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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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“Variants rs838145 and rs838133 were associated with low protein and fat consumption and increased consumption of carbohydrates [89,90] and variant rs838145 was also correlated with circulating levels of FGF21 [90].”
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“A genome-wide meta-analysis indicated that several genetic variations, in different genes, were associated with differences in macronutrient consumption in humans [24].”
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“In addition, two genome-wide meta-analyses associated genetic variations in a locus including Fgf21 with significant differences in macronutrient intake [6, 70].”
Shungin, D., Deng, W. Q., Varga, T. V., Luan, J., Mihailov, E., Metspalu, A., Morris, A. P., Forouhi, N. G., Lindgren, C. M., Magnusson, P. K. E., et al. (2017) · PLoS Genetics · doi:10.1371/journal.pgen.1006812 · Cited by 23
“FTO is an excellent example, as it conveys strong marginal effects [13], exhibits high between-genotype heterogeneity here (Tables 2 and 3 and Fig 1B) and elsewhere [5], and reportedly interacts with physical activity, diet and other lifestyle exposures [2,14,15] and is associated with macronutrient intake [16,17].”
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“In addition, FGF-21 could regulate macronutrient intake in humans as genome wide associations studies show that certain variants in the FGF-21 locus are associated with a reduced protein and/or lipid intake but with an increased carbohydrate intake [21,22].”
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“There is also evidence suggesting an impact of FTO genotype on food preference with higher relative protein intake [12, 13], higher relative fat intake [14] and energy-dense food [15] in subjects with risk genotypes.”
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“Moreover, the BMI-increasing allele (rs1421085) of the FTO (fat mass and obesity-associated) gene was found to be associated with higher protein intake((18)).”
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“Thousands of GWA studies have been published associating one or more single nucleotide variants to ~800 phenotypes that include disease [106], diet intake [94], metabolism [8, 81], anthropometry [106], pharmacogenomics [17, 70], and brain-related disorders [56].”
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“The loci have not been identified in genome-wide association studies for macronutrients (24, 25), which supports the need for stratifying by BMI.”
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Genetic associations with micronutrient levels identified in immune and gastrointestinal networks
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“…interactions based on single-nucleotide polymorphisms (SNPs) and nutrient intake (Fenech et al. 2011; Lee et al. 2011; Ordovás et al. 2011), and recent genome-wide association studies (GWAS) have identified SNPs associated with dietary preference (Hamza et al. 2011; Tanaka et al. 2013).”
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Diet/lifestyle and risk of diabetes and glycemic traits: a Mendelian randomization study
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“subjects’ preference for it [34] and the A-allele was found to be significantly associated with higher carbohydrate intake on genome-wide scale [35].”
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“So far, only a few genetic variants have been reported to show weak associations with circulating FGF21 levels (11,12).”
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“dependently of BMI [59].”
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“The fat mass and obesity-associated ( FTO ) gene is recognized as associated with enhanced adiposity and seems to influence the risk of obesity in various populations 9,10 .”
BackgroundAPOH interacts with FTO to predispose to healthy thinness
Hasstedt, S. J., Coon, H. H., Xin, Y., Adams, T. D., & Hunt, S. C. (2015) · Human Genetics · doi:10.1007/s00439-015-1629-3 · Cited by 13
“2014) and BMI-increasing alleles of FTO SNPs are associated with increased protein intake (Tanaka et al. 2013).”
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“Previously published GWA studies [18] reported the rs1421085 polymorphism increased the risk of obesity [19], BMI [20], T2D [21], intake of macronutrients [22], and fat mass [23] in the European and Japanese population.”
BackgroundNasreddine, L., Akika, R., Mailhac, A. C., Tamim, H., & Zgheib, N. K. (2019) · Journal of Personalized Medicine · doi:10.3390/jpm9010011 · Cited by 13
“Note that none of the three SNPs were associated with differences in macronutrient intake, a finding that was established in a recent genome-wide meta-analysis [31].”
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“showed that both the FTO and FGF21 genes are very strongly connected to food intake regulation [82].”
BackgroundMcCaffery, J. M., Jablonski, K. A., Franks, P. W., Delahanty, L. M., Aroda, V. R., Marrero, D. G., Hamman, R. F., Horton, E. S., Dagogo-Jack, S. E., Wylie‐Rosett, J., et al. (2016) · Psychosomatic Medicine · doi:10.1097/psy.0000000000000380 · Cited by 12
“In a recent GWAS of dietary intake, fat mass and obesity-associated gene (FTO) was associated, albeit inconsistently, with a greater percentage of calories from protein (12,13) and fat (14).”
Self-citationSaber-Ayad, M. M., Hammoudeh, S. M., Radwan, H. M., Manzoor, S., Jabbar, H. A., Wardeh, R., Ashraf, A., Habib, P. T., Alsamman, A. M., & Hamoudi, R. (2020) · Journal of Advanced Research · doi:10.1016/j.jare.2020.05.020 · Cited by 11
“The ‘‘A” allele of FGF21 at rs838133 is associated with higher carbohydrate intake, despite insignificant change of total calorie intake [7,8], with predeliction to sugary food [9].”
BackgroundStudies of Human Twins Reveal Genetic Variation That Affects Dietary Fat Perception
Lin, C., Colquitt, L. R., Wise, P. M., Breslin, P. A. S., Rawson, N. E., Genovese, F., Maina, I. W., Joseph, P. V., Fomuso, L. B., Slade, L., et al. (2020) · Chemical Senses · doi:10.1093/chemse/bjaa036 · Cited by 11
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“GWAS on macronutrient intake in a sample population of more than 70 000 European individuals showed that the BMI-related loci of FTO is associated with increased protein intake after adjusting for effect on BMI (P = 3 10) [41].”
BackgroundRamne, S., García‐Ureña, M., Gillum, M. P., Ängquist, L. H., Hansen, T., Merino, J., & Grarup, N. (2024) · Molecular Metabolism · doi:10.1016/j.molmet.2024.102049 · Cited by 11
“The same was shown for rs838145 [19].”
Parsing the Potential Neuroendocrine Actions of FGF21 in Primates
Gillum, M. P. (2018) · Endocrinology · doi:10.1210/en.2018-00208 · Cited by 9
Al-Jawadi, A. A., Priliani, L., Oktavianthi, S., Febinia, C. A., Daya, M., Artika, I. M., & Malik, S. G. (2021) · BMC Research Notes · doi:10.1186/s13104-021-05823-1 · Cited by 10
“Several studies reported that FTO rs1421085 is associated with both obese-related phenotypes and dietary macronutrient intake [16, 17, 33].”
BackgroundNew insights into the inter-organ crosstalk mediated by ChREBP
Carbinatti, T., Régnier, M., Parlati, L., Benhamed, F., & Postic, C. (2023) · Frontiers in Endocrinology · doi:10.3389/fendo.2023.1095440 · Cited by 13
“Single nucleotide polymorphisms at the Fgf21 locus were associated with increased carbohydrate preference, but no relationship with ChREBP was reported (42, 43).”
BackgroundAssociation between polygenic propensity for psychiatric disorders and nutrient intake
Hunjan, A. K., Hübel, C., Lin, Y., Eley, T. C., & Breen, G. D. (2021) · Communications Biology · doi:10.1038/s42003-021-02469-4 · Cited by 10
Genetic variants in AKR1B10 associate with human eating behavior
Rohde, K., Federbusch, M., Horstmann, A., Keller, M., Villringer, A., Stümvoll, M., Tönjes, A., Kovacs, P. L., & Böttcher, Y. (2015) · BMC Genetics · doi:10.1186/s12863-015-0189-9 · Cited by 9
“There is a good evidence for the role of genetics in human eating behavior [16-19] or in altered eating behavior”
BackgroundRuiz-Padilla, A. J., Morales-Hernandez, G., Ruíz‐Noa, Y., Alonso‐Castro, Á. J., Lazo-de-la-Vega-Monroy, M.-L., Preciado‐Puga, M. D. C., Rangel-Salazar, R., & Ibarra‐Reynoso, L. D. R. (2019) · Journal of Pediatric Endocrinology and Metabolism · doi:10.1515/jpem-2018-0546 · Cited by 9
“Similar studies identified other polymorphisms close to the FGF21 gene which were associated with macronutrient intake, specifically carbohydrate and fat intake [15, 16].”
ResultThe Genetic Determinants of Common Obesity-Susceptibility
Loos, R. J. F. (2011) · Springer eBooks · doi:10.1007/978-1-4614-0965-6_10 · Cited by 9
Self-citationThe Sweetest Thing: Regulation of Macronutrient Preference by FGF21
Adams, A. C., & Gimeno, R. E. (2016) · Cell Metabolism · doi:10.1016/j.cmet.2016.01.013 · Cited by 8
“Specifically, SNPs in and around the FGF21 gene have been reported to be associated with enhanced preference for carbohydrates, raising the question of whether altered FGF21 levels can impact macronutrient choice (Chu et al., 2013; Tanaka et al., 2013).”
BackgroundCheung, M. M., Hubert, P. A., Reed, D. R., Pouget, E. R., Jiang, X., & Hwang, L. (2024) · PLoS ONE · doi:10.1371/journal.pone.0300071 · Cited by 7
Vámos, A., Arianti, R., Vinnai, B. Á., Alrifai, R., Shaw, A., Póliska, S., Guba, A., Csősz, É., Csomós, I., Mocsár, G., et al. (2023) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2023.1155673 · Cited by 7
“Studies in European and Japanese populations reported that the presence of the obesity-risk C allele increased the susceptibility for obesity, elevated fat mass and food intake [Wheeler et al., 2013; Felix et al., 2016; Imamura et al., 2016; Tanaka et al., 2013].”
Nutri-informatics: a new kid on the block?
Döring, F., & Rimbach, G. H. (2014) · Genes & Nutrition · doi:10.1007/s12263-014-0394-6 · Cited by 7
“…and Food Science, University of Kiel, Heinrich-Hecht-Platz 10, 24118 Kiel, Germany e-mail: sek@molprev.uni-kiel.de G. Rimbach Food Science, Institute of Human Nutrition and Food Sciences, University of Kiel, Hermann-Rodewald-Strasse 6, 24098 Kiel, Germany 1 We used explicitly the term…”
BackgroundMethodInfluentialLee, H. J., Shon, J., & Park, Y. J. (2023) · Nutrients · doi:10.3390/nu15102385 · Cited by 5
“FGF21gene variants such as rs838133 and rs838145 are associated with high carbohydrate intake and low protein or fat intake, respectively [59,60].”
BackgroundBasolo, A., Hollstein, T., Shah, M. H., Walter, M. F., Krakoff, J. A., Votruba, S. B., & Piaggi, P. (2021) · American Journal of Clinical Nutrition · doi:10.1093/ajcn/nqab204 · Cited by 6
Gijbels, A., Schutte, S., Esser, D., Michielsen, C. C. J. R., Siebelink, E., Mars, M., Mensink, M., & Afman, L. A. (2022) · Nutrients · doi:10.3390/nu14235061 · Cited by 5
Chen, B., Li, Z., Chen, J., Ji, J., Shen, J., Xu, Y., Zhao, Y., Liu, D., Shen, Y., Zhang, W., et al. (2018) · Endocrine Journal · doi:10.1507/endocrj.ej17-0554 · Cited by 5
Sokary, S., Almaghrbi, H., & Bawadi, H. A. (2024) · Diabetes Metabolic Syndrome and Obesity · doi:10.2147/dmso.s452660 · Cited by 4
“32 Accordingly, food preferences have been recently shown to be partially genetically determined, such as a high consumption of sugar and carbohydrates.”
BackgroundIngestive Behavior and Precision Nutrition: Part of the Puzzle
Biruete, A., Buobu, P. S., Considine, R. V., Hoxha, E. M., Eicher‐Miller, H. A., Kinzig, K. P., Panjwani, A. A., Running, C. A., Rutigliani, G., Savaiano, D. A., et al. (2025) · Advances in Nutrition · doi:10.1016/j.advnut.2025.100531 · Cited by 7
“Several studies have reported potential genetic roles in associations between reduced sensitivity to oleogustus (fat taste) and preference for and higher intake of high-fat foods [232 – 238].”
Precision Nutrition for Type 2 Diabetes
Ben-Yacov, O., & Rein, M. (2022) · Springer eBooks · doi:10.1007/978-3-030-98927-9_12 · Cited by 4
Kanter, M. M., Aaron, S., Austad, S. N., Brown, A. W., Burd, N. A., Campbell, W. W., Cope, M. B., Davis, T. A., Erdman, J. W., Freitas, M., et al. (2026) · Critical Reviews in Food Science and Nutrition · doi:10.1080/10408398.2026.2658728 · Cited by 3
“…strongly supports the proposition In humans, as in rodents, FGF-21 is elevated in response to low-protein, high-carbohydrate intakes, and genetic variants are associated with altered dietary macronutrient intake (Chu et al. 2013; Tanaka et al. 2013; Ramne et al. 2023; 2024; Nicolaisen et al. 2025).”
Li, L., Chang, H., Huang, T., Zheng, Y., Qi, L., Xiao, X., & Li, M. (2017) · Journal of Psychiatry and Brain Science · doi:10.20900/jpbs.20170001 · Cited by 3
Self-citationBuilding a growing genomic repository for maternal and fetal health through the PING Consortium
Abdelmalek, C. M., Singh, S., Fasil, B., Horvath, A. R., Mulkey, S. B., Curé, C., Campos, M., Cavalcanti, D. P., Tong, V. T., Mercado, M., et al. (2025) · Pediatric Research · doi:10.1038/s41390-024-03793-1 · Cited by 3
Genetics of Energy and Macronutrient Intake in Humans
Tanaka, T. (2014) · Current Nutrition Reports · doi:10.1007/s13668-014-0083-5 · Cited by 3
Self-citationInteraction of Genetic Factors With Nutrition in Cancer
Freudenheim, J. L., & Gower, E. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-802928-2.00033-3 · Cited by 4
Trends in the plant-based anti-aging diet in different continents of the world
Banjerdpongchai, R., Suttajit, M., & Ratanavalachai, T. (2022) · Elsevier eBooks · doi:10.1016/b978-0-323-90581-7.00014-1 · Cited by 3
Frayling, T. M., Beaumont, R. N., Jones, S. E., Yaghootkar, H., Tuke, M. A., Ruth, K. S., Casanova, F., West, B., Locke, J. M., Sharp, S. A., et al. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/214700 · Cited by 3
“7%), which results in a synonymous change to the first exon of FGF21, is associated with higher carbohydrate and lower protein and fat intake, with no effect on total calorie intake[12-14].”
BackgroundMerino, J., Dashti, H. S., Sarnowski, C., Lane, J. M., Udler, M. S., Todorov, P. V., Song, Y., Wang, H., Kim, J., Tucker, C., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/623728 · Cited by 3
Self-citationStevanović, D., Hebert, A. J., Desai, B. N., Singhal, G., Adams, A. C., Flier, J. S., & Maratos–Flier, E. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.01.27.921361 · Cited by 3
Fabian, P., Blander, G., Deehan, R., Torkamani, A., & Nogal, B. (2025) · Human Genomics · doi:10.1186/s40246-025-00756-3 · Cited by 2
“Moreover, rs1421085 has also previously been indicated in dietary protein-seeking, independent of its effects on adiposity [52].”
Janzi, S., Ramne, S., Kou, M., Lu, X., Stubbendorff, A., Ke, C., Borné, Y., Qi, L., & Sonestedt, E. (2025) · Clinical Nutrition · doi:10.1016/j.clnu.2025.08.020 · Cited by 2
Self-citationGenetic predisposition to macronutrient preference and workplace food choices
Merino, J., Dashti, H. S., Levy, D. E., Sevilla-González, M. D. R., Hivert, M., Porneala, B., Saxena, R., & Thorndike, A. N. (2023) · Molecular Psychiatry · doi:10.1038/s41380-023-02107-x · Cited by 2
Seifi, N., Bahari, H., Foroumandi, E., Hasanpour, E., Nikoumanesh, M., Ferns, G. A., Esmaily, H., & Ghayour‐Mobarhan, M. (2024) · Journal of Clinical Hypertension · doi:10.1111/jch.14832 · Cited by 2
Nutritional Genomics: Exploration of Personal Genetic Testing in the Classroom
Hansen, J., & Stadler, D. D. (2019) · Journal of the Academy of Nutrition and Dietetics · doi:10.1016/j.jand.2019.02.011 · Cited by 2
The impact of polyphenols on chondrocyte growth and survival: a preliminary report
Fernández‐Arroyo, S., Huete‐Toral, F., de Lara, M. J. P., Cádiz‐Gurrea, M. D. L. L., Legeai‐Mallet, L., Micol, V., Segura‐Carretero, A., Joven, J., & Pintor, J. J. (2015) · Food & Nutrition Research · doi:10.3402/fnr.v59.29311 · Cited by 2
Villagrán, M., Petermann-Rocha, F. E., Mardones, L., Garrido-Méndez, Á., Martorell, M., Natalia Ulloa, M., Santos, J. L., Pérez‐Bravo, F., & Celis-Morales, C. A. (2018) · Revista médica de Chile · doi:10.4067/s0034-98872018001101252 · Cited by 2
Εvangelou, Ε., Gao, H., Chu, C., Ntritsos, G., Blakeley, P., Butts, A. R., Pazoki, R., Suzuki, H., Koskeridis, F., Yiorkas, A. M., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/453332 · Cited by 2
Self-citationLe, T. D. V., Fathi, P. A., Watters, A. B., Ellis, B. J., Bozadjieva-Kramer, N., Perez, M. B., Sullivan, A. I., Rose, J. P., Baggio, L. L., Koehler, J. A., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.01.03.522509 · Cited by 2
Cheung, M. M., Hubert, P. A., Reed, D. R., Pouget, E. R., Jiang, X., & Hwang, L. (2023) · Research Square · doi:10.21203/rs.3.rs-3644422/v1 · Cited by 2
Macronutrient mixtures and interactions in health and disease
Simpson, S. J., Couteur, D. G. L., Small, L., Brandon, A. E., & Raubenheimer, D. (2026) · Nature Reviews Endocrinology · doi:10.1038/s41574-026-01266-5 · Cited by 1
Wali, J. A., Ramos-Nieves, J. M., Binia, A., & van der Beek, E. M. (2026) · Advances in Nutrition · doi:10.1016/j.advnut.2026.100713 · Cited by 1
“However, findings from GWAS indicate that the FGF21 variants (rs838133 and rs838145) associated with higher carbohydrate intake are also linked to lower fat intake [86,87,101].”
Programming effects of FTO in the development of obesity
Sebert, S. P., Salonurmi, T., Keinanen-Kiukaanniemi, S. M., Savolainen, M. J., Herzig, K., Symonds, M. E., & Järvelin, M. (2014) · STM:n Hallinnonalan avoin julkaisuarkisto (Julkari) · Cited by 1
Precision Nutrition and Obesity
Bell, J. D., & Heber, D. (2023) · Elsevier eBooks · doi:10.1016/b978-0-443-15315-0.00020-1 · Cited by 1
Teymoori, F., Mokhtari, E., Farhadnejad, H., Ahmadirad, H., Akbarzadeh, M., Riahi, P., Zarkesh, M., DANESHPOUR, M. S., Mirmiran, P., & Vafa, M. (2024) · Clinical Nutrition ESPEN · doi:10.1016/j.clnesp.2024.03.016 · Cited by 1
GENETIC VARIATIONS OF NUTRITION RELATED GENES AND FOOD PREFERENCES IN THE KAZAKHS OF KAZAKHSTAN
Sikhayeva, N. S., Talzhanov, Y. A., Dzharmukanov, Z., Shevtsov, A., Zholdybayeva, E. V., Karabayeva, R., Benberin, V. V., Филипенко, М. Л., & Ramankulov, Y. M. (2021) · Eurasian journal of applied biotechnology · doi:10.11134/btp.4.2021.2 · Cited by 1
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
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