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Gene x dietary pattern interactions in obesity: analysis of up to 68 317 adults of European ancestry
Univ Texas Houston, Hlth Sci Ctr, Sch Publ Hlth, Div Epidemiol Human Genet & Environm Sci, Houston, TX USA..
Univ St Thomas, Dept Math, Houston, TX 77006 USA..
Boston Univ, Sch Publ Hlth, Dept Biostat, Boston, MA 02215 USA..
Jean Mayer USDA Human Nutr Res Ctr Aging, Boston, MA USA.;Tufts Univ, Friedman Sch Nutr Sci & Policy, Boston, MA 02111 USA..
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2015 (English)In: Human Molecular Genetics, ISSN 0964-6906, E-ISSN 1460-2083, Vol. 24, no 16, 4728-4738 p.Article in journal (Refereed) Published
Abstract [en]

Obesity is highly heritable. Genetic variants showing robust associationswith obesity traits have been identified through genome wide association studies. We investigated whether a composite score representing healthy diet modifies associations of these variants with obesity traits. Totally, 32 body mass index (BMI)- and 14 waist-hip ratio (WHR)-associated single nucleotide polymorphismswere genotyped, and genetic risk scores (GRS) were calculated in 18 cohorts of European ancestry (n = 68 317). Diet score was calculated based on self-reported intakes of whole grains, fish, fruits, vegetables, nuts/seeds (favorable) and red/processed meats, sweets, sugar-sweetened beverages and fried potatoes (unfavorable). Multivariable adjusted, linear regression within each cohort followed by inverse variance-weighted, fixed-effects meta-analysis was used to characterize: (a) associations of each GRS with BMI and BMI-adjustedWHR and (b) diet score modification of genetic associations with BMI and BMI-adjusted WHR. Nominally significant interactions (P = 0.006-0.04) were observed between the diet score and WHR-GRS (but not BMI-GRS), two WHR loci (GRB14 rs10195252; LYPLAL1 rs4846567) and two BMI loci (LRRN6C rs10968576; MTIF3 rs4771122), for the respective BMI-adjustedWHR or BMI outcomes. Although the magnitudes of these select interactions were small, our data indicated that associations between genetic predisposition and obesity traits were stronger with a healthier diet. Our findings generate interesting hypotheses; however, experimental and functional studies are needed to determine their clinical relevance.

Place, publisher, year, edition, pages
2015. Vol. 24, no 16, 4728-4738 p.
National Category
Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy) Medical Genetics
URN: urn:nbn:se:uu:diva-264673DOI: 10.1093/hmg/ddv186ISI: 000361315400020PubMedID: 25994509OAI: oai:DiVA.org:uu-264673DiVA: diva2:861309
Swedish Research Council
Available from: 2015-10-16 Created: 2015-10-15 Last updated: 2016-01-25Bibliographically approved

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Ax, ErikaSjögren, PerIngelsson, Erik
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Clinical Nutrition and MetabolismMolecular epidemiologyScience for Life Laboratory, SciLifeLab
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Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)Medical Genetics

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