| Title: | Genomic analysis of diet composition finds novel loci and associations with health and lifestyle |
| Journal: | Molecular Psychiatry |
| Published: | 11 May 2020 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/32393786/ |
| DOI: | https://doi.org/10.1038/s41380-020-0697-5 |
| URL: | https://www.nature.com/articles/s41380-020-0697-5.pdf |
Publication 9112
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
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.</p>
43 Authors
- S. Fleur W. Meddens
- Ronald de Vlaming
- Peter Bowers
- Casper A. P. Burik
- Richard Karlsson Linnér
- Chanwook Lee
- Aysu Okbay
- Patrick Turley
- Cornelius A. Rietveld
- Mark Alan Fontana
- Mohsen Ghanbari
- Fumiaki Imamura
- George McMahon
- Peter J. van der Most
- Trudy Voortman
- Kaitlin H. Wade
- Emma L. Anderson
- Kim V. E. Braun
- Pauline M. Emmett
- Tonũ Esko
- Juan R. Gonzalez
- Jessica C. Kiefte-de Jong
- Claudia Langenberg
- Jian'an Luan
- Taulant Muka
- Susan Ring
- Fernando Rivadeneira
- Harold Snieder
- Frank J. A. van Rooij
- Bruce H. R. Wolffenbuttel
- George Davey Smith
- Oscar H. Franco
- Nita G. Forouhi
- M. Arfan Ikram
- Andre G. Uitterlinden
- Jana V. van Vliet-Ostaptchouk
- Nick J. Wareham
- David Cesarini
- K. Paige Harden
- James J. Lee
- Daniel J. Benjamin
- Carson C. Chow
- Philipp D. Koellinger
1 Application
| Application ID | Title |
|---|---|
| 11425 | The Social Science Genetic Association Consortium |
Enabling scientific discoveries that improve human health