Genomics research is advancing rapidly, and links between genes and obesity continue to be discovered and better defined. A growing number of single nucleotide polymorphisms (SNPs) in multiple genes have been shown to alter an individual's response to dietary macronutrient composition. Based on prior genetic studies evaluating the body's physiological responses to dietary carbohydrates or fats, we identified multi-locus genotype patterns with SNPs from three genes (FABP2, PPARG, and ADRB2): a low carbohydrate-responsive genotype (LCG) and a low fat-responsive genotype (LFG). In a preliminary, retrospective study (using the A TO Z weight loss study data), we observed a 3-fold difference in 12-month weight loss for initially overweight women who were determined to have been appropriately matched vs. mismatched to a low carbohydrate (Low Carb) or low fat (Low Fat) diet based on their multi-locus genotype pattern. OBJECTIVE: The primary objective of this study is to confirm and expand on the preliminary results and determine if weight loss success can be increased if the dietary approach (Low Carb vs. Low Fat) is appropriately matched to an individual's genetic predisposition (LCG vs. LFG) toward those diets. This study will target both women and men (the A TO Z study involved only women), and address a set of specific aims intended to further elaborate on potential mechanisms and the clinical utility of these results. A new secondary aim has been added to this resubmitted application that will involve a rigorous exploratory investigation of additional SNPs that have shown genome-wide significant associations with obesity and metabolic phenotypes that might improve on the 3-SNP signature. DESIGN: The main study is a randomized trial employing a 2X2 parallel design to test the central hypothesis that there will be greater weight loss when 320 overweight/obese non- diabetic adults are matched vs. mismatched by genetic predisposition (LCG vs. LFG) to a 12-month Low Carb vs. Low Fat weight loss diet (n=80/cell). Participants will be genotyped prior to randomization, and blinding will be maintained for the genotyping results for both participants and data collectors during the study. Other than the primary outcome of weight change, which will be assessed monthly, primary data collection will occur at 0, 3, 6, and 12 months and include energy intake (3-day unannounced 24-hour recalls, NDS-R), appetite/satiety/hunger, energy expenditure (resting energy expenditure), body composition (DEXA), and blood variables (lipids, insulin, glucose, OGTT). IMPACT: If the intriguing preliminary retrospective results are confirmed in this full scale study, the results will demonstrate that inexpensive DNA testing could help dieters predict whether they will have greater weight loss success on a Low Carb or a Low Fat diet. Commensurate with increasing scientific interest in personalized medicine approaches to intervention development, this would provide an example of the potentially substantial health impacts that could be obtained through understanding specific gene-environment interactions that have been anticipated from the unraveling of the human genome.

Public Health Relevance

Genomics research is rapidly advancing and links between genes and obesity continue to be discovered and better defined. The current study proposes to address whether knowledge of genotype patterns determined from a simple cheek swab can be used to help dieters predict whether they will have greater weight loss success with a low carbohydrate or low fat diet.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Research Project (R01)
Project #
5R01DK091831-03
Application #
8723168
Study Section
Clinical and Integrative Diabetes and Obesity Study Section (CIDO)
Program Officer
Karp, Robert W
Project Start
2012-09-15
Project End
2017-08-31
Budget Start
2014-09-01
Budget End
2015-08-31
Support Year
3
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Stanford University
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
City
Stanford
State
CA
Country
United States
Zip Code
94304
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