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The key objective of this study is to identify the most suitable diet (i.e. high protein, high fat, low GI, high GI) for an individual. Importantly, we further seek to identify the biological determinants of inter-individual variability and to understand how these determinants affect blood glucose. The deep metabolic phenotyping, multi-omics profiling of each subject and fine-mapping of their glycemic responses to different diets will allow us to obtain preliminary data on the mechanistic basis underlying inter-individual dietary glycemic response. Data from this study will form the basis of large clinical trials, the development of novel foods, and/or novel technologies to alter the gut micro-biome for optimal blood glucose control.
Diet plays a large role in determining our blood glucose levels, which in turn, can affect our risk of diabetes mellitus and heart disease. Traditionally, dietary recommendations are made for populations or groups of people. There is increasing recognition that each of us is an individual, with our own genetic background, physiology, and lifestyle. Each of these affects the way we digest and use the nutrients in foods that we consume. Recent studies have shown that different individuals consuming the same meal have very different glycaemic responses. The optimal diet for one person may not be the optimal diet for another. This could explain the controversies around our attempts to define the best diet for the population - there simply isn't one diet that is optimal for everybody. In our study, we will utilize an n-of-1 study design where each person receives all 3 diets one after another in a random sequence. We will measure blood glucose using a device that measures the interstitial blood glucose every 15 minutes for 2 weeks. The glycaemic effects of each diet will then be compared with the control diet in the same individual such that each person serves as his/her own control. The response is thus individualized.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| High Protein Diet | Experimental | Diet consisting of 40% carbohydrate, 40% protein, 20% fat, with Glycemic Index ~55-65. |
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| High Fat Diet | Experimental | Diet consisting of 40% carbohydrate, 40% fat (25% monounsaturated fatty acids), 20% protein, with Glycemic Index ~55-65. |
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| High Carbohydrate-Low Glycemic Index Diet | Experimental | Diet consisting of 60% carbohydrate, 20% fat, 20% protein, with Glycemic Index ~45-50. |
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| High Carbohydrate-High Glycemic Index Diet | Placebo Comparator | Diet consisting of 60% carbohydrate, 20% fat, 20% protein. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| High Protein Diet | Dietary Supplement | Subjects will be provided with high protein diet meals for breakfast, lunch, and dinner. A continuous glucose monitoring device will be used to measure post-prandial glycemic responses. |
| Measure | Description | Time Frame |
|---|---|---|
| Inter-individual differences in glycemic response to various meal types. | To quantify inter-individual differences in glycemic response to high carbohydrate-high glycemic index, high carbohydrate-low glycemic index, high-protein and high-fat diets using continuous glucose monitoring. | 14 days |
| Measure | Description | Time Frame |
|---|---|---|
| Correlation of metagenomic profile to inter-individual glycemic response differences from various meal types. | Correlation of metagenomic profile from shotgun sequencing of DNA to differences in inter-individual glycemic response of individuals from various meal types (primary outcome). | 14 days |
| Correlation of metabolome profile to inter-individual glycemic response differences from various meal types. |
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Inclusion Criteria:
Exclusion Criteria:
Female
A current smoker, or has smoked in the past 2 years
History or presence of current lipid and cardiovascular disorders, respiratory, hepatic, renal, gastrointestinal, endocrine, lipid disorder, haematological, malignancy or neurological disorders capable of significantly altering the performance of the biomarker panel; or of interfering with the interpretation of data
History of food allergies to test foods
Regular use of medication that may affect glucose metabolism (e.g. steroids)
History of type 1/type 2 diabetes and use of anti-diabetic medications in the past
History of regular use of aspirin or vitamin C (both can affect glucose readings on CGM)
Regularly use known drugs or abuse within 3 years
Known or ongoing psychiatric disorders within 3 years
Have donated blood of more than 500 mL within 4 weeks of study enrolment
Have an average weekly alcohol intake that exceeds 21 units per week (males) and 14 units per week (females):
Uncontrolled hypertension (blood pressure [BP] >160/100mmHg)
Active infection requiring systemic antiviral or antimicrobial therapy that will not be completed prior to Study Day 1
Treatment with any investigational drug, or biological agent within one (1) month of screening or plans to enter into an investigational drug/ biological agent study during the duration of this study
Treatment with any investigational drug, or biological agent within one (1) month of screening or plans to enter into an investigational drug/ biological agent study during the duration of this study
History of bleeding diathesis or coagulopathy
Any of the following laboratory values at screening:
Fasting glucose >=126mg/dL(>=7mmol/L) or 2 hour post-prandial glucose >=200mg/dL (>=11.1mmol/L)
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| Name | Affiliation | Role |
|---|---|---|
| Mei Hui Liu | National University of Singapore | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| National University of Singapore | Singapore | Singapore | 118177 | Singapore |
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A 120 single-subject trials (n-of-1 trials) is proposed to compare the glycaemic response of three common diets, i.e. a high carbohydrate-low glycemic index diet, a high protein diet, and a high fat diet. An n-of-1 trial is a clinical trial in which a single individual is the entire trial. Each individual serves as his/her own control, and different intervention are administered in a cross-over design.
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Participant will be blinded as to which diet they are receiving for each day of the 14-day study.
| High Fat Diet | Dietary Supplement | Subjects will be provided with high fat diet meals for breakfast, lunch, and dinner. A continuous glucose monitoring device will be used to measure post-prandial glycemic responses. |
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| High Carbohydrate-Low Glycemic Index Diet | Dietary Supplement | Subjects will be provided with high carbohydrate-low glycemic index diet meals for breakfast, lunch, and dinner. A continuous glucose monitoring device will be used to measure post-prandial glycemic responses. |
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| High Carbohydrate-High Glycemic Index Diet | Dietary Supplement | Subjects will be provided with high carbohydrate-high glycemic index diet meals for breakfast, lunch, and dinner. A continuous glucose monitoring device will be used to measure post-prandial glycemic responses. |
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Correlation of metabolome profile from blood samples to differences in inter-individual glycemic response of individuals from various meal types (primary outcome). |
| 14 days |
| Correlation of sleep score quality to different glycemic responses from various meal types. | Correlation of sleep score quality derived from Fitbit active watch to different glycemic responses from various meal types (primary outcome). | 14 days |
| Correlation of number of step counts from physical activity to different glycemic responses from various meal types. | Correlation of number of step counts from physical activity derived from Fitbit active watch to different glycemic responses from various meal types (primary outcome). | 14 days |
| ID | Term |
|---|---|
| D000073600 | Diet, High-Protein |
| D059305 | Diet, High-Fat |
| ID | Term |
|---|---|
| D004035 | Diet Therapy |
| D044623 | Nutrition Therapy |
| D013812 | Therapeutics |
| D004032 | Diet |
| D009747 | Nutritional Physiological Phenomena |
| D000066888 | Diet, Food, and Nutrition |
| D010829 | Physiological Phenomena |
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