High Blood Glucose
Conditions
Keywords
Seaweed, Insulin, Glucose tolerance, C-peptide, Appetide, Metabolomics
Brief summary
The project is a randomized, 3-way, blinded crossover trial in which 20 healthy, fasted participants consume meals with 30 g of a linear corn starch and 5 g of one of the seaweeds, Laminara digitata or Undaria pinnatifida or a pea protein control. The primary aim is to investigate whether the brown seaweeds affect the postprandial glucose Area Under the Curve (AUC). Stomach emptying, insulin, C-peptide, appetite-regulating hormones (oxyntomodulin, glucagon, GLP-1 and PYY), and specific metabolites from the seaweeds in the urine and plasma as well as subjective satiety are also analyzed.
Detailed description
Brown seaweeds may contain bioactive compounds as they contain secondary plant metabolites, including flavonoids and other phenolic compounds as well as carotenoids. Dietary fibre is the major component of brown seaweeds, mainly composed from laminarans, alginates, fucans and cellulose. Several dietary fibers and secondary plant metabolites have been shown to have an impact on health and more specifically on glycemic control. Therefore, the aim of this study was to investigate whether two selected brown seaweeds have an effect on the postprandial glucose response to a starch load as well as several secondary measures, including appetite responses. In a controlled crossover trial, 20 healthy fasted participants consumed 5 g of either Laminaria digitata (LD) or Undaria pinnatifida (UP) or 1 g of pea protein (CTR). The volunteers concomitantly ingested 200 mL of a drink with corn starch. Blood samples were drawn at baseline, as well as 20, 40, 60, 90, 120 and 180 min after the meal. Differences in glucose, insulin, C-peptide, plasma incretin concentrations, and insulin sensitivity index (ISI) were analyzed and appetite was scored by a visual analogue scale and a subsequent ad libitum test meal.
Interventions
OTHERLD
Participants ingested 5 g of Laminaria digitata followed by 30 g of corn starch mixed with 200 mL of water.
OTHERUP
Participants ingested 5 g of Undaria pinnatifida followed by 30 g of corn starch mixed with 200 mL of water.
OTHERCTR
Participants ingested 30 g of corn starch and 1 g of pea protein powder mixed with 200 mL of water.
Sponsors
Ministry of Education, Malaysia
Universiti Malaysia Pahang
University of Copenhagen
Study design
Allocation
RANDOMIZED
Intervention model
CROSSOVER
Primary purpose
PREVENTION
Masking
DOUBLE (Investigator, Outcomes Assessor)
Eligibility
Sex/Gender
ALL
Age
20 Years to 50 Years
Healthy volunteers
Yes
Inclusion criteria
BMI 20-25 kg/m2. Waist circumference \< 102 cm. Non-smoking. Like (can tolerate) seaweed, pasta, meat sauce as these foods are part of the test meal. Can tolerate paracetamol (Pinex, Actavis, Denmark).
Exclusion criteria
Systemic infections, psychiatric or metabolic diseases, and any clinical condition, chronic or frequent use of medication (including blood thinners, excluding contraceptives), smoking (throughout the trial and 12 months before the start of the experiment), blood donations during or in the month leading up to the study period, elite athletes (\> 10 hours of hard exercise / week, self-reported), high intake of alcohol (defined as a weekly intake of \> 7 units for women and \> 14 units for men), have or have had a drug addiction, participation in other scientific studies during the study period, lactating, pregnancy or ongoing planning of pregnancy, and vegetarianism or veganism.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Plasma glucose Area Under the Curve (Glucose AUC) | 0- 180 min | The area under the plasma glucose concentration curve was calculated from 0-180 min after 30 g of corn starch was ingested. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Plasma glucose concentrations | 20, 40, 60, 90, 120 and 180 min | Changes in the glucose concentrations determined by a mixed model analysis and subsequently at each time point with time 0 as a co-variate. |
| Serum Insulin Area Under the Curve | 0-180 min | Area Under the Curve (AUC) for serum insulin. |
| Serum Insulin concentrations | : 20, 40, 60, 90, 120 and 180 min | Changes in the insulin concentrations determined by a mixed model analysis and subsequently at each time point with time 0 as a co-variate. |
| ISI (0-180) | 0-180 min | Matsuda's Insulin Sensitivity Index |
| Serum C-peptide Area Under the Curve | 0-180 min | Area Under the Curve (AUC) for serum C-peptide. |
| Plasma GLP-1 concentrations | 20, 40, 60, 90, 120 and 180 min | Changes in the plasma GLP-1 concentrations determined by a mixed model analysis and subsequently at each time point with time 0 as a co-variate |
| Subjective appetite scores assessed by visual analogue scale (VAS) | 0-180 min | Area Under the Curve (AUC) for all VAS outcomes (satiety, hunger, fullness, prospective food consumption and comfort) |
| Serum C-peptide concentrations | 20, 40, 60, 90, 120 and 180 min | Changes in the C-peptide concentrations determined by a mixed model analysis and subsequently at each time point with time 0 as a co-variate. |
| Plasma GLP-1 Area Under the Curve | 0-180 min | Area Under the Curve (AUC) for plasma GLP-1. |
Other
| Measure | Time frame | Description |
|---|---|---|
| Metabolic profile in urine | 0-24 hrs | Untargeted metabolic profile of urine samples measured in all samples collected before the meal and postprandially from 0-90 min, 90-180 min as well as in samples collected up to 24 hours later. The totality of the profiles is used to explore for changes after baseline as detected by multivariate statistics (PLS-DA) after dividing the data into a training and test set. Contrasts between each of the treatment groups and the placebo group will be assessed using the receiver-operator characteristics (ROC curves) comparing the training and test set. |
| Metabolic profile in plasma | 0-180 min | Untargeted metabolic profile of plasma measured in all samples collected before the meal and postprandially from 0-180 min. The totality of the profile is used to explore for changes after baseline as detected by multivariate statistics (PLS-DA) after dividing the data into a training and test set. Contrasts between each of the treatment groups and the placebo group will be assessed using the receiver-operator characteristics (ROC curves) comparing the training and test set. |
Countries
Denmark
Outcome results
None listed