National University of Singapore
Singapore, 118177
NCT Number: NCT05402085
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.
This study is active but is not currently recruiting participants.
Notify Me21 year–60 year
Male
Interventional
Not applicable
Singapore, 118177
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.
Healthy volunteers accepted: Yes
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
Fasting glucose >=126mg/dL(>=7mmol/L) or 2 hour post-prandial glucose >=200mg/dL (>=11.1mmol/L)
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.
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.
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.
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.
Time frame: 14 days
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.
Time frame: 14 days
Correlation of metagenomic profile from shotgun sequencing of DNA to differences in inter-individual glycemic response of individuals from various meal types (primary outcome).
Time frame: 14 days
Correlation of metabolome profile from blood samples to differences in inter-individual glycemic response of individuals from various meal types (primary outcome).
Time frame: 14 days
Correlation of sleep score quality derived from Fitbit active watch to different glycemic responses from various meal types (primary outcome).
Time frame: 14 days
Correlation of number of step counts from physical activity derived from Fitbit active watch to different glycemic responses from various meal types (primary outcome).
National University of Singapore
Other
Physiological, Biochemical and Gut Microbial Determinants of Individual Variability in Post-prandial Glycemic Response to Diets of Varying Macronutrient Composition- Towards Personalized Nutrition Through Aggregated N=1 Trials
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