Abstract
Combining multiple genetic variants related to obesity into a genetic risk score (GRS)
might improve identification of individuals at risk of developing obesity. Moreover,
characterizing gene–diet interactions is a research challenge to establish dietary
recommendations to individuals with higher predisposition to obesity. Our objective
was to analyze the association between an obesity GRS and body mass index (BMI) in
the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) population, focusing
on gene–diet interactions with total fat and saturated fatty acid (SFA) intake, and
to replicate findings in the Multi-Ethnic Study of Atherosclerosis (MESA) population.
Cross-sectional analyses included 783 white US participants from GOLDN and 2,035 from
MESA. Dietary intakes were estimated with validated food frequency questionnaires.
Height and weight were measured. A weighted GRS was calculated on the basis of 63
obesity-associated variants. Multiple linear regression models adjusted by potential
confounders were used to examine gene–diet interactions between dietary intake (total
fat and SFA) and the obesity GRS in determining BMI. Significant interactions were
found between total fat intake and the obesity GRS using these variables as continuous
for BMI (P for interaction=0.010, 0.046, and 0.002 in GOLDN, MESA, and meta-analysis, respectively).
These association terms were stronger when assessing interactions between SFA intake
and GRS for BMI (P for interaction=0.005, 0.018, and <0.001 in GOLDN, MESA, and meta-analysis, respectively).
SFA intake interacts with an obesity GRS in modulating BMI in two US populations.
Although determining the causal direction requires further investigation, these findings
suggest that potential dietary recommendations to reduce BMI effectively in populations
with high obesity GRS would be to reduce total fat intake mainly by limiting SFAs.
Keywords
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References
- Developments in obesity genetics in the era of genome-wide association studies.J Nutrigenet Nutrigenom. 2011; 4: 222-238
- Energy density and its role in the control of food intake: Evidence from metabolic and community studies.Appetite. 1996; 26: 153-174
- Regulation of body weight in humans.Physiol Rev. 1999; 79: 451-480
- Molecular basis of obesity: Current status and future prospects.Curr Genomics. 2011; 12: 154-168
- A Database of gene–environment interactions pertaining to blood lipid traits, cardiovascular disease and type 2 diabetes.J Data Mining Genomics Proteomics. 2011; 2 (pii: 106)
- Fat and carbohydrate intake modify the association between genetic variation in the FTO genotype and obesity.Am J Clin Nutr. 2009; 90: 1418-1425
- A high intake of saturated fatty acids strengthens the association between the fat mass and obesity-associated gene and BMI.J Nutr. 2011; 141: 2219-2225
- Dietary fatty acid distribution modifies obesity risk linked to the rs9939609 polymorphism of the fat mass and obesity-associated gene in a Spanish case-control study of children.Br J Nutr. 2012; 107: 533-538
- Dietary fat intake and polymorphisms at the PPARG locus modulate BMI and type 2 diabetes risk in the D.E.S.I.R. prospective study.Int J Obes (Lond). 2012; 36: 218-224
- Interaction between a peroxisome proliferator-activated receptor gamma gene polymorphism and dietary fat intake in relation to body mass.Hum Mol Genet. 2003; 12: 2923-2929
- PPARγ Pro12Ala interacts with fat intake for obesity and weight loss in a behavioural treatment based on the Mediterranean diet.Mol Nutr Food Res. 2011; 55: 1771-1779
- APOA2, dietary fat, and body mass index: Replication of a gene–diet interaction in 3 independent populations.Arch Intern Med. 2009; 169: 1897-1906
- Association between the APOA2 promoter polymorphism and body weight in Mediterranean and Asian populations: Replication of a gene–saturated fat interaction.Int J Obes (Lond). 2011; 35: 666-675
- Sugar-sweetened beverages and genetic risk of obesity.N Engl J Med. 2012; 367: 1387-1396
- Genetic susceptibility to obesity and diet intakes: Association and interaction analyses in the Malmö Diet and Cancer Study.Genes Nutr. 2013; 8: 535-547
- The -256T>C polymorphism in the apolipoprotein A-II gene promoter is associated with body mass index and food intake in the genetics of lipid lowering drugs and diet network study.Clin Chem. 2007; 53: 1144-1152
- Multi-ethnic study of atherosclerosis: Objectives and design.Am J Epidemiol. 2002; 156: 871-881
- Multi-Ethnic Study of Atherosclerosis Field Center Manual of Operations.University of Washington, Seattle, WA2001
- Cognitive research enhances accuracy of food frequency questionnaire reports: Results of an experimental validation study.J Am Diet Assoc. 2002; 102: 212-225
- Comparative validation of the Block, Willett, and National Cancer Institute food frequency questionnaires: The Eating at America's Table Study.Am J Epidemiol. 2001; 154: 1089-1099
- Validation of a self-administered diet history questionnaire using multiple diet records.J Clin Epidemiol. 1990; 43: 1327-1335
- Validity and reproducibility of a food frequency interview in a Multi-Cultural Epidemiology Study.Ann Epidemiol. 1999; 9: 314-324
- Dietary patterns are associated with biochemical markers of inflammation and endothelial activation in the Multi-Ethnic Study of Atherosclerosis (MESA).Am J Clin Nutr. 2006; 83: 1369-1379
- Moderate physical activity patterns of minority women: The Cross-Cultural Activity Participation Study.J Womens Health Gend Based Med. 1999; 8: 805-813
- Physical inactivity interacts with an endothelial lipase polymorphism to modulate high density lipoprotein cholesterol in the GOLDN study.Atherosclerosis. 2009; 206: 500-504
- Genome-wide association to body mass index and waist circumference: The Framingham Heart Study 100K project.BMC Med Genet. 2007; 8: S1-S18
- CLOCK genetic variation and metabolic syndrome risk: Modulation by monounsaturated fatty acids.Am J Clin Nutr. 2009; 90: 1466-1475
- SNAP: A web-based tool for identification and annotation of proxy SNPs using HapMap.Bioinformatics. 2008; 24: 2938-2939
- Preliminary evidence of genetic determinants of adiponectin response to fenofibrate in the Genetics of Lipid Lowering Drugs and Diet Network.Nutr Metab Cardiovasc Dis. 2013; 23: 987-994
- Estimating heritability using family and unrelated individuals data.BMC Proc. 2011; 5: S34
- Physical activity attenuates the genetic predisposition to obesity in 20,000 men and women from EPIC-Norfolk prospective population study.PLoS Med. 2010; 7
- Could the quality of dietary fat, and not just its quantity, be related to risk of obesity?.Obesity (Silver Spring). 2008; 16: 7-15
- Comparison of the Atkins, Zone, Ornish, and LEARN diets for change in weight and related risk factors among overweight premenopausal women: The A TO Z Weight Loss Study: A randomized trial.JAMA. 2007; 297: 969-977
- Saturated fatty acids produce an inflammatory response predominantly through the activation of TLR4 signaling in hypothalamus: Implications for the pathogenesis of obesity.J Neurosci. 2009; 29: 359-370
- What is an optimal diet? Relationship of macronutrient intake to obesity, glucose tolerance, lipoprotein cholesterol levels and the metabolic syndrome in the Whitehall II study.Int J Obes Relat Metab Disord. 2001; 25: 45-53
- Dietary fat composition and human adiposity.Eur J Clin Nutr. 1998; 52: 2-6
- Effect of fat sources on satiety.Obes Res. 2003; 11: 183-187
- Acute effects of three high-fat meals with different fat saturations on energy expenditure, substrate oxidation and satiety.Clin Nutr. 2009; 28: 39-45
- Differential oxidation of individual dietary fatty acids in humans.Am J Clin Nutr. 2000; 72: 905-911
Biography
P. Casas-Agustench is a postdoctoral researcher, Nutrition and Genomic Laboratory, Jean Mayer US Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA, and a postdoctoral researcher, Instituto Madrileño de Estudios Avanzados Alimentación, Ciudad Universitaria de Cantoblanco, Madrid, Spain.
Biography
D. K. Arnett is a professor, Department of Epidemiology, School of Public Health, and a professor, Clinical Nutrition Research Center, University of Alabama at Birmingham.
Biography
C. E. Smith is a scientist III, Nutrition and Genomic Laboratory, Jean Mayer US Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA.
Biography
C.-Q. Lai is a research molecular biologist, Nutrition and Genomic Laboratory, Jean Mayer US Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA.
Biography
L. D. Parnell is a computational biologist, Nutrition and Genomic Laboratory, Jean Mayer US Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA.
Biography
Y.-C. Lee is a PhD candidate, Nutrition and Genomic Laboratory, Jean Mayer US Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA.
Biography
I. B. Borecki is a professor, Division of Statistical Genomics in the Center for Genome Sciences, Washington University School of Medicine, St Louis, MO.
Biography
A. C. Frazier-Wood is a professor, Division of Epidemiology, Human Genetics, and Environmental Sciences, The University of Texas School of Public Health, Houston, and a professor, US Department of Agriculture/Agricultural Research Service Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX.
Biography
M. Allison is a professor, Department of Family and Preventive Medicine, University of California-San Diego, La Jolla.
Biography
Y.-D. I. Chen is a professor, Laboratory for Biochemistry, Microarray, and Molecular Phenotyping, Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA.
Biography
K. D. Taylor is a professor, Laboratory for High Throughput Genotyping and Bioinformatics, Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA.
Biography
J. I. Rotter is a professor, Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA.
Biography
S. S. Rich is a professor, Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA.
Biography
J. M. Ordovás is a senior scientist and director, Nutrition and Genomic Laboratory, Jean Mayer US Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA, a scientific director, Instituto Madrileño de Estudios Avanzados Alimentación, Ciudad Universitaria de Cantoblanco, Madrid, Spain, and a senior collaborating scientist, Department of Cardiovascular Epidemiology and Population Genetics, Centro Nacional de Investigaciones Cardiovasculares, Madrid, Spain.
Article info
Publication history
Published online: May 01, 2014
Accepted:
March 17,
2014
Footnotes
STATEMENT OF POTENTIAL CONFLICT OF INTEREST No potential conflict of interest was reported by the authors.
FUNDING/SUPPORT Supported by the National Institutes of Health (grant nos. 1R21AR055228-01A1, HL54776, 5R21HL114238-02, and U01 HL72524), the National Institute of Diabetes and Digestive and Kidney Diseases (grant no. DK075030), and the US Department of Agriculture Research Service (grant nos. 53-K06-5-10, 58–1950-9-001, and K08 HL112845-01); support for MESA is provided by contracts N01-HC-95159, N01-HC-95160, N01-HC-95161, N01-HC-95162, N01-HC-95163, N01-HC-95164, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, N01-HC-95169, UL1-TR-001079, and UL1-TR-000040; SHARE genotyping was provided by National Heart, Lung, Blood Institute contract NO2-HL-64278, the provision of genotyping data was supported in part by the National Center for Advancing Translational Sciences, Clinical and Translational Science Institute grant UL1TR000124, and the National Institute of Diabetes and Digestive and Kidney Disease Diabetes Research Center grant DK063491 to the Southern California Diabetes Endocrinology Research Center. Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the US Department of Agriculture. The US Department of Agriculture is an equal opportunity provider and employer. This research project received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no. PIOF-GA-2010-272581.
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© 2014 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.
