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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Magnitudes of such potential gene-diet interactions are often small.
“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]
Large investigations pooling multiple cohorts have observed main (population) effects of either dietary influences or genes on major cardiometabolic risk factors.
“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]
Evidence for interactions between diet and these genes is uncommon.
“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]
Genome-wide association studies have identified SNPs at the FGF21 locus that significantly correlate with changes in carbohydrate intake.
“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]
Pharmacological administration of FGF21 decreases sugar and alcohol intake in mice.
“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]
SNPs at the FGF21 locus are associated with changes in macronutrient intake.
“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]
Variants rs838133 and rs838145 are associated with higher carbohydrate intake, and FGF21 is a candidate gene in the region.
“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]
Human genetic linkage studies identified variants in the FGF21 locus associated with protein, carbohydrate, and fat intake.
“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]
FGF21 sequence variants are linked with alterations in macronutrient preference and alcohol intake in humans.
“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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Herman, M. A., & Samuel, V. T. (2016) · Trends in Endocrinology and Metabolism · doi:10.1016/j.tem.2016.06.005 · Cited by 249 · see citing works
“However, in humans, polymorphisms in the FGF21 locus that increase circulating FGF21 levels associate with increased, rather than decreased, carbohydrate consumption [75, 76].”
Fructose ingestion acutely stimulates circulating FGF21 levels in humans
Dushay, J. R., Toschi, E., Mitten, E. K., Fisher, F. M., Herman, M. A., & Maratos-Flier, E. (2015) · Molecular Metabolism · doi:10.1016/j.molmet.2014.09.008 · Cited by 233 · see citing works
Sweet Sixteenth for ChREBP: Established Roles and Future Goals
Abdul-Wahed, A., Guilmeau, S., & Postic, C. (2017) · Cell Metabolism · doi:10.1016/j.cmet.2017.07.004 · Cited by 231 · see citing works
“These findings support earlier reports associating variants in the FGF21 locus with increased carbohydrate preference in human cohorts (Chu et al., 2013; Tanaka et al., 2013).”
Fibroblast Growth Factor 21: A Versatile Regulator of Metabolic Homeostasis
BonDurant, L. D., & Potthoff, M. J. (2018) · Annual Review of Nutrition · doi:10.1146/annurev-nutr-071816-064800 · Cited by 222 · see citing works
FGF21 Is a Sugar-Induced Hormone Associated with Sweet Intake and Preference in Humans
Søberg, S., Sandholt, C. H., Jespersen, N. Z., Toft, U., Madsen, A. L., von Holstein-Rathlou, S., Grevengoed, T. J., Christensen, K. B., Bredie, W. L. P., Potthoff, M. J., et al. (2017) · Cell Metabolism · doi:10.1016/j.cmet.2017.04.009 · Cited by 216 · see citing works
“Finally, independent genomewide association studies (GWASs) have correlated variants at the FGF21 locus (rs838133 and rs838145) with increased relative carbohydrate but decreased protein and fat intake (Chu et al., 2013; Tanaka et al., 2013).”
BackgroundResultInfluentialGene-Diet Interaction and Precision Nutrition in Obesity
Heianza, Y., & Qi, L. (2017) · International Journal of Molecular Sciences · doi:10.3390/ijms18040787 · Cited by 209 · see citing works
Self-citationNovel locus including FGF21 is associated with dietary macronutrient intake
Chu, A. Y., Workalemahu, T., Paynter, N. P., Rose, L. M., Giulianini, F., Tanaka, T., Ngwa, J. S., Qi, Q., Curhan, G. C., Rimm, E. B., et al. (2013) · Human Molecular Genetics · doi:10.1093/hmg/ddt032 · Cited by 195 · see citing works
Self-citationCole, J. B., Florez, J. C., & Hirschhorn, J. N. (2020) · Nature Communications · doi:10.1038/s41467-020-15193-0 · Cited by 186 · see citing works
Diószegi, J., Llanaj, E., & Ádány, R. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.01272 · Cited by 184 · see citing works
Personalized Nutrition: Tailoring Dietary Recommendations through Genetic Insights
Singar, S., Nagpal, R., Arjmandi, B. H., & Akhavan, N. S. (2024) · Nutrients · doi:10.3390/nu16162673 · Cited by 178 · see citing works
“Specifically, a variation located at the chromosome 19 locus (rs838145) has been associated with increased carbohydrate intake and decreased fat consumption [40].”
BackgroundThe ‘Fat Mass and Obesity Related’ (FTO) gene: Mechanisms of Impact on Obesity and Energy Balance
Speakman, J. R. (2015) · Current Obesity Reports · doi:10.1007/s13679-015-0143-1 · Cited by 175 · see citing works
Jensen-Cody, S. O., Flippo, K. H., Claflin, K. E., Yavuz, Y., Sapouckey, S. A., Walters, G. C., Usachev, Y. M., Atasoy, D., Gillum, M. P., & Potthoff, M. J. (2020) · Cell Metabolism · doi:10.1016/j.cmet.2020.06.008 · Cited by 166 · see citing works
“Single nucleotide polymorphisms (SNPs) at the FGF21 locus are associated with changes in macronutrient intake, specifically increased carbohydrate intake (Chu et al., 2013; Frayling et al., 2018; Tanaka et al., 2013) and increased preference for sweets (Soberg et al.”
BackgroundA critical role for ChREBP-mediated FGF21 secretion in hepatic fructose metabolism
Fisher, F. M., Kim, M., Doridot, L., Cunniff, J. C., Parker, T. S., Levine, D. M., Hellerstein, M. K., Hudgins, L. C., Maratos-Flier, E., & Herman, M. A. (2017) · Molecular Metabolism · doi:10.1016/j.molmet.2016.11.008 · Cited by 166 · see citing works
“DNL was measured as previously described [7].”
Genomic analysis of diet composition finds novel loci and associations with health and lifestyle
Meddens, S. F. W., de Vlaming, R., Bowers, P., Burik, C. A. P., Linnér, R. K., Lee, C. W., Okbay, A., Turley, P., Rietveld, C. A., Fontana, M. A., et al. (2020) · Molecular Psychiatry · doi:10.1038/s41380-020-0697-5 · Cited by 164 · see citing works
Self-citationFGF21: A Novel Regulator of Glucose and Lipid Metabolism and Whole-Body Energy Balance
Szczepańska, E., & Gietka‐Czernel, M. (2022) · Hormone and Metabolic Research · doi:10.1055/a-1778-4159 · Cited by 155 · see citing works
Perspective: Dietary Biomarkers of Intake and Exposure—Exploration with Omics Approaches
Maruvada, P., Lampe, J. W., Wishart, D. S., Barupal, D. K., Chester, D. N., Dodd, D., Djoumbou-Feunang, Y., Dorrestein, P. C., Dragsted, L. O., Draper, J., et al. (2019) · Advances in Nutrition · doi:10.1093/advances/nmz075 · Cited by 151 · see citing works
Self-citationBray, M. S., Loos, R. J. F., McCaffery, J. M., Ling, C., Franks, P. W., Weinstock, G. M., Snyder, M. P., Vassy, J. L., Agurs‐Collins, T., & The Conference Working Group (2016) · Obesity · doi:10.1002/oby.21381 · Cited by 138 · see citing works
“In recent GWAS of dietary intake, FTO emerged as associated with a greater percentage of calories from protein (83,84) and fat (85), although inconsistently so.”
BackgroundSelf-citationLatest approaches for the treatment of obesity
Jackson, V. M., Breen, D. M., Fortin, J.-P., Liou, A., Kuzmiski, J. B., Loomis, A. K., Rives, M.-L., Shah, B., & Carpino, P. A. (2015) · Expert Opinion on Drug Discovery · doi:10.1517/17460441.2015.1044966 · Cited by 132 · see citing works
“Variants in FGF21 , while not associated with BMI or obesity, are significantly associated with food preference and macro-nutrient intake in humans [128,129] .”
Circulating FGF21 in humans is potently induced by short term overfeeding of carbohydrates
Lundsgaard, A.-M., Fritzen, A. M., Sjøberg, K. A., Myrmel, L. S., Madsen, L., Wojtaszewski, J. F. P., Richter, E. A., & Kiens, B. (2017) · Molecular Metabolism · doi:10.1016/j.molmet.2016.11.001 · Cited by 126 · see citing works
Fibroblast growth factor 21: a regulator of metabolic disease and health span
Xie, T., & Leung, P. S. (2017) · American Journal of Physiology-Endocrinology and Metabolism · doi:10.1152/ajpendo.00101.2017 · Cited by 121 · see citing works
The Hormone FGF21 Stimulates Water Drinking in Response to Ketogenic Diet and Alcohol
Song, P., Zechner, C., Hernandez, G., Canovas, J. A., Xie, Y., Sondhi, V., Wagner, M., Stadlbauer, V., Horvath, A., Leber, B., et al. (2018) · Cell Metabolism · doi:10.1016/j.cmet.2018.04.001 · Cited by 103 · see citing works
“In human genome-wide association studies (GWASs), SNPs in and around the FGF21 and b-Klotho genes were linked to carbohydrate and alcohol consumption (Chu et al., 2013; Schumann et al., 2016; Tanaka et al., 2013).”
Frayling, T. M., Beaumont, R. N., Jones, S. E., Yaghootkar, H., Tuke, M. A., Ruth, K. S., Casanova, F., West, B., Locke, J., Sharp, S., et al. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.03.070 · Cited by 101 · see citing works
“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 (Chu et al., 2013; Soberg et al., 2017; Tanaka et al., 2013).”
InfluentialSelf-citationFGF21 and the physiological regulation of macronutrient preference
Hill, C. M., Qualls-Creekmore, E., Berthoud, H.-R., Soto, P., Yu, S., McDougal, D. H., Münzberg, H., & Morrison, C. D. (2020) · Endocrinology · doi:10.1210/endocr/bqaa019 · Cited by 99 · see citing works
Obesity and FTO: Changing Focus at a Complex Locus
Tung, Y. C. L., Yeo, G. S. H., O’Rahilly, S., & Coll, A. P. (2014) · Cell Metabolism · doi:10.1016/j.cmet.2014.09.010 · Cited by 95 · see citing works
“However, a recent GWAS of macronutrient intake in more than 70,000 individuals identified the BMI-increasing allele of FTO SNPs as highly significantly associated with increased protein intake (Tanaka et al., 2013).”
BackgroundBaruch, A., Wong, C., Chinn, L. W., Vaze, A., Sonoda, J., Gelzleichter, T., Chen, S., Lewin-Koh, N., Morrow, L., Dheerendra, S., et al. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2012073117 · Cited by 95 · see citing works
New alcohol-related genes suggest shared genetic mechanisms with neuropsychiatric disorders
Εvangelou, Ε., Gao, H., Chu, C., Ntritsos, G., Blakeley, P., Butts, A. R., Pazoki, R., Suzuki, H., Koskeridis, F., Yiorkas, A. M., et al. (2019) · Nature Human Behaviour · doi:10.1038/s41562-019-0653-z · Cited by 84 · see citing works
Self-citationHwang, L., Lin, C., Gharahkhani, P., Cuéllar-Partida, G., Ong, J., An, J., Gordon, S. D., Zhu, G., MacGregor, S., Lawlor, D. A., et al. (2019) · American Journal of Clinical Nutrition · doi:10.1093/ajcn/nqz043 · Cited by 88 · see citing works
Huang, C., Chen, W., & Wang, X. (2022) · Genes & Diseases · doi:10.1016/j.gendis.2022.04.014 · Cited by 91 · see citing works
“For example, a GWAS conducted by Tanaka et al for macronutrient intake in more than 70,000 participants confirmed variants in FTO to be significantly relevant to increased protein intake.(116) Chuang et al firstly reported the pleiotropic longitudinal effects of the FTO gene and its influence on personality, brain fun…”
Fibroblast Growth Factor 21 and the Adaptive Response to Nutritional Challenges
Martínez‐Garza, Ú., Torres‐Oteros, D., Yarritu, A., Marrero, P. F., Haro, D., & Relat, J. (2019) · International Journal of Molecular Sciences · doi:10.3390/ijms20194692 · Cited by 87 · see citing works
“These data together with the GWAS studies available reinforce the role of FGF21 as a regulator of, at least, sugar and protein intake behavior [33,111,115].”
MethodComplex Relationship between Obesity and the Fat Mass and Obesity Locus
Yang, Q., Xiao, T., Guo, J., & Su, Z. (2017) · International Journal of Biological Sciences · doi:10.7150/ijbs.17051 · Cited by 82 · see citing works
“( P =0.007) [75] rs1421085 2016 a longitudinal multi-ethnic study (clinical trial) T/C the ages of 18–85 years 17,423 (10,608 women and 6799 men) six ethnic groups a mean BMI of 30.2 (SD= 6.22) kg/m2 a mean BAI of 33.0 (SD= 7.49) BMI Reduced by 57”
InfluentialFGF19 and FGF21: In NASH we trust
Talukdar, S., & Kharitonenkov, A. (2020) · Molecular Metabolism · doi:10.1016/j.molmet.2020.101152 · Cited by 82 · see citing works
“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 [87,88].”
BackgroundCirculating FGF21 Levels in Human Health and Metabolic Disease
Keuper, M., Häring, H., & Staiger, H. (2019) · Experimental and Clinical Endocrinology & Diabetes · doi:10.1055/a-0879-2968 · Cited by 82 · see citing works
“This is further supported by large genome-wide association studies showing an association of single nucleotide polymorphisms (SNPs) in or near the human FGF21 gene with macronutrient intake in humans independently of BMI: SNP rs838145, about 10 kb upstream of the FGF21 gene, associates with higher energy intake from c…”
ResultBiomarkers: background, classification and guidelines for applications in nutritional epidemiology.
Corella, D., & Ordovás, J. M. (2015) · PubMed · doi:10.3305/nh.2015.31.sup3.8765 · Cited by 80 · see citing works
Lifestyle precision medicine: the next generation in type 2 diabetes prevention?
Mutie, P. M., Giordano, G. N., & Franks, P. W. (2017) · BMC Medicine · doi:10.1186/s12916-017-0938-x · Cited by 72 · see citing works
Self-citationWalther, B., Lett, A. M., Bordoni, A., Tomás‐Cobos, L., Nieto, J. A., Dupont, D., Danesi, F., Shahar, D. R., Echaniz, A., Re, R., et al. (2019) · Molecular Nutrition & Food Research · doi:10.1002/mnfr.201900677 · Cited by 69 · see citing works
Meal timing and its role in obesity and associated diseases
Peters, B., Vahlhaus, J., & Pivovarova-Ramich, O. (2024) · Frontiers in Endocrinology · doi:10.3389/fendo.2024.1359772 · Cited by 72 · see citing works
Homeostatic sensing of dietary protein restriction: a case for FGF21
Hill, C. M., Berthoud, H.-R., Münzberg, H., & Morrison, C. D. (2018) · Frontiers in Neuroendocrinology · doi:10.1016/j.yfrne.2018.06.002 · Cited by 68 · see citing works
Dietary strategies with anti-aging potential: Dietary patterns and supplements
Duan, H., Pan, J., Guo, M., Li, J., Yu, L., & Fan, L. (2022) · Food Research International · doi:10.1016/j.foodres.2022.111501 · Cited by 69 · see citing works
Merino, J., Dashti, H. S., Li, S. X., Sarnowski, C., Justice, A. E., Graff, M., Papoutsakis, C., Smith, C. E., Dedoussis, G. V., Lemaitre, R. N., et al. (2019) · Molecular Psychiatry · doi:10.1038/s41380-018-0079-4 · Cited by 66 · see citing works
Self-citationProtein appetite as an integrator in the obesity system: the protein leverage hypothesis
Raubenheimer, D., & Simpson, S. J. (2023) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2022.0212 · Cited by 68 · see citing works
“Results from rodents are consistent with experimental and genome-wide association data in humans, showing that FGF21 is elevated under low-protein intakes (e.g. [52,54,65]) and that genetic variants are linked to macronutrient intake [66,67].”
ResultA new frontier in FGF21 biology
Potthoff, M. J. (2017) · Nature Reviews Endocrinology · doi:10.1038/nrendo.2016.206 · Cited by 63 · see citing works
The role of the FTO (Fat Mass and Obesity Related) locus in regulating body size and composition
Yeo, G. S. H. (2014) · Molecular and Cellular Endocrinology · doi:10.1016/j.mce.2014.09.012 · Cited by 61 · see citing works
The biology of FTO: from nucleic acid demethylase to amino acid sensor
Gulati, P., & Yeo, G. S. H. (2013) · Diabetologia · doi:10.1007/s00125-013-2999-5 · Cited by 61 · see citing works
Heianza, Y., Ma, W., Huang, T., Wang, T., Zheng, Y., Smith, S. R., Bray, G. A., Sacks, F. M., & Qi, L. (2016) · Diabetes Care · doi:10.2337/dc16-1111 · Cited by 59 · see citing works
“Our studies consistently showed that the genetic variation in the FGF21 region was associated with carbohydrate or fat intake (3,4).”
InfluentialSelf-citationLivingstone, K. M., Celis-Morales, C. A., Lara, J., Ashor, A. W., Lovegrove, J. A., Martínez, J. A., Saris, W. H. M., Gibney, M. J., Μanios, Y., Traczyk, I., et al. (2015) · Obesity Reviews · doi:10.1111/obr.12290 · Cited by 58 · see citing works
“A recent GWAS has found a robust association between FTO genotype and protein intake (11) but associations between FTO genotype and intakes of macronutrients (12,13) and of total energy (14–16) are less consistent (17).”
DRD2: Bridging the Genome and Ingestive Behavior
Sun, X., Luquet, S. H., & Small, D. M. (2017) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2017.03.004 · Cited by 59 · see citing works
Mukherjee, S., Walter, S., Kauwe, J. S. K., Saykin, A. J., Bennett, D. A., Larson, E. B., Crane, P. K., Glymour, M. M., Adult Changes in Thought Study Investigators, & Religious Orders Study/Memory and Aging Project Investigators (2015) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2015.05.015 · Cited by 55 · see citing works
“Our allocation of these SNPs to the “appetite” subscore was due to evidence that FTO expression regulates appetite and that the SNPs correlated with dietary intake, including selection of energy dense foods.[43-45] IRX3, however, is hypothesized to influence obesity via energy homeostasis, calling into question whethe…”
BackgroundImpact of Genes and Environment on Obesity and Cardiovascular Disease
Heianza, Y., & Qi, L. (2018) · Endocrinology · doi:10.1210/en.2018-00591 · Cited by 54 · see citing works
Self-citationZanetti, D., Rao, A. S., Gustafsson, S., Assimes, T. L., Montgomery, S. B., & Ingelsson, E. (2019) · Kidney International · doi:10.1016/j.kint.2018.12.017 · Cited by 51 · see citing works
Hosseini‐Esfahani, F., Koochakpoor, G., DANESHPOUR, M. S., Sedaghati-khayat, B., Mirmiran, P., & Azizi, F. (2017) · Nutrients · doi:10.3390/nu9101064 · Cited by 50 · see citing works
Doaei, S., Kalantari, N., Izadi, P., Salonurmi, T., Jarrahi, A. M., Rafieifar, S., Tabesh, G. A., Rahimzadeh, G., Gholamalizadeh, M., & Goodarzi, M. O. (2019) · Adipocyte · doi:10.1080/21623945.2019.1693745 · Cited by 49 · see citing works
“found that a high-fat diet in comparison with a normal carbohydrate diet in mice did not change FTO gene expression [27,28].”
BackgroundFlippo, K. H., Jensen-Cody, S. O., Claflin, K. E., & Potthoff, M. J. (2020) · Scientific Reports · doi:10.1038/s41598-020-76593-2 · Cited by 49 · see citing works
Diverse proteins aggregate in mild cognitive impairment and Alzheimer’s disease brain
Kepchia, D., Huang, L., Dargusch, R., Rissman, R. A., Shokhirev, M. N., Fischer, W. H., & Schubert, D. A. (2020) · Alzheimer s Research & Therapy · doi:10.1186/s13195-020-00641-2 · Cited by 48 · see citing works
Heritability of the timing of food intake
Lopez-Minguez, J., Dashti, H. S., Madrid-Valero, J. J., Madrid, J. A., Saxena, R., Scheer, F. A. J. L., Ordoñana, J. R., & Garaulet, M. (2019) · Clinical Nutrition · doi:10.1016/j.clnu.2018.03.002 · Cited by 45 · see citing works
Le, T. D. V., Fathi, P. A., Watters, A. B., Ellis, B. J., Besing, G.-L. K., Bozadjieva-Kramer, N., Perez, M. B., Sullivan, A. I., Rose, J. P., Baggio, L. L., et al. (2023) · Molecular Metabolism · doi:10.1016/j.molmet.2023.101718 · Cited by 48 · see citing works
Niarchou, M., Byrne, E. M., Trzaskowski, M., Sidorenko, J., Kemper, K. E., McGrath, J. J., O’Donovan, M. C., Owen, M. J., & Wray, N. R. (2020) · Translational Psychiatry · doi:10.1038/s41398-020-0688-y · Cited by 45 · see citing works
He, L., Kernogitski, Y., Culminskaya, I. V., Loika, Y., Arbeev, K. G., Loiko, E., Bagley, O., Duan, M., Yashkin, A. P., Ukraintseva, S. V., et al. (2016) · Frontiers in Genetics · doi:10.3389/fgene.2016.00179 · Cited by 45 · see citing works
“A detailed description of the method for the mediation analyses is provided in the supplementary materials Text S1.”
Fibroblast growth factor 21: an endocrine inhibitor of sugar and alcohol appetite
von Holstein‐Rathlou, S., & Gillum, M. P. (2019) · The Journal of Physiology · doi:10.1113/jp277117 · Cited by 44 · see citing works
“It is the same variant that was previously associated with altered macronutrient consumption (rs838133-A) (Chu et al. 2013; Tanaka et al. 2013).”
BackgroundPersonalized nutrition and obesity
Qi, L. (2014) · Annals of Medicine · doi:10.3109/07853890.2014.891802 · Cited by 43 · see citing works
“In another similarly-sized GWAS ( n 38,360) (49), it was found that a variant in the same gene (rs838145) was associated with higher carbohydrate intake.”
Self-citationLi, M., Wu, D., Yao, Y., Huo, Y., Liu, J.-W., Su, B., Chasman, D. I., Chu, A. Y., Huang, T., Qi, L., et al. (2015) · Schizophrenia Bulletin · doi:10.1093/schbul/sbv070 · Cited by 42 · see citing works
Self-citationEating, diet, and nutrition for the treatment of non-alcoholic fatty liver disease
Semmler, G., Datz, C., & Trauner, M. A. (2022) · Clinical and Molecular Hepatology · doi:10.3350/cmh.2022.0364 · Cited by 42 · see citing works
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McKeown, N. M., Dashti, H. S., Ma, J., Haslam, D. E., Jong, J. C. K., Smith, C. E., Tanaka, T., Graff, M., Lemaître, R. N., Rybin, D. V., et al. (2017) · Diabetologia · doi:10.1007/s00125-017-4475-0 · Cited by 40 · see citing works
“We and others have recently reported that SNPs in the FGF21 locus are associated with higher circulating FGF21 concentrations and higher carbohydrate relative to fat intake in humans [24, 25].”
Self-citationFibroblast growth factor 21 in lipid metabolism and non-alcoholic fatty liver disease
Su, X., Kong, Y., & Peng, D. (2019) · Clinica Chimica Acta · doi:10.1016/j.cca.2019.08.005 · Cited by 40 · see citing works
Dorling, J. L., Clayton, D. J., Jones, J., Carter, W. G., Thackray, A. E., King, J. A., Pucci, A. B. F., Batterham, R. L., & Stensel, D. J. (2019) · American Journal of Clinical Nutrition · doi:10.1093/ajcn/nqz188 · Cited by 39 · see citing works
“Our results are in agreement with studies indicating that individuals with 364 the A-allele of rs9939609 exhibit reduced satiety (4,7,39), higher food intake (5,6) and 365 elevated protein intake (40).”
ResultDietary Fat Modifies the Effects of FTO Genotype on Changes in Insulin Sensitivity
Zheng, Y., Huang, T., Zhang, X., Rood, J., Bray, G. A., Sacks, F. M., & Qi, L. (2015) · Journal of Nutrition · doi:10.3945/jn.115.210005 · Cited by 38 · see citing works
“Research in Genomic Epidemiology consortium (10).”
Self-citationLarsson, S. C., Michaëlsson, K., Mola-Caminal, M., Höijer, J., & Mantzoros, C. S. (2022) · Metabolism · doi:10.1016/j.metabol.2022.155329 · Cited by 39 · see citing works
“The strongest SNP near the FGF21 locus that was identified in our GWAS is in modest linkage disequilibrium ( R 2 ≈ 0.3) with SNPs (rs838133 and rs838145) previously found to associate with relative intake of macronutrients in GWAS analyses [19,20].”
InfluentialRecent Advances in Fatty Acid Perception and Genetics
Reed, D. R., & Xia, M. B. (2015) · Advances in Nutrition · doi:10.3945/an.114.007005 · Cited by 37 · see citing works
“Thus far, genomewide association studies have reported loci for dietary fat intake (53) but have not examined fat perception.”
BackgroundTopless, R., Major, T. J., Florez, J. C., Hirschhorn, J. N., Cadzow, M. J., Dalbeth, N., Stamp, L. K., Wilcox, P. L., Reynolds, R. J., Cole, J. B., et al. (2021) · Arthritis Research & Therapy · doi:10.1186/s13075-021-02444-8 · Cited by 36 · see citing works
Revisiting the evolutionary origins of obesity: lazy versus peppy‐thrifty genotype hypothesis
Reddon, H., Patel, Y. S., Turcotte, M., Pigeyre, M., & Meyre, D. (2018) · Obesity Reviews · doi:10.1111/obr.12742 · Cited by 36 · see citing works
“Variation in FGF21 rs838133 has been linked to increased consumption of protein and carbohydrates and decreased consumption of fats, and FTO rs10163409 has been associated with increased protein and carbohydrate intake, independent of BMI (134,135).”
Freuer, D., Meisinger, C., & Linseisen, J. (2021) · Clinical Nutrition · doi:10.1016/j.clnu.2021.01.047 · Cited by 35 · see citing works
“Macronutrient intake is a genetically complex phenotype [33,34].”
BackgroundPirastu, N., Kooyman, M., Traglia, M., Robino, A., Willems, S. M., Pistis, G., Amin, N., Sala, C. F., Karssen, L. C., van Duijn, C. M., et al. (2016) · Reviews in Endocrine and Metabolic Disorders · doi:10.1007/s11154-016-9354-3 · Cited by 34 · see citing works
“Recently, Tanaka and collaborators reported association of variants in the FTO gene with higher carbohydrate and lower fat consumption, independent of BMI, supporting the role of genetic variants on macronutrient consumption in humans [3].”
BackgroundResultProtein Appetite at the Interface between Nutrient Sensing and Physiological Homeostasis
Khan, M. S. H., Spann, R. A., Münzberg, H., Yu, S., Albaugh, V. L., He, Y., Berthoud, H., & Morrison, C. D. (2021) · Nutrients · doi:10.3390/nu13114103 · Cited by 35 · see citing works
Putting the Genome in Context: Gene-Environment Interactions in Type 2 Diabetes
Franks, P. W., & Paré, G. (2016) · Current Diabetes Reports · doi:10.1007/s11892-016-0758-y · Cited by 33 · see citing works
Self-citationSasaki, T. (2017) · Nutrients · doi:10.3390/nu9101151 · Cited by 35 · see citing works
En, M., Kazantseva, A. Y., Dubinina, A., Jakovleva, T., Balybina, N., Baranov, K. O., & Бажан, Н. М. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms221910561 · Cited by 33 · see citing works
González-Herrera, L. J., Zavala‐Castro, J., Ayala‐Cáceres, C., Pérez‐Mendoza, G., López‐González, M. J., Pinto-Escalante, D. D. C., Canto‐Cetina, T., García‐Escalante, M. G., Rubí‐Castellanos, R., Contreras‐Capetillo, S., et al. (2018) · American Journal of Human Biology · doi:10.1002/ajhb.23192 · Cited by 32 · see citing works
“FTO SNPs have been associated with increased energy intake, dietary fat or protein intake, increased appetite and reduced satiety, poor food choices or eating habits, and loss of control overeating (Hubacek, Pikhart, Peasey, & Bobak, 2011; Tanaka et al., 2013; Tanofsky-Kraff et al., 2009).”
BackgroundGenomic analysis of diet composition finds novel loci and associations with health and lifestylePreprint
Meddens, S. F. W., de Vlaming, R., Bowers, P., Burik, C. A. P., Linnér, R. K., Lee, C. W., Okbay, A., Turley, P., Rietveld, C. A., Fontana, M. A., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/383406 · Cited by 32 · see citing works
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“macronutrient consumption in observational studies (14).”
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“SNPs in IZUMO1, FUT1 and FGF21 on chromosome 19q13 were reported to influence components of caloric intake in a genome-wide metaanalysis of European population-based cohorts [10] and potentially influenced expression of FGF21 protein [9].”
Self-citation
- 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.
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