Genomic analysis of diet composition finds novel loci and associations with health and lifestyle

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  • dc.contributor.author Meddens, S. Fleur W.
  • dc.contributor.author González, Juan Ramón
  • dc.contributor.author Koellinger, Philipp D.
  • dc.date.accessioned 2022-05-27T05:50:57Z
  • dc.date.available 2022-05-27T05:50:57Z
  • dc.date.issued 2021
  • dc.description.abstract We conducted genome-wide association studies (GWAS) of relative intake from the macronutrients fat, protein, carbohydrates, and sugar in over 235,000 individuals of European ancestries. We identified 21 unique, approximately independent lead SNPs. Fourteen lead SNPs are uniquely associated with one macronutrient at genome-wide significance (P < 5 × 10-8), while five of the 21 lead SNPs reach suggestive significance (P < 1 × 10-5) for at least one other macronutrient. While the phenotypes are genetically correlated, each phenotype carries a partially unique genetic architecture. Relative protein intake exhibits the strongest relationships with poor health, including positive genetic associations with obesity, type 2 diabetes, and heart disease (rg ≈ 0.15-0.5). In contrast, relative carbohydrate and sugar intake have negative genetic correlations with waist circumference, waist-hip ratio, and neighborhood deprivation (|rg| ≈ 0.1-0.3) and positive genetic correlations with physical activity (rg ≈ 0.1 and 0.2). Relative fat intake has no consistent pattern of genetic correlations with poor health but has a negative genetic correlation with educational attainment (rg ≈-0.1). Although our analyses do not allow us to draw causal conclusions, we find no evidence of negative health consequences associated with relative carbohydrate, sugar, or fat intake. However, our results are consistent with the hypothesis that relative protein intake plays a role in the etiology of metabolic dysfunction.
  • dc.description.sponsorship This research was carried out under the auspices of the Social Science Genetic Association Consortium (SSGAC, https://www.thessgac.org/). The research has also been conducted using the UK Biobank Resource under Application Number 11425. The study was supported by funding from the Ragnar Söderberg Foundation (E9/11 and E42/15), the Swedish Research Council (421-2013-1061), The Jan Wallander and Tom Hedelius Foundation, an ERC Consolidator Grant to Philipp Koellinger (647648 EdGe), the Pershing Square Fund of the Foundations of Human Behavior, The Open Philanthropy Project (2016-152872, 010623-00001), and the NIA/NIH through grants P01-AG005842, P01-AG005842-20S2, P30-AG012810, and T32-AG000186-23 to NBER, and R01-AG042568-02 and R56-AG042568-04 to the University of Southern California. CCC was supported by the Intramural Research Program of the NIH/NIDDK and thanks Kevin Hall for informative discussions. PME was funded by Nestlé Nutrition. We thank the DietGen and CHARGE consortia for sharing diet-composition GWAS summary statistics, and we thank 23andMe, Inc., for sharing physical activity GWAS summary statistics. A full list of acknowledgements is provided in Supplementary Information 13.
  • dc.format.mimetype application/pdf
  • dc.identifier.citation Meddens SFW, de Vlaming R, Bowers P, Burik CAP, Linnér RK, Lee C et al. Genomic analysis of diet composition finds novel loci and associations with health and lifestyle. Mol Psychiatry. 2021 Jun;26(6):2056-69. DOI: 10.1038/s41380-020-0697-5
  • dc.identifier.doi http://dx.doi.org/10.1038/s41380-020-0697-5
  • dc.identifier.issn 1359-4184
  • dc.identifier.uri http://hdl.handle.net/10230/53281
  • dc.language.iso eng
  • dc.publisher Nature Research
  • dc.relation.ispartof Mol Psychiatry. 2021 Jun;26(6):2056-69
  • dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/647648
  • dc.rights © The Author(s) 2020. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
  • dc.rights.accessRights info:eu-repo/semantics/openAccess
  • dc.rights.uri http://creativecommons.org/licenses/by/4.0/
  • dc.subject.keyword Diseases
  • dc.subject.keyword Genetics
  • dc.title Genomic analysis of diet composition finds novel loci and associations with health and lifestyle
  • dc.type info:eu-repo/semantics/article
  • dc.type.version info:eu-repo/semantics/publishedVersion