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

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 ev...

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Autores principales: Pirastu, Nicola, McDonnell, Ciara, Grzeszkowiak, Eryk J., Mounier, Ninon, Imamura, Fumiaki, Merino, Jordi, Day, Felix R., Zheng, Jie, Taba, Nele, Concas, Maria Pina, Repetto, Linda, Kentistou, Katherine A., Robino, Antonietta, Esko, Tõnu, Joshi, Peter K., Fischer, Krista, Ong, Ken K., Gaunt, Tom R., Kutalik, Zoltán, Perry, John R. B., Wilson, James F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9162356/
https://www.ncbi.nlm.nih.gov/pubmed/35653391
http://dx.doi.org/10.1371/journal.pgen.1010162
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author Pirastu, Nicola
McDonnell, Ciara
Grzeszkowiak, Eryk J.
Mounier, Ninon
Imamura, Fumiaki
Merino, Jordi
Day, Felix R.
Zheng, Jie
Taba, Nele
Concas, Maria Pina
Repetto, Linda
Kentistou, Katherine A.
Robino, Antonietta
Esko, Tõnu
Joshi, Peter K.
Fischer, Krista
Ong, Ken K.
Gaunt, Tom R.
Kutalik, Zoltán
Perry, John R. B.
Wilson, James F.
author_facet Pirastu, Nicola
McDonnell, Ciara
Grzeszkowiak, Eryk J.
Mounier, Ninon
Imamura, Fumiaki
Merino, Jordi
Day, Felix R.
Zheng, Jie
Taba, Nele
Concas, Maria Pina
Repetto, Linda
Kentistou, Katherine A.
Robino, Antonietta
Esko, Tõnu
Joshi, Peter K.
Fischer, Krista
Ong, Ken K.
Gaunt, Tom R.
Kutalik, Zoltán
Perry, John R. B.
Wilson, James F.
author_sort Pirastu, Nicola
collection PubMed
description 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.
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spelling pubmed-91623562022-06-03 Using genetic variation to disentangle the complex relationship between food intake and health outcomes Pirastu, Nicola McDonnell, Ciara Grzeszkowiak, Eryk J. Mounier, Ninon Imamura, Fumiaki Merino, Jordi Day, Felix R. Zheng, Jie Taba, Nele Concas, Maria Pina Repetto, Linda Kentistou, Katherine A. Robino, Antonietta Esko, Tõnu Joshi, Peter K. Fischer, Krista Ong, Ken K. Gaunt, Tom R. Kutalik, Zoltán Perry, John R. B. Wilson, James F. PLoS Genet Research Article 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. Public Library of Science 2022-06-02 /pmc/articles/PMC9162356/ /pubmed/35653391 http://dx.doi.org/10.1371/journal.pgen.1010162 Text en © 2022 Pirastu et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Pirastu, Nicola
McDonnell, Ciara
Grzeszkowiak, Eryk J.
Mounier, Ninon
Imamura, Fumiaki
Merino, Jordi
Day, Felix R.
Zheng, Jie
Taba, Nele
Concas, Maria Pina
Repetto, Linda
Kentistou, Katherine A.
Robino, Antonietta
Esko, Tõnu
Joshi, Peter K.
Fischer, Krista
Ong, Ken K.
Gaunt, Tom R.
Kutalik, Zoltán
Perry, John R. B.
Wilson, James F.
Using genetic variation to disentangle the complex relationship between food intake and health outcomes
title Using genetic variation to disentangle the complex relationship between food intake and health outcomes
title_full Using genetic variation to disentangle the complex relationship between food intake and health outcomes
title_fullStr Using genetic variation to disentangle the complex relationship between food intake and health outcomes
title_full_unstemmed Using genetic variation to disentangle the complex relationship between food intake and health outcomes
title_short Using genetic variation to disentangle the complex relationship between food intake and health outcomes
title_sort using genetic variation to disentangle the complex relationship between food intake and health outcomes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9162356/
https://www.ncbi.nlm.nih.gov/pubmed/35653391
http://dx.doi.org/10.1371/journal.pgen.1010162
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