The DOI matches its Crossref record; 51 of the 51 references it cites were found in a registry or an index.
Genome-wide meta-analysis of observational studies shows common genetic variants associated with macronutrient intake
Open accessAbstract
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).
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“Large investigations pooling multiple cohorts have observed main (population) effects of either dietary influences or genes on major cardiometabolic risk factors, but evidence for interactions between diet and these genes is uncommon and, more relevantly, magnitudes of such potential interactions are often small.78-83”
From Dietary and Policy Priorities for Cardiovascular Disease, Diabetes, and Obesity: A Comprehensive Review (2016) · cites this paper as [80]
In the citing paper
“Large investigations pooling multiple cohorts have observed main (population) effects of either dietary influences or genes on major cardiometabolic risk factors, but evidence for interactions between diet and these genes is uncommon and, more relevantly, magnitudes of such potential interactions are often small.78-83”
From Dietary and Policy Priorities for Cardiovascular Disease, Diabetes, and Obesity: A Comprehensive Review (2016) · cites this paper as [80]
In the citing paper
“Large investigations pooling multiple cohorts have observed main (population) effects of either dietary influences or genes on major cardiometabolic risk factors, but evidence for interactions between diet and these genes is uncommon and, more relevantly, magnitudes of such potential interactions are often small.78-83”
From Dietary and Policy Priorities for Cardiovascular Disease, Diabetes, and Obesity: A Comprehensive Review (2016) · cites this paper as [80]
In the citing paper
“Genome-wide association studies correlating changes in macronutrient intake with genetic variants have identified single-nucleotide polymorphisms at the FGF21 locus that significantly correlate with changes in carbohydrate intake117,118.”
From Metabolic messengers: FGF21 (2021) · cites this paper as [118]
In the citing paper
“Pharmacological administration of FGF21 decreases plasma glucose and lipid levels, improves insulin and leptin sensitivity, decreases hepatic steatosis, increases energy expenditure [[131], [132], [133], [134], [135], [136]], and decreases sugar and alcohol intake in mice [[137], [138], [139], [140], [141], [142]].”
From Hepatokines and metabolism: Deciphering communication from the liver (2021) · cites this paper as [139]
In the citing paper
“Two independent studies revealed that single nucleotide polymorphisms (SNPs) at the FGF21 locus are associated with changes in macronutrient intake (20, 127).”
From Fibroblast Growth Factor 21: A Versatile Regulator of Metabolic Homeostasis (2018) · cites this paper as [127]
In the citing paper
“Specifically, these studies reported that variants rs838133 and rs838145 were associated with higher carbohydrate intake and that FGF21 was a candidate gene in the region (20, 127).”
From Fibroblast Growth Factor 21: A Versatile Regulator of Metabolic Homeostasis (2018) · cites this paper as [127]
In the citing paper
“These 2 original studies identified variants in the FGF21 locus that were associated with protein, carbohydrate, and fat intake”
From FGF21 and the physiological regulation of macronutrient preference (2020) · cites this paper as [172]
In the citing paper
“FGF21 sequence variants are linked with alterations in macronutrient preference and alcohol intake in humans”
From FGF21 and the physiological regulation of macronutrient preference (2020) · cites this paper as [172]
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Metadata
- Authors
- Tanaka, T., Ngwa, J. S., van Rooij, F. J., Zillikens, M. C., Wojczynski, M. K., Frazier-Wood, A. C., Houston, D. K., Kanoni, S., Lemaitre, R. N., Luan, J., Mikkilä, V., Renstrom, F., Sonestedt, E., Zhao, J. H., Chu, A. Y., Qi, L., Chasman, D. I., de Oliveira Otto, M. C., Dhurandhar, E. J., Feitosa, M. F., Johansson, I., Khaw, K.-T., Lohman, K. K., Manichaikul, A., McKeown, N. M., Mozaffarian, D., Singleton, A., Stirrups, K., Viikari, J., Ye, Z., Bandinelli, S., Barroso, I., Deloukas, P., Forouhi, N. G., Hofman, A., Liu, Y., Lyytikäinen, L.-P., North, K. E., Dimitriou, M., Hallmans, G., Kähönen, M., Langenberg, C., Ordovas, J. M., Uitterlinden, A. G., Hu, F. B., Kalafati, I.-P., Raitakari, O., Franco, O. H., Johnson, A., Emilsson, V., Schrack, J. A., Semba, R. D., Siscovick, D. S., Arnett, D. K., Borecki, I. B., Franks, P. W., Kritchevsky, S. B., Lehtimäki, T., Loos, R. J., Orho-Melander, M., Rotter, J. I., Wareham, N. J., Witteman, J. C., Ferrucci, L., Dedoussis, G., Cupples, L. A., & Nettleton, J. A.
- Affiliations
- National Institutes of Health (US)
- Boston University (US)
- Washington University in St. Louis (US)
- University of Cambridge (GB)
- University of Turku (FI)
- University of Washington (US)
- ORCID
- Tanaka, Toshiko
- Ngwa, Julius S
- Zillikens, M Carola
- Wojczynski, Mary K
- Houston, Denise K
- Kanoni, Stavroula
- Luan, Jian’an
- Sonestedt, Emily
- Zhao, Jing Hua
- Chu, Audrey Y
- Qi, Lu
- Chasman, Daniel I
- Dhurandhar, Emily J
- Feitosa, Mary F
- Johansson, Ingegerd
- Khaw, Kay-Tee
- Manichaikul, Ani
- McKeown, Nicola M
- Mozaffarian, Dariush
- Singleton, Andrew
- Stirrups, Kathleen
- Viikari, Jorma
- Bandinelli, Stefania
- Barroso, Inês
- Deloukas, Panos
- Forouhi, Nita G
- Lyytikäinen, Leo-Pekka
- North, Kari E
- Dimitriou, Maria
- Kähönen, Mika
- Langenberg, Claudia
- Uitterlinden, André G
- Hu, Frank B
- Kalafati, Ioanna-Panagiota
- Raitakari, Olli
- Franco, Oscar H
- Johnson, Andrew
- Emilsson, Valur
- Schrack, Jennifer A
- Semba, Richard D
- Siscovick, David S
- Arnett, Donna K
- Borecki, Ingrid B
- Franks, Paul W
- Kritchevsky, Stephen B
- Lehtimäki, Terho
- Loos, Ruth JF
- Rotter, Jerome I
- Wareham, Nicholas J
- Ferrucci, Luigi
- Dedoussis, George
- Cupples, L Adrienne
- Venue
- The American Journal of Clinical Nutrition
- Publisher
- Elsevier BV
- Published
- 2013-06
- Volume
- 97
- Issue
- 6
- Pages
- 1395-1402
- ISSN
- 0002-9165 (ISSN-L)
- PMC
- PMC3652928
- OpenAlex
- W2129570057
- Cited by
- 226
- References
- 51
- Citations by year
- 2026: 8 · 2025: 4 · 2024: 11 · 2023: 12 · 2022: 15 · 2021: 23 · 2020: 19 · 2019: 25 · 2018: 21 · 2017: 23 · 2016: 18 · 2015: 21 · 2014: 19 · 2013: 5
- FWCI
- 2.58
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- American Journal of Clinical Nutrition (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (publishedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (submittedVersion)
- RePub (Erasmus University Rotterdam) (submittedVersion, other-oa)
- UCL Discovery (University College London) (submittedVersion)
- Lund University Publications (Lund University) (submittedVersion)
- Funders
- U.S. Department of Agriculture
- Wellcome Trust
- Cancer Research UK (14136)
- European Commission (014-93-015)
- Kela
- Erasmus Medisch Centrum (014-93-015)
- Suomen Kulttuurirahasto
- Ministero della Salute
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (014-93-015)
- Hjärt-Lungfonden
- Juho Vainion Säätiö
- Novo Nordisk
- Vetenskapsrådet
- Emil Aaltosen Säätiö
- Tampereen Tuberkuloosisäätiö
- Paavo Nurmen Säätiö
- Turun Yliopistollinen Keskussairaala
- National Institutes of Health (UL1TR000124, 5r01hl087700-03)
- Canadian Institutes of Health Research
- Medical Research Council (MC_UU_12015/5, MC_UU_12015/1)
- National Institute on Aging (R01AG027012)
- National Heart, Lung, and Blood Institute (R01-HL087700, U01HL072524, R01HL105756, R01HL091357, T32HL007575)
- National Institute of Diabetes and Digestive and Kidney Diseases (R01DK091718, P30DK063491)
- National Center for Advancing Translational Sciences
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Nutrition, Genetics, and Disease
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Physical Performance
- Keywords
- macronutrient intake, genetic variants, dietary fat, dietary protein, dietary carbohydrates, FTO, FGF21, rs1421085, body mass index, obesity genetics, nutrient metabolism, food frequency questionnaire, European populations, gene-environment interaction
- MeSH terms
- Alleles, Energy Intake, Dietary Carbohydrates, Dietary Fats, Dietary Proteins, Fibroblast Growth Factors, Follow-Up Studies, Genotype, Humans, Life Style, Obesity, Prospective Studies, Surveys and Questionnaires, Body Mass Index, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Quantitative Trait Loci, White People, Atherosclerosis, Genome-Wide Association Study, Gene-Environment Interaction
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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