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Genome-wide meta-analysis of observational studies shows common genetic variants associated with macronutrient intake.
Am J Clin Nutr 2013; 97(6):1395-402AJ

Abstract

BACKGROUND

Macronutrient intake varies substantially between individuals, and there is evidence that this variation is partly accounted for by genetic variants.

OBJECTIVE

The objective of the study was to identify common genetic variants that are associated with macronutrient intake.

DESIGN

We performed 2-stage genome-wide association (GWA) meta-analysis of macronutrient intake in populations of European descent. Macronutrients were assessed by using food-frequency questionnaires and analyzed as percentages of total energy consumption from total fat, protein, and carbohydrate. From the discovery GWA (n = 38,360), 35 independent loci associated with macronutrient intake at P < 5 × 10(-6) were identified and taken forward to replication in 3 additional cohorts (n = 33,533) from the DietGen Consortium. For one locus, fat mass obesity-associated protein (FTO), cohorts with Illumina MetaboChip genotype data (n = 7724) provided additional replication data.

RESULTS

A variant in the chromosome 19 locus (rs838145) was associated with higher carbohydrate (β ± SE: 0.25 ± 0.04%; P = 1.68 × 10(-8)) and lower fat (β ± SE: -0.21 ± 0.04%; P = 1.57 × 10(-9)) consumption. A candidate gene in this region, fibroblast growth factor 21 (FGF21), encodes a fibroblast growth factor involved in glucose and lipid metabolism. The variants in this locus were associated with circulating FGF21 protein concentrations (P < 0.05) but not mRNA concentrations in blood or brain. The body mass index (BMI)-increasing allele of the FTO variant (rs1421085) was associated with higher protein intake (β ± SE: 0.10 ± 0.02%; P = 9.96 × 10(-10)), independent of BMI (after adjustment for BMI, β ± SE: 0.08 ± 0.02%; P = 3.15 × 10(-7)).

CONCLUSION

Our results indicate that variants in genes involved in nutrient metabolism and obesity are associated with macronutrient consumption in humans. Trials related to this study were registered at clinicaltrials.gov as NCT00005131 (Atherosclerosis Risk in Communities), NCT00005133 (Cardiovascular Health Study), NCT00005136 (Family Heart Study), NCT00005121 (Framingham Heart Study), NCT00083369 (Genetic and Environmental Determinants of Triglycerides), NCT01331512 (InCHIANTI Study), and NCT00005487 (Multi-Ethnic Study of Atherosclerosis).

Authors+Show Affiliations

Translational Gerontology Branch, National Institute on Aging, Baltimore, MD 21225, USA. tanakato@mail.nih.govNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Journal Article
Meta-Analysis
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.

Language

eng

PubMed ID

23636237

Citation

Tanaka, Toshiko, et al. "Genome-wide Meta-analysis of Observational Studies Shows Common Genetic Variants Associated With Macronutrient Intake." The American Journal of Clinical Nutrition, vol. 97, no. 6, 2013, pp. 1395-402.
Tanaka T, Ngwa JS, van Rooij FJ, et al. Genome-wide meta-analysis of observational studies shows common genetic variants associated with macronutrient intake. Am J Clin Nutr. 2013;97(6):1395-402.
Tanaka, T., Ngwa, J. S., van Rooij, F. J., Zillikens, M. C., Wojczynski, M. K., Frazier-Wood, A. C., ... Nettleton, J. A. (2013). Genome-wide meta-analysis of observational studies shows common genetic variants associated with macronutrient intake. The American Journal of Clinical Nutrition, 97(6), pp. 1395-402. doi:10.3945/ajcn.112.052183.
Tanaka T, et al. Genome-wide Meta-analysis of Observational Studies Shows Common Genetic Variants Associated With Macronutrient Intake. Am J Clin Nutr. 2013;97(6):1395-402. PubMed PMID: 23636237.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Genome-wide meta-analysis of observational studies shows common genetic variants associated with macronutrient intake. AU - Tanaka,Toshiko, AU - Ngwa,Julius S, AU - van Rooij,Frank J A, AU - Zillikens,M Carola, AU - Wojczynski,Mary K, AU - Frazier-Wood,Alexis C, AU - Houston,Denise K, AU - Kanoni,Stavroula, AU - Lemaitre,Rozenn N, AU - Luan,Jian'an, AU - Mikkilä,Vera, AU - Renstrom,Frida, AU - Sonestedt,Emily, AU - Zhao,Jing Hua, AU - Chu,Audrey Y, AU - Qi,Lu, AU - Chasman,Daniel I, AU - de Oliveira Otto,Marcia C, AU - Dhurandhar,Emily J, AU - Feitosa,Mary F, AU - Johansson,Ingegerd, AU - Khaw,Kay-Tee, AU - Lohman,Kurt K, AU - Manichaikul,Ani, AU - McKeown,Nicola M, AU - Mozaffarian,Dariush, AU - Singleton,Andrew, AU - Stirrups,Kathleen, AU - Viikari,Jorma, AU - Ye,Zheng, AU - Bandinelli,Stefania, AU - Barroso,Inês, AU - Deloukas,Panos, AU - Forouhi,Nita G, AU - Hofman,Albert, AU - Liu,Yongmei, AU - Lyytikäinen,Leo-Pekka, AU - North,Kari E, AU - Dimitriou,Maria, AU - Hallmans,Goran, AU - Kähönen,Mika, AU - Langenberg,Claudia, AU - Ordovas,Jose M, AU - Uitterlinden,André G, AU - Hu,Frank B, AU - Kalafati,Ioanna-Panagiota, AU - Raitakari,Olli, AU - Franco,Oscar H, AU - Johnson,Andrew, AU - Emilsson,Valur, AU - Schrack,Jennifer A, AU - Semba,Richard D, AU - Siscovick,David S, AU - Arnett,Donna K, AU - Borecki,Ingrid B, AU - Franks,Paul W, AU - Kritchevsky,Stephen B, AU - Lehtimäki,Terho, AU - Loos,Ruth J F, AU - Orho-Melander,Marju, AU - Rotter,Jerome I, AU - Wareham,Nicholas J, AU - Witteman,Jacqueline C M, AU - Ferrucci,Luigi, AU - Dedoussis,George, AU - Cupples,L Adrienne, AU - Nettleton,Jennifer A, Y1 - 2013/05/01/ PY - 2013/5/3/entrez PY - 2013/5/3/pubmed PY - 2013/7/17/medline SP - 1395 EP - 402 JF - The American journal of clinical nutrition JO - Am. J. Clin. Nutr. VL - 97 IS - 6 N2 - BACKGROUND: Macronutrient intake varies substantially between individuals, and there is evidence that this variation is partly accounted for by genetic variants. OBJECTIVE: The objective of the study was to identify common genetic variants that are associated with macronutrient intake. DESIGN: We performed 2-stage genome-wide association (GWA) meta-analysis of macronutrient intake in populations of European descent. Macronutrients were assessed by using food-frequency questionnaires and analyzed as percentages of total energy consumption from total fat, protein, and carbohydrate. From the discovery GWA (n = 38,360), 35 independent loci associated with macronutrient intake at P < 5 × 10(-6) were identified and taken forward to replication in 3 additional cohorts (n = 33,533) from the DietGen Consortium. For one locus, fat mass obesity-associated protein (FTO), cohorts with Illumina MetaboChip genotype data (n = 7724) provided additional replication data. RESULTS: A variant in the chromosome 19 locus (rs838145) was associated with higher carbohydrate (β ± SE: 0.25 ± 0.04%; P = 1.68 × 10(-8)) and lower fat (β ± SE: -0.21 ± 0.04%; P = 1.57 × 10(-9)) consumption. A candidate gene in this region, fibroblast growth factor 21 (FGF21), encodes a fibroblast growth factor involved in glucose and lipid metabolism. The variants in this locus were associated with circulating FGF21 protein concentrations (P < 0.05) but not mRNA concentrations in blood or brain. The body mass index (BMI)-increasing allele of the FTO variant (rs1421085) was associated with higher protein intake (β ± SE: 0.10 ± 0.02%; P = 9.96 × 10(-10)), independent of BMI (after adjustment for BMI, β ± SE: 0.08 ± 0.02%; P = 3.15 × 10(-7)). CONCLUSION: Our results indicate that variants in genes involved in nutrient metabolism and obesity are associated with macronutrient consumption in humans. Trials related to this study were registered at clinicaltrials.gov as NCT00005131 (Atherosclerosis Risk in Communities), NCT00005133 (Cardiovascular Health Study), NCT00005136 (Family Heart Study), NCT00005121 (Framingham Heart Study), NCT00083369 (Genetic and Environmental Determinants of Triglycerides), NCT01331512 (InCHIANTI Study), and NCT00005487 (Multi-Ethnic Study of Atherosclerosis). SN - 1938-3207 UR - https://www.unboundmedicine.com/medline/citation/23636237/Genome_wide_meta_analysis_of_observational_studies_shows_common_genetic_variants_associated_with_macronutrient_intake_ L2 - https://academic.oup.com/ajcn/article-lookup/doi/10.3945/ajcn.112.052183 DB - PRIME DP - Unbound Medicine ER -