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Trial · Interventional

CompletedPhase 4Results postedRegistry data

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

NCTNCT02765399 (opens ClinicalTrials.gov in a new tab)Other idLIRA
Open at ClinicalTrials.govAsk about this trial

Overview

Status
Completed
Phase
Phase 4
Enrollment
23 participants (actual)
Sponsor
Helsinki University Central Hospital · Other
Design
Randomized · Single masking
Countries
1 country

Finland

Start
1 Feb 2015
Primary completion
28 Feb 2019
Completion
28 Feb 2019
First posted
6 May 2016 (estimated)
Last update posted
12 Apr 2022
Conditions
Type 2 Diabetes

Timeline

1 trial · 1 completed · 1 with posted results

  • Completed
  • Ongoing
  • Not yet recruiting
  • Stopped
  • Estimated dates (est.)
  • Results posted
201520162017201820192020
  1. Ph 4

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

    NCT02765399

    1 Feb 2015 to 28 Feb 2019

Registry summary

Text and fields below are the sponsor's entries at ClinicalTrials.gov, shown as posted.

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.

Interventions

  • LiraglutideDrug
  • PlaceboDrug

Arms2

  • 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.

  • 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.

Primary outcomes10

Outcomes the sponsor listed as primary.

  1. Change in Liver Fat Content

    Time frame · Baseline and after 16 weeks

    Registry description

    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.

  2. Plasma Triglyceride (TG) Area Under Curve (AUC)

    Time frame · Baseline and after 16 weeks

    Registry description

    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.

  3. Body Weight

    Time frame · Baseline and after 16 weeks

    Registry description

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

  4. Change in HbA1c Level

    Time frame · Baseline and after 16 weeks

    Registry description

    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.

  5. Change in fP-glucose Level

    Time frame · Baseline and after 16 weeks

    Registry description

    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.

  6. Change in Insulin Level

    Time frame · Baseline and after16 weeks

    Registry description

    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.

  7. Change in Matsuda Index

    Time frame · Baseline and after 16 weeks

    Registry description

    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.

  8. Change in VAT Area

    Time frame · Baseline and after 16 weeks

    Registry description

    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.

  9. Change in SAT Area

    Time frame · Baseline and after 16 weeks

    Registry description

    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.

  10. Change in ApoCIII Level

    Time frame · Baseline and after 16 weeks

    Registry description

    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 outcomes(11)

  1. Change in Hepatic de Novo Lipogenesis

    Time frame · Baseline and after 16 weeks

    Registry description

    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.

  2. Change in Systolic RR

    Time frame · Baseline and after 16 weeks

    Registry description

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

  3. Mean Total Production of apoB48

    Time frame · Baseline and after 16 weeks

    Registry description

    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.

  4. Mean Production Rate of apoB48 in CM

    Time frame · Baseline and after 16 weeks

    Registry description

    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.

  5. Mean apoB48 FTR to VLDL1 Particles

    Time frame · Baseline and after 16 weeks

    Registry description

    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.

  6. Mean TG Fractional Catabolic Rates in CM

    Time frame · Baseline and after 16 weeks

    Registry description

    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.

  7. Mean CM FDC of apoB48

    Time frame · Baseline and after 16 weeks

    Registry description

    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.

  8. Change in Direct CM-apoB48 Clearance

    Time frame · Baseline and after 16 weeks

    Registry description

    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.

  9. Mean CM-apoB48 Transfer Rates to VLDL1

    Time frame · Baseline and after 16 weeks

    Registry description

    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.

  10. Mean VLDL1-TG Production Rates

    Time frame · Baseline and after16 weeks

    Registry description

    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.

  11. Mean Fractional Catabolic Rate of VLDL2-apoB100

    Time frame · Baseline and after 16 weeks

    Registry description

    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.

Posted results

Values are shown as posted at ClinicalTrials.gov, with their units. PepBank has not converted, pooled or compared them.

Primary outcome results

Primary outcomeMean· Baseline and after 16 weeks

Change in Liver Fat Content

GroupValue (fat %)Spread
Liraglutide14.87.4
Placebo16.19.3
Primary outcomeMean· Baseline and after 16 weeks

Plasma Triglyceride (TG) Area Under Curve (AUC)

GroupValue (mmol/l per h)Spread
Liraglutide22.07.4
Placebo17.54.8
Primary outcomeMean· Baseline and after 16 weeks

Body Weight

GroupValue (kg)Spread
Liraglutide98.611.0
Placebo92.07.4
Primary outcomeMean· Baseline and after 16 weeks

Change in HbA1c Level

GroupValue (HbA1c %)Spread
Liraglutide7.01.0
Placebo6.30.3
Primary outcomeMean· Baseline and after 16 weeks

Change in fP-glucose Level

GroupValue (mmol/L)Spread
Liraglutide8.32.4
Placebo6.50.8
Primary outcomeMean· Baseline and after16 weeks

Change in Insulin Level

GroupValue (μU/mL)Spread
Liraglutide13.94.8
Placebo13.86.9
Primary outcomeMean· Baseline and after 16 weeks

Change in Matsuda Index

GroupValue (index)Spread
Liraglutide2.51.0
Placebo3.11.7
Primary outcomeMean· Baseline and after 16 weeks

Change in VAT Area

GroupValue (cm3)Spread
Liraglutide3403941
Placebo2710836

Adverse events, as posted

Adverse events as posted: participants affected out of participants at risk, by group
GroupDeathsSerious eventsOther events
LiraglutideLiraglutide 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. Liraglutide0 / 160 / 164 / 16
PlaceboPlacebo 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.0 / 70 / 71 / 7

Each cell reads participants affected / participants at risk, as the registry posted them.

Registry data comes from ClinicalTrials.gov. Study results come from studies, not from the registry. How PepBank works

Studies2

Studies that cite this trial.

Studies with results

1 study on this page

Indexing hint: Randomized controlled trial · 2019

12 results

Liraglutide treatment improves postprandial lipid metabolism and cardiometabolic risk factors in humans with adequately controlled type 2 diabetes: A single-centre randomized controlled study.

Matikainen et al. 2019Diabetes, obesity & metabolismcited by 103

PMID 30073766PMC6585708DOI 10.1111/dom.13487PUB-30073766

Free to read · publisher termsCC BY-NC12 results
Read at sourceSee results (12)

More studies

1 study on this page

PubMed tag: none · 2021

Effects of liraglutide on the metabolism of triglyceride-rich lipoproteins in type 2 diabetes.

Taskinen et al. 2021Diabetes, obesity & metabolismcited by 33

PMID 33502078DOI 10.1111/dom.14328PUB-33502078

Free to read · publisher termsCC BY-NC-ND
Read at source

Other registry references

References listed at the registry that are not in PepBank. They link to PubMed.

  • ResultBjornson 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. PMID 30779243

Eligibility

Who could join, as posted.

Sex
All
Age
from 30 Years up to 75 Years
Healthy volunteers
Not accepted
Inclusion and exclusion criteria, as posted
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

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