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Exploring the Molecular Basis to Healthy Obesity: The Diabetes Risk Assessment Study (DRA)

U

University of Guelph

Status

Completed

Conditions

Type-2 Diabetes
Obesity
Dyslipidemia
Metabolic Syndrome

Treatments

Other: High fat/high calorie meal

Study type

Interventional

Funder types

Other

Identifiers

NCT01884714
10AP033

Details and patient eligibility

About

The purpose of this study is to better understand the genetic and metabolic differences in obese individuals with and without type 2 diabetes. It is expected that this research will help improve our understanding of the variability observed between obese and diabetic individuals.

Full description

PURPOSE: Diabetes is one of the fastest growing diseases in Canada; however, lifestyle changes (e.g. changes in diet and physical activity) can prevent or postpone the development of this metabolic disease. The proposed research project hypothesizes that knowledge of the diabetic and obese metabolic phenotype (i.e. the metabotype) has value in predicting these diseases, preventing their downstream complications, and personalizing therapeutic and lifestyle interventions to improve diabetes and obesity management. The overall purpose of this research is to identify biomarkers that uniquely reflect the metabolic perturbations associated with type 2 diabetes and obesity. This information will be invaluable in the design of more personalized interventions to manage these disease states

RATIONALE: Type-2 diabetes is a disease state that affects multiple organs of the biological system, including alterations in adipocyte and muscle insulin signalling, hepatic glucose production, glucose absorption from the gastrointestinal tract, and pancreatic insulin deficiency caused by the loss of β-cell mass and function. Understanding the molecular communication taking place both within and between these tissues is paramount to unravel the metabolic regulatory networks and mechanisms underlying diabetes. Global gene expression profiling (i.e. transcriptomics) and metabolite profiling (i.e. metabolomics) offer powerful approaches to understand the biological processes associated with diabetes and obesity. The analysis of gene expression profiles provides an opportunity to identify early markers of metabolic dysregulation. In contrast, metabolites represent an endpoint of gene and protein function; thus metabolomics is ideally suited for the identification of biomarkers that reflect the biochemical processes underlying a physiological state. By integrating gene expression profiling with metabolite profiling, we will have the opportunity to improve our understanding of the metabolic perturbations related to obesity and/or type-2 diabetes.

OBJECTIVES: The specific goals of this project are to:

  1. Recruit a sample of lean, lean/diabetic, obese, and obese/diabetic research participants from the Guelph community.
  2. Assess blood glucose and insulin levels in these 4 groups both at baseline and after the consumption of a standardized high fat/high calorie meal.
  3. Define the metabotype of these 4 groups by profiling plasma metabolites with mass spectrometry. The current study will examine only blood metabolites.
  4. Define subcutaneous adipose tissue gene expression profiles of these 4 groups using microarray technology.

Enrollment

80 patients

Sex

All

Ages

35 to 70 years old

Volunteers

Accepts Healthy Volunteers

Inclusion criteria

  • Stable body weight (± 2 kg) for at least 3 months.

Exclusion criteria

  • Evidence of acute or chronic inflammatory disease
  • Infectious diseases
  • Viral infection
  • Cancer
  • Alcohol consumption (i.e. more than 2 drinks/day, where 1 drink = 10 g alcohol).

Trial design

Primary purpose

Basic Science

Allocation

N/A

Interventional model

Single Group Assignment

Masking

None (Open label)

80 participants in 1 patient group

High fat/high calorie meal
Experimental group
Description:
All subjects are provided a high calorie (\~1300kcal) and high fat (\~60g fat) breakfast meal.
Treatment:
Other: High fat/high calorie meal

Trial contacts and locations

1

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Data sourced from clinicaltrials.gov

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