Metabolic Syndrome, Type 2 Diabetes, Cardiovascular Disease, Abdominal Obesity
Conditions
Keywords
Medium chain fatty acids, Saturated fatty acids, Whey protein, Casein protein, Metabolic syndrome, Type 2 diabetes, Cardiovascular disease, Dairy products, Dietary intervention
Brief summary
Dairy food contains a large amount of long-chain saturated fat, which traditionally has been linked to increased risk of cardiovascular disease (CVD). However, recent data indicates a more neutral role. Milk fat contains large amounts of medium-chain saturated fatty acids (MC-SFA), which may have beneficial effects on human health. In addition, milk proteins and in particular whey proteins have been shown to have a beneficial effect on glucose disposal as well as anti-inflammatory properties. Therefore dairy products have a potential role in the treatment of the metabolic abnormalities of metabolic syndrome (MeS). However, human data from intervention studies are lacking. Aims of this project is to explore and understand the influence on human health of both medium-chain saturated fatty acids from milk fat and bioactive milk proteins per se as well as their interaction and potential positive synergy on the MeS. The investigators hypothesize that whey protein and medium-chain saturated fatty acids improve insulin sensitivity, postprandial lipid metabolism, blood pressure and inflammatory stress in humans and that they possess preventive effects on the risk of developing CVD and type 2 diabetes mellitus (T2DM). A total of 64 people with MeS or abdominal obesity will be included. The design is a randomized double-blinded, controlled parallel diet-intervention trial. Subjects are assigned one of four experimental diets for 12 weeks. The diets consist of either a diet with low levels of MC-SFA + whey protein (LF + whey), a diet high in MC-SFA + whey protein (HF + whey), a diet high in MC-SFA + casein protein (HF + casein) or a diets with low levels of MC-SFA + casein protein (LF + casein). The subjects are advised how to integrate the test foods in their habitual diet, which also continues unchanged. The subjects' energy intake is matched so they are kept weight stable throughout the study.
Detailed description
See above.
Interventions
Sponsors
Aarhus University Hospital
Arla Foods
Wageningen University
University of Dublin, Trinity College
University of Aarhus
Study design
Allocation
RANDOMIZED
Intervention model
FACTORIAL
Primary purpose
TREATMENT
Masking
QUADRUPLE (Subject, Caregiver, Investigator, Outcomes Assessor)
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
Metabolic syndrome * Central obesity (Waist: female ≥ 80 cm; male ≥ 94 cm) * with two or more of the following * Fasting triglyceride \> 1.7 mmol/l * HDL-cholesterol; male \< 1.03 mmol/l, female \< 1.29 mmol/l * BP ≥ 130/85 * Fasting plasma glucose ≥ 5,6 mmol/l (but not diabetes) Or abdominal obesity (Waist: female ≥ 80 cm; male ≥ 94 cm)
Exclusion criteria
* Significant cardiovascular, renal or endocrine disease * Psychiatric history * Treatment with steroids * Alcohol- or drug-addiction * Pregnancy or lactation
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Postprandial triglyceride response | Change from week 0 to week 12 | Compare the changes in mean difference of 6 hours incremental area under the curve (iAUC) (week 12 - week 0) between the groups and the intervention components. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Indirect calorimetry | Change from week 0 to week 12 | Measured 2 times during meal test. |
| Dexa-scan (body composition) | Change from week 0 to week 12 | Total body fat percentage, lean mass, gynoid, and android fat percentage, and total body weight. |
| Weight | Change from week 0 to week 12 | — |
| Biomarkers in blood samples | Change from week 0 to week 12 | Glucose, insulin, glucagon, HbA1c. free fatty acids, Lipid profile (total-cholesterol, low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglyceride). Inflammations markers (interleukin-6 (IL-6), interleukin-10 (IL-10), interleukin-1 receptor antagonist (IL-1RA), interleukin-1 beta (IL-1b), high sensitive c-reactive protein (hs-CRP), adiponectin, monocyte chemoattractant protein-1 (MCP-1), Rantes (CCL5)). Incretins (GLP-1, GIP). Nutrigenomics. Metabolomics. Proteomics. |
| Waist and hip circumference | Change from week 0 to week 12 | — |
| 24 hour blood pressure (BP) | Change from week 0 to week 12 | Spacelabs, model 90207/90217, USA |
| Biomarkers in urine | Change from week 0 to week 12 | Nutrigenomics and metabolomics |
| Glucose tolerance | Change from week 0 to week 12 | Oral glucose tolerance test (OGTT) (with insulin and glucose measurement at time -15 min, -10 min, 0 min, 30 min, 60 min, and 120 min). Hereby calculating the homeostatic model assessment of insulin resistance (HOMA-IR) and the Matsuda index. |
| Dietary compliance | Change from week 0 to week 12 | 3-day food diary. |
| Postprandial apolipoprotein-48 (apoB-48), 6 hour | Change from week 0 to week 12 | Meal test, blood samples at time 0,2,4 and 6 hours. |
| Fat tissue biopsy | Change from week 0 to week 12 | Fat tissue gene expression. Twice during meal test. |
Countries
Denmark
Outcome results
None listed