| Title: | Using genetic variation to disentangle the complex relationship between food intake and health outcomes |
| Journal: | PLOS Genetics |
| Published: | 2 Jun 2022 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/35653391/ |
| DOI: | https://doi.org/10.1371/journal.pgen.1010162 |
| URL: | https://journals.plos.org/plosgenetics/article/file?id=10.1371/journal.pgen.1010162&type=printable |
| Citations: | 21 (19 in last 2 years) as of 8 Aug 2024 |
Publication 10316
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Abstract
Diet is considered as one of the most important modifiable factors influencing human health, but efforts to identify foods or dietary patterns associated with health outcomes often suffer from biases, confounding, and reverse causation. Applying Mendelian randomization in this context may provide evidence to strengthen causality in nutrition research. To this end, we first identified 283 genetic markers associated with dietary intake in 445,779 UK Biobank participants. We then converted these associations into direct genetic effects on food exposures by adjusting them for effects mediated via other traits. The SNPs which did not show evidence of mediation were then used for MR, assessing the association between genetically predicted food choices and other risk factors, health outcomes. We show that using all associated SNPs without omitting those which show evidence of mediation, leads to biases in downstream analyses (genetic correlations, causal inference), similar to those present in observational studies. However, MR analyses using SNPs which have only a direct effect on the exposure on food exposures provided unequivocal evidence of causal associations between specific eating patterns and obesity, blood lipid status, and several other risk factors and health outcomes.</p>
21 Authors
- Nicola Pirastu
- Ciara McDonnell
- Eryk J. Grzeszkowiak
- Ninon Mounier
- Fumiaki Imamura
- Jordi Merino
- Felix R. Day
- Jie Zheng
- Nele Taba
- Maria Pina Concas
- Linda Repetto
- Katherine A. Kentistou
- Antonietta Robino
- Tõnu Esko
- Peter K. Joshi
- Krista Fischer
- Ken K. Ong
- Tom R. Gaunt
- Zoltán Kutalik
- John R. B. Perry
- James F. Wilson
1 Application
| Application ID | Title |
|---|---|
| 19655 | Quantitative and population genetics in UK Biobank |
Enabling scientific discoveries that improve human health