|
Collaborators and Investigators
Collaborators
Investigators
- Principal Investigator: Niina Matikainen, MD, PhD, Senior Endocrinologist
Publications and helpful links
General Publications
- Matsuda M, DeFronzo RA. Insulin sensitivity indices obtained from oral glucose tolerance testing: comparison with the euglycemic insulin clamp. Diabetes Care. 1999 Sep;22(9):1462-70. doi: 10.2337/diacare.22.9.1462.
- Bjornson E, Packard CJ, Adiels M, Andersson L, Matikainen N, Soderlund S, Kahri J, Sihlbom C, Thorsell A, Zhou H, Taskinen MR, Boren J. Investigation of human apoB48 metabolism using a new, integrated non-steady-state model of apoB48 and apoB100 kinetics. J Intern Med. 2019 May;285(5):562-577. doi: 10.1111/joim.12877. Epub 2019 Mar 12.
- Zech LA, Grundy SM, Steinberg D, Berman M. Kinetic model for production and metabolism of very low density lipoprotein triglycerides. Evidence for a slow production pathway and results for normolipidemic subjects. J Clin Invest. 1979 Jun;63(6):1262-73. doi: 10.1172/JCI109421.
- Kernan WN, Inzucchi SE, Viscoli CM, Brass LM, Bravata DM, Shulman GI, McVeety JC, Horwitz RI. Pioglitazone improves insulin sensitivity among nondiabetic patients with a recent transient ischemic attack or ischemic stroke. Stroke. 2003 Jun;34(6):1431-6. doi: 10.1161/01.STR.0000071108.00234.0E. Epub 2003 May 1.
- Matikainen N, Soderlund S, Bjornson E, Pietilainen K, Hakkarainen A, Lundbom N, Taskinen MR, Boren J. Liraglutide treatment improves postprandial lipid metabolism and cardiometabolic risk factors in humans with adequately controlled type 2 diabetes: A single-centre randomized controlled study. Diabetes Obes Metab. 2019 Jan;21(1):84-94. doi: 10.1111/dom.13487. Epub 2018 Sep 4.
- Taskinen MR, Bjornson E, Matikainen N, Soderlund S, Pietilainen KH, Ainola M, Hakkarainen A, Lundbom N, Fuchs J, Thorsell A, Andersson L, Adiels M, Packard CJ, Boren J. Effects of liraglutide on the metabolism of triglyceride-rich lipoproteins in type 2 diabetes. Diabetes Obes Metab. 2021 May;23(5):1191-1201. doi: 10.1111/dom.14328. Epub 2021 Mar 5.
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Actual)
Study Completion (Actual)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Estimate)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- LIRA
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
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