Using genetic variation to disentangle the complex relationship between food intake and health outcomes.

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Version: Final published version
License: CC BY 4.0
Serval ID
serval:BIB_2429EBBE8317
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Using genetic variation to disentangle the complex relationship between food intake and health outcomes.
Journal
PLoS genetics
Author(s)
Pirastu N., McDonnell C., Grzeszkowiak E.J., Mounier N., Imamura F., Merino J., Day F.R., Zheng J., Taba N., Concas M.P., Repetto L., Kentistou K.A., Robino A., Esko T., Joshi P.K., Fischer K., Ong K.K., Gaunt T.R., Kutalik Z., Perry JRB, Wilson J.F.
ISSN
1553-7404 (Electronic)
ISSN-L
1553-7390
Publication state
Published
Issued date
06/2022
Peer-reviewed
Oui
Volume
18
Number
6
Pages
e1010162
Language
english
Notes
Publication types: Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
Publication Status: epublish
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.
Keywords
Causality, Eating, Genetic Variation, Humans, Outcome Assessment, Health Care, Risk Factors
Pubmed
Web of science
Open Access
Yes
Create date
11/10/2022 15:08
Last modification date
23/01/2024 7:21
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